Handbook of Research on Integrating ICTs in STEAM Education [1 ed.] 1668438615, 9781668438619

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Handbook of Research on Integrating ICTs in STEAM Education Stefanos Xefteris University of Western Macedonia, Greece

A volume in the Advances in Educational Technologies and Instructional Design (AETID) Book Series

Published in the United States of America by IGI Global Information Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA, USA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com Copyright © 2022 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Names: Xefteris, Stefanos, 1977- editor. Title: Handbook of research on integrating ICTs in STEAM education / Stefanos Xefteris, editor. Description: Hershey, PA : Information Science Reference, [2022] | Includes bibliographical references and index. | Summary: “This book will provide both practicing educators and researchers in the field of education science with novel teaching scenarios and interventions as well as frameworks of operation for integrating multiple technologies in novel STEAM based scenarios”-- Provided by publisher. Identifiers: LCCN 2022001256 (print) | LCCN 2022001257 (ebook) | ISBN 9781668438619 (hardcover) | ISBN 9781668438633 (ebook) Subjects: LCSH: Educational technology. | Education--Effect of technological innovations on. | Computer-assisted instruction. | Inquiry-based learning. Classification: LCC LB1028.3 .P73 2022 (print) | LCC LB1028.3 (ebook) | DDC 371.33--dc23/eng/20220209 LC record available at https://lccn.loc.gov/2022001256 LC ebook record available at https://lccn.loc.gov/2022001257 This book is published in the IGI Global book series Advances in Educational Technologies and Instructional Design (AETID) (ISSN: 2326-8905; eISSN: 2326-8913) British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the authors, but not necessarily of the publisher. For electronic access to this publication, please contact: [email protected].

Advances in Educational Technologies and Instructional Design (AETID) Book Series Lawrence A. Tomei Robert Morris University, USA

ISSN:2326-8905 EISSN:2326-8913 Mission

Education has undergone, and continues to undergo, immense changes in the way it is enacted and distributed to both child and adult learners. In modern education, the traditional classroom learning experience has evolved to include technological resources and to provide online classroom opportunities to students of all ages regardless of their geographical locations. From distance education, MassiveOpen-Online-Courses (MOOCs), and electronic tablets in the classroom, technology is now an integral part of learning and is also affecting the way educators communicate information to students. The Advances in Educational Technologies & Instructional Design (AETID) Book Series explores new research and theories for facilitating learning and improving educational performance utilizing technological processes and resources. The series examines technologies that can be integrated into K-12 classrooms to improve skills and learning abilities in all subjects including STEM education and language learning. Additionally, it studies the emergence of fully online classrooms for young and adult learners alike, and the communication and accountability challenges that can arise. Trending topics that are covered include adaptive learning, game-based learning, virtual school environments, and social media effects. School administrators, educators, academicians, researchers, and students will find this series to be an excellent resource for the effective design and implementation of learning technologies in their classes.

Coverage

• Curriculum Development • Virtual School Environments • Digital Divide in Education • Instructional Design Models • Bring-Your-Own-Device • Game-Based Learning • Educational Telecommunications • Online Media in Classrooms • Higher Education Technologies • Adaptive Learning

IGI Global is currently accepting manuscripts for publication within this series. To submit a proposal for a volume in this series, please contact our Acquisition Editors at [email protected] or visit: http://www.igi-global.com/publish/.

The Advances in Educational Technologies and Instructional Design (AETID) Book Series (ISSN 2326-8905) is published by IGI Global, 701 E. Chocolate Avenue, Hershey, PA 17033-1240, USA, www.igi-global.com. This series is composed of titles available for purchase individually; each title is edited to be contextually exclusive from any other title within the series. For pricing and ordering information please visit http://www.igi-global.com/book-series/advances-educational-technologies-instructional-design/73678. Postmaster: Send all address changes to above address. Copyright © 2022 IGI Global. All rights, including translation in other languages reserved by the publisher. No part of this series may be reproduced or used in any form or by any means – graphics, electronic, or mechanical, including photocopying, recording, taping, or information and retrieval systems – without written permission from the publisher, except for non commercial, educational use, including classroom teaching purposes. The views expressed in this series are those of the authors, but not necessarily of IGI Global.

Titles in this Series

For a list of additional titles in this series, please visit: www.igi-global.com/book-series

Assistive Technologies for Differently Abled Students Sangeeta Dhamdhere-Rao (Modern College of Arts, Science and Commerce, India) and Frederic Andres (National Insitute of Informatics, Japan) Information Science Reference • © 2022 • 305pp • H/C (ISBN: 9781799847366) • US $195.00 Global Perspectives and Practices for Reform-Based Mathematics Teaching Ozgul Kartal (University of Wisconsin, Whitewater, USA) Gorjana Popovic (Illinois Institute of Technology, USA) and Susie Morrissey (Mercer University, USA) Information Science Reference • © 2022 • 378pp • H/C (ISBN: 9781799894223) • US $195.00 Integrating Transparency in Learning and Teaching (TILT) An Effective Tool for Providing Equitable Opportunity in Higher Education Devi Akella (Albany State University, USA) Laxmi Paudel (Albany State University, USA) Nadeepa Wickramage (Albany State University, USA) Michael Rogers (Albany State University, USA) and Annalease Gibson (Albany State University, USA) Information Science Reference • © 2022 • 325pp • H/C (ISBN: 9781799895497) • US $195.00 Design and Measurement Strategies for Meaningful Learning José Luis Gómez Ramos (University of Castilla-La Mancha, Spain) and Isabel María Gómez-Barreto (University of Castilla-La Mancha, Spain) Information Science Reference • © 2022 • 297pp • H/C (ISBN: 9781799891284) • US $195.00 Technology-Supported Interventions for Students With Special Needs in the 21st Century Xiongyi Liu (Cleveland State University, USA) and Patrick Wachira (Cleveland State University, USA) Information Science Reference • © 2022 • 289pp • H/C (ISBN: 9781799888741) • US $195.00 Cases on Practical Applications for Remote, Hybrid, and Hyflex Teaching Valerie Harlow Shinas (Lesley University, USA) Chu N. Ly (Framingham State University, USA) and Sule Yilmaz Ozden (Sakarya Üniversitesi, Turkey) Information Science Reference • © 2022 • 355pp • H/C (ISBN: 9781799891680) • US $195.00 Affordances of Film for Literacy Instruction Jason D. DeHart (Appalachian State University, USA) Information Science Reference • © 2022 • 277pp • H/C (ISBN: 9781799891369) • US $195.00

701 East Chocolate Avenue, Hershey, PA 17033, USA Tel: 717-533-8845 x100 • Fax: 717-533-8661 E-Mail: [email protected] • www.igi-global.com

This book is dedicated to my daughter, Katerina. May you always find solace in knowledge and wonder in discovery.



Editorial Advisory Board Tharrenos Bratitsis, University of Western Macedonia, Greece Irene-Angelica Chounta, University of Duisburg-Essen, Germany Irini Geraniou, University College London, UK Kostas Karpouzis, Panteion University, Greece Elena Petelos, Charite University, Germany Iro Voulgari, Institute of Digital Games, University of Malta, Malta

 

List of Contributors

Acar, Veli / Ozel Ege Lisesi, Turkey................................................................................................... 219 Arvanitakis, Ioannis / University of Western Macedonia, Greece.................................................... 132 Arvaniti, Virginia / Educational Association Anatolia, Greece......................................................... 61 Barroca, Ana / Projeto Schole LDA, Portugal.................................................................................... 61 Bratitsis, Tharrenos / University of Western Macedonia, Greece...................................................... 61 Brouzos, Ioannis / Challedu, Greece................................................................................................... 41 Brouzou, Asimina / Challedu, Greece................................................................................................ 41 Büyükdede, Mert / Ozel Ege Lisesi, Turkey...................................................................................... 219 Camilleri, Vanessa / University of Malta, Malta................................................................................... 1 Christoforou, Andri / European University, Cyprus.......................................................................... 41 Díaz, Arcadio Sotto / Universidad Rey Juan Carlos, Spain................................................................. 61 Eng, Bob / Advisors for Good, USA................................................................................................... 390 Hartley, Thomas Francis / Independent Researcher, Australia......................................................... 361 Hatzikraniotis, Euripides / Aristotle University of Thessaloniki, Greece........................................ 176 Kalemis, Georgios / Hellenic Open University, Greece.................................................................... 344 Karpouzis, Kostas / Panteion University of Social and Political Science, Greece......................... 1, 22 Koliakou, Iro / Educational Association Anatolia, Greece................................................................. 61 Korompili, Anastasia / University of Piraeus, Greece........................................................................ 22 Kostas, Apostolos / University of the Aegean, Greece....................................................................... 153 Kourias, Spyros / University of Thessaly, Greece............................................................................. 109 Kousloglou, Manolis / Aristotle University of Thessaloniki, Greece................................................ 176 Lasica, Ilona-Elefteryja / University of the Aegean, Greece............................................................ 153 Manesis, Dionysios / National and Kapodistrian University of Athens, Greece............................... 201 Meletiou-Mavrotheris, Maria / European University, Cyprus.......................................................... 41 Molohidis, Anastasios / Aristotle University of Thessaloniki, Greece.............................................. 176 Mpalafouti, Efthalia / National and Kapodistrian University of Athens, Greece............................. 201 Pitsikalis, Stavros / University of the Aegean, Greece...................................................................... 153 Polatoglou, Hariton M. / Aristotle University of Thessaloniki, Greece............................................. 296 Psycharis, Sarantos / ASPETE, Greece............................................................................................. 344 Raave, Doris Kristina / University of Tartu, Estonia......................................................................... 320 Roa, Eric Roldan / Univerisity of Tartu, Estonia............................................................................... 320 Roldan-Roa, Erika / Technische Universität Münche, Germany & EPFL Lausanne, Switzerland.................................................................................................................................... 320 Roussou, Evgenia / Directorate of Primary Education of Piraeus, Greece........................................ 84 Rovshenov, Atajan / Ozel Ege Lisesi, Turkey.................................................................................... 219 



Sarmento, Teresa / Centro de Engenharia d Desenvolvimento, Portugal........................................... 61 Sharma, Amartya / George Washington University, USA................................................................ 390 Sharma, Dinesh / Steam Works Studio, LLC, USA............................................................................ 390 Sitsanlis, Ilias / 1st General Lyceum of Alexandroupolis, Greece..................................................... 296 Stouraitis, Elias / Palladio School, Greece............................................................................................ 1 Stylianou, Elena / European University, Cyprus................................................................................. 41 Theocharopoulos, Ioannis / European School Brussels III, Belgium............................................... 265 Theofanellis, Timoleon / ASPETE, Greece....................................................................................... 239 Tobajas, Nuria Olga León / Ceipso Maestro Rodrigo, Spain.............................................................. 61 Tsolakis, Savvas / University of Thessaly, Greece............................................................................. 239 Vekiri, Ioanna / European University, Cyprus.................................................................................... 41 Vitsilaki, Chryssi / University of the Aegean, Greece....................................................................... 153 Voulgari, Evagelia / Experimental High School of Magnesia, Greece............................................. 239 Voulgari, Iro / University of Malta, Malta............................................................................................. 1 Xefteris, Stefanos / University of Western Macedonia, Greece......................................................... 132 Zacharis, Georgios / Aristotle University of Thessaloniki, Greece................................................... 344 Zoupidis, Anastasios / Democritus University of Thrace, Greece.................................................... 176

Table of Contents

Preface................................................................................................................................................... xx Chapter 1 Artificial Intelligence and Machine Learning Education and Literacy: Teacher Training for Primary and Secondary Education Teachers........................................................................................... 1 Iro Voulgari, University of Malta, Malta Elias Stouraitis, Palladio School, Greece Vanessa Camilleri, University of Malta, Malta Kostas Karpouzis, Panteion University of Social and Political Science, Greece Chapter 2 An Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines............................................................................................................................................. 22 Anastasia Korompili, University of Piraeus, Greece Kostas Karpouzis, Panteion University of Social and Political Sciences, Greece Chapter 3 Adopting a Role-Model, Game-Based Pedagogical Approach to Gender Equality in STEAM: The FemSTEAM Mysteries Digital Game................................................................................................... 41 Ioanna Vekiri, European University, Cyprus Maria Meletiou-Mavrotheris, European University, Cyprus Asimina Brouzou, Challedu, Greece Ioannis Brouzos, Challedu, Greece Andri Christoforou, European University, Cyprus Elena Stylianou, European University, Cyprus Chapter 4 MiniOpenLab: Open Community and Hands-On Approach to Sustainable Development and STEM Education – An Innovative Approach........................................................................................ 61 Tharrenos Bratitsis, University of Western Macedonia, Greece Iro Koliakou, Educational Association Anatolia, Greece Arcadio Sotto Díaz, Universidad Rey Juan Carlos, Spain Virginia Arvaniti, Educational Association Anatolia, Greece Teresa Sarmento, Centro de Engenharia d Desenvolvimento, Portugal Nuria Olga León Tobajas, Ceipso Maestro Rodrigo, Spain Ana Barroca, Projeto Schole LDA, Portugal 



Chapter 5 Computational Thinking and Robotics in Kindergarten: An Implemented Educational Scenario........ 84 Evgenia Roussou, Directorate of Primary Education of Piraeus, Greece Chapter 6 Control Technologies as Mind-Tools: Emerging Mathematical Thinking Through Experiential Coding Activities in the Preschool Classroom.................................................................................... 109 Spyros Kourias, University of Thessaly, Greece Chapter 7 A Proposal for Creating Mixed Reality, Embodied Learning Interventions Integrating Robotics, Scratch, and Makey-Makey.................................................................................................................. 132 Stefanos Xefteris, University of Western Macedonia, Greece Ioannis Arvanitakis, University of Western Macedonia, Greece Chapter 8 Preparing Teachers for the 21st Century: A Mixed-Methods Evaluation of TPD Programs Under the Lens of Emerging Technologies in STE(A)M Education.............................................................. 153 Stavros Pitsikalis, University of the Aegean, Greece Ilona-Elefteryja Lasica, University of the Aegean, Greece Apostolos Kostas, University of the Aegean, Greece Chryssi Vitsilaki, University of the Aegean, Greece Chapter 9 Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning.................... 176 Manolis Kousloglou, Aristotle University of Thessaloniki, Greece Anastasios Zoupidis, Democritus University of Thrace, Greece Anastasios Molohidis, Aristotle University of Thessaloniki, Greece Euripides Hatzikraniotis, Aristotle University of Thessaloniki, Greece Chapter 10 Junior High School Pupils’ Perceptions and Self-Efficacy of Using Mobile Devices in the Learning Procedure.............................................................................................................................. 201 Dionysios Manesis, National and Kapodistrian University of Athens, Greece Efthalia Mpalafouti, National and Kapodistrian University of Athens, Greece Chapter 11 Integration of Educational Robotics to STEM Education................................................................... 219 Atajan Rovshenov, Ozel Ege Lisesi, Turkey Mert Büyükdede, Ozel Ege Lisesi, Turkey Veli Acar, Ozel Ege Lisesi, Turkey Chapter 12 Introducing STEAM Through Tinkercad and Arduino....................................................................... 239 Savvas Tsolakis, University of Thessaly, Greece Timoleon Theofanellis, ASPETE, Greece Evagelia Voulgari, Experimental High School of Magnesia, Greece



Chapter 13 A Sound Design and Electronic Music Production STEAM Course for Secondary Education.......... 265 Ioannis Theocharopoulos, European School Brussels III, Belgium Chapter 14 Designing a Set of Web-Based Simulations to Facilitate STEAM Activities on How to Travel From Earth to Mars.............................................................................................................................. 296 Ilias Sitsanlis, 1st General Lyceum of Alexandroupolis, Greece Hariton M. Polatoglou, Aristotle University of Thessaloniki, Greece Chapter 15 Supporting Education in Marginalized Communities With Workshops Combining Music and Mathematics......................................................................................................................................... 320 Eric Roldan Roa, Univerisity of Tartu, Estonia Erika Roldan-Roa, Technische Universität Münche, Germany & EPFL Lausanne, Switzerland Doris Kristina Raave, University of Tartu, Estonia Chapter 16 Use of STEM Intervention Teaching Scenarios to Investigate Students’ Attitudes Toward STEM Professions and Their Self-Evaluation of STEM Subjects.................................................................. 344 Georgios Kalemis, Hellenic Open University, Greece Sarantos Psycharis, ASPETE, Greece Georgios Zacharis, Aristotle University of Thessaloniki, Greece Chapter 17 A Teaching Sequence Proposal Using Microcontrollers Programmed With BASIC.......................... 361 Thomas Francis Hartley, Independent Researcher, Australia Chapter 18 STEAM and Sustainability: Lessons From the Fourth Industrial Revolution..................................... 390 Dinesh Sharma, Steam Works Studio, LLC, USA Bob Eng, Advisors for Good, USA Amartya Sharma, George Washington University, USA Compilation of References................................................................................................................ 408 About the Contributors..................................................................................................................... 452 Index.................................................................................................................................................... 462

Detailed Table of Contents

Preface................................................................................................................................................... xx Chapter 1 Artificial Intelligence and Machine Learning Education and Literacy: Teacher Training for Primary and Secondary Education Teachers........................................................................................... 1 Iro Voulgari, University of Malta, Malta Elias Stouraitis, Palladio School, Greece Vanessa Camilleri, University of Malta, Malta Kostas Karpouzis, Panteion University of Social and Political Science, Greece Artificial intelligence (AI) education and literacy are gaining momentum over the past few years; AI systems are permeating our daily lives and mediate our social, cultural, and political interactions. The implications of AI extend beyond the technical aspects and involve ethical, cultural, and social issues such as misinformation and bias. Understanding how an AI system works and critical thinking skills have, therefore, become ever more crucial for children and young people in order to be able to identify the benefits and challenges of AI. The role of the educators is, at this point, critical. This chapter is situated in the context of AI education and literacy and aims to propose a framework for teacher training on AI and ML education. The design of the teacher training courses and initial findings are described. Through an exploratory approach, insights on the attitudes, the requirements, and the recommendations of the teachers emerged. Chapter 2 An Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines............................................................................................................................................. 22 Anastasia Korompili, University of Piraeus, Greece Kostas Karpouzis, Panteion University of Social and Political Sciences, Greece This research examines the design, implementation, and impact of an educational robotics intervention for first and second grade students. It controls for gender-related performance differences and compares the interest shown towards robotics. The authors also examine if factors such as students’ stance towards different professions can contribute to a difference in performance. In the course of its work, custom designed worksheets for the UARO educational robotics product were used, as well as questionnaires given to students after meetings. The results showed that all genders responded equally well and with the same enthusiasm to the robotics activities and understood concepts of physics, mechanics, and mathematics through them. Participants differ in how they use their leisure time and in their professional orientation; however, this didn’t affect their performance in the robotics activities. These results highlight the  need for further examination of the social institutions and factors that influence the formation of gender orientations during the early childhood age.



Chapter 3 Adopting a Role-Model, Game-Based Pedagogical Approach to Gender Equality in STEAM: The FemSTEAM Mysteries Digital Game................................................................................................... 41 Ioanna Vekiri, European University, Cyprus Maria Meletiou-Mavrotheris, European University, Cyprus Asimina Brouzou, Challedu, Greece Ioannis Brouzos, Challedu, Greece Andri Christoforou, European University, Cyprus Elena Stylianou, European University, Cyprus The aim of this chapter is to discuss the use of serious games in STEAM education and to present FemSTEAM Mysteries, a serious game that was developed in the context of an EU-funded project. The game is intended for teenagers (age 12-15) and its goal is to promote gender equality in STEAM by inspiring all students to pursue STEAM careers, and to enhance the acquisition of key skills and competences for STEAM studies. It is based on role-model STEAM pedagogy and introduces students to important STEAM researchers and professionals in ways that challenge gender stereotypes as well as stereotypes about the characteristics of scientists and artists. The chapter presents the design and theoretical framework of the game which is based on both bibliographical and field research that was carried out in the context of the FemSTEAM Mysteries project. Chapter 4 MiniOpenLab: Open Community and Hands-On Approach to Sustainable Development and STEM Education – An Innovative Approach........................................................................................ 61 Tharrenos Bratitsis, University of Western Macedonia, Greece Iro Koliakou, Educational Association Anatolia, Greece Arcadio Sotto Díaz, Universidad Rey Juan Carlos, Spain Virginia Arvaniti, Educational Association Anatolia, Greece Teresa Sarmento, Centro de Engenharia d Desenvolvimento, Portugal Nuria Olga León Tobajas, Ceipso Maestro Rodrigo, Spain Ana Barroca, Projeto Schole LDA, Portugal Education for sustainable development and STEM education are two major EU priorities. Both should be addressed from an early age. At school, children must be motivated to learn maths and science and to imagine working in these fields, and to learn about sustainability and develop attitudes and behaviours that are in line with the UN’s SD Goals. Over the past years, children have taken interest in SD and in some cases. By contrast, STEM is still regarded as difficult and unattractive by many children. Thus, it may be beneficial to couple both these fields. The project MiniOpenLabs proposes to set-up and test a different methodology with a higher prevalence of experiential learning and relying on the collaboration between science and technology organisations, enterprises, and civil society to ensure relevant and meaningful engagement of all societal actors with science and increase the uptake of science studies, citizen science initiatives and science-based careers, employability, and competitiveness.



Chapter 5 Computational Thinking and Robotics in Kindergarten: An Implemented Educational Scenario........ 84 Evgenia Roussou, Directorate of Primary Education of Piraeus, Greece Ever since technology became an integral part of human life, a range of new concepts have surfaced. Computational thinking (CT) has been extensively discussed in the last 15 years and has been gaining popularity in the educational world. Following an overview of the basic literature published on this evasive new concept, an attempt is made to outline the connection between computational thinking and programming with emphasis on tangible programming of educational robots. An implemented educational programme, which attests to the positive impact of robotics on the acquisition of computational thinking skills in early childhood, is presented and evaluated. The study took place in a typical Greek kindergarten in 2017 and focused on the development of particular aspects of computational thinking with the use of a programmable floor robot. Chapter 6 Control Technologies as Mind-Tools: Emerging Mathematical Thinking Through Experiential Coding Activities in the Preschool Classroom.................................................................................... 109 Spyros Kourias, University of Thessaly, Greece In mathematics education, especially in early childhood that is considered the most formative period in children’s lives, there is an always growing need to design, test, and validate tools and activities that take advantage of recent pedagogical and technological advancements but still focus on the creative learning process, instead of quantifying the outcomes and emphasizing numerical data and performance. Educational robotics as a context for interdisciplinary problem-solving scenarios in preschool education can be an interesting starting point, since modern control technologies are usually thought to provide a rich variety of mind-tools that encourage active learning and children’s creative thinking. Such activities may stimulate students to “do” mathematics in a seamless, creative, playful way in order to solve meaningful and appealing (for them) problems. The study tries to explore and validate emerging preschoolers’ opportunities to unconsciously “mathematize” their environment in everyday playful robotics activities in the context of brief teaching experiments. Chapter 7 A Proposal for Creating Mixed Reality, Embodied Learning Interventions Integrating Robotics, Scratch, and Makey-Makey.................................................................................................................. 132 Stefanos Xefteris, University of Western Macedonia, Greece Ioannis Arvanitakis, University of Western Macedonia, Greece In current research we observe a clear trend that calls for novel teaching practices that involve multidisciplinary approaches that integrate information and communication technologies (ICT) into “traditional” workflows, employing embodied affordances in multimodal learning interventions. The educational process can therefore be augmented and transformed making use of available tools like educational robotics, tinkering with electronics (such as Makey Makey), and programming environments like Scratch to produce gamified versions of teaching sequences in a mixed reality context that “physicalizes” abstract concepts and improves both “21st century skills” and knowledge of traditional classroom material. Under the embodied cognition framework, the authors make use of robots as tangible agents in a gamified mixed reality setting. In this chapter, they provide a proposal for creating educationally effective, immersive, and engaging learning environments, as well as primary results from experimental application in various multi- and transdisciplinary teaching interventions.



Chapter 8 Preparing Teachers for the 21st Century: A Mixed-Methods Evaluation of TPD Programs Under the Lens of Emerging Technologies in STE(A)M Education.............................................................. 153 Stavros Pitsikalis, University of the Aegean, Greece Ilona-Elefteryja Lasica, University of the Aegean, Greece Apostolos Kostas, University of the Aegean, Greece Chryssi Vitsilaki, University of the Aegean, Greece This chapter provides an overview of (1) the current situation concerning teacher professional development (TPD) programs through studies referring to existing challenges; (2) the TPD programs under discussion that have been implemented during the last three years (2018-2021) in the context of European projects, including their structure and descriptions of the educational content; (3) teachers’ views and feedback concerning the TPD program they attended, based on a specific evaluation framework, with focus on issues relevant to emerging technologies. The researchers provide directions towards an effective framework for horizontal TPD programs targeting large numbers of teachers, aiming to allow them to gain the appropriate knowledge and skills in order to integrate emerging technologies as concepts in interdisciplinary STE(A) M-based instructional scenarios, especially in the levels of Secondary general (Gymnasium and Lyceum in Greece) and (post)secondary vocational education (EPAL and IEK in Greece). Chapter 9 Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning.................... 176 Manolis Kousloglou, Aristotle University of Thessaloniki, Greece Anastasios Zoupidis, Democritus University of Thrace, Greece Anastasios Molohidis, Aristotle University of Thessaloniki, Greece Euripides Hatzikraniotis, Aristotle University of Thessaloniki, Greece STEM education promotes scientific inquiry and engineering design, including mathematics, incorporating appropriate technologies. Portable technologies motivate active learning of students and enable accessing to learn resources, facilitating cross-disciplinary designing tasks. This chapter initially presents theoretical approaches of STEM education, mobile learning, and inquiry-based learning, and then it describes an inquiry-based short-term intervention that took advantage of portable digital devices in a STEM class. The aim of the intervention was to study its affection on students’ motivation about physics. Results indicate that students who participated in the activity had higher motivation scores than their classmates who attended lessons with conventional teaching methods. The findings also show that the students involved in a guided inquiry-based process became more profoundly engaged in STEM than their classmates who followed a structured inquiry process. Other factors, such as grade point average (GPA) and gender, did not seem to affect student motivation. Chapter 10 Junior High School Pupils’ Perceptions and Self-Efficacy of Using Mobile Devices in the Learning Procedure.............................................................................................................................. 201 Dionysios Manesis, National and Kapodistrian University of Athens, Greece Efthalia Mpalafouti, National and Kapodistrian University of Athens, Greece The study of this chapter investigated junior high school pupils’ perceptions and self-efficacy of using mobile devices in the learning procedure. A 33-item questionnaire was administered to 91 pupils aged 12-15 years old in different Greek schools. Most of the pupils had showed favorable perceptions about



the use of mobile devices for educational purposes. Nevertheless, the majority of pupils had a relatively medium degree of self-efficacy of using mobile devices in learning activities. Perceived usefulness was indicated as the major factor in predicting the adoption and use of mobile devices for educational purposes. The higher the level of perceived usefulness pupils have about mobile devices, the higher the possibility to use mobile devices as a learning tool. Pupils were more interested in using mobile devices for learning mathematics, history, English, and ancient Greek language. The findings of this study have implications for secondary education instructors, policy makers, and researchers. Chapter 11 Integration of Educational Robotics to STEM Education................................................................... 219 Atajan Rovshenov, Ozel Ege Lisesi, Turkey Mert Büyükdede, Ozel Ege Lisesi, Turkey Veli Acar, Ozel Ege Lisesi, Turkey Science, technology, engineering, and mathematics (STEM) education is integrated into education programs in many countries because it benefits the national economy and raises qualified manpower. During STEM-based activities, students increase their problem-solving and research skills by using technology and engineering knowledge together with science and mathematics knowledge. When the studies in the literature are examined, although it is seen that STEM education has positive contributions, it is encountered that the current resources for teachers are limited. The lack of up-to-date resources for teachers causes them to be insufficient in their field knowledge. Apart from this, teachers need to follow current technologies to be able to correctly apply the technology and engineering steps in STEM education and to have a high level of technological literacy. This study will provide information about the integration of educational robots in the researches to be done in the field of STEM education and give an idea to the studies to be done on the subject. Chapter 12 Introducing STEAM Through Tinkercad and Arduino....................................................................... 239 Savvas Tsolakis, University of Thessaly, Greece Timoleon Theofanellis, ASPETE, Greece Evagelia Voulgari, Experimental High School of Magnesia, Greece During the last years, educators were challenged to move their lessons from the physical classroom to online classrooms due to the COVID-19 pandemic. Due to this situation, they had to come up with new teaching methods and applications and even use ICT to implement hands-on activities. Teaching robotics, a significant subject to promote STEAM education and computational thinking, had to be continued under these circumstances. In this chapter, the work and the results of teaching robotics in online classes are presented. Tinkercad simulation platform was used to teach robotics and plan projects that later were implemented using the Arduino platform robotic system in the physical classroom as hands-on activities. Chapter 13 A Sound Design and Electronic Music Production STEAM Course for Secondary Education.......... 265 Ioannis Theocharopoulos, European School Brussels III, Belgium In this chapter, a music-centered STEAM course implemented in the European School (Schola Europaea) Brussels III is presented. This course, driven by constructivist conversation pedagogy, aims at students in secondary grade and is independent of their prior involvement in music. In the Sound Design module



of the course, which is presented in detail, students explore the world of electronic, software-based instruments through the use of software synthesizers and subtractive synthesis. Visual programming with Max/MSP is applied for the design and implementation of basic synthesizers although dedicated software synthesizers are also used. In this chapter, a brief overview on the composition, arrangement, production, mastering, and development modules of the course is also provided. Chapter 14 Designing a Set of Web-Based Simulations to Facilitate STEAM Activities on How to Travel From Earth to Mars.............................................................................................................................. 296 Ilias Sitsanlis, 1st General Lyceum of Alexandroupolis, Greece Hariton M. Polatoglou, Aristotle University of Thessaloniki, Greece In this chapter, the authors analyze a subject that is suitable for STEAM education and design a set of web-based simulations and material for blended learning to support STEAM activities on how to travel from Earth to Mars. Interplanetary travel involves astronomy, biology, and physics for science; technology to make it possible; engineering to optimize a possible solution; art to produce artwork based on the orbits of planets and boost creativity; and mathematics to solve the differential equations, obtain data, and perform data analysis to reach conclusions. Based on the ADDIE model, the presently related and available simulations were analyzed and based on that analysis a set of streamlined simulations are proposed, designed, developed, implemented, and evaluated. Similarly, a didactic sequence was implemented. The evaluation of the didactic sequence and the streamlined simulations by expert educators testifies that the proposed method to create STEAM inquiry and simulation-based activities is productive and can be used with a variety of interesting STEAM integration subjects. Chapter 15 Supporting Education in Marginalized Communities With Workshops Combining Music and Mathematics......................................................................................................................................... 320 Eric Roldan Roa, Univerisity of Tartu, Estonia Erika Roldan-Roa, Technische Universität Münche, Germany & EPFL Lausanne, Switzerland Doris Kristina Raave, University of Tartu, Estonia In this chapter, the authors present the experience of a series of workshops given in a marginalized community in Mexico during the COVID pandemic as a mean to mitigate the educational gap lockdowns provoked. The whole intervention consisted of 12 workshop sessions plus a closing activity. The workshops aimed to jointly promote learners’ conceptual and procedural knowledge of basic mathematics and develop musical rhythmic awareness and sensitivity in a collaborative problem-solving manner. Seventy children, ranging from 8 to 12 years old, participated in the workshops facilitated by an educational game, namely Musical Monkeys, consisting of a board game and an app. Using an initial evaluation, the authors mapped students’ profiles in terms of background knowledge (procedural and conceptual) to form balanced playing teams, including low and high achievers, and to adjust the workshops according to students’ needs and levels. The setting, challenges encountered during the intervention, and future research directions are discussed.



Chapter 16 Use of STEM Intervention Teaching Scenarios to Investigate Students’ Attitudes Toward STEM Professions and Their Self-Evaluation of STEM Subjects.................................................................. 344 Georgios Kalemis, Hellenic Open University, Greece Sarantos Psycharis, ASPETE, Greece Georgios Zacharis, Aristotle University of Thessaloniki, Greece The present research initiated from the hypothesis that students’ misconceptions can be resolved and replaced with new knowledge that is structured and organized through robust hypothetically-driven mental models. The assumption being that when students engage in teaching interventions that include hypothesis building and testing through STEM teaching scenarios and constructions, and are given the opportunity to discover the knowledge themselves, consequently, they enhance their attitudes towards STEM courses and career pathways as well as their own self-evaluation in mathematics and science. The quasi-experimental research methodology included a sample of 15-year-old students divided into an experimental and control group. The teaching intervention consisted of three scenarios developed primarily by the European Space Agency (ESA) but later adapted to meet the aptitude levels of students. Results showed improved attitudes in certain STEM courses and career pathways and a positive change in student’s self-evaluations in science. Chapter 17 A Teaching Sequence Proposal Using Microcontrollers Programmed With BASIC.......................... 361 Thomas Francis Hartley, Independent Researcher, Australia This chapter presents three electronics-based projects at increasing levels of sophistication. Two of the projects use the PIC microcontroller-based MicroMite chip. One uses the new Raspberry Pi PICO microcontroller board. All three deliver base level units that monitor atmospheric pressure (Projects 1 and 2) and ambient light levels (Project 3). All three communicate bidirectionally with an app on an Android mobile phone via the popular and well supported Bluetooth protocols. In the final technical section of the chapter, the content of those Bluetooth communications are ‘pushed’ onto a local IoT intranet design. The chapter closes with a brief summary of the STEAM initiatives in Australia plus a brief discussion of the importance of electronics in contemporary life which arguably justifies their inclusion in STEAM curricula content.



Chapter 18 STEAM and Sustainability: Lessons From the Fourth Industrial Revolution..................................... 390 Dinesh Sharma, Steam Works Studio, LLC, USA Bob Eng, Advisors for Good, USA Amartya Sharma, George Washington University, USA The educational challenge of sustainability remains unexplored in the development of children in the K-12 curriculum in the United States and potentially in the educational curriculum of many of the member states of the United Nations. Using a case study method, this chapter shows how sustainability can be an educational value and a public good, transmitted to students through everyday instruction. By conducting a regional analysis in specific cultural groupings, using fieldwork and applied research methodology, students can demonstrate competence for sustainable education on a whole host of issues relevant for the Sustainable Development Goals (SDG 2030). With younger age groups consisting of students in middle and elementary school, the chapter examines an activity-based approach for socializing young children to issues of sustainability and preparing them for what is known as “the fourth industrial revolution.” Finally, it is imperative that corporations adopt a socially responsible approach towards investing that is environmentally conscious of long-term governance impact. Compilation of References................................................................................................................ 408 About the Contributors..................................................................................................................... 452 Index.................................................................................................................................................... 462

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Modern society gives great importance to scientific and technological literacy, development of the socalled “21st century skills” and creating individuals that are not passive users of ICT tools but active thinkers and even tinkerers. UNESCO in 2002 has identified ICT as being developed into one of the pillars of modern society. It is a prevalent notion in modern educational frameworks that mastering ICT related skills and meta-skills is as essential as reading, writing and arithmetic. Through the integration of ICT tools in modern curricula, we aim to transform the educational process so that it does truly support and develop the widely sought-after 21st century skills: From setting goals and making evidence-based decisions, to thinking critically and solving problems while efficiently managing time and from using technology to cooperating ethically and communicating effectively, the learning process is constantly evolving to accommodate and facilitate students to acquire these skills. The inclusion of ICT tools in education has a long history, which is full of great promises and fraught with great disappointments. It is arguable that up till very recently, the impact of technology on the way people learn had been rather minimal. Educators have long strived to deploy ICT-rich educational interventions, but at the same time, quite often forgot a basic tenet: If the augmentation of a teaching sequence with ICT tools has the same learning effect with a “traditional” approach, why did we use ICT in the first place? Educators and researchers should never stop aiming higher: Transforming our teaching sequences with ICT tools should and can have a measurable and improved learning impact compared to traditional approaches. In the wider inclusion of ICT tools in modern educational scenario, STEAM is the approach to learning that uses concepts from natural sciences, technology, engineering, arts, and mathematics like springboards for the development of the skills of exploration, cooperation, communication, creativity, and critical thinking. The desired result is students who participate in experiential learning, developing critical thinking skills, work together, and explore the learning environment within the context of a creative process. In this framework, students stop begin passive receptacles of ex-cathedra presented knowledge, and turn to active and engaged stakeholders, with the teacher in the role of facilitator and mentor rather than presenter of material. The Handbook of Research on Integrating ICTs in STEAM Education is a collection of both academiabased research and actual practical applications from active educators, examining a multitude of different aspects concerning the integration of STEAM and ICT educational practices, tools, workflows, and frameworks of operation that encourage science skills, but also skills related to the arts and humanities such as creativity, imagination, and reflection on ethical implications. Covering topics ranging from early childhood education, machine learning education, and web-based simulations, to secondary and higher education, with tools such as electronics and IoT, robotics and  

Preface

Makey-Makey, educational software and coding platforms, tackling subjects such as the education of educators themselves and facilitating STEAM inclusion for female students, this collective tome aims to become an essential resource for active educators at all levels, for academics and researchers in the field of education technology, engineers, libraries, pre-service teachers, as well as computer scientists. Researchers can use this tome to find novel ideas, possible frameworks and testbeds to use in their future experiments, educators can find valuable resources for applying full educational scenarios or using the books’ examples as roadmaps and conceptual bases on which to build their own sequences, interventions and workflows. Chapter 1, named “Artificial Intelligence and Machine Learning Education and Literacy: Teacher Training for Primary and Secondary Education Teachers,” tackles the issue of training educators in the integration of Artificial Intelligence and Machine Learning concepts. The chapter provides a holistic approach, examining both the technical aspects of AI and ML, as well as the implications of AI and ML such as ethical, cultural, social and misinformation/bias dimensions. This chapter provides a solid framework for teacher training on AI and ML education, also including a report on initial experimental findings. The chapter also provides insights on attitudes, requirements and recommendations of the teachers involved. In Chapter 2, “An Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines,” the authors provide a much needed insight into the inclusion and engagement of female students with STEM disciplines through educational robotics in early childhood. This research introduces an educational robotics teaching intervention suitable for first and second grade students and describes the design process, the implementation and the impact. This significant chapter tackles the issues of gender-related performance differences and the examination of the highly interesting results shows that there are no discernible gender-related differences in the overall response, interest and performance of the students, but rather in the way they make use of their free time as well as their stated “professional orientation”. In Chapter 3, “Adopting a Role-Model, Game-Based Pedagogical Approach to Gender Equality in STEAM: The FemSTEAM Mysteries Digital Game,” the authors present another highly interesting and impactful approach to STEAM education aimed towards gender equality: The chapter presents and discusses the use of a serious game called “FemSTEAM Mysteries”, which was the product of a funded research project that comprised partners from Greece, Cyprus and Spain. The FemSTEAM Mysteries serious game, introduces teenage students (age 12-15) to a role-model based STEAM framework, presenting important researchers and professionals in ways that challenge gender stereotypes and stereotypes concerning characteristics of scientists and artists. In Chapter 4, “MiniOpenLab: Open Community and Hands-On Approach to Sustainable Development and STEM Education: An Innovative Approach,” the authors present another academic-based work, part of the European Union funded MiniOpenLabs research project. This chapter takes a high-level approach on the integration of ICT’s in modern curricula, focusing on the translation of extant policies into significant and impactful actions. The chapter focuses on and combines two major EU priorities, namely Education for Sustainable Development and STEAM education, tackling the subject from an early age. In this chapter the authors present the design and experimental application of a methodology based on experiential learning and relying on a multi-faceted collaboration between science and technology organisations, enterprises and civil services, in order to facilitate the students engagement with science and technology, as well as envision working in the relevant fields under the umbrella of a sustainable development modus operandi. xxi

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This impactful research project aims at increasing locally in the partner countries the uptake of science studies, citizen science initiatives and science-based careers, employability and competitiveness. In Chapter 5, “Computational Thinking and Robotics in Kindergarten: An Implemented Educational Scenario,” the author presents a research work implemented in real life conditions, concerning computational thinking skills through the application of educational robotics in kindergarten. Actual teaching interventions from on-the-filed active teachers, are not rare in literature, but are often “steamrolled” out, as academic researchers dominate publications. In this chapter, the author is an active kindergarten teacher, with experience on STEAM and ICT in education, presenting a study conducted in a typical Greek kindergarten, focusing on the highly significant aspects of computational thinking development through the use of educational robots, attempting to emphasize on how tangibility facilitates the development of computational thinking. In Chapter 6, “Control Technologies as Mind-Tools: Emerging Mathematical Thinking Through Experiential Coding Activities in Preschool Classroom,” the author focuses on the development of mathematics related skills in early education, and attempts to integrate mathematics learning with a creative learning process and coding activities with educational robotics affordances. The goal of this interesting chapter is to transform mathematics learning through a playful set of activities which enables students to -unconsciously- engage in “complex” (for their age) mathematical thinking and facilitate the “mathematization” of their routine observation of their surroundings. In a seamless, creative and gamified framework, pre-schoolers use ICT as the titular “mind-tools” and stimulated to “do” mathematics in a fun and engaging environment. In Chapter 7, “A Proposal for Creating Mixed Reality Embodied Learning Interventions Integrating Robotics, Scratch, and Makey-Makey,” the authors aim to present a new kind of intervention-design workflow, that combines multiple technologies and provides a fertile ground for the creation of immersive and engaging teaching sequences, making use of multiple technologies. The authors integrate educational robotics as tangible agents, with Makey-Makey enabled mixed reality surfaces augmented with Scratch games through a projector. Teaching interventions are created using a game-based / treasure hunt-like format, where robots act as the game protagonists and games include multi- and trans-disciplinary thematics; Mathematics and history, geography and history, English learning and coding, cryptography and music are some of the published examples. The chapter provides the ground tools and description for building such immersive teaching interventions as well as primary results from experimental application of a number of sequences based on this format. In Chapter 8, “Preparing Teachers for the 21st Century: A Mixed-Methods Evaluation of TPD Programs Under the Lens of Emerging Technologies in STE(A)M Education,” takes the reader conceptually higher than practical application of ICTs in education and tackles the prominent issues of Teacher Professional Development programs, the challenges they face, their recent curricula and the actual participants evaluations on TPD programs. The research team provides also directions towards design and implementation of effective TPD programs, aiming to facilitate 21st century teachers to integrate STEAM concepts through ICT in their careers. In Chapter 9, “Enhancing Student Motivation by STEM-Oriented, Mobile Inquiry-Based Learning,” the authors begin with a theoretical background of STEM education, Mobile Learning and Inquiry-based learning and then move on to the description of an inquiry-based learning intervention making use of mobile devices. The intervention is built around a junior high school level physics class and the main goal was to study the approach’s effect on students’ motivation on physics related subjects. The experiment involved a technologically-excluded control group that was taught the same material with conventional xxii

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methods and the promising results discussed show a specific difference and higher motivation scores among students who participated in the ICT augmented intervention. In Chapter 10, “Junior High School Pupil Perceptions and Self-Efficacy of Using Mobile Devices in the Learning Procedure,” the authors investigate how the students themselves perceive their efficacy on the use of mobile devices during the learning process. The study was conducted via a 33-item questionnaire and had 91 junior high school students from different Greek schools participated. The highly interesting result in this publication is that how students perceive the usefulness of mobile devices, directly correlates to the efficient use of them in educational settings. Thus, the study provides significant findings that can be of high interest to a range of education-related professionals, such as policy makers, educators and researchers. In Chapter 11, “Integration of Educational Robotics to STEM Education,” we have another hands-on experience from active teachers in a high-school in Turkey. The authors begin from the assertion that STEM education has been increasingly integrated in school practice around the world, with a multitude of available ICT affordances being integrated in teaching interventions. The authors identify a specific gap in literature, concerning the lack of teacher-targeted available resources that facilitate the integration of robotics in everyday school practice. Authors assert that while there is significant research activity from higher education institutions, and STEAM affordances have been proven consistent in providing positive outcomes, on the other hand “actionable” teacher resources are somewhat limited. So, the authors try to bridge that gap, and provide a brief but succinct roadmap, that aims to be instrumental in providing teachers in the field with a general outline on how to integrate educational robotics in their everyday practice, as well as provide a general outline of recent research on the field. It is highly notable that while academic researchers feel that the field of STEM is almost saturated with research, active teachers more often than not feel that they don’t have real access to current material or feel excluded from it because of its’ highly ‘academic” presentation style in conference and journal publications. This chapter aims to be a simple yet effective introduction of how to integrate robotics in the classroom. Chapter 12, “Introducing STEAM Through Tinkercad and Arduino,” is another school-tried, work from active educators in secondary education, along with a highly current twist: How high school educators tackled STEAM education and Computational Thinking challenges in online classes during the CoVid quarantine era in Greece. The move from physical to virtual classrooms has more often than not negatively affected all aspects of the educational process. Educators on all levels strived to keep up with course material, keep students engaged and immersed and many of them keep up with use of technological tools they were not familiarized with. In this chapter the authors present their own interesting approach of novel teaching methods and applications to implement activities in a STEAM framework, teaching robotics through the Tinkercad simulation platform to design and save projects later implemented on Arduino based boards in physical classrooms as hands-on activities. The chapter presents the relevant work and discusses the results of this very interesting approach that signifies the quick “educational reflexes” of active teachers on public schools in Greece. In Chapter 13, “A Sound Design and Electronic Music Production STEAM Course for Secondary Education,” the author, a teacher in the European School of Brussels in Belgium, describes a different approach to STEAM based learning: One that integrates music in the teaching practice. This chapter also is heavy on implementation details and presents the whole course material in a very detailed way, and keeping it light in pedagogical background and theories – which may seem lacking for a publication in a collective tome. On the other hand, one of the goals of the specific tome was to highlight active onthe-filed educators along with researchers, and this means that some of the chapters while scientifically xxiii

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sound and highly interesting -such as this- may seem “unacademic” to some colleagues. Nevertheless, this chapter provides a highly interesting and student-favorite educational approach to STEAM material. The course is based on the constructivist conversation framework and makes use of electronic, software based instruments, through the use of software synthesizers and subtractive synthesis. The course requires no previous musical knowledge on behalf of the students. Through visual programming with Max/ MSP students program basic synthesizers along the use of pre-programmed ones. The chapter provides a fascinating a overview of this highly successful course material and modules. In Chapter 14, “Designing a Set of Web-Based Simulations to Facilitate STEAM Activities on How to Travel From Earth to Mars,” the authors make use of web-based tools to simulate the design and implementation of an Earth to Mars voyage. The authors provide the simulations and aterial designed for blended learning activities in a STEAM framework, combining elements from astronomy, biology and physics for overall design of the endeavor, technology and engineering for optimization of proposed solutions, art and creativity for the creation of visuals based on astronomy, as well as mathematics to obtain and perform data analysis to reach conclusions. The authors based on the ADDIE model to build a set of streamlined simulations and evaluate them, through a didactic sequence. The chapter concludes discussing the results of the evaluation sequence, indicating that the proposed teaching intervention is effective and productive and can be used as a general roadmap to implement a variety of STEAM based teaching sequences. In Chapter 15, “Supporting Education in Marginalized Communities With Workshops Combining Music and Mathematics,” authors from Estonian based research centers tackle an often overlooked but very significant aspect of the deployment of STEAM based teaching interventions: How educators can deploy impactful teaching scenaria in marginalized communities. The authors here present the experiences they had, deploying a series of workshops in a marginalized community in Mexico, during the CoVid pandemic. The workshops combined mathematics with music and were deployed in 12 sessions, plus a final “closing” activity. The authors present a significant contribution concerning learning in marginalized communities, describing workshops that aimed to promote the conceptual and procedural awareness of basic mathematics notions among students in such communities, combined with the development of musical and rhythmical awareness, all integrated in a collaborative environment rich with problem-solving activities. Seventy children from 8 to 12 years old participated in this research, centered around a musical game named “Musical Monkeys” consisting of a board game and an app. The authors discuss the implementation, setting and encountered challenges, and give insightful remarks on future research directions. Chapter 16, “Use of STEM Intervention Teaching Scenarios to Investigate Student Attitudes Toward STEM Professions and Their Self-Evaluation of STEM Subjects” is built around the notion of bringing forth and dissolving students’ misconceptions. The authors provide some groundwork in how active participation and self-discovery foster the creation of new knowledge and facilitate students to create conceptual anchors through STEM based teaching scenaria and constructs. The authors deployed a European Space Agency-developed teaching sequence, modified to meet the aptitude level of their students, engaging them with hypothesis-making and testing and discover knowledge themselves, in order to evaluate their attitudes toward STEM-based career paths, as well as their own self-evaluation of maths and science skills. The authors discuss their results which clearly indicate a positive impact on the students’ perceived career pathways regarding STEM related fields, as well as improved attitudes towards STEM related school courses.

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In Chapter 17, “A Teaching Sequence Proposal Using Microcontrollers Programmed With BASIC,” the author presents a highly detailed, tutorial-style proposal for the deployment of three electronics based projects of increasing difficulty in Australian high schools. Two of the projects make use of the MicroMite chip and one uses the Raspberry Pi PICO microcontroller. The chapter is heavy in detail and light in academic background, choosing to provide a much needed very detailed description of all possible minutiae involved in the implementation of the proposed projects, making this chapter accessible to even the absolute beginner in the relevant technologies. The proposed projects communicate with an Android based application and also include IoT capabilities. The chapter also briefly presents the STEAM inclusion challenges in Australia curriculum. Chapter 18, “STEAM and Sustainability: Lessons From the Fourth Industrial Revolution,” is the most suitable conclusion to this -hopefully- very interesting collection of diverse approaches to the integration of ICT’s in educational context. The authors of the chapter focus their presentation mainly drawing from experience in the United States of America, but similar remarks can without loss of generality be applied to all countries. The authors of the paper tackle the issue of sustainability in education through STEAM practices. In a case-study methodological approach, the authors try to approach the issue of “teaching about sustainability” in modern curricula. The chapter “transforms” the notion of sustainability to an “educational asset” or a “public good” that should and needs to be consistently and continuously ingrained to students through all aspects of their education. Based on the Sustainable Development Goals (SDG 2030) set in the United States, the authors describe a modus operandi employing regional analysis in specific cultural groupings, fieldwork and applied research methodologies, in order to demonstrate competence for sustainable education. The chapter authors examine relevant activities designed to familiarize students with sustainability issues and prepare them for what is known as the “fourth industrial revolution” – the world of big data, full automation and ubiquitous machine learning and AI. ICTs have been and continue to be a massive influence on our lives. Educational practice has been also greatly impacted, but not always successfully or in a meaningful way. Education is the field where academics and educators strive and aim to improve greatly in the near future, with ICTs transforming the whole process top-to-bottom and bottom-up. ICT-enhanced models facilitate the development of “old-fashioned” skills, but also provide a fertile ground on which to cultivate the much-sought after 21st century skills -which the “digital natives” generation does not possess by default. It is time to transform notions such as “critical thinking”, “computational and abstract thinking”, “social skills and teamwork” and “design thinking” into concrete elements of multimodal and transdisciplinary teaching interventions, fostering creativity, boosting immersiveness and engagement, motivating students to participate in highly impactful and meaningful teaching interventions. In the same spirit, we should look higher up, to prepare to educate the next generations of educators and make them tech-savvy and creative, fostering their need for innovation and “escape” from the educational and didactic hurdles they experienced as students themselves, providing them with the base material to create themselves the novel STEAM and ICT based interventions their students need. In this publication, the editor and all authors, hope that we did our best to provide both academics and educators with interesting material, giving them some excellent groundwork on which to further build their own teaching interventions. Stefanos Xefteris University of Western Macedonia, Greece April 2022

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Chapter 1

Artificial Intelligence and Machine Learning Education and Literacy:

Teacher Training for Primary and Secondary Education Teachers Iro Voulgari University of Malta, Malta Elias Stouraitis Palladio School, Greece Vanessa Camilleri University of Malta, Malta Kostas Karpouzis Panteion University of Social and Political Science, Greece

ABSTRACT Artificial intelligence (AI) education and literacy are gaining momentum over the past few years; AI systems are permeating our daily lives and mediate our social, cultural, and political interactions. The implications of AI extend beyond the technical aspects and involve ethical, cultural, and social issues such as misinformation and bias. Understanding how an AI system works and critical thinking skills have, therefore, become ever more crucial for children and young people in order to be able to identify the benefits and challenges of AI. The role of the educators is, at this point, critical. This chapter is situated in the context of AI education and literacy and aims to propose a framework for teacher training on AI and ML education. The design of the teacher training courses and initial findings are described. Through an exploratory approach, insights on the attitudes, the requirements, and the recommendations of the teachers emerged. DOI: 10.4018/978-1-6684-3861-9.ch001

Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Artificial Intelligence and Machine Learning Education and Literacy

INTRODUCTION In this chapter a framework for teacher training in Artificial Intelligence (AI) and Machine Learning (ML) education and literacy, for primary and secondary education students is presented. The main components of the framework are introduced and discussed, such as principles, relevant AI concepts and means to communicate them, educational approaches, and educational material, as well as preliminary insights from implemented teacher training workshops. AI refers to the processes and algorithms through which an application learns to perform tasks such as problem-solving and decision-making. ML is a subset of AI and involves a set of algorithms through which a system adapts and improves its performance by processing and analyzing data (Webb et al., 2020). AI and ML applications are currently ubiquitous in everyday life; they have a positive impact in areas such as healthcare and education; they further mediate our social, cultural, and political interactions through, for example, search engines, voice and face recognition applications, recommendation systems, and personalized information in newsfeeds and social media (Rahwan et al., 2019; Webb et al., 2020). Concerns, though, have also been raised regarding the role, the challenges, and the limitations of AI and ML in areas involving ethical decisions, autonomous systems, and the delivery of information (Russell et al., 2015). AI education and literacy seems to be even more critical now. Children and young people need to be able to understand how AI and ML works and develop critical thinking skills for identifying the benefits and challenges of AI, access and assess information and data, and recognize cultural and social bias embedded in the design of AI systems (Hsu et al., 2018; Koltay, 2011). In this context, the goal of this chapter is to introduce a framework for the training and support of teachers regarding AI and ML education and literacy of primary and secondary education students. Our framework aims to address understanding of the technical aspects, the key elements, concepts, and principles of AI and ML such as Supervised Learning and Reinforcement learning, and also encourage critical thinking of students and teachers on the ethical, societal and cultural implications of AI. The role, the benefits, and the challenges of AI could become clearer and more meaningful to students and teachers if an interdisciplinary approach is adopted, highlighting the links between AI and a wide range of fields such as sustainable development, healthcare, economy, history, mathematics, and art (Rahwan et al., 2019; Vinuesa et al., 2020.) Therefore, our target group for this teacher training course was not only computer science teachers but also other school subjects such as History, Arts, and Literature. For our framework we considered the varied levels of AI or computer programming expertise and understanding of educators, and the diversity of disciplines and education levels. Work described in this chapter is situated in the context of the Erasmus+ Learn to Machine Learn project (LearnML) which aims to develop a framework and a toolkit of AI and ML education through game-based learning resources and activities. The LearnML project is a three-year Strategic Partnership in the field of Education aiming to produce an innovative solution for the teaching and learning of crucial 21st century skills relating to digital literacy, computational thinking, AI, and ML. In the framework of this project, the partners conducted workshops with teachers from primary and secondary education. The consortium developed a network of stakeholders and particularly educators, so as to engage in reflective discussions through meetings and workshops during the teacher training phase. This chapter describes the process and the results of the teacher training phase; the materials and resources used to further refine the teacher training process are further presented. The workshop participants’ ideas and concerns about AI and ML were recorded. Data collected, such as participant observation notes, facili-

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tators’ reports, surveys, the participants’ comments and responses, were analyzed qualitatively so as to identify main themes and patterns. Τhe scope of the chapter is to illustrate the outcomes from a project which has produced a number of AI-resources as a support to teachers for their class-based practice as well as offer insights and best practice recommendations to education stakeholders and policy makers. In this project we focus on the design of teacher training programmers, resources, and material to help teachers and students develop AI literacy skills and more broadly, digital literacy skills. Through the design and development of appropriate material, resources, and practices, the critical thinking and AI literacy skills of students and teachers on the factors that shape AI systems may be scaffolded. Appropriate material and resources may further provide not only awareness and knowledge of AI and ML implications, but also practical tools and ways to envision and bring about positive change, using AI and ML as drivers for systemic change.

BACKGROUND Over the past few years, research and educational practice in AI education have expanded. AI education is no longer limited to computer science graduate students and the technical aspects of AI, but further considers young students, and awareness of the ethical and societal implications of AI systems. For instance, in Kahn et al.’s (2018) study, 16-17 year old students explored AI concepts by developing AI applications using Snap!, and in Bilstrup et al.’s (2020) workshops, high school students reflected upon the ethical and moral dilemmas in ML systems, through a card-based game. Middle schoolers (12-13 years), in Vartiainen et al.’s study (2021), developed their own ML applications to solve real-world problems such as facilitate the work of the teachers or help people with special needs. Even younger children can explore abstract AI concepts through the appropriate methodologies and tools; 3-9 year old children developed their datasets and trained models using Google’s Teachable Machine (Vartiainen et al., 2020). PopBots is a toolkit and curriculum for teaching children aged 4-7 about AI through building and programming (Williams et al., 2019) and MIT developed a curriculum and learning material on AI, the technical concepts and relevant ethical implications, such as algorithmic bias, for middle school students (Payne, 2019.) Some countries have already started addressing this need for emphasis to AI in education, such as China that introduced AI into primary and secondary schools curricula, and USA through an initiative to develop an AI education framework for K-12, sponsored by the Association for the Advancement of Artificial Intelligence (AAAI) and the Computer Science Teachers Association (CSTA) (Webb et al., 2020). Introducing, though, advanced, abstract AI concepts to novices, younger students or students with limited computer science expertise, is challenging. The critical role of supporting material and the guidance of the teacher were discussed by Parker & Becker (2014) in their review of the learning effectiveness of the game “ViPER” aiming to teach ML to middle-schoolers. Teacher guidance may help students attain a better understanding of the concepts. Appropriate instructional design is also needed such as design-based pedagogies rooted in Papert’s constructionism, collaboration, active learning, and problem solving (Vartiainen et al., 2021.) In this context, the role of the educators is critical. It is important that primary and secondary education teachers have the knowledge, the skills, and the resources to support their students in developing AI and ML literacy skills. The role of the teachers is particularly important if we further consider the design and application of AI-enhanced education systems, involving student scoring, grading, selection, and management, and the emerging concerns about bias, representation, and 3

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inclusiveness of students from different backgrounds (Baker & Hawn, 2021). Research so far, though, has mainly focused on approaches and practices for teaching the students. Few initiatives focus on teacher support, such as Camilleri et al.’s (2019) teacher’s guide which includes lesson plans, resources, and worksheets for AI education. Considering the critical role of the teachers and the educational approaches for the effectiveness of AI education in formal and non-formal education settings, we shift our focus to AI education for the teachers. In the next sections, we present our teacher training approach and preliminary insights from the teacher training courses implemented.

DESIGNING AND IMPLEMENTING THE TEACHER TRAINING COURSES The first step of our educational design for the teacher training courses was the discussion with stakeholders such as teachers, policy makers, researchers, and students. Nine focused reflective workshops were organized in the three partner countries (Malta, Greece, Norway) during 2019-2020, with 73 participants in total (51 adults such as teachers, university students, policy makers, researchers and 22 primary and secondary education students). The workshops included a short introduction on the main concepts of AI, discussions with the participants on their perceptions and attitudes towards AI, the requirements and learning objectives for an effective implementation of AI in formal education, and design of educational scenarios on AI education. Their duration was approximately 3 hours (see more details in Giannakos and Papavlasopoulou, 2020). Specifically, the design of these preliminary workshops was as follows: Phase 1 Introduction: Introductions of the participants, introduction to AI and ML, presentation of tools and games for learning about AI and ML, presentation of AI applications and relevant implications (e.g., social media, fake news, ethics, the algorithms “hidden” behind the use of internet.) Phase 2 Discussion with the Participants: Participants were asked to record their answers (e.g., using pen and paper, or discussion) on the current state in schools for the implementation of AI education in the classroom, the potential learning objectives for AI education, challenges, and requirements of infrastructure, and teacher and student skills. Phase 3 Design of learning scenarios: The participants worked in groups of 3-4 and designed a potential educational scenario (lesson plan) for classroom implementation. Focusing specifically on the educators’ requirements, we examined their responses regarding the current state in schools, AI topics and implications, and their perceptions and attitudes towards AI. The main themes that emerged, which we further considered for the design of the Teacher Training Course, were: •

•

4

Enhance and support the participants’ knowledge and understanding of AI and ML regarding the technical aspects, the ethical, social, and personal implications, and everyday life applications of AI. Teachers, except for IT teachers, lack knowledge on IT and programming. Considering that AI literacy and education is a cross-curricular topic for primary and secondary education, particular attention should be paid to the more technical topics such as algorithms, and AI and ML functions. Guide the educators to the design of relevant lesson plans, considering the existing curricula and their students’ background and interests. Students may come from different backgrounds, with varied skills and expertise in coding and AI systems. Existing curricula do not include AI and ML, and even IT courses may be limited to a few hours each week, particularly in primary education.

 Artificial Intelligence and Machine Learning Education and Literacy

•

•

Provide them with resources they can readily use in their classes such as games, reading material, online tools, examples of applications. Infrastructure (computers, tablets) is often limited, especially in public schools. Resources for licensed software can be limited, restricting teachers and students to software and tools freely available, with low processing requirements. Listen to the teachers’ insights, needs, requirements, concerns, and consider them for the design of the material as well as for our suggestions for the implementation of AI education in formal education curricula. The theme of a bottom-up approach for the design of material and curricula and the consideration of the needs of students and teachers were recurring themes in these workshops.

The Teacher Training Courses were designed with these considerations in mind. Due to the COVID-19 restrictions, the courses had to be held online. For this purpose, the process, material, and activities had to be designed accordingly. After the initial Teacher Training Course design, focus groups and a pilot course were conducted with primary and secondary education teachers from a project partner school in Greece. This allowed us to adjust our course design considering the teachers’ insights about online training, their needs, and the introduction of AI-related concepts and themes. Specifically, as it emerged from the pilot course and focus groups, emphasis should be put on the familiarization of the teachers with the educational scenarios and their implementation in the classroom. One of the main challenges was the active engagement of the participants for creating new content based on skills and knowledge they acquired during the workshops. This had to be balanced with the duration of the courses; longer or multiple sessions would be very demanding for teachers during the pandemic, combined with the online teaching during lockdowns. In the next sections, the training course design is discussed, as well as the findings and insights from its implementation in the three partner countries.

Teacher Training Course Design: Implementing AI Education in Primary and Secondary Schools The main emphasis in the design and content of the courses was on the background information about AI and ML the familiarization of the participants (educators) with the concepts, and practical examples of materials, tools, and activities. In each iteration of the course, we tried to adapt the pace and content to the profile and background of the participants, after examining their previous experience and attitudes towards AI and ML. In this section, the design of the course is described. For an outline, see Table 1. Examining the participants’ profile: The participants are asked to complete an introductory survey about their background and profile. These background information help adapt the presentation and activities to the profile of the participants. For instance, if the participants are history or preschool teachers, relevant examples, applications, activities, and scenarios are presented and discussed; or if AI expertise is low, the technical aspects of AI are discussed more in detail. Exploring the participants perceptions of AI: The participants are asked to describe their perceptions about AI, what they know so far, and any examples of AI applications they may be familiar with. This step provides more insights on the potential gaps or misconceptions about AI and acts as a bridge for the next step, the presentation of AI concepts and applications. Presentation of AI concepts, applications, and implications: The participants are introduced to the meaning of AI, examples of applications, concepts of ML such as Supervised Learning, Reinforcement Learning, algorithms, training data, and testing data. The facilitators, considering the results of the initial surveys, introduce and discuss the following themes: 5

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• • •

•

Examples of AI applications such as recommendation systems (e.g., YouTube, Netflix), voice and image recognition applications, search engines, personalized information in newsfeeds and social media, self-driving vehicles Definition of AI and ML concepts, features, and elements such as reinforcement learning, supervised learning, training dataset, testing dataset, learning rate, use experience, exploration, rewards, labeling (data) Presentation of positive and negative social, cultural, and ethical implications of AI and ML and potential issues and challenges emerging, for instance, regarding diagnosis systems in healthcare, grading systems in education, work-automation, autonomous cars or weapons, filter bubbles, disinformation Tools, applications, software, and games for teaching AI and ML to students (see more details in the section Materials.)

Playing games about AI: Participants are introduced to the games developed in the framework of the project (see more details in the section Materials.) The games are available online and aim to teach concepts of Supervised Learning, Reinforcement Learning, and neural networks. They are separated into groups (e.g., 3-6 members per group depending on the total number of participants.) The groups join the dedicated virtual rooms and play the games. The participants then discuss about the games and their potential. Educational scenarios about AI and ML: Presentation of indicative educational scenarios (lesson plans) of AI education, and discussion with the participants. Scenarios for primary and secondary education are presented to the teachers. The scenarios constitute the basis for a semi-structured discussion with the participants regarding the structure, the learning goals, the relevant learning subjects, their potential for use in the classroom, possible adjustments that need to be made, links to existing curricula, relevance to their students’ background and interests. The goals of this session are to familiarize the teachers with the design of educational scenarios and school activities for AI education, and to provide insights on the opportunities and challenges for the integration of AI literacy in formal education settings Adapting an Educational Scenario: Participants are working in groups, using a shared document or whiteboard, to adapt an existing educational scenario. They are given two scenarios from the guidebook on AI education by Camilleri et al. (2019) and are asked to adapt them for their students. The main questions were: Which scenario would you use in your classroom? What changes would you do in order to adapt it in your classroom? Specifically, the educational scenarios provided were the “Rock, Paper, Scissors” and “Making Machines Learn”. The participants are asked to note their teaching subject, curriculum objectives, and country they teach in. The goal of this activity is to explore how AI and ML education can fit into existing curricula and scaffold the practical experience of the teachers. After the group activity, the participants are gathered back to the main room of the video conferencing environment and present their adapted scenarios. Designing an Educational Scenario: This is a group session, with the groups in their own dedicated virtual rooms and a shared document or whiteboard. Each group is given an educational scenario template and design a scenario for the classroom. Ideally, the groups consist of educators of the same teaching subject. Otherwise, they may try to collaboratively create an interdisciplinary scenario which could be applied to different teaching subjects with small alterations. After the activity, participants return to the main room, they present their scenarios, and peer-assess them focusing specifically on the learning goals and procedure. 6

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Exploring Change in Teachers’ Perceptions of AI: Repeating the process and questions of “Step 2 Exploring the participants perceptions of AI” (i.e., How would you describe what Artificial Intelligence is? Do you use any AI applications?), with a new response form. The responses will allow for a comparison between the perceptions of the teachers before and after the course, as a tool to assess its effectiveness. Alternatively, the responses may be posted on the chat channel. Table 1. Outline of the online teacher training course design No.

Step

Description

Materials

Time

Examining the participants’ profile

The participants are welcomed and are asked to complete a short survey. Results of this survey help adapt the content and pace of the course.

• Online survey using tools such as Google Forms. Questions about gender (for demographic reasons), years of teacher experience, specialty/field, their AI expertise (5-point scale)

5 minutes

2

Exploring the participants’ perceptions of AI

Mapping background on AI of the participants. Basis of discussion and presentation in next step.

• Online survey using tools such as Padlet, Google Forms, or the chat channel of the video conferencing system. Questions: How would you describe what Artificial Intelligence is? Do you use any AI applications?

5 minutes

3

Presentation of AI concepts, applications, and implications

Presentation of AI concepts, applications, social implications, examples of educational material.

• Presentation

20 minutes

4

Playing games about AI

Group activity Playing the games on AI developed by LearnML partners Feedback and debriefing.

• ArtBot game • Evolutionary Cars game • Evolutionary Flappy Bird game

20 minutes

5

Educational scenarios about AI and ML

Presentation of indicative educational scenarios (lesson plans) of AI education, and discussion with the participants.

• Presentation of the template and indicative scenarios from Camilleri et al. (2019)

15 minutes

20 minutes

1

6

Adapting an Educational Scenario

Group activity Participants adapt an existing scenario for their classrooms.

• The scenarios “Rock, Paper, Scissors” and “Making Machines Learn” from Camilleri et al. (2019) • A shared document or whiteboard for each group • Main questions: Which scenario would you use in your classroom? What changes would you do in order to adapt it in your classroom?

7

Designing an Educational Scenario

Group activity Participants design an educational scenario.

• Template of educational scenario • Shared document or whiteboard for each group

30 minutes

8

Exploring Change in Teachers’ Perceptions of AI

Exploring potential shifts in the perceptions of the teachers before and after the course.

• A new online survey using tools such as Padlet, Google Forms, or the chat channel of the video conferencing system. Questions: How would you describe what Artificial Intelligence is? Do you use any AI applications?

5 minutes

9

Conclusions and end of workshop

Total: 130 minutes

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Materials In this section, the materials used in the course, such as presentations, tools, games, are described.

Background Information The presentation included examples of AI applications such as YouTube, Netflix, smart homes, face recognition, social media (e.g., Facebook, Instagram), spam email recognition, Siri, Alexa, Google search, self-driving cars. Their features and the role of AI were discussed. The terms Artificial Intelligence, Machine Learning, Supervised Learning, Reinforcement Learning, data, training set, testing set, classification, rewards, punishment, learning rate, use experience, and exploration were defined. Implications such as algorithmic bias (e.g., in face recognition systems), human bias in data, bias against gender and social status, equal representation and access, spread of information in social media, filter bubbles based on personalized interests, decision making and accountability for self-driving vehicles and weapons were presented as issues for further reflection both at a personal and at a societal level. Tools, applications, software, and games for teaching AI and ML to students were presented and more specifically: the Teachable Machine (Teachable Machine, n.d.), Microsoft’s Project Malmo involving Minecraft (Project Malmo, n.d.), Semi-Conductor (Semi-Conductor, n.d.), Minecraft. Hour of Code: AI for Good (Minecraft Hour of Code, n.d.), Machine Learning for Kids (Machine Learning for Kids, n.d.), The Moral Machine (Moral Machine, n.d.), Akinator (Elokence.com, n.d.), Quick Draw! (Quick, Draw!, n.d.), and AI for Oceans (AI for Oceans, n.d.).

Digital Games The following games were developed in the framework of the LearnML project, by project partners. ArtBot: The aim of the game is to introduce players to core principles and concepts of Artificial Intelligence. Players have the quest to find and retrieve valuable art objects that have been stolen and hidden. Through the first part of the game, the process of supervised learning is introduced; players train their AI helper to recognize specific art objects (i.e., paintings and sculptures). They classify a set of training data, experiment with different parameters, and then see how well the helper was trained by observing how it classifies a set of testing data (see Figure 1.) This is where the players teach their helper to recognize which objects they are looking for. During the second part of the game, the players and their AI helper need to navigate through a series of dungeons, locate, and collect the stolen art objects. In this part, the players are introduced to the processes of reinforcement learning; they guide their helper by indicating what type of objects to look for and which ones to avoid (e.g., traps), by assigning rewards to the right objects. The AI helper tries to find its path based on the parameters set by the players, such as the exploration and exploitation rates. The players watch the process, they can pause or accelerate it, and think what the optimal settings would be for helping the AI find as many objects as possible. The game was designed by a team of educators, game developers, and AI experts with the aim to support AI literacy of primary and secondary education students. Beyond the technical aspects of AI, our goal was to trigger the critical thinking of players on the aspects, factors and bias that may shape the architecture and behavior of AI agents and systems. The game guides the player through a set of actions, but also provides opportunities for exploration, experimentation, and reflection; players are encouraged to construct their knowledge by observing the outcomes of their actions, evaluate the results, make, and 8

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test their hypotheses. Through the design of the game, we tried to avoid common stereotypes and address students’ misconceptions of AI, such as the anthropomorphic nature of AI systems - the AI helper is an unidentified artifact rather than a robot. Players, though, have the option to choose and modify the avatar of the AI helper. By setting the game in the context of cultural heritage (art objects) our aim was to address the application of AI systems in multiple different areas, beyond computing and programming, such as archaeology, art, and transportation (see also Voulgari et al., 2021; Zammit et al., 2021.) The game is available at http://art-bot.net/ Figure 1. Interface of the ArtBot game; the players classify cultural artifacts and train their AI agent

Evolutionary Cars: This game (original version by Coding Train, 2021) demonstrates how evolutionary algorithms can guide a virtual car along an unknown racetrack (see Figure 2). The game starts with a population of 100 cars, each of them equipped with a separate neural network; as the cars try to navigate, they utilize a number of virtual sensor inputs, providing them with their distance from the edge of the track. Based on this, they choose their speed and whether they should turn towards their right or left, so as to avoid hitting the track boundaries and get eliminated. The initial parameters of the neural networks which decide each car’s route are random; as a result, some of them survive for a longer period. As soon as all cars are eliminated, the algorithm creates a new generation, based on the best performing cars, and slightly alters their neural network brains (as per the evolutionary strategy of this approach). As generations progress, the self-driving cars become better in navigating across the given track and are quite competent when presented with a previously unseen one. When interacting with the game, players can change the speed of the cars (mostly related to viewing their course, not with the actual calculations), the mutation rate (i.e., the percentage of the neural network parameters evolved with each generation, affecting the speed of the evolution process), the life span of each car (the amount of frames or calculated decisions after which each car is forcibly eliminated to trigger evolution) and the sight range (how far each virtual sensor can ‘see’ the track boundaries). As a general rule, these parameters affect how quickly and efficiently the evolution process will generate a self-steering car; it makes sense that tracks with sharper turns require more evolutionary generations to adapt the initial random neural network, since it would take more complex and advanced maneuvers to navigate across these turns.

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Figure 2. Interface of the adapted Evolutionary Cars game; the different controls adapt the behavior of the algorithm

Evolutionary Flappy Bird: Evolutionary Flappy Bird (original version from Geektoni, 2021) is based on the popular “Flappy Bird” mobile and web game and uses an evolutionary algorithm to create a bot that plays without any human input or competes with human players (see Figure 3). This implementation starts with a population of 30 birds, again equipped with a randomly initialized neural network brain, which try to navigate an obstacle course. The inputs to this neural network consist of the distance to the next pipe, the flight altitude, the position of the space between the pipes through which the birds are supposed to navigate, and the speed of vertical motion of the pipes (if any). With each game frame, birds choose to flap their wings and fly higher or change their course with gravity and go lower; if a bird crashes into the ground or one of the vertical pipes, it is eliminated from the current generation (Karpouzis & Yannakakis, 2016). Figure 3. Evolutionary Flappy Bird interface

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Again, some of the birds survive for a longer distance; the next generation will be based on the neural networks guiding those birds, slightly evolved to cater for a possibly better performance. After a number of generations, the evolved self-flying birds can navigate across every pipe pattern, even those that require abrupt changes in their flying pattern. This game allows players to experiment with different parameters, and also compete against evolved bot-birds (Human vs AI option). They can also enter an “Impossible” game mode, where pipes move up and down, making navigation harder or “Freeze Weights” and store the neural network evolved up to that point, using that in head-to-head competition.

A Case Study Implementation of the Teacher Training Courses The courses were implemented from May until September 2021, with a total of 194 participants, using the platforms Zoom, Microsoft Teams, and Cisco Webex. For a summary of the courses see Table 2. Athens Science Festival, online, Greece: the first two workshops were organized in the framework of the Athens Science Festival in March 2021. It is one of the most prestigious and popular science events for teachers and students in Greece. Due to the Covid-19 restrictions it was held online. In this event, students, teachers, and the public had the opportunity to explore scientific and technological advancements in an entertaining, innovative, and interactive way. The 2021 theme was “The Era of Heroes” and several researchers, scientists, educators, and artists communicated science concepts and current trends. AI was one of the major topics in this festival. Two training workshops were organized for teachers and a parallel session for students. Each workshop lasted two hours. More than 65 teachers had initially registered for these events. Seminar for teachers organized by the 3rd Secondary Education Office in Attika, online, Greece: Secondary Education Offices in Greece are under the jurisdiction of the Ministry of Education, and their role is, among others, to manage, coordinate, monitor, and assess schools and teachers within their area of control, supervise public and private schools, provide guidance and guidelines, and take initiative regarding the implementation of new technologies in education, such as the organization of seminars and workshops for teachers. Teacher training seems to be even more critical now, with the implementation of the “Skill Labs 21+” program by the Ministry of Education and Religious affairs (Institute of Educational Policy, Ministry of Education and Religious Affairs, Greece, 2022), introducing topics such as STEM, robotics, and digital literacy. The project partners were invited to organize a teacher training workshop on AI and ML in education which was held in May 2021. The interest of the teachers seemed to be quite high, as it was also commented by the organizers, officers of the Secondary Education Office. Although this was organized by a secondary education institution, primary education teachers -including preschool teachers- also participated, from various teaching fields such as Programming, Science, Philology, Art, Mathematics, Biology and Chemistry. They were mainly teachers from public schools with extensive teaching experience (N=66, M= 20.78 years). Previous experience and knowledge of AI was heterogeneous, since Programming and IT teachers were familiar with the concept and applications, while Social Sciences and Humanities teachers (Philology, Art, etc.) were not (M=2.27 in a 5-point scale.) Science Centre Pembroke, online, Malta: This teachers’ training webinar was organized in July 2021 by the Science Centre within the Directorate for Learning and Assessment Programmes (DLAP). The call for participation was distributed to the network of schools in Malta, and specifically to all heads of the college network and heads of primary, middle and secondary schools (state and non-state). Again, as discussed by the organizers, the interest and participation were high. Their teaching subjects included 11

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Computer Science, Mathematics, Primary Education, Economics, Biology, Maltese, and Ethics/Religion; their teaching experience was quite high as most of them had ten years of experience and three up to twenty years (N=21, M=13 years), and they reported having a medium experience and knowledge of AI and ML (M=2.43 in a 5-point scale). This session deviated slightly from the original time-schedule as approximately 45 minutes were dedicated to the presentation of main concepts, processes, and examples of AI to ensure that participants received an overview of the theory, before proceeding to the hands-on part of the webinar (i.e., games and educational scenarios). Teacher Training Course on Computing at the Norwegian University of Science and Technology (NTNU), online, Norway: The workshop took place in the framework of a teacher training course offered by the NTNU. The course offers programming as a subject and provides insight into how it can be used to create digital solutions. Over the past few years, the Ministry of Education in Norway has published a strategy requiring strengthening of digital skills, programming, and technology in all grades (from primary to upper secondary education) as elective courses and as cross-curricular subjects in Mathematics, Science, Music, and Arts and Crafts. This is particularly challenging for teachers lacking digital competences. This course was the basis for the students (i.e., teachers) who may take a follow up course focusing on how programming can be communicated to school students with a focus on creativity and collaboration in problem solving. The participants were teachers from all Norway, with extensive teaching experience (N=6, M=15,4 years), from varied teaching fields such Programming, English, Mathematics, Science, and Arts. They had little or no experience with AI and ML (M=1.80 in a 5-point scale), and they had never taught AI and ML concepts in their classrooms. 42 teachers participated in the workshop, while the material was disseminated to more than 200 students attending the course. The course was implemented in September 2021 and the duration was 45 minutes. Table 2. Summary of the Teacher Training Courses implemented in the three partner countries. The venue, number and profile of participants are outlined Venue

No. of Participants

Profile of Participants

55

• Primary and secondary education teachers • Most of the participants were Computer Science teachers but there were also teachers from science education, linguistics and arts

75

• Primary and secondary education teachers mainly in public schools • Variety of teaching subjects i.e., programming, science, philology, art, mathematics, biology, chemistry, language • More women than men • The majority had more than twenty years of teaching experience and only four participants had less than ten years • Most of the participants were not familiar or had medium knowledge of AI

Science Centre Pembroke, online, Malta

22

• Primary, middle, secondary education teachers, other stakeholders (e.g., heads of school, school inspectors, researchers) • From state, private, and church schools • Various teaching fields e.g., computing, technology, biology, mathematics, Maltese, English, French.

Teacher Training Course on Computing at the Norwegian University of Science and Technology (NTNU), online, Norway

42

• Teachers in Programming, English, Mathematics, Science, Arts • No or very little experience in AI and ML • Extensive teaching experience

Athens Science Festival, online, Greece (2 workshops)

Seminar for teachers organized by the 3rd Secondary Education Office in Attika, online, Greece

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INSIGHTS FROM THE IMPLEMENTATION OF THE TEACHER TRAINING COURSES For getting a better insight of the impact of the courses, a qualitative approach was adopted. The participants’ comments and responses were recorded and analyzed thematically for identifying the positive aspects, the challenges, and their suggestions in relation to the content and structure of the course, and the potential of AI and ML education in formal learning settings (Auerbach & Silverstein, 2003, p. 38.) The analysis of the comments was conducted independently by two researchers and after discussion, an agreement was reached concerning the categories that emerged (Campbell et al., 2013). The reports of the facilitators of the courses were also considered for shedding light to the process of the courses. Specifically, the three reports from the respective partners in the three countries were considered. We further examined the input of the participants prior and after the course for examining potential changes in attitudes and knowledge of AI applications. We describe our findings in relation to three axes: (a) the perceptions of AI and ML, (b) the evaluation of the course content and structure, and (c) the challenges for the implementation of AI and ML education in formal education.

Perceptions of AI and ML Their first responses about the description of AI were vague and superficial while few of them gave specific examples such as automated cars or robots. Nevertheless, in most of the comments, the participants attempted to give a definition of AI. Very few reported that they had no perception of what AI is. The comparison with and the metaphor of human cognition, behavior, and intelligence emerged as a recurring theme. Human-like characteristics were attributed to AI. In most of the comments, AI was described as a system, a piece of software, or a computer system that simulates human intelligence, behavior, or cognitive functions. Some indicative excerpts: Computer systems that mimic human behaviour in the fields of algorithmic thinking and learning. A machine that is capable of reproducing human functions and solve problems The way we can teach machines to react and behave like humans AI was mainly defined through its outcomes and specifically problem-solving and decision-making. The participants described AI as systems programmed or trained to solve problems or make decisions. For instance: The ability of the machines to make decisions A computer program that solves problems and simulates human senses and behaviour. Robotics also came up as a recurring theme. Teachers, particularly in the workshops in Greece, linked AI to robotics. AI was described as “applications of robotics” or “robots”. Very few responses included a more specific, objective, and technical definition of AI, as for example:

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Artificial intelligence (AI) is intelligence demonstrated by machines. Leading AI textbooks define the field as the study of intelligent agents: any system that perceives its environment and takes actions that maximize its chance of achieving its goals. When asked, though, about AI applications in their daily lives, most of the participants reported that they had no experience with AI, except for the teachers in Malta who reported more examples of AI applications. Indicative applications reported are: ChatBots, robotic cleaners, speech-to-text, Quickdraw, Thing Translator, autonomous cars, Amazon, Netflix, AI agents in games, Facebook, and Google Translate. When the perceptions of the participants about AI after the workshops were analyzed, the humanlike aspects had receded, and more specific definitions and terms emerged. The participants used terms such as algorithms, autonomy, predictions, data, training, machine learning, and rewards. Indicatively: AI is integrated in a machine which can process data and make decisions Training a machine to make decisions Furthermore, they were able to identify more AI applications they used in their daily lives. Although there were still negative responses (the participant reported that he/she had not used any AI applications), more examples of AI applications emerged such as: YouTube, Google, “too many”, text auto-completion, and face recognition. Indicatively, one of the teachers responded “Now that I know the variety of how AI is included, yes most apps I use are through AI”.

Evaluation of the Courses The interest of primary and secondary education teachers for the topic (AI education) was overwhelming in most cases; high numbers of teachers enrolled and participated in the teacher training events (e.g., in Greece, Workshop by Secondary Education Office, there were 115 initial registrations and 75 participated, and in Malta there were 43 initial registrations and 22 participated.) The participants’ comments on the chat channel or on shared whiteboards further indicated their interest in the topic and in similar courses and training in the future. Indicative comments: “You are giving us some wonderful ideas!!!”, “This was a particularly pleasant and definitely illuminating seminar. I would be happy to participate in the next one”. The participants seemed to have acquired a better grasp of AI and its implications. They commented that they received a general overview on what AI is, and they learnt more about concepts such as Supervised and Reinforcement Learning (e.g., “It helped us move away from the stereotype of artificial intelligence [equals] robot”.) Nevertheless, as also commented by participants and facilitators, the teachers need more training. As one of the facilitators reported “teachers are not yet prepared to incorporate AI concepts into their teaching practice”. The limited duration of the courses didn’t seem to allow for more in-depth discussion on the technical aspects, the social implications, and hands-on experience. It also did not allow for the participants to study the material, think, and design their own scenarios, as commented by facilitators and participants. One of the facilitators reported that “more emphasis on AI in education, readymade examples / scenarios / lesson plans that target specific curricular learning outcomes, and knowledge about AI per se” is needed. Another facilitator commented on the challenges of the online format and of the limited time “[…] participants were separated into breakout rooms in order to create 14

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their own scenarios, but this was not easy to happen because of the online situation and also because of the fact that each participant had a different background. As such, we discussed only their general ideas”. This comment further implies that the heterogeneity of the participants’ backgrounds presented additional challenges. They seemed to understand how education can be linked to the concept of AI, the significance of AI education, and the need to introduce AI education interdisciplinary; the teaching subjects the teachers mentioned were Mathematics, English, Computing, and also Social Sciences e.g., Philosophy, Linguistics, and History. They further linked AI education to digital literacy (“I believe that it promotes the empowerment of digital and critical literacy”.) They appreciated the ready-made material and scenarios and, as commented by a facilitator, “Teachers found it easy to use in their classrooms and some teachers from secondary education reported that they can use it for their early years of secondary education.” More scenarios and practical examples would though benefit teachers more. As commented by the participants “[we need more] semi-structured and structured lesson plans as inspiration to create our own lesson plans”. During the courses, in most cases, the participants took an active role; they engaged in discussion, asked questions, commented, and shared their experiences and insights. The examples of AI applications triggered their interest. For instance, as one facilitator reported, the Moral Machine triggered discussion about Reinforcement Learning and autonomous vehicles, as well as the ethical implications and dilemmas emerging. The game AI for Oceans and a relevant lesson plan triggered discussion on its potential to be used in primary and early childhood education to introduce children to the process and implications of Supervised Learning. The lesson plans, the practical examples, and the applications were helpful and interesting for the participants and motivated them to engage in “reflective comments on how they can use the educational scenarios in their classrooms”, as commented by a facilitator.

Challenges for the Implementation of AI and ML Education in Formal Education For identifying the challenges, the participants’ and facilitators’ comments were reviewed. Three main themes emerged: (a) public policy, (b) teacher training, and (c) school culture. More specifically, the public policy for education and the curriculum may provide challenges and opportunities. Not all three countries had equivalent education policies and conditions. When new policies for promoting digital skills for students are introduced, such as the new IT and coding strategy in Norway and the “Skill Labs 21+” program in Greece, they present new challenges for the teachers who lack digital skills and educational material but also provide the framework for integrating AI education in the classroom. Even when an IT and coding curriculum is established, further specialization to AI literacy is needed; as one of the facilitators reported “[a public policy for AI in education] would provide guidelines to support innovative ecosystems to nurture opportunities of AI in the field of education”. Another aspect of the curriculum and the public policies commented by the participants was the exam-oriented culture of the education system; a system that focuses on exams and tests results as the main form of student assessment, specifically in secondary education, seems to constraint educators and limit flexibility for the implementation of more innovative approaches and subjects. Following up on the lack of digital skills and materials mentioned, the “professional preparation of teachers/educators for AI powered education” constitutes a “major challenge” as reported by one of the facilitators. Certainly, more teacher training and educational material are needed for the effective integration of AI education in formal education. Teachers seem to be willing to expand their skills and 15

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explore new and current topics with their students. Proper training, supporting material, concrete lesson plans and activities that are flexible with alternative options (e.g., as one time activity for an academic hour, or as self-study as part of a lab hour) and with the option to integrate them in different standard curricula subjects, are crucial factors and prerequisites for AI education in the classroom. The multidisciplinary aspect of AI, involving different disciplines such as IT, history, ethics, mathematics, arts, and language, can only be addressed by the collaboration of educators from different teaching fields, for example the collaboration of the IT teacher with the Arts teacher. School culture and the educational system may not always facilitate such collaborations, as reported by the participants. A culture, as well as opportunities for collaboration, are needed, providing the infrastructure, the time, and the space to the teachers to design and implement such interdisciplinary projects. Communities of practice for the exchange of knowledge, expertise, and insights was also among the suggestions of the participants. They expressed the need to participate in an ongoing dialogue with the community of teachers and researchers involved in AI education, as this would facilitate their work, allow them to solve problems, get ideas and inspiration, and share their practices. Other issues that emerged, mainly from participants and facilitators in Malta, were data privacy and security, and the establishment of a centralized institution for AI education. Specifically, it was commented that “Investment in AI research to establish a national academic centre of excellence in AI, scholarships and research network” is needed, and “Data privacy and security is the immediate question that comes up in any discussion regarding data ethics. The challenge lies in using personal data while ensuring the protection of individual privacy preferences and personally identifiable information”.

DISCUSSION AND CONCLUSIONS This chapter focused on the design and implementation of a teacher training course for AI education in primary and secondary education. We presented the design of the course and insights from its implementation in different settings. Even though the online format of the workshops restricted the hands-on participation and the interactions among facilitators and participants, we found that it allowed for a higher participation of teachers from various, and even remote areas of the partner countries. The heterogeneity of participants presented certain opportunities and challenges. It allowed for a richer dialogue and exchange of knowledge, expertise, insights, and ideas among teachers from different disciplines, different education levels (primary and secondary), and different IT and AI expertise levels. But it also called for adjustments in the content and pace of the presentation of theory and background information and presented difficulties in the collaborative design of lesson plans. This can probably be addressed by the separation to homogeneous groups during the collaborative lesson plan design phase, when possible. Although this was in our original considerations during the design of the courses, it was not always possible due to the large numbers of participants and the time constraints. This heterogeneity, though, was among our objectives for highlighting our multidisciplinary approach to AI education involving multiple fields, and for establishing a dialogue among the educators as a basis for a community of practice. In many cases, the interest of the participants was accompanied by a lack of confidence in their competences to support the students in this topic, or by superficial knowledge and by concerns about AI and its role in the students’ lives and society. Teachers from primary and secondary education, and particularly non-IT teachers, do not feel confident yet to explore concepts of AI and ML with their students. 16

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They seemed willing to implement AI education activities in their classrooms, provided that they could have more training and supporting educational material. Regarding the courses, enough time needs to be allocated to the presentation of the background material, practical examples, study of material by the educators, and hands-on training and experience in the design of learning activities relevant to their field. Certainly, our findings regarding the attitudes of teachers towards AI education cannot be generalized to the population of teachers in all countries. The sample is rather biased, since the participation in the courses was voluntary, and probably mainly teachers already interested in the topic and open to new themes and approaches participated. Most of the courses, though, were advertised through open calls to communities and networks of teachers, and participation was free and open to all. This allowed us to attract a wide and varied audience and identify issues that may be relevant to educators of different backgrounds and settings. To summarize the themes that emerged from this study regarding the design and implementation of teacher training courses in AI education: • • • •

• •

The teacher training courses raised awareness of the teachers on AI applications, and the role and implications of AI to daily life. The courses should promote discussions and the development of communities of practice, for the exchange of good practices or challenges. Opportunities for a dialogue among teachers of different disciplines and expertise levels are needed. This would facilitate further collaboration, necessary for a multidisciplinary approach in AI education. The presentation and provision of a wide range of practical examples such as lesson plans, activities, and materials, ready to be used or adapted for the classroom is essential. The examples should be simple, and relevant to teachers and students of different AI expertise, digital skills, levels of education, and subjects. Emphasis and time should be allocated for practical, hands-on activities by the teachers, specifically in the design of lesson plans which can be later used in real classroom settings. Lesson plans and materials should be linked to the established curricula and to specific learning goals for students of different age groups. This would facilitate integration of AI education in different settings and learning subjects.

This was an initial exploration of insights based on participants’ and facilitators’ comments. The main goal of this chapter was to introduce an approach for the design of teacher training courses for the implementation of AI education and literacy in formal education. Certainly, further implementation of teacher training courses, development of educational material, and systematic research is needed, but hopefully considerations and requirements were identified and discussed for the establishment of a framework to support and facilitate AI education and literacy of teachers and students.

ACKNOWLEDGMENT This work is supported by the “Learn to Machine Learn” (LearnML) project, under the Erasmus+ Strategic Partnership program (Project Number: 2019-1-MT01-KA201-051220). The authors would like to thank the participants, the organizers, and the facilitators of the workshops, Josmar Borg for organizing

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the Malta teachers’ training, Georgios Yannakakis, Desiree Scicluna Bugeja, and Sofia Papavlasopoulou for coordinating this project.

REFERENCES AI for Oceans. (n.d.). Code.Org. Retrieved 1 February 2022, from https://code.org/oceans Auerbach, C., & Silverstein, L. B. (2003). Qualitative Data: An Introduction to Coding and Analysis. NYU Press. Baker, R. S., & Hawn, A. (2021). Algorithmic Bias in Education. EdArXiv. doi:10.35542/osf.io/pbmvz Bilstrup, K.-E. K., Kaspersen, M. H., & Petersen, M. G. (2020). Staging Reflections on Ethical Dilemmas in Machine Learning: A Card-Based Design Workshop for High School Students. Proceedings of the 2020 ACM Designing Interactive Systems Conference, 1211–1222. doi:10.1145/3357236.3395558 Camilleri, V., Dingli, A., & Montebello, M. (2019). AI in Education A Practical Guide for Teachers and Young People. Department of AI, University of Malta. http://learnml.eu/docs/AI_in_Education.pdf Campbell, J. L., Quincy, C., Osserman, J., & Pedersen, O. K. (2013). Coding In-depth Semistructured Interviews: Problems of Unitization and Intercoder Reliability and Agreement. Sociological Methods & Research, 42(3), 294–320. https://doi.org/10.1177/0049124113500475 Elokence.com. (n.d.). Akinator. Retrieved 1 February 2022, from https://en.akinator.com/ Geektoni. (2021). GitHub - geektoni/evolutionary-FlappyBird: Playing the (in)famous Flappy Bird game using NEAT and Differential Evolution. GitHub. Retrieved February 2, 2022, from https://github.com/ geektoni/evolutionary-FlappyBird Giannakos, M., & Papavlasopoulou, S. (2020). IO1: A LearnML Pedagogical Framework Development (Intellectual Output 1). Technical Report, Learn to Machine Learn (LearnML), Erasmus+ Project. Hsu, T. C., Chang, S. C., & Hung, Y. T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126, 296–310. https://doi. org/10.1016/j.compedu.2018.07.004 Kahn, K. M., Megasari, R., Piantari, E., & Junaeti, E. (2018). AI programming by children using Snap! Block programming in a developing country. https://ora.ox.ac.uk/objects/uuid:9a82b522-6f9f-4c67b20d-be6c53019b3b Karpouzis, K., & Yannakakis, G. N. (2016). Emotion in Games. Springer. Koltay, T. (2011). The media and the literacies: Media literacy, information literacy, digital literacy. Media Culture & Society, 33(2), 211–221. https://doi.org/10.1177/0163443710393382 Machine Learning for Kids. (n.d.). Retrieved 1 February 2022, from https://machinelearningforkids.co.uk Minecraft Hour of Code. Facilitator Training 2019. (n.d.). Microsoft Educator Center. Retrieved 1 February 2022, from https://education.microsoft.com/en-us/course/beb9828a/0

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Moral Machine. (n.d.). Moral Machine. Retrieved 1 February 2022, from http://moralmachine.mit.edu Parker, J. R., & Becker, K. (2014). ViPER : Game That Teaches Machine Learning Concepts—A Postmortem. 2014 IEEE Games and Entertainment Media Conference (GEM), 5. Payne, B. H. (2019). An Ethics of Artificial Intelligence Curriculum for Middle School Students. MIT Media Lab. Retrieved 13 April 2021, from https://www.media.mit.edu/projects/ai-ethics-for-middleschool/overview/ Project Malmo. (n.d.). Microsoft Research. Retrieved 1 February 2022, from https://www.microsoft. com/en-us/research/project/project-malmo/ Quick, Draw! (n.d.). Retrieved 1 February 2022, from https://quickdraw.withgoogle.com/ Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J.-F., Breazeal, C., Crandall, J. W., Christakis, N. A., Couzin, I. D., Jackson, M. O., Jennings, N. R., Kamar, E., Kloumann, I. M., Larochelle, H., Lazer, D., McElreath, R., Mislove, A., Parkes, D. C., & Pentland, A., … Wellman, M. (2019). Machine behaviour. Nature, 568(7753), 477–486. doi:10.1038/s41586-019-1138-y Ray Casting. (2021). Coding Train. Retrieved February 2, 2022, from https://codingtrain.github.io/ NeuroEvolution-Vehicles/ Russell, S., Dewey, D., & Tegmark, M. (2015). Research Priorities for Robust and Beneficial Artificial Intelligence. AI Magazine, 36(4), 105. https://doi.org/10.1609/aimag.v36i4.2577 Semi-Conductor. (n.d.). Retrieved 1 February 2022, from https://semiconductor.withgoogle.com/ Teachable Machine. (n.d.). Retrieved 1 February 2022, from https://teachablemachine.withgoogle.com/ Vartiainen, H., Tedre, M., & Valtonen, T. (2020). Learning machine learning with very young children: Who is teaching whom? International Journal of Child-Computer Interaction, 100182. doi:10.1016/j. ijcci.2020.100182 Vartiainen, H., Toivonen, T., Jormanainen, I., Kahila, J., Tedre, M., & Valtonen, T. (2021). Machine learning for middle schoolers: Learning through data-driven design. International Journal of ChildComputer Interaction, 29, 100281. https://doi.org/10.1016/j.ijcci.2021.100281 Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., & Fuso Nerini, F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature Communications, 11(1), 233. https://doi.org/10.1038/s41467-019-14108-y Voulgari, I., Zammit, M., Stouraitis, E., & Liapis, A. (2021). Learn to Machine Learn: Designing a Game Based Approach for Teaching Machine Learning to Primary and Secondary Education Students. Interaction Design and Children, 593–598. doi:10.1145/3459990.3465176 Webb, M. E., Fluck, A., Magenheim, J., Malyn-Smith, J., Waters, J., Deschênes, M., & Zagami, J. (2020). Machine learning for human learners: Opportunities, issues, tensions and threats. Educational Technology Research and Development. doi:10.1007/s11423-020-09858-2

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Williams, R., Park, H. W., Oh, L., & Breazeal, C. (2019). PopBots: Designing an Artificial Intelligence Curriculum for Early Childhood Education. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9729–9736. https://doi.org/10.1609/aaai.v33i01.33019729 Zammit, M., Voulgari, I., Liapis, A., & Yannakakis, G. (2021). The Road to AI Literacy Education: From Pedagogical Needs to Tangible Game Design. Proceedings of the European Conference on Games Based Learning, 10.

ADDITIONAL READING Druga, S., Vu, S. T., Likhith, E., & Qiu, T. (2019). Inclusive AI literacy for kids around the world. Proceedings of FabLearn, 2019, 104–111. doi:10.1145/3311890.3311904 Giannakos, M., Voulgari, I., Papavlasopoulou, S., Papamitsiou, Z., & Yannakakis, G. (2020). Games for Artificial Intelligence and Machine Learning Education: Review and Perspectives. In M. Giannakos (Ed.), Non-Formal and Informal Science Learning in the ICT Era (pp. 117–133). Springer. doi:10.1007/978981-15-6747-6_7 Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2021). Ethics of AI in Education: Towards a Community-Wide Framework. International Journal of Artificial Intelligence in Education. Advance online publication. doi:10.100740593-021-00239-1 Voulgari, I., Zammit, M., Stouraitis, E., Liapis, A., & Yannakakis, G. (2021). Learn to Machine Learn: Designing a Game Based Approach for Teaching Machine Learning to Primary and Secondary Education Students. Interaction Design and Children, 593–598. doi:10.1145/3459990.3465176 Webb, M. E., Fluck, A., Magenheim, J., Malyn-Smith, J., Waters, J., Deschênes, M., & Zagami, J. (2020). Machine learning for human learners: Opportunities, issues, tensions and threats. Educational Technology Research and Development. Advance online publication. doi:10.100711423-020-09858-2 Yannakakis, G. N., & Togelius, J. (2018). Artificial intelligence and games (Vol. 2). Springer. doi:10.1007/978-3-319-63519-4 Zammit, M., Voulgari, I., Liapis, A., & Yannakakis, G. (2021). The Road to AI Literacy Education: From Pedagogical Needs to Tangible Game Design. Proceedings of the European Conference on Games Based Learning, 10.

KEY TERMS AND DEFINITIONS Artificial Intelligence: the study of computational processes that attempt to mimic what humans do across several tasks including behavior, pattern recognition, decision making, cognitive processing, and emotion recognition.

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Artificial Intelligence (AI) Literacy: AI literacy involves skills and competencies for using AI technologies and applications as tools, viewing them critically, understanding their context and embedded principles, and questioning their design and implementation. Educational Scenario (Lesson Plan): A structured plan detailing the process, steps, content and learning objectives of a lesson or a course. It supports and guides the educators through the teaching process. Evolutionary Algorithm: A global optimization type of algorithm inspired by the Darwinian evolution of living organisms that aims to solve problems through the evolution of a population of solutions to a given task. Machine Learning: Machine Learning is a field of Artificial Intelligence through which a computing process progressively adapts and improves its performance in a specific task or set of tasks, by analyzing large amounts of data. It largely involves the paradigms of unsupervised, supervised and reinforcement learning. Reinforcement Learning: Reinforcement learning is a machine learning paradigm in which the algorithm learns through rewards and penalties. The system learns to take actions that maximize its rewards (or minimize its penalties) by interacting with an environment that provides such rewards and penalties. Supervised Learning: Supervised Learning is a machine learning paradigm in which the system processes examples of data belonging to different categories (for example images of cats, dogs, or humans) and identifies similarities and differences among them so as to learn to identify the category of unseen data.

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Chapter 2

An Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines Anastasia Korompili University of Piraeus, Greece Kostas Karpouzis Panteion University of Social and Political Sciences, Greece

ABSTRACT This research examines the design, implementation, and impact of an educational robotics intervention for first and second grade students. It controls for gender-related performance differences and compares the interest shown towards robotics. The authors also examine if factors such as students’ stance towards different professions can contribute to a difference in performance. In the course of its work, custom designed worksheets for the UARO educational robotics product were used, as well as questionnaires given to students after meetings. The results showed that all genders responded equally well and with the same enthusiasm to the robotics activities and understood concepts of physics, mechanics, and mathematics through them. Participants differ in how they use their leisure time and in their professional orientation; however, this didn’t affect their performance in the robotics activities. These results highlight the need for further examination of the social institutions and factors that influence the formation of gender orientations during the early childhood age.

INTRODUCTION Means and approaches in childhood education advance and evolve rapidly, empowered by internet and social media connectivity, as well as the abundance of inexpensive, readily available technology; Friedman states that innovative tools may enter our lives as quickly as every six months (Friedman, 2012). DOI: 10.4018/978-1-6684-3861-9.ch002

Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

In this context, research conducted as early as 1980 shows that girls fall behind in distance learning and using educational software, and this may be attributed to the stereotype of technology being a boys-only activity (Hilbert, 2011). This early gender gap leads to an even wider gap in STEM-related studies, which only worsens in academia and high-level job posts related to Science and Engineering, even though the interest shown by girls has increased recently (Makarova et al., 2019). In order to tackle the STEM gender gap issue, many research and development efforts have focused on primary and secondary education. However, there are only a few approaches fit to be deployed in preschool and early childhood (Sullivan, 2016). In our work, we investigate gender differences with respect to interest and performance in STEM in children aged 6-7, as well as students’ outlook on STEM-related professions, in general. To this end, we designed and tested a set of robotics and make-ing activities using RoboRobo’s UARO platform [http://www.uaroedu.com/en] . We opted to use an educational robotics platform, assorted with simple engineering and make-ing activities, since research has shown that it can be used to advance cognitive and teamwork skills to young children, besides technical and scientific subjects (Malatesta, 2009). More specifically, a wide range of experiments and tasks can be built using an educational robotics platform, including introducing students to algorithmic thinking and problem solving; such activities typically also require interaction and cooperation between students, leading to their use as a team building activity (Nugent et al., 2014). With respect to ‘hard’ STEM skills, educational robotics have been used to teach Physics, Mathematics and Geometry, Engineering and Technology, History, and also interdisciplinary subjects, such as STEM combined with art or environmental studies. Beyond these disciplines, educational robotics have been associated with a number of ‘soft’ skills, both cognitive and emotional/social (Cowie et al., 2008; Cowie et al, 2011). Often termed ‘21st century skills’, these include teamwork, problem solving (analysis, design and development of solutions, experimentation, and evaluation), innovation, project management and scheduling, communication and creativity. The pedagogical contribution of educational robotics is consistent with Piaget’s theory of affective and cognitive development (Richmond, 2013), who suggested that learning is an active process of constructing knowledge based on experiences from the real world; it also matches Vygotsky’s philosophy of Constructivism (Liu, 2005) with respect to the social dimension of constructing knowledge. In essence, both theories assume that learning is based on the experiences of students, their pre-existing knowledge, and the ways to organize emerging learning experiences (Jonassen, 2000): in its foundation, constructivism includes rich, user-focused interaction, dealing with authentic problems to be solved, cooperative learning and the teaching experience of building new knowledge. Educational robotics is especially instrumental to this approach, since it involves building and manipulating a tangible object or simple machine, thus offering students the opportunity to work in groups and build mental models more easily. In addition, they cater for exploration and creativity when it comes to how robot assemblies can be built (Resnick, 2005) and offer important feedback about their functionality. According to Merkouris et al. (2017), integrating a robot-related activity in learning is a four-step process: imagining and visualizing how to build a robot, develop the operating software using visual programming, downloading the software to the robot, and executing the software. An important aspect of our research has to do with investigating how and when the gender gap is founded. Underrepresentation of women in STEM is a multi-faceted issue: according to NSF, women are awarded 59% of Biology, 43% of Mathematics and 41% of Science degrees, but only 18% of Computer Science and 19% of Engineering degrees. Research has shown that the gap across genders with respect to STEM fields begins to appear as early as primary school (Ceci, 2010) and that targeted educational interventions can be extremely effective in reducing it, by increasing engagement and self-esteem in 23

 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

girls (Master, 2017). These interventions are also useful in terms of increasing interest towards technology and interconnected devices, since boys seems to spend more time with them during that period, interact in richer ways and, consequently, consider careers in Computer Science more often than girls (Cheryan, 2017). In the following sections we discuss robotics and its introduction to education. More specifically, the terms ‘robotics’ and ‘educational’ robotics are being clarified, as well as the term ‘STEM’ and how it is interconnected with robotics. There is also a section with the benefits and incentives that students gain through such an educational process. Existing research on the attitude of girls with respect to science and STEM is being analyzed; motivations and proposed practices of attracting girls to the world of technology and science are also considered. Then, we discuss the proposed intervention, the research questions, as well as the results that emerged. Finally, our conclusions and suggestions for future research are being presented.

BACKGROUND Educational Robotics as a Concept Educational robotics can be considered as a specific and important field of ​educational informatics. Its main tool is a programmable robot, an entity endowed with limited and pre-determined autonomy, capable of fulfilling certain of the prior actions within a changing environment. A robot can be used in school or out of school as an effective tool for the development of cognitive structures by children, while the possibilities it offers for understanding technical concept cannot be ignored (Komis, 2004). The fact that the average cost of obtaining a robotic device in terms of material (hardware) is declining rapidly, in combination by developing new software tools capable of simulating robotic applications in virtual worlds and the capability of designing a robot from scratch, make it clear that robotics constitutes a teaching and creativity tool that’s equally accessible and affordable with existing, conventional teaching aids (cf. Chatzopoulos et al., 2021; Plaza et al., 2019). A wide range of experiments, covering ‘hard’ (i.e., related to concept taught in classroom, mostly related to the STEM disciplines) and ‘soft’, A.K.A. social concepts can be performed with the help of robotic structures, introducing students to programming and problem solving, in the process. The involvement of students in hands-on activities, which require the solution of real problems ensures the most efficient knowledge building. The students’ interaction, collaboration and expression are encouraged by teachers aim for a more complete understanding of the underlying concepts. Educational robotics facilitates the development of an environment of authentic activities, through involvement of students in the analysis, design and implementation of robotic structures (Tzagkaraki et al., 2021).

Use of Educational Robotics Tools The interest in robotics has grown at an astonishing rate in recent times years (Benitti, 2012) and is currently considered as an option even in pre-school education (Schiffer & Ferrein, 2018). In general, developments in technology are ubiquitous and are integrated into every aspect of our lives. Over the past few years, mobile learning devices and computers have been widely used to enhance teaching. Although their lives are full of different devices technology, students rarely think about how their devices work. 24

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There have been several educational movements in recent years that encourage educational innovation, such as the introduction of K-12 coding (codification of education for primary and secondary education). During the Computer Science Training Week, in December 2013, a classroom coding initiative was launched called “Hour of Code”. During this week, Code.org reported that 15 million students from 170 countries participated in this initiative. One in five US students participated. Modern measurements show that about 100 million of students have visited the Hour of code website so far. Educational robotics encourages students to explore the creative side of computer science through activities such as coding computer programs (e.g., using a student-friendly environment such as Scratch) and collaborating with other students in designing, building, and testing technological constructions, including robots (Chalmers, 2018). The integration of computational thinking in the analytical program of primary and secondary education is another movement that encourages K-12 coding. Katehi et al. (2009), in their work titles “Engineering in K-12 training: Understanding the status and improving its Perspectives” underline the importance of integration of engineering education in the curriculum of primary and secondary education, claiming that it will also improve technological education as a whole.

STEM and Educational Robotics The term STEM concerns the fields related to physical Sciences, Technology, Engineering and Mathematics. It was formally used by biologist Judith A. Ramaley in 2001; as director of the national Science Foundation, Ramaley’s role was to develop new curricula. Using the term ‘STEM’, a reference is made to the introduction of technology and engineering into the teaching of mathematics and physics, which are necessary for a comprehensive understanding of the function of the physical world. There is clear evidence that robotics programs are educational tools that successfully teach STEM concepts (Barker et al., 2012). If robotics is to be used as the basis for a sustainable STEM pipeline, we must first understand the basis of the effectiveness of robotics in promoting students’ interest in STEM courses and careers.

The Benefits of using Robotics in Education Robotics can be a fun and interesting activity that gives students the opportunity to engage in the action and can be used across all levels of education to teach various concepts, mainly related to simple machines and engineering. However, robotics can also be useful in a wider range of school courses, such as: • • • • •

Physics (study of movement and the effect of friction on movement and direction, study and interaction of forces, energy transfer, etc.) Mathematics and Geometry (ratios and measurements, basic geometry entities and concepts, e.g., circular motions or circle perimeters, etc.) Engineering and Technology (constructions, auditing and evaluation of mechanical structures, technology literacy) History (ancient technology and engineering, e.g., the Archimedes catapult or the Maidservant of Philon) Interdisciplinary subjects, such as STEM combined with art or environmental studies

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 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

21st Century Skills Educational Robotics has positive effects not only with respect to hard skills, but also to emotional (self-esteem, self-confidence) and social (socialization) competencies (Kandlhofer & Steinbauer, 2016; Ponticorvo et al., 2020). With the help of robotics, teachers can focus on the development: • • • • • • •

Teamwork Problem solving (analysis, design, implementation, testing and experimentation, evaluation) Innovation Project management (time management, project and resource allocation, etc.) Planning Communication skills Valuable mental skills (analytical and synthetic thinking, creativity, critical thinking, etc.)

Educational Robotics, STEM and Gender Perspective The gender gap in STEM is large and exists to this day. This gap is significantly larger in technological fields, such as computer science and engineering, than in mathematics and science. Gender differences start early: young girls report less interest and self-efficacy in technology compared to boys in elementary school. In their study, Master et al. (2017) evaluated a sample of 96 children about the stereotypes of 6-year-olds about STEM fields and examined an intervention to develop girls’ STEM motivation despite these stereotypes. First graders reported stereotypes that boys were better than girls in robotics and programming, but this did not apply to math and science. Girls reported well-founded stereotypes about robotics and programming, recounting lower interest and self-efficacy in these areas. Sullivan & Bers (2012) examined gender differences using the TangibleK Robotics Program to determine if boys and girls in kindergarten were equally successful in a range of construction and programming tasks, following up with an 8-week curriculum (Sullivan & Bers, 2016). The TangibleK program consists of a six-month robotics course and curriculum applied to three different kindergarten classes in a sample of 53 students. Although previous research has shown that boys outperform girls in robotic and programming fields, it is assumed that the young age of participants and their limited gender stereotypes will allow boys and girls to be equal success in the activities. Although boys scored higher than girls on more than half of the tasks, very few of these differences were statistically significant. Boys scored significantly higher than girls in only two areas: proper placement of robotic materials and programming using IF statements. Overall, both boys and girls were able to successfully complete the program.

Causes of Gender gap in Technology Why are there gender gaps regarding motivation to study or pursue a career computer science and engineering? The following constitute the key social and structural factors that influence girls’ involvement in computation, often preventing them from choosing a future education or career in technology (UniteIT Gender Equality workgroup, 2014). •

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Social acceptance that computer technology is “masculine”: Any hypothesis that women are inherently a worse fit for science and technology has been repeatedly rejected by research. Any

 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

•

• •

•

•

biological differences do not function to prevent girls from participating in technology or computer science disciplines. Many studies show that when gender discrimination is low, girls have comparable performance as boys. Stereotypical attitude of the media: The way IT and technology are portrayed in magazines, on the internet, on television and in movies, influences ideas of who is suitable for computer work when certain types of people are showed doing specific tasks: coders, makers, hackers are typically Caucasian or Asian males, often distanced from society or even antisocial. Absence of female role models: But where can a girl find such technologically advanced female models? At home, fathers are more likely to be considered computer experts or makers than mothers. Actual female role models are very rarely promoted by larger media outlets. Lack of early experiences - racial segregation of toys: Studies have shown that early computer use improves success in future computer classes. More males report early exposure to home computers: 63% men versus 37% women. And when it comes to creating content or software with technology and not just using it, studies have shown that boys typically have earlier experience with programming than girls. Another possible reason why girls may show lower motivation than boys for computer science and engineering is the fact that they have less experience with technology to build their interest and build self-efficacy (Nugent et al., 2014; Martin & Dinella, 2002). Many see gaming as a very promising way to promote interest in computers at a very early age. While boys have spent more time playing games in the past, recent findings show that this gap is narrowing (Karpouzis and Yannakakis, 2016). Stereotype threat: Gender stereotypes have a negative effect on girls’ performance in STEM, a phenomenon known as the “stereotype threat” (Flore & Wicherts, 2015; Régner et al., 2014) and on adult motivation in STEM (Thoman et al., 2013). The prevalence of STEM gender stereotypes can be an important social factor influencing girls’ interest in STEM (Kessels, 2015; Master et al., 2016). STEM stereotypes can work as “gatekeepers” and prevent girls from pursuing interests in computer science and engineering (Cheryan et al., 2015). If children have stereotypes that boys are better than girls in computer science and engineering, girls can predict that they are performing poorly and are prevented from engaging in related activities. Lack of understanding of what ICT jobs entail: Girls (and often boys) still have limited knowledge or inaccuracies about what IT careers entail. In general, girls find that careers in computer science have little or no interaction with others, and that IT workers are obsessed with computers.

RESEARCH PROCESS Research Approach The global problem of low participation of women in technology highlights the need to examine the evolution of this issue over the years, as well as the need for ongoing research into the reasons why this is happening; this is essential to come up with good practices that will reduce the gender gap in the technology sector. This study seeks to achieve the following: a) to check if there is a difference between boys and girls in the ability to understand technological and mechanical concepts and processes, b) to check for the technological gender gap specifically in the early school years, c) to check the suitability of

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 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

the UARO educational robotic product for technological interventions and d) to record the professional aspirations and approaches of all genders in the first school age.

The UARO Platform UARO is an educational robotics solution, integrated with programming and design software. Its main educational elements help children develop creativity, reasoning, problem solving and understanding, while assembling and programming robots on their own. UARO is designed to be easy to use for children, since it consists of large pieces with vivid colors, which helps coordinate the eyes and hands and develop motor skills through the assembly process. Students can also practice coding and algorithmic thinking, as well as pattern recognition depending on image, shape, and color. It consists of 4 complementary training kits: kit 1 introduces basic parts of a construction or simple machine, kit 2 brings in a motorized controller, a CPU processor, and a distance sensor, kit 3 gives students the opportunity to program the movement of the robot through a specialized programming device and associated command blocks, while kit 4 allows for visualization and representation of a robot on a mobile device running iOS or Android. Figure 1. UARO platform

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 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

Figure 2. Construction

Research Questions The Research Questions (RQ) that this research aims to answer are: RQ1: Is there a difference in performance across genders in technology and engineering. Null hypothesis: there is no difference Alternative hypothesis: there is a difference in performance RQ2: Does the students’ stance towards different professions affect their performance in engineering and technology Null hypothesis: there is no difference Alternative hypothesis: there is a difference in performance RQ3: Is the UARO platform suitable to teach STEM subjects in early school years?

Research Measurement Tools Worksheets and a questionnaire given after the meetings were used to collect data related to the research questions. The worksheet is based on is the theory of discovery learning (Bruner, 2009), where students acquire knowledge through exploratory processes and exploratory strategies. Teachers aim to help students practice and at the same time acquire specific knowledge about the subject they are examining. Usually, these principles are associated with collaborative teaching and the development of critical thinking, following the social requirement for the formation of critical and autonomous citizens. Within the framework of this research, four different worksheets were created, appropriately designed for primary school children. The first stage of the worksheets introduces students to the construction process: they are invited to cooperate in small group to create the respective construction, always following instructions in printed form. The success of this stage depends on whether the student teams will cooperate and whether they will concentrate on performing the steps.

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 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

The second stage is that of exploration: children are asked to answer questions related to concepts of physics, technology, engineering and mathematics through testing and observation of structures. Figure 3. Exploration

During the third stage, the young students experiment with the robots they built; this was, as they reported, the most fun part of the process. Their familiarity with technology comes in handy, as well as perception and problem-solving skills. Figure 4. Robot operations

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 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

At the end of each meeting, students are asked to evaluate their experience based on their interest and engagement. In order to introduce students to physics-related concepts (i.e., energy) and allow them to experiment with how their design choices affect the robot’s operation and performance, we designed the “Rob the Robot” worksheet. “Max the Crane” helps children get acquainted with the sizes of the pieces used for construction and compare different lengths experimenting with the robot’s axis. With “Bonnie the Dog”, students learn to orient and practice with directions (front, back, left, right), while with “Miss butterfly”, children explore the concept of symmetry. Figure 5. Evaluation of the process

These specially designed worksheets were used to evaluate the performance of the participating students. During the last meeting, students were given a questionnaire appropriately designed to answer our research questions.

Student Profile-Sampling Our research was conducted in a public Primary School in the region of Attica, Greece. A total of 4 meetings took place during March and April 2018 with 16 first grade (6 years old) children and 38 second grade (7 years old) children divided into groups. The first grade class consists 8 boys and 8 girls, the first group of the second grade class consists of 9 boys and 10 girls, while the second group consists of 11 boys and 8 girls. Therefore, our sample in total consists of 28 boys and 26 girls.

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 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

Data Analysis SPSS (Statistical Package for Social Science) was used to analyze the data (answers to the student worksheets, and questionnaire responses) and extract the results. Each student obtained an anonymous ID and blank answers were entered as missing values. When analyzing the answers, wrong answers gave the student 0 points, incomplete answers contributed 1 point, while correct answers added 2 points. A total score was created for each worksheet that includes the total points that the students collected from their correct answers.

Gender and Performance After a normal distribution test with K-S Normality Test, it was found that the performance of boys and girls in all four worksheets does not follow a normal distribution, therefore a Mann-Whitney test is suitable.

“Rob the Robot” Worksheet After analyzing the answers of the children in the first worksheet, (questions related to energy, e.g., “Circle where the robot gets its energy from”), girls averaged 6.82 points, while boys averaged 6.7. Results from this worksheet are shown in Table 1 and Table 2. It is observed that Sig 0.777>0.05 so we accept the null hypothesis for RQ1, that there is no statistically significant difference in the performance of the two genders. Figure 6. UARO- Robot constructions

“Max the Crane” Worksheet In this worksheet, girls averaged 7.45 points, while boys 7.10. Results from this worksheet are shown in Table 3 and Table 4. Table 1. Mann-Whitney U Test - “Rob the Robot” worksheet Gender

N

Mean rank

Sum of ranks

Girl

22

25.61

563.50

Boy

27

24.50

661.50

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 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

Table 2. Statistics from activity 1 Test statistics

Score

Mann-Whitney U

283.50

Wilcoxon W

661.50

Z

-0.283

Asymp. Sig. (2-tailed)

0.777

Grouping variable

Gender

Table 3. Mann-Whitney U Test - “Max the Crane” worksheet Gender

N

Mean rank

Sum of ranks

Girl

22

22.34

491.50

Boy

20

20.58

411.50

Table 4. Statistics from activity 2 Test statistics

Score

Mann-Whitney U

201.50

Wilcoxon W

411.50

Z

-0.606

Asymp. Sig. (2-tailed)

0.545

Grouping variable

Gender

Again, Sig 0.545> 0.05, so we accept the null hypothesis for RQ1, that there is no statistically significant difference in the performance of the two genders.

“Bonnie the Dog” Worksheet This worksheet consists of one question, so the maximum grade a student can get is 2. Here, girls have a slight lead over the boys with an average of 1.71 versus 1.65. Table 5 and Table 6 show the results from this activity. It is observed that Sig 0.867> 0.05 so we accept the null hypothesis for RQ1 and there is no statistically significant difference in the performance of the two genders.

“Miss Butterfly” Worksheet The “Miss Butterfly” worksheet consists of two questions, consequently the maximum score is 4. Girls scored 3.23 points on average, while boys performed slightly better with 3.41 points on average. Results from this activity are shown in Table 7 and Table 8. We observe from the above table that Sig 0.462 > 0.05 so we accept the null hypothesis for RQ1 and there is no statistically significant difference in the performance of the two genders.

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 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

Table 5. Mann-Whitney U Test - “Bonnie the Dog” worksheet Gender

N

Mean rank

Sum of ranks

Girl

24

24.25

582.00

Boy

23

23.74

546.00

Table 6. Statistics from activity 3 Test statistics

Score

Mann-Whitney U

270.00

Wilcoxon W

546.00

Z

-0.168

Asymp. Sig. (2-tailed)

0.867

Grouping variable

Gender

Table 7. Mann-Whitney U Test - “Miss Butterfly” worksheet Gender

N

Mean rank

Sum of ranks

Girl

22

23.48

516.50

Boy

27

26.24

708.50

Table 8. Statistics from activity 4 Test statistics

Score

Mann-Whitney U

263.50

Wilcoxon W

516.50

Z

-0.736

Asymp. Sig. (2-tailed)

0.462

Grouping variable

Gender

Suitability of the UARO Platform In the last questionnaire, students were asked questions about any difficulties they may have encountered during the activities. 80% of girls and 80.8% of boys answered positively to the question “Were the constructions easy for you?”, while 15% of girls and 10.3% of boys gave a negative answer to the question “Were the instructions easy for you?”. Finally, 20% of girls and 15.4% of boys reported that they encountered difficulties with the questionnaires related to the construction tasks.

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 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

Gender and Interest in Educational Robotics All girls responded positively to the question “Did you like Robotics?” and only one boy answered that the process was not interesting for him. In addition, all kids answered that they would love to get involved in robotics activities, as shown by their answers to the question “Would you participate again in robotics activities?”. They also mentioned that the gained new knowledge from the activity sheet (90% of girls, 92,3% of boys). The questionnaire also included an open question: “What is your favorite game/toy1?”. Children had the opportunity to answer how they like to spend their free time. After processing the collected data ‘Constructions with LEGO bricks’ and ‘Role-playing games with dolls’ have prominent positions in the preferences of girls, while for boys ‘electronic toys’ and the ‘constructions with LEGO bricks’ were the most popular choices. In the open question “What profession do you want to do when you grow up?”, the most common answers of girls are ‘I do not know’ with 26.3% as well as ‘Teacher / Kindergarten Teacher’ with 21.1%. The most common answers of the boys are ‘Policeman’ (20%), ‘Soccer player’ (15%) and ‘Astronaut’ (10%).

OVERVIEW OF RESULTS The educational intervention was tested with 54 children (28 boys, 26 girls), aged 5-6 (16 5-year-olds, 38 6-year-olds). The first questions in the questionnaire revolved around the experience and stance of the young students towards robotics: the gender gap already exists at this early age, with 72.4% of the boys mentioning that they had previously built a robot before the intervention, while only 44% of girls indicating some experience in the field. This is consistent with a difference in use of technology and engineering activities in the students’ free time: 47% of boys stated that digital games are their favorite pastime, followed by construction games (such as LEGOs and Playmobil), while only 25% of girls share the same hobby. Regarding the students’ stance towards their future profession, boys mentioned ‘police officer’, ‘soccer player’ and ‘astronaut’ as possible careers with a few of them adding ‘video game designer’ as a possibility. The most popular answer from girls was kindergarten/primary school teacher, followed by ‘I don’t know’; none of the girls who participated in the intervention brought up a career in STEM. Regarding the interest and performance of the young students, almost all of them (all girls and all but one boy) stated that they enjoyed the experience and all of them would definitely like to participate again in a similar activity. They also mentioned that they gained new knowledge from the activity sheet (90% of girls, 92.3% of boys). The vast majority of the students (80%) thought that the activity sheets were straightforward and easy to comprehend and that the robots given to them were easy to build. Girls also found it easier to work in groups (80%, compared to 74.1% for boys) and performed slightly better; a Mann-Whitney U test, though, showed that this difference was not significant, and as a result, the null hypothesis stands for RQ1 and for all four activity sheets. The other two Research Questions were answered through the students’ responses in the questionnaire: even though there is a noticeable difference between the interests and stance towards STEM and robotics among boys and girls, this did not affect their performance, while the suitability of UARO to teach STEM subjects in early schoolers was shown by the participants’ engagement and the success they had in building the constructions described in the activity sheets and the answers in the questions they contained. 35

 Early Childhood Introduction to Robotics as a Means to Motivate Girls to Stay With STEM Disciplines

SUGGESTIONS FOR FUTURE RESEARCH AND STUDY Since this is one of the few studies which discusses robotics and STEM at such a young age, possible extensions are numerous: the UARO product could be used by a larger number of students and compared to other educational robotic products, while the same research could also be conducted in the presence of a control group for more reliable results (cf. Vargianniti and Karpouzis, 2019 or Chiotaki and Karpouzis, 2020). Finally, it would be very profitable to control for the students’ socio-economic background, against their performance, interests and inclinations or career aspirations. Regarding the focus of this study, which is the investigation of gender issues associated with STEM activities and careers in the context of early education, our experiment confirmed that even at this very young age, girls rarely see themselves as working in science or technology. This may very well be an issue related to representation (Piatek-Jimenez et al., 2018), since there are hardly any female scientists, engineers, innovators, or entrepreneurs in the news, so as to inspire young girls and make them realize their potential and imagine themselves following in their footsteps. Even in toys or literature targeted at this young age, females are rarely portrayed as professionals in these fields, helping to establish stereotypes so early and powerfully that they’re almost impossible to fight (Bian et al., 2017). From the point of view of performance, our study found that there is no statistically significant difference across genders when it comes to robotics; this finding also supports the claim that the lack of representation is fundamental in building and maintaining such stereotypes. In order to tackle this issue, not only female scientists and professionals in STEM disciplines should be presented with more opportunities to advance through the ranks, but also their achievements should be better advertised, and their work-life balance assisted through policies and interventions (Tan-Wilson & Stamp, 2015).

CONCLUSION We described a rare educational intervention involving educational robotics in early schoolers, investigating the suitability of the proposed activities and the existence and effect of the gender gap towards STEM. Besides investigating the appropriateness of the intervention using qualitative methods, such as questionnaires, we also tested for its efficacy in terms of learning outcomes. Our findings are consistent with the literature and verify that the gender gap is already founded in the students’ early years; this, however, does not affect the girls’ performance, meaning that their interest and engagement can be increased through targeted interventions. In addition, educational robotics can be used to constructively teach STEM subjects in early school years, without the need to opt for expensive platforms, heavy on computational methods and requirements.

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Plaza, P., Sancristobal, E., Carro, G., Blazquez, M., García-Loro, F., Muñoz, M., & Castro, M. (2019, April). STEM and educational robotics using scratch. In 2019 IEEE Global Engineering Education Conference (EDUCON) (pp. 330-336). IEEE. 10.1109/EDUCON.2019.8725028 Ponticorvo, M., Rubinacci, F., Marocco, D., Truglio, F., & Miglino, O. (2020). Educational robotics to foster and assess social relations in students’ groups. Frontiers in Robotics and AI, 7, 78. doi:10.3389/ frobt.2020.00078 PMID:33501245 Resnick, M., & Silverman, B. (2005). Some reflections on designing construction kits for kids. Proceedings of the 2005 conference on Interaction design and children, (pp. 117-122). 10.1145/1109540.1109556 Schiffer, S., & Ferrein, A. (2018). ERIKA—Early Robotics Introduction at Kindergarten Age. Multimodal Technologies and Interaction, 2(4), 64. doi:10.3390/mti2040064 Sullivan, A., & Bers, M. U. (2016). Robotics in the early childhood classroom: Learning outcomes from an 8-week robotics curriculum in pre-kindergarten through second grade. International Journal of Technology and Design Education, 26(1), 3–20. doi:10.100710798-015-9304-5 Sullivan, A., & Bers, M. U. (2012). Gender differences in kindergarteners’ robotics and programming achievement. International Journal of Technology and Design Education. Advance online publication. doi:10.100710798-012-9210-z Tan-Wilson, A., & Stamp, N. (2015). College students’ views of work–life balance in STEM research careers: Addressing negative preconceptions. CBE Life Sciences Education, 14(3), es5. doi:10.1187/ cbe.14-11-0210 PMID:26163564 Thoman, D. B., Smith, J. L., Brown, E. R., Chase, J., & Lee, J. Y. K. (2013). Beyond performance: A Motivational Experiences Model of Stereotype Threat. Educational Psychology Review, 25(2), 211–243. doi:10.100710648-013-9219-1 PMID:23894223 Tzagkaraki, E., Papadakis, S., & Kalogiannakis, M. (2021). Exploring the Use of Educational Robotics in primary school and its possible place in the curricula. In Educational Robotics International Conference (pp. 216-229). Springer. 10.1007/978-3-030-77022-8_19 Vargianniti, I., & Karpouzis, K. (2019). Effects of game-based learning on academic performance and student interest. In International Conference on Games and Learning Alliance (pp. 332-341). Springer. 10.1007/978-3-030-34350-7_32

ADDITIONAL READING Bers, M. U., & Horn, M. S. (2010). Tangible programming in early childhood. High-Tech Tots: Childhood in a Digital World, 49, 49-70. Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering: Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145–157. doi:10.1016/j.compedu.2013.10.020

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Cejka, E., Rogers, C., & Portsmore, M. (2006). Kindergarten robotics: Using robotics to motivate math, science, and engineering literacy in elementary school. International Journal of Engineering Education, 22(4), 711. Jung, S. E., & Won, E. S. (2018). Systematic review of research trends in robotics education for young children. Sustainability, 10(4), 905. doi:10.3390u10040905 Kazakoff, E., & Bers, M. (2012). Programming in a robotics context in the kindergarten classroom: The impact on sequencing skills. Journal of Educational Multimedia and Hypermedia, 21(4), 371–391. Lee, K. T., Sullivan, A., & Bers, M. U. (2013). Collaboration by design: Using robotics to foster social interaction in kindergarten. Computers in the Schools, 30(3), 271–281. doi:10.1080/07380569.2013.805676

KEY TERMS AND DEFINITIONS Control Group: A group of people participating in research who do not engage in the activity to be evaluated; useful to estimate the effect of the proposed activity Educational Intervention: An organized activity orchestrated by the teacher, utilizing concepts and material from books or other sources, leading towards a predefined set of learning objectives. Educational Robotics: In- or after-school activities which aim to introduce students to engineering and programming concepts by building a robot, often using it in the context of other STEM subjects. Gender Stereotype: The presumption that some professions, school courses, activities or even toys are better suited for a particular gender than others. Make-Ing: Engaging in tinkering activities, using inexpensive electronics and circuitry materials, resulting in putting together larger constructions which work on batteries. Soft Skills: Skills and knowledge related to communication, interaction, cooperation, coping mechanisms, etc., as opposed to skills related to a profession or academic discipline (‘hard skills’). STEM: A wide variety of courses and concepts related to Science, Technology, Engineering and Mathematics, often in after school activities or complementing the school curriculum.

ENDNOTE 1



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We use the same word for game (digital/analog) or toy in Greek, so we made no distinction here.

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Chapter 3

Adopting a Role-Model, GameBased Pedagogical Approach to Gender Equality in STEAM: The FemSTEAM Mysteries Digital Game Ioanna Vekiri European University, Cyprus Maria Meletiou-Mavrotheris https://orcid.org/0000-0001-6749-3266 European University, Cyprus Asimina Brouzou Challedu, Greece

Ioannis Brouzos Challedu, Greece Andri Christoforou European University, Cyprus Elena Stylianou European University, Cyprus

ABSTRACT The aim of this chapter is to discuss the use of serious games in STEAM education and to present FemSTEAM Mysteries, a serious game that was developed in the context of an EU-funded project. The game is intended for teenagers (age 12-15) and its goal is to promote gender equality in STEAM by inspiring all students to pursue STEAM careers, and to enhance the acquisition of key skills and competences for STEAM studies. It is based on role-model STEAM pedagogy and introduces students to important STEAM researchers and professionals in ways that challenge gender stereotypes as well as stereotypes about the characteristics of scientists and artists. The chapter presents the design and theoretical framework of the game which is based on both bibliographical and field research that was carried out in the context of the FemSTEAM Mysteries project.

DOI: 10.4018/978-1-6684-3861-9.ch003

Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Adopting a Role-Model, Game-Based Pedagogical Approach to Gender Equality in STEAM

INTRODUCTION It is a common ground, supported by international surveys (e.g., European Institute for Gender Equality, 2018; OECD, 2020), that females are underrepresented in scientific fields during school and university education, and career development. Girls appear to lose interest in STEM subjects with age (AT Kerney, 2016), and by the time they reach late adolescence they become reluctant to follow STEM careers (under 35% enroll in scientific fields at European level) and instead tend to choose the fields of education, health, and welfare (OECD, 2020). Women’s underrepresentation in STEM fields limits their opportunities for employment in engineering- and technology-related professions, which are in great demand and have higher pay-levels (EIGE, 2018; OECD, 2016) and, therefore, it perpetuates economic gender inequalities. Also, it deprives STEM fields from the breath of human resources which can lead to research-based innovations that support economic development (European Commission, 2019). In this chapter we discuss how serious games can serve the goals and pedagogical approaches of STEAM education, and, more specifically, explain how they can be used to promote gender equality in STEAM. The chapter will focus on FemSTEAM Mysteries, which is a serious game that was developed in the context of an EU-funded project (Nov 2020-Oct 2022) with the aim to challenge gender stereotypes about STEAM careers and to inspire more students, particularly females, to pursue studies in STEAM. After examining the use of serious games in education, we discuss the theoretical framework and key findings from field research that guided the development of the FemSTEAM Mysteries game, and then present its design and gameplay.

SERIOUS GAMES IN STEAM EDUCATION Learning games are digital games that aim at supporting specific learning goals (Klopfer, Osterweil, & Salen, 2009). They differ from entertainment games because, although the latter can be utilized in the classroom and can support knowledge learning, let alone the development of a wide range of skills (Boyle et al., 2016; Prensky, 2005), their primary purpose is entertainment. “Serious games” is another term that is used to characterize lerning games, although there are diverse views about its exact meaning (Blumberg, Almonte, Antony, & Hashimoto, 2013). The term may refer to games which are designed to be used for educational and training purposes but differ from “drill and practice” edutainment games whose purpose is also educational, because serious games engage students more actively and support higher levels of learning than knowledge acquisition through repetition (Ke, 2016). According to a broader definition of serious games however, the category includes even commercial off-the-shelf games such as World of Warcraft or SimCity (Blumberg et al., 2013) that may also teach players knowledge and skills and can be integrated in classroom learning (Van Eck, 2009). “Game-based learning” is a term that refers to the use of a fully-fledged serious game in the learning process, not to be confused with the term “gamified learning”, which involves augmenting the learning process by adding game elements (Sailer & Hommer, 2020). Serious games have all the characteristics of other types of digital games, such as rules and constraints, challenge, constant feedback, competition, autonomy, and fantasy (Alessi & Trollip, 2001), most of which are considered to contribute significantly to their motivational appeal (Blumberg et al., 2013; Wouters, Van Nimwegen, Van Oostendorp, & Van Der Spek, 2013). In addition, modern serious games capitalize on computer technology and state-of-the-art graphics to provide interactive simulations 42

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of real-life environments and situations, in which students can participate by taking specific roles or perspectives. Activities in modern serious games are typically complex and authentic, often requiring students to respond to problems and situations that relate to the real world. As players, learners need to make knowledge-based decisions that can influence the storyline, which enables them to experience agency, to experiment, and to observe the consequences of their actions, without however having to suffer their real-life emotional or physical impact (Barab, Gresalfi, & Arici, 2009; Klopfer et al., 2009). Various taxonomies and criteria have been proposed to classify learning games (e.g., Blumberg et al., 2012; Breuer & Bente, 2010; Prensky, 2005), although a game may have characteristics from more than one category. A recent taxonomy proposed by Ke (2016) uses two criteria, which determine how players interact with the game (the gameplay). These criteria are (a) the characteristics of game narrative, which include setting, plot, and characters, and (b) game mechanics, that is, the rules and actions of gameplay. Examples of categories include adventure, strategy, role playing, construction, and simulation games. Escape rooms is another category that is becoming popular, which is based on the physical game. Physical escape rooms are collaborative games in which players work together to solve puzzles (i.e. problems, challenges or activities) in a limited amount of time, so as to achieve a common goal that is embedded in a story/narrative (Nicholson, 2015). Puzzles may depend on thinking skills and logic, they may involve the manipulation of artifacts or they may require the solution of other puzzles (in which case they are called meta-puzzles)(Veldkamp et al., 2020). Escape rooms require a diverse set of skills, such as the ability to search for clues and to discern important information, to recognize patterns, and to relate various pieces of information (Wiemker, Elumir, & Clare, 2015). A good escape room includes a variety of puzzles that require different types of skills, which is important when the game is collaborative because it enables all team members to contribute to its solution. Research has shown that, due to their characteristics, serious games can be more effective than other forms of instruction, such as conventional instruction and simulations, in terms of learning and motivation. According to recent literature reviews and meta-analyses (Boyle et al., 2016; Clark, Tanner-Smith, & Killingsworth, 2016; Lamb, Annetta, Firestone, & Etopio, 2018; Wouters et al., 2013) some of their advantages include engagement in learning and increased “flow experience”, a state in which learners are immersed in the activity (Csikszentmihalyi, 1990), as well as improved content understanding, retention of information, and the development of problem-solving and social skills. As such, serious games have the potential to advance several STEAM goals, including motivation to learn STEAM content, interest in STEAM fields, and the development of problem solving and inquiry skills (Gao, Li, & Sun, 2020). Also, serious games can be easily integrated in STEAM curricula and projects because they can support authentic learning activities as well as inquiry and problem-based approaches to learning, which are compatible with STEAM pedagogy (Bush & Cook, 2019). There are various challenges and barriers, however, in game-based learning (Klopfer et al., 2009). One important challenge is the design of quality educational games, which are games that help students achieve specific learning goals and at the same time provide an enjoyable and engaging experience (Prensky, 2005). An important characteristic of effective educational games is the level of “intrinsic integration” between gameplay and learning content (Alessi & Trollip, 2001; Habgood & Ainsworth, 2011; Ke, 2016). This level is high when the learning activities in the fantasy world of the game are quite similar to what the learner would actually have to do in a comparable situation in the real world. Intrinsic integration can foster learning because it appears to enhance intrinsic motivation and a state of “flow”, in which learners are more focused, aroused, and task persistent because they are deeply engaged in the game (Habgood & Ainsworth, 2011). Other game characteristics that may contribute 43

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positively to learners’ flow experience are clear goals, immediate and clear feedback, opportunities for social interaction, adequate levels of challenge and autonomy, and perceived usability and knowledge improvement (Fu, Su, & Yu, 2009; Petri, von Wangenheim, & Borgatto, 2016). Other challenges in using serious games in the classroom relate to teachers’ perceptions of the value of games, their own gaming experiences, their knowledge of appropriate games for their students and for the grade-level they teach as well as their familiarity with appropriate game-based learning pedagogical techniques (Dickey, 2015; Hsu, Liang, Chai, & Tsai, 2013; Meletiou-Mavrotheris & Prodromou, 2016; Proctor & Marks, 2013). Finally, in order to integrate a game into their regular classroom teaching, teachers need to resolve logistical problems relative to student access to computers and the time structure of a typical school day, depending on the time needed to complete and discuss the game (Klopfer et al., 2009). These are all issues that should be considered in the design of educational games. For example, games that can be broken up into individual parts or sections, to be played on separate days, can be integrated more easily into a regular school lesson. Also, serious games should be accompanied with teacher guides and resources that describe their learning objectives and potential alignment with curriculum goals and/ or learning value, as well as provide content background information and educational scenarios to guide teachers on how to use the games in the classroom.

THE THEORETICAL FRAMEWORK OF THE FEMSTEAM MYSTERIES GAME Women’s Underrepresentation in STEM Over the past decades research has established that women’s underrepresentation in STEM/STEAM fields cannot be attributed to differences in cognitive abilities and academic achievement (OECD, 2019; Wang & Degol, 2017). As various international assessments and meta-analyses of relevant studies show (Mullis, Martin, Foy, Kelly, & Fishbein, 2020; OECD, 2019; Siddiq & Scherer, 2019), adolescent girls have caught up with adolescent boys in science, mathematics, and ICT literacy. However, according to PISA 2018 results (OECD, 2019), on average across OECD countries only 14% of the girls who were top performers in science or mathematics reported that they expected to work as professionals who use science and engineering training, as opposed to more than 26% of top performing boys. In other words, female students who perform well in science and mathematics are highly unlikely to pursue studies in STEM fields. Student academic choices and career aspirations are influenced by gendered psychological processes, which include students’ subjective perceptions of their abilities and of the value of certain academic subjects as well as cultural values, stereotypes, and family expectations (Bleeker & Jacobs, 2004; Eccles, 2007; Gunderson, Ramirez, Levine, & Beilock, 2012; Wang & Degol, 2017). To pursue a particular academic subject, students need to think that they can succeed in learning it as well as that it is interesting, important, and useful to them (Eccles, 2007). These perceptions are influenced by students’ own interpretations of their learning experiences and by the opinions and expectations communicated by important socialization agents, which are often based on cultural stereotypes and misconceptions (Bleeker and Jacobs, 2004; Gunderson et al., 2012). Hence, female students may underestimate their abilities in certain academic subjects even when they perform well academically (Sáinz & Eccles, 2012; Wach, Spengler, Gottschling, & Spinath, 2015). Several studies have shown, for example, that adolescent girls tend as a group to express lower confidence in their math and ICT abilities even when they perform 44

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equally well with adolescent boys (Sáinz & Eccles, 2012; Wach et al., 2015). Students may also have inaccurate understandings of the nature and scope of STEM professions and, as a result, think that taking math, and science courses at school is not useful and important to them (Eccles, 2007; Mann, Denis, Schleicher, Ekhtiari, Forsyth, Liu, & Chambers, 2020). According to gender stereotypes women are considered suited for low-status roles that involve caring for others and they are expected to place more priority on their family than on their professional achievement. The opposite, however, is expected by men, who, due to their physical strength, are seen as predisposed for high status roles that require agency (Ellemers, 2018). In educational contexts, STEM fields are considered “masculine” because they are supposed to require innate intellectual talent (e.g., abstract thinking) and agentic traits, such as leadership skills, independence, persistence, and risk taking, which are linked to men (Carli, Alawa, Lee, Zhao, & Kim, 2016; Leslie, Cimpian, Meyer, & Freeland, 2015). Women are perceived to possess higher levels of communal traits, and, therefore, they are considered more suitable for fields that allegedly require more empathy and/or hard work (Carli, et al., 2016; Leslie et al., 2015). Gender stereotypes are still pervasive in social discourse and can be found even in textbooks and educational resources, reinforcing the view that STEM fields are masculine (Kerkhoven, Russo, LandZandstra, Saxena, & Rodenburg, 2016; Moser & Hannover, 2014). Research has shown that gender stereotypes create psychological obstacles for women and influence their academic and career choices (Dicke, Safavian, & Eccles, 2019; Ertl, Luttenberger, & Paechter, 2017; Flore & Wicherts, 2015). Female students who internalize gender stereotypes about STEM tend to underestimate their ability to succeed in STEM fields and are less likely to aspire to and to pursue careers in STEM fields (Dicke et al., 2019; Ertl et al., 2017). In a longitudinal study Dicke et al. (2019) found that women who had endorsed traditional gender-role views in adolescence acquired lower levels of education in adulthood and were less likely to have occupations within male-typed STEM domains at age 42, compared with women who did not endorse such stereotypes when they were adolescent students. However, even if they do not espouse gender stereotypes themselves, female students are susceptible to a phenomenon that is called “stereotype-threat”: due to physiological stress caused by the possibility to confirm gender stereotypes, they may perform bellow their ability level in STEM tasks, especially in contexts where gender bias is salient (Flore & Wicherts, 2015). Students’ educational and occupational choices may be influenced by negative stereotypes about the nature of STEM fields (Cheryan, Master, & Meltzoff, 2015; Ehlinger, Plant, Hartwig, Vossen, Columb, & Brewer, 2018). Non-specialists, including teachers, parents, and students, often have inaccurate understandings of the types, settings, and ethics of STEM research and professional activities and may hold stereotypical views of STEM researchers and professionals (Christidou, Hatzinikita, & Samaras, 2012; DeWitt, Archer, & Osborn, 2013; Sáinz, Pálmen, & García-Cuesta, 2012). They may perceive math, science, and computing as impersonal, non-creative, and mechanistic activities, or even as morally ambiguous activities motivated by self-interest, and they may view STEM researchers and professionals as eccentric geniuses who have no social skills and personal lives (Christidou et al., 2012; Critchley, 2008; DeWitt et al., 2013; Sáinz et al., 2012). Such stereotypes about STEM fields and professionals may discourage students from aspiring to STEM/STEAM careers, especially if they are interested in jobs that are creative, provide opportunities for social interaction and enable them to benefit society. This is particularly important for female students who, due to their socialization, are more likely than males to place importance on humanistic job characteristics (Guzdial, Ericson, McKlin, & Engleman, 2012; Weisgram, Dinella, & Fulcher, 2011). Also, 45

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many female and male students, who think that only exceptionally smart people or “nerds” pursue studies in STEM, may feel that they do not themselves belong in STEM (Erlinger et al., 2018). On the other hand, research has shown that students who hold non-stereotypical images of STEM professionals tend to perceive higher identity compatibility between themselves and STEM as well as to be more likely to intend to major in a STEM field (Nguyen & Riegle-Crumb, 2021; Shin, Levy, & London, 2016). These research findings indicate that students need exposure to a variety of images and role models that present a more balanced view of STEM researchers and professionals (Cheryan et al., 2015; DeWitt et al., 2013).

The Importance of Role Models in Students’ Academic and Career Choices Parents and teachers as well as other adults can influence young people’s aspirations and study choices by acting as role models. Several theories, such as social cognitive theory (Bussey & Bandura, 1999) and social role theory (Eagly & Wood, 2016), have highlighted the importance of role models, and more particularly of same-gender role models, on children’s development. According to social role theory (Eagly & Wood, 2016), young people attribute the differences they observe in the gendered distribution of social roles to inherent characteristics and, as a result, perceive certain behaviors to be more appropriate for their gender. Observing men and women in gender stereotypical roles (either directly through social interactions or indirectly, e.g. through mass media) gives rise to gender stereotypes which then promote aspirations and behaviors that are considered gender congruent. In industrialized economies, for example, women are more likely to hold caretaking jobs and men to hold leadership positions. Finding that only a few women have STEM professions and leadership roles may signal to adolescent girls that they do not have the skills and traits to succeed in these domains or that these domains are not appropriate for them. Research has shown that students’ exposure to STEM-related stereotypical role models is associated with the endorsement of gender stereotypes (Beilock, Gunderson, Ramirez, & Levine, 2010) while exposure to role models that challenge stereotypes can change students’ perceptions (Shin et al., 2016; Van Camp, Gilbert, O’Brien, 2019). In a recent literature review, Olson and Martiny (2018) concluded that interventions that aim at targeting women’s underrepresentation in male-typed academic fields using exposure to countersterotypical role models, such as successful female scientists, can influence females’ aspirations and gender-related views even if the duration of these interventions is brief. Based on the literature reviewed so far, research has shown that stereotypes about the nature of STEM fields and professions and their suitability for women have a negative impact on female students’ career aspirations and study choices. Therefore, to increase the number of women in STEM fields, it is important to overhaul gender stereotypes and to diversify the images of STEM fields and professionals, so that students, both female and male, do not feel that they need to fit a particular prototype to succeed and to be satisfied as students and professionals in these fields (Cheryan et al., 2015; Wang & Degol, 2017). Based on several promising studies (Olson & Martiny, 2018; Shin et al., 2016; Van Camp et al., 2019), it appears that one way to break down gender stereotypes and stereotypical images of STEM professionals is to expose students to diverse images of scientists as well as to both female and male STEM role-models. It is also essential that, as important socializers and role-models, teachers become aware of the impact of gender stereotypes and of their own expectations and behaviors in shaping young people’s academic interests and career aspirations (DeWitt et al., 2013; Sáinz et al., 2012; Vekiri, 2012). Finally, teachers need to have access to learning materials and resources that will help them both reflect on their own classroom practices and provide students with appropriate learning experiences.

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Gender Equity and STEAM Education STEAM education is a new pedagogical approach that combines STEM subjects with Art(s). According to a dominant approach, among several alternative perspectives (Perignat & Katz-Buonincontro, 2019), regarding the definition of “A” in STEAM, A stands for various art forms, including dance, theater, music, visual and media arts (Martinez, 2017). It is expected that integrating the arts in STEM learning will help students develop a unique set of diverse skills, such as problem solving and algorithmic thinking as well as creativity and trans-disciplinary thinking, that are considered important in 21st century (Henriksen, 2014; Meletiou-Mavrotheris, 2019; Perignat & Katz-Buonincontro, 2019). Further, STEAM education is expected to increase innovation in STEM fields (Perignat & Katz-Buonincontro, 2019). Many important STEM thinkers, including many Nobel Prize winners, had multiple talents and artistic avocations which helped them develop skills useful in their research, such as visual imagination and aesthetic sensibility (Root-Bernstein et al., 2008). Therefore, adding artistic and design concepts to STEM learning is expected to facilitate the development of thinking processes required in STEM, such as deductive and analogical reasoning (Henriksen, 2014; Wajnkurt & Sloan, 2019). Another approach regarding the definition and purpose of A(rts) in the STEAM acronym proposes that, in addition to various art forms, liberal arts and humanities are also a part of “A” and should thus be included in STEAM (Perignat & Katz-Buonincontro, 2019). An advantage of this approach is that, besides preparing the future workforce for STEM jobs and facilitating a more holistic understanding of complex topics, combining the arts and humanities with STEM subjects may attract more students, particularly females, to STEM studies and careers. STEAM education may help them better understand the connection between STEM and real-world problems and situations, and, therefore, appreciate the value and social contributions of STEM fields (Wajnkurt & Sloan, 2019). Another reason why STEAM education is expected to attract more students to STEM fields is because it employs pedagogical approaches which can increase student motivation. Research has shown that students’ motivational beliefs can increase with the use of inquiry-oriented, problem solving or construction activities that are personally relevant, and by pedagogical practices that create links between academic subjects and encourage collaboration and creativity (Carbonaro, Szafron, Cutumisu, & Schaeffer, 2010; Chi, Wang, & Liu, 2021; Hazari, Sonnert, Saddler, Shanahan, 2010; Vekiri, 2013). These pedagogical approaches and practices have been found to influence positively not only female students’ interest in and enjoyment of STEM subjects but also their intention to pursue STEM studies and careers (Hazari et al., 2010; Sharma, Torrado, Gómez, & Jaccheri, 2021). In STEAM education projects students engage in investigations about authentic, ill-structured problems which often originate in situations that they encounter in their everyday lives (Bush & Cook, 2019; Martinez, 2017; Roehring, Dare, Ring-Whalen, & Wieselmann, 2021). This may help students recognize the relevance of STEAM knowledge and skills to the real world and develop a better understanding of STEM/STEAM fields and professional activities (Cairns, 2019; Chi et al., 2021): their diversity, their collaborative and creative nature, their relevance to everyday life, and their contribution to society. In STEAM educational scenarios students have opportunities to experience several aspects of STEAM professional and research activities: they work in groups and therefore they need to explain and negotiate their ideas with others, they need to search for and to analyze information, carry out experiments and design algorithms and products as solutions to problems, and, finally, they need to present their conclusions and solutions and to convince others about the quality of their ideas.

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FIELD RESEARCH ON STUDENTS’ VIEWS AND EXPERIENCES As part of the FemSTEAM Mysteries project a survey was carried out, involving adolescent students (ages 12-15) from 3 schools in Cyprus, Spain, and Greece (n = 361). The purpose of the survey was to gather information about students’ backgrounds, experiences, and views, which would be utilized in the development of the project methodological guidelines and the design of the FemSTEAM Mysteries game. The instrument addressed various topics about STEM/STEAM studies and careers, student views about gender and STEM/STEAM studies and careers, and their school and after-school experiences. In this section only some key findings of this study will be presented, as a detailed presentation of data analysis and results will appear in other project publications. Overall, the results of the field study are consistent with the main conclusions of the literature review. One interesting finding is that students are being encouraged to take higher-level math or science courses by their family (n=240, 66.7%) and that the percentages of boys and girls who receive encouragement to take higher-level math or science courses are quite similar (e.g. 68.9% of boys and 65.1% of girls reported receiving parental encouragement). However, only about half of the students reported knowing about STEAM/STEAM careers (n=146, 40.5%) and how to find information about them (n=161, 44.7%). Also, they seem to rely a lot on the media to get career advice, and mostly on the internet (n=310, 85.9%) and on social media (n=105, 29.1%) which provide access to information sources that are not necessarily trustworthy. In addition, significant proportions of students expressed stereotypes about the nature of STEM professions and provided responses showing that they were not aware of the job prospects in STEM. For example, several students agreed or strongly agreed with the statements “science, technology, or engineering related jobs are monotonous” (28% of boys and 23% of girls) and that “science, technology, or engineering related jobs are rather solitary” (33% of boys and 26% of girls). Also, only a little more than half of the students thought that “science, technology, or engineering related jobs pay higher wages” (58.8% of all students) and that “there are many interesting STEM related jobs” (59.8% of all students). Finally, although students overall did not endorse gender stereotypes about the ability of women to succeed in STEM studies, a considerable proportion of male students expressed conservative views regarding the role of women in STEM careers and the impact that a STEM career might have on their family responsibilities. For example, around one-third (31.1%) of male students (vs. 17.7% of female students) agreed with the statement that “a woman who is really dedicated to a career in science, technology, or engineering would not be able to devote much time or energy to her family”. Taken together, the above findings highlight the need to provide both male and female students with learning experiences that will challenge stereotypes about gender and STEM careers as well as stereotypes about the nature of STEM research and professional activities. Also, students do not seem to be adequately informed on the scope and prospects of STEM/STEAM studies and careers and will therefore benefit from learning experiences and resources that will help them improve their understanding and make informed study and career choices.

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THE DESIGN OF THE FEMSTEAM MYSTERIES GAME The Purpose of the Game and its Pedagogical Design The FemSTEAM Mysteries game has been developed in the context of the FemSTEAM Mysteries project (REF.#: 2020-1-CY01-KA201-066058), an EU-funded two-year project (November 2020-October 2022) which focuses on gender equality in the fields of STEAM. Τhe game is addressed to teenagers (age 12-15) and aims at creating a new culture and attitude amongst teachers and students that will: (i) bring out the important role of women in STEAM; (ii) fight stereotypes of students and teachers; (iii) inspire young girls to follow STEAM careers; (iv) enhance acquisition of key skills and competences for STEAM studies and careers of all students (boys and girls); (v) enhance teachers’ skills in dealing with gender equality in STEAM. Based on role-model STEAM pedagogy, the game introduces students to important female and male scientists and artists, so as to challenge stereotypes about the characteristics of STEAM fields and about their appropriateness for females. FemSTEAM Mysteries is a story-telling digital game including 8 escape rooms, each dedicated to a specific female or male personality who, for the purpose of the game, serves as a STEAM role model. Two personalities are represented from each project partner country (Cyprus, Spain, Greece, and Germany), who were selected due to both their contributions to their respective fields as well as their leading role in activities and/or institutions aiming at promoting gender equality. Examples of these personalities include Christiane Nüsslein-Volhard, a German biochemist who won a Nobel prize in Medicine for her research in genetics and embryology and who established a foundation to support promising young female scientists, and Eleni Stroulia, an award-winning Greek computer scientist who, in addition to her scientific research at the University of Alberta, founded a support group for women and other disadvantaged groups among computing students. Also, some of these personalities, such as Tefcros Michaelidis and Carlos Pacheco Perujo, have academic and professional backgrounds in both STEM and the Arts: Tefcros Michaelidis is a Cypriot math teacher with a PhD in mathematics as well as an award-winning writer of crime novels that combine mathematics with mystery stories, and Carlos Pacheco Perujo is an award-winning Spanish comic book artist with a background in biochemistry and molecular biology. To solve the mystery of each escape room, game players need to study the biography of each role model and collect information regarding their studies, scientific and professional contributions and accomplishments, and their activities relative to the promotion of gender equality. It is expected that learning about these personalities will challenge students’ stereotypes about gender and STEAM fields as well as about the characteristics of scientists and artists and the nature of their work. Students may realize that there are several distinguished female scientists who made significant contributions to their fields and who were also successful at combining their career with a fulfilling personal life. This information challenges stereotypes about the intellectual talents of women relative to STEM fields as well as about the appropriateness of STEM/STEAM careers for women, due to the conflict of such careers with women’s stereotypical social roles. At the same time, students may become aware of the gender bias and the various types of difficulties that women may face when pursuing careers in STEAM and, also, acknowledge the need to fight against stereotypes that create obstacles for women. Providing a variety of STEAM biographies is expected to increase the possibility that female students may relate with particular STEAM role-models that they consider a better fit for them (e.g., due to common country of origin or interests), so as to get inspired for their future studies and career. Also, playing the game may help both female and male students learn about the variety of careers and career paths that are available to students 49

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who pursue studies in STEAM after completing compulsory education. Finally, by requiring students to find, associate and put together pieces of information to solve the 8 mysteries, the game contributes to the development of various cognitive skills, such as search, observation, reasoning, problem-solving skills and critical thinking (Wiemker et al., 2015), which are important in STEAM studies and beyond. Figure 1. A snapshot of the lab space assigned to Christiane Nusslein-Volhard

Figure 2. A close-up of the lab space assigned to Christiane Nusslein-Volhard

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Figure 3. A snapshot of the notebook tool

FemSTEAM Mysteries Gameplay In the FemSTEAM Mysteries game, players undertake the role of investigators, to resolve a mystery involving 8 STEAM scholars and professionals who lost their memories. When they start the game students are informed that a great magician, who claims that he can erase people’s memories, uses a big STEAM Conference that attracts many famous scientists and artists as an opportunity to prove his abilities. The magician manages to erase the memory of everyone in the building which hosts the conference and provides accommodation for its participants. Game players, that is, students and their teacher, survived this magic trick and are therefore asked to find the identities of the 8 leading scientists and artists working or staying in the building, to give them back their memory. To do so students need to visit the rooms of these STEAM personalities (the 8 escape rooms) and find information to figure out their identities. The design of each room (space, furniture, objects, puzzles, and clues) is based on the field of expertise, achievements, contributions, and studies of the personality who stays or works in the room. After getting into a room, players can use a variety of ways to move around and interact with objects (e.g. letters, email messages, photos, presentations, invitations), to find clues about the scientist or artist who uses the room. For example, players can look at a specific point or object from different angles, zoom in on an object, open cabinets and drawers to find hidden objects, and take objects for their inventory, for later use. To win a room, students must use the clues provided in some of these objects and fill in the correct information in a notebook, describing the profile of the scientist or artist who they think uses the room. If players solve all puzzles and correctly identify the personality living/working in the room, then his/her name, field, title of presentation, and country of origin appears automatically in the STEAM Conference agenda and one piece of the mystery is solved. Snapshots of the game are shown in Figures 1-3. In Figure 1 we can see the room (lab space) that is assigned to Christiane Nusslein-Volhard. Players can look around to search for clues (see Figure 2) and if they find a useful object they can save it in their backpack (that appears on the upper-left corner of Figures 1 and 2). Using the clues that they

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have collected students can visit their notebook (that appears on the lower right corner of the screen in Figure 1) to fill in information regarding the specific role model, such as his/her country of origin, field of expertise and significant accomplishments. A screenshot of a Notebook page appears in Figure 3.

FemSTEAM Mysteries in the Classroom Escape room games have become popular in education because they are problem-based, require collaboration, improve motivation, support the development of cognitive skills, involve students actively in learning and encourage them to think unconventionally (Vidergor, 2021; Wiemker et al., 2015). Recent reviews (e.g., Fotaris & Mastoras, 2019) indicate that educators show preference for physical rooms, which they find easy to develop, while digital or hybrid escape room games (offering both virtual and physical objects) are less common. Also, it seems that escape room games have not found their way in secondary or elementary school settings, as most relevant published studies focus on higher education (Fotaris & Mastoras, 2019; Vidergor, 2021). One challenge of implementing physical escape room games, that may partly explain teachers’ reluctance to integrate them in classroom activities, is that student teams who work in the same space may distract each other, while having student teams work in multiple separate spaces simultaneously is very difficult for teachers to manage. Another challenge is that designing and setting up physical games and clearing away activities is time demanding for teachers (Fotaris & Mastoras, 2019; Veldkamp et al., 2020). Using digital games, however, can help teachers overcome these challenges because setting up the game is much easier, and all student teams can work synchronously in the same physical space or from a distance (e.g., from home). FemSTEAM Mysteries is a digital game and as such it can be played in a variety of physical and social settings. Students need approximately 15-20 minutes to solve the puzzles and exit one room, so it is easy to play and discuss one complete part of the game within one class period. FemSTEAM Mysteries will be available in English as well as in three other languages (Greek, Spanish, and German, which are the official languages of the four project partner countries) and will be accompanied by a teacher guidebook. In the guidebook teachers may find information about the allocation of the 8 escape rooms as well as about the 8 role models. This enables them to select and assign specific rooms to students, to play either in one class period or as a homework assignment at home. Also, teachers have the option to use only one or a few rooms instead of the entire game, to support the learning objectives of a particular lesson. In addition to the guidebook, various other resources will be available to secondary school teachers to support the use of the digital game in the classroom. These include a collection of STEAM educational scenarios, providing ideas and recommendations both for integrating the game in the classroom and for extension activities, and a Library with learning materials for role-model and game-based pedagogy as well as with resources on legendary female scientists. Finally, given the important role of teachers in the enactment of STEAM pedagogy and in the development of students’ beliefs and academic aspirations, as well as the fact that teachers are often unfamiliar or uncomfortable with incorporating STEAM activities, professional development is a key priority of the FemSTEAM Mysteries project. A blended professional development course on promoting gender equality in STEAM through serious games, game-based activities and tools, and role-models has been developed. Participating teachers were familiarized with the FemSTEAM Mysteries pedagogical approach, so as to use the FemSTEAM Mysteries game and to create accompanying STEAM educational scenarios to implement in their classrooms. The professional development course initially targeted secondary school STEAM teachers in partner countries. However, the course material and resources 52

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will be revised based upon feedback received from the pilot testing and follow-up experimentations in participating teachers’ classrooms and will be released for independent use by any interested stakeholder across Europe and internationally.

CONCLUSION Serious games have the potential to advance several goals of STEAM education, including motivation to learn STEAM content, interest in STEAM fields, and the development of 21st century skills, such as creative thinking as well as reasoning, problem solving and inquiry skills (Boyle et al., 2016; Clark et al., 2016; Lamb et al., 2018; Vidergor, 2021; Vogel et al., 2006; Wouters et al., 2013. Although there are several quality commercial off-the-shelf games that can be used in the classroom (Van Eck, 2009), it is quite challenging for teachers to integrate a commercial game in a way that its use serves specific curriculum and lesson goals and does not distract from learning (Marklund & Alklind Taylor, 2016; Romero & Barma, 2015). Therefore, there is a need for learning games which are aligned with the curriculum and support students to achieve specific learning goals while at the same time also providing students with an enjoyable and engaging experience. By presenting the design of an educational escape room game, this book chapter highlights several game design issues that should be taken into account, to support effective game-based learning in STEAM. First of all, good learning games should be fun to play, and this is an issue that was taken into account in the FemSTEAM Mysteries game which was designed to have the characteristics of an escape room game, to engage and motivate learners: a challenge including puzzles and meta-puzzles embedded in a narrative, “intrinsic integration” between gameplay and learning content, as puzzles in the game world are relatively similar to what the player would have to do in the real world, interesting graphics, fantasy, interactivity, and continuous feedback. In addition, it is important that game design is based on a solid theoretical framework that justifies the educational value of the game and supports its pedagogical approach. The pedagogical design of the FemSTEAM Mysteries game draws upon several bodies of literature and addresses an important educational and societal problem (the underrepresentation of females in STEM/STEAM) using a pedagogical approach (role-model education, STEAM education) that is based on a thorough analysis of the problem. Finally, the design of learning games that are intended for classroom integration needs to consider several of the contextual factors that may constitute barriers to game-based learning. These factors may include logistical challenges, relative to school schedules and infrastructure, as well as teacher knowledge, views, and attitudes. As explained in the previous section, the FemSTEAM Mysteries game was designed so as to be easily integrated in the typical daily school program or to be played at home. Also, it is accompanied by a teacher’s guidebook and various learning resources for teachers (including educational scenarios and professional development materials) to support its effective implementation in the classroom.

ACKNOWLEDGMENT This research was supported by the European Commission [grant number 2020-1-CY01-KA201-066058].

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Van Camp, A. R., Gilbert, P. N., & O’Brien, L. T. (2019). Testing the effects of a role model intervention on women’s STEM outcomes. Social Psychology of Education, 22(3), 649–671. doi:10.100711218-01909498-2 Van Eck, R. (2008). COTS in the classroom: A teacher’s guide to integrating commercial off-the-shelf (COTS) games. In R. E. Ferdig (Ed.), Handbook of research on effective electronic gaming in education (pp. 179–199). IGI Global. doi:10.4018/978-1-59904-808-6.ch011 Vekiri, I. (2010). Users and experts: Greek primary teachers’ views about boys, girls, ICTs and computing. Technology, Pedagogy and Education, 22(1), 73–87. doi:10.1080/1475939X.2012.753779 Vekiri, I. (2013). Information science instruction and changes in girls’ and boy’s expectancy and value beliefs: In search of gender-equitable pedagogical practices. Computers & Education, 64, 104–115. doi:10.1016/j.compedu.2013.01.011 Veldkamp, A., Daemen, J., Teekens, S., Koelewijn, S., Knippels, M.-C. P. J., & van Joolingen, W. R. (2020). Escape boxes: Bringing escape room experience into the classroom. British Journal of Educational Technology, 51(4), 1220–1239. doi:10.1111/bjet.12935 Vidergor, H. E. (2021). Effects of digital escape room on gameful experience, collaboration, and motivation of elementary school students. Computers & Education, 166, 104156. doi:10.1016/j.compedu.2021.104156 Wach, F.-S., Spengler, M., Gottschling, J., & Spinath, F. M. (2015). Sex differences in secondary school achievement-The contribution of self-perceived abilities and fear of failure. Learning and Instruction, 36, 104–112. doi:10.1016/j.learninstruc.2015.01.005 Wajngurt, C., & Sloan, P. J. (2019). Overcoming gender bias in STEM: The effect of adding the arts (STEAM). InSight: A Journal of Scholarly Teaching, 14, 13-28. Wang, M. T., & Degol, J. L. (2017). Gender gap in science, technology, engineering, and mathematics (STEM): Current knowledge, implications for practice, policy, and future directions. Educational Psychology Review, 29(1), 119–140. doi:10.100710648-015-9355-x PMID:28458499 Weisgram, E. S., Dinella, L. M., & Fulcher, M. (2011). The role of masculinity/femininity, values, and occupational value affordances in shaping young men’s and women’s occupational choices. Sex Roles, 65(3-4), 243–258. doi:10.100711199-011-9998-0 Wiemker, M., Elumir, E., & Clare, A. (2015). Escape room games: “Can you transform an unpleasant situation into a pleasant one?” In J. Haag, J. Weißenböck, M. W. Gruber, M. Christian, & F. FreislebenTeutscher (Eds.), Game based learning (pp. 55–68). St. Pölten, Austria: Fachhochschule st Pölten GmbH. Wouters, P., Van Nimwegen, C., Van Oostendorp, H., & Van Der Spek, E. D. (2013). A meta-analysis of the cognitive and motivational effects of serious games. Journal of Educational Psychology, 105(2), 249–265. doi:10.1037/a0031311

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ADDITIONAL READING Bado, N. (2019). Game-based learning pedagogy: A review of the literature. Interactive Learning Environments, 1–13. doi:10.1080/10494820.2019.1683587 Bamberger, Y. M. (2014). Girls into science and technology with feminine role model: Does this work? Journal of Science Education and Technology, 23(4), 546–561. doi:10.100710956-014-9487-7 Gladstone, J. R., & Cimpian, A. (2021). Which role models are effective for which students? A systematic review and four recommendations for maximizing the effectiveness of role models in STEM. International Journal of STEM Education, 8(1), 1–20. doi:10.118640594-021-00315-x PMID:34868806 Good, J. J., Woodzicka, J. A., & Wingfield, L. C. (2010). The effects of gender stereotypic and counterstereotypic textbook images on science performance. The Journal of Social Psychology, 150(2), 132–147. doi:10.1080/00224540903366552 PMID:20397590 Marklund, B. B., & Taylor, A. S. A. (2016). Educational games in practice: The challenges involved in conducting a game-based curriculum. Electronic Journal of e-Learning, 14(2), 122-135. Plass, J. L., Homer, B. D., & Kinzer, C. K. (2015). Foundations of game-based learning. Educational Psychologist, 50(4), 258–283. doi:10.1080/00461520.2015.1122533 Quigley, C. F., & Herro, D. (2019). An educator’s guide to STEAM: Engaging students using real-world problems. Teachers College Press. Tobias, S., Fletcher, J. D., & Wind, A. P. (2014). Game-based learning. In Handbook of Research on Educational Communications and Technology (pp. 485-503). New York: Springer Science+Business Media. doi:10.1007/978-1-4614-3185-5_38

KEY TERMS AND DEFINITIONS Escape Room: A game type which involves solving a challenge that is embedded in a narrative and includes many puzzles. Game-Based Learning: A pedagogical approach to integrating games in the teaching and learning process, which involves playing a fully developed game. Gender Stereotypes: Expectations about gender-appropriate roles and behaviors that are attributed to biological differences. Learning Games: Games that are developed to support specific learning goals. Role Model Pedagogy: A pedagogical approach that involves using role models to demonstrate the execution of a task or to inspire and motivate students by showing that a goal is desirable and attainable. Role Models: Individuals who serve as good examples of the attributes and traits (or of the values, attitudes, and behaviors) associated with a role. Serious Games: Complex digital games whose entertainment quality is used for educational, training, and/or communication purposes.

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Chapter 4

MiniOpenLab:

Open Community and Hands-On Approach to Sustainable Development and STEM Education – An Innovative Approach Tharrenos Bratitsis https://orcid.org/0000-0003-4257-2755 University of Western Macedonia, Greece

Virginia Arvaniti Educational Association Anatolia, Greece

Iro Koliakou Educational Association Anatolia, Greece

Teresa Sarmento Centro de Engenharia d Desenvolvimento, Portugal

Arcadio Sotto Díaz Universidad Rey Juan Carlos, Spain

Nuria Olga León Tobajas Ceipso Maestro Rodrigo, Spain

Ana Barroca Projeto Schole LDA, Portugal

ABSTRACT Education for sustainable development and STEM education are two major EU priorities. Both should be addressed from an early age. At school, children must be motivated to learn maths and science and to imagine working in these fields, and to learn about sustainability and develop attitudes and behaviours that are in line with the UN’s SD Goals. Over the past years, children have taken interest in SD and in some cases. By contrast, STEM is still regarded as difficult and unattractive by many children. Thus, it may be beneficial to couple both these fields. The project MiniOpenLabs proposes to set-up and test a different methodology with a higher prevalence of experiential learning and relying on the collaboration between science and technology organisations, enterprises, and civil society to ensure relevant and meaningful engagement of all societal actors with science and increase the uptake of science studies, citizen science initiatives and science-based careers, employability, and competitiveness.

DOI: 10.4018/978-1-6684-3861-9.ch004

Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

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INTRODUCTION The Education for Sustainable Development and STEM Education are 2 major priorities for the EU. As climate change, overpopulation, and inequalities begin to take their toll on our planet and on global human development, the Education for Sustainable Development (ESD) emerged as a response in order to change attitudes and behaviours and mobilize people around the objective of Sustainability. On the Other hand, Science, Technology, Engineering and Mathematics (STEM) Education is key for an increasingly complex knowledge-based society. “Knowledge of and about science are integral to preparing our population to be actively engaged and responsible citizens, creative and innovative, able to work collaboratively and fully aware of and conversant with the complex challenges facing society” (Science Education for Responsible Citizenship, EC, 2015). Both Sustainable Development (SD) and STEM should be addressed from an early age. At school, children must be motivated to learn maths and science and to imagine working in these fields, and to learn about sustainability and develop attitudes and behaviours that are in line with the UN’s SD Goals. However, the way children perceive and react to these 2 fields is generally different. Over the past few years, children have taken a great and genuine interest in SD and in some cases, they are even in the forefront of the battle for a more sustainable world. By contrast, STEM is still regarded as difficult and unattractive by the majority of children. Having this in mind, it may be beneficial to couple both these fields. If, in one hand, SD needs to look at science and technology for answers, on the other hand, STEM education can be made more interesting and appealing if applied to a specific field that gathers particular interest, like SD. Thus, the general interest in SD can be used to attract children to STEM. If coupling these areas of education might be beneficial, it is not enough to gather children’s interest if the learning methodologies don’t step up and respond to the needs of children. The dominant approach to STEM Education and ESD in schools is still teacher-driven. This, in part, is responsible for the students’ lack of interest in pursuing STEM studies and careers and for not exploring to a greater length the genuine interest of children in SD topics. In this context, education of STEM and Sustainable topics must take on new models with a higher prevalence of experiential learning and that can bring together schools and other actors in the local community. The MiniOpenLabs project, an EU Erasmus+ KA201 project, proposes to set-up and test a different methodology with a higher prevalence of experiential learning and relying on the collaboration between science and technology organisations, enterprises and civil society, to ensure relevant and meaningful engagement of all societal actors with science and increase the uptake of science studies, citizen science initiatives and science-based careers, employability and competitiveness. This chapter reflects upon the MiniOpenLabs concept as it was initially conceptualized by the consortium members and refined by the qualitative research carried out via the focus groups. The methodology followed will be described and insights gathered will be reported. The remaining of the chapter is structured as follows: initially a brief theoretical background is presented, justifying the significance of the involved disciplinary areas. Then the research methodology is described, followed by a reflective report of the findings. The chapter concludes with a discussion and a brief presentation of the MiniOpenLabs concept.

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BACKGROUND In this section, a brief overview of the involved disciplinary areas and the corresponding terminology is presented. Two main pillars consist the background of the project, namely STEM Education and ESD.

STEM Education The term STEM was first introduced by Judith Ramalay, a biologist, head of the National Foundation of Sciences (NSF) in the USA, in 2001(Breiner et al., 2012). The acronym refers to science, mathematics, engineering and technology. The initial idea was to see how the T and E constituents could be used to teach S and M, deriving from earlier educational attempts and policies in the USA in the late 80s-early 90s which aimed at enhancing S and M education (Sanders, 2009). Originally, SMET was introduced as the corresponding term (e.g. NSFDE, 1980). Since then, the term has gained significant momentum, although many cases can be found in which the S, M and T constituent terms are used with the STEM term interchangeably. The latter has been a rather important problem in the educational (mainly) but also the research community. Until recently, STEM education has been ill-defined, and even those involved in STEM-related careers often cannot adequately identify how STEM connects to their career, how they use STEM on a day-to-day basis, or the impact STEM has on their given field (Breiner et al., 2012). Many educators mainly seem to focus on the disciplinary area they treat, especially in secondary education, also integrating ate least one of the other constituents of STEM (Breiner et al., 2012), a misconception which merely still exists. Besides, Holmlud et al. (2018) state that STEM education can be considered a single or multi-disciplinary field, and in the case of the latter, no clear consensus exists on the nature of the content and pedagogic interplay among the STEM fields. They justify their claim by explaining that although Science and Mathematics education are well-defined, although separate, entities across the curricula, mainly Engineering and Technology education concerned higher levels of education until recently. Bybee (2010) provides five (5) different STEM definitions as follows: 1. 2. 3. 4. 5.

a general term referring to education (of all ages) in STEM-related fields, a “slogan” used in the marketing of education services worldwide, a term that has replaced the reference to mathematics and the sciences in general, market opportunities for graduates of the faculties and sciences of education; and a holistic approach to the teaching of science in the school environment and not only.

These definitions are broad and cover the issues addressed in the education of minors and adults, their vocational rehabilitation and the reference to the term. In fact, STEM has been used as a term in many context and in many ways that its meaning can be considered ambiguous (Bybee, 2013; Sanders, 2009). STEM programs in schools can differ significantly with each other. Depending on the infrastructure (e.g. access to robotics, 3D printers, computers, etc), their program can focus on the T of STEM but have little to no incorporation of engineering or science and math. Another school can have very little technology but have students ideating, building, and conversing about real-world problems. As there is no universal definition of STEM, there is a wide variety of ways in which it is being incorporated into schools (Ansorger, 2020).

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Attempting to fully conceptualize STEM Breiner et al. (2012) examine it from an educational, a political - societal and a personal perspective. Mainly focusing on the former, they state “STEM is often considered a traditional disciplinary coursework (science, mathematics, technology, and engineering) lacking an integrated approach”. Thus, they follow the term integrated STEM, as originally proposed by Sanders (2009) or Labov et al. (2010) who claim that “STEM is the purposeful integration of the various disciplines as used in solving real-world problems”. Following this approach, all four disciplines would be treated as one unit, a cohesive entity for the purpose of solving realistic problems, with the mindset of “purposeful design and inquiry” which combines technical design with scientific inquiry (Sanders, 2009: 21). As Sanders (2009) explains, the reason is that in the world outside of schools, “design and scientific inquiry are routinely employed concurrently in the engineering of solutions to real-world problems. This fully complies with the definition of STEM provided by the Southwest Regional STEM Network (Nathan & Nilsen, 2009), which is “STEM education is an interdisciplinary approach to learning where rigorous academic concepts are coupled with real world lessons as students apply science, technology, engineering, and mathematics in contexts that make connections between school, community, work, and the global enterprise enabling the development of STEM literacy and with it the ability to compete in the new economy”. This definition opens up to the societal aspects of STEM education, connecting it with competence development in order to become a useful citizen and a valued professional in the contemporary society and economy. Kelley & Knowles (2016) define integrated STEM as incorporating two or more STEM subjects and using STEM practices in an authentic context which connects the content in a way which supports student learning. Following this approach, each subject can interact with and affect the others, thus further enhancing the perspective of examining STEM as what Stergiopoulou et al. (2017) refer to as “an invisible whole”. Wang et al. (2011), differentiate between interdisciplinary and multidisciplinary approaches. In the latter, concepts and skills of a subject are learned separately in each discipline. Students need to link the content from different subjects by themselves. An interdisciplinary approach, starts with problems or real-world problems and emphasis on interdisciplinary content and skills such as critical thinking and problem-solving, instead of subject-specific content and skills (Arifin & Mahmud, 2021). Stohlmann et al. (2012), describe the merging of disciplines into one activity, a common practice in STEM approaches, as content integration and the teaching of the content of one discipline that uses contexts from other disciplines to make content more relevant as context integration. In the case of integrated STEM, mainly the term refers to the creation of explicit relationships across the 4 disciplines via the combination of some or all four disciplines of science, technology, engineering, and mathematics into one class, unit, or lesson based on the relationship between subjects and real-world problems (Moore et al., 2014). On a wider perspective, referring to the whole curriculum, Breiner et al. (2012) refer to the integration of concepts of the four disciplines in a way that reflects STEM professional practice to encourage students to pursue the STEM profession. For Kelley & Knowles (2016) but also Schnittka (2016), STEM integration in school settings refers to scientific research practices which involve students in constructing their own questions and investigations, technological literacy in which students use instruments, engineering design to provide a systematic approach to problem solving, and mathematical solutions. Despite the term definition, most researchers agree on the importance of STEM Education. Smith, Douglas & Cox (2009) for that matter focus on interactive learning and innovation. More specifically, they explain that with STEM teachers are allowed to:

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• • • •

Increase student participation, Improve their teaching methods, Increase interest, Apply the methods of inclusive education.

Moreover, Subotnik, Edmiston, & Rayhack (2007) describe STEM based programs that mainly concern students from disadvantaged groups or students with excellent performance. Foltz, Gannon, & Kirschmann (2014) also focus on students belonging to minorities, who analyze how STEM can affect and be used with such categories of students, regardless of age. They identify a tendency of minorities to choose STEM studies, considering that it will offer them a higher social status. But, at the same time, they observe that social order affects the understanding of social phenomena and, therefore, the course of these individuals, both professional and social. It is also reported that the more familiar children are with concepts related to technology and science, the greater their chances of success in these areas. For this reason, it is emphasized that the study of STEM concerns, indeed, both the field of technological education and sciences, as well as tools, practical and didactic approaches. Freeman, Dorph, & Chi (2009) explain that the STEM approach is very significant in the modern business environment, since it allows the emergence of new sciences. They introduce the term “STEM - Literate - Workforce”, a term which refers to whether one has sufficient knowledge in the above areas (technology, science, engineering and mathematics), as well as the methods by which a student learns. For Freeman, Dorph & Chi (2009), STEM can be applied: • • •

Within the classroom as a tool, Outside the classroom (for studying), In the macroeconomic environment, especially if one studies the demand for skilled jhuman resources.

Thus, one can define STEM as “the ability of the individual to study and understand science”. This definition is derived from the overall analysis of the study by Freeman, Dorph & Chi, (2009), as well as the definitions provided by Sanders (2009), Breiner et al. (2012), Smith, Douglas & Cox (2009), Subotnik, Edmiston, & Rayhack (2007) and Foltz, Gannon, & Kirschmann (2014). Besides, as Bybee (2010) described, the STEM integration approach can be applied to solve global problems on energy, health and the environment, population growth, environmental problems, agricultural productions and many more. It requires a global approach supported by in-depth research in science and technology to address this issue (Thomas & Watters, 2015). The traditional way of thinking is not enough to deeply understand the complex problems that can affect the environmental, social and economic domains (Davis & Stroink, 2016). Sampurno, Sari & Wijaya (2015) focus on the contribution of STEM in creating competitive professional, and therefore the impact of education on the economy, development and research / technology, in the future. For researchers, investing in this field will have the following positive effects: • •

The observation and critical ability of pupils and students will increase, Students will be encouraged to engage in an active dialogue about the real problems facing society today

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Thus, the benefits are both economic and social but, mainly, are found in the field of education (Sampurno, Sari, & Wijaya, 2015). The key point, seems to concern how one can integrate these tools in the existing educational process. Rosicka (2016) highlights the importance of including in STEM Education definitions also different teaching methods and procedures used to help students understand scientific theories, and to acquire problem-solving and analytical thinking skills. Prinsley & Johnston (2015) believe that, in order for education to evolve as a sector and for teachers to be able to offer a high level of knowledge to students, it is necessary to invest in STEM approaches, starting from Primary Education. Research shows that various models exist for the content and instructional practices associated with STEM education (Holmlund et al., 2018). These include the incorporation of an engineering design process into the curriculum (Lesseig et al. 2017; Ring et al. 2017; Roehrig et al. 2012), a thematic approach centered around contemporary issues or problems that integrates two or more STEM areas (Bybee 2010; Zollman 2012), and makeroriented programs such as robotics, coding, and Maker Faires, which may occur outside of the regular school curriculum (Bevan et al. 2014). Overall, one cannot deny the significance of STEM Education, despite the diverse approaches in defining or implementing it. Likewise, the fact that STEM Education can lead to the development of competences related to the understanding of complex real-life problems and the acquisition of systematic ways to solving them cannot be disputed. Thus, the MiniOpenLabs conceptual approach attempts to address these issues in an innovative way, extending STEM Education outside the traditional classroom settings, as described later in this chapter.

Education for Sustainable Development Education for sustainable development (ESD) is defined as education that encourages changes in students’ competences (defined as sets of knowledge, skills, values and attitudes) to enable a more sustainable and just society for all (UNESCO, 2013a). It empowers learners of all ages with the competences to address the interconnected global challenges we are facing, including climate change, environmental degradation, loss of biodiversity, poverty and inequality. According to UNESCO (2013a), learning must prepare students and learners of all ages to find solutions for the challenges of today and the future. It aims at equipping current and future generations to meet their needs using a balanced and integrated approach to the economic, social and environmental dimensions of sustainable development (UNESCO, 2018). ESD is an indispensable and transformative component of the international agenda on Quality Education and Lifelong Learning (SDG 4.7 – Human Rights Education). ESD is a key element of the 2030 Agenda for Sustainable Development. As it integrates the goals of SDG 4.7, it is considered a driver for the achievements of all 17 SDGs. It supports learners, educators, schools and their communities vis-à-vis global societal and challenges by focusing on the knowledge, skills, values and attitudes that people need to be active citizens and contribute to the well-being of people and the planet. ESD empowers everyone to make informed decisions in favour of environmental integrity, economic viability and a just society for present and future generations. It aims to provide the knowledge, skills, attitudes and values necessary to address sustainable development challenges. Furthermore, it strives to integrate issues related to all dimensions of sustainable development in curricula, pedagogical approaches, learning materials and teacher education and strengthen evidence-based approaches. UNESCO has identified ESD as a crucial element in preparing for and tackling global crises such as COVID-19.

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Figure 1. ESD process (UNESCO, 2013b)

Source: UNESCO, 2013b

The concept of ESD emerged from the need for education to address the growing and changing environmental challenges facing the planet (UNESCO, 2018). As societies around the world struggle to keep pace with the progress of technology and globalization, they encounter many new challenges. These include (among others) increasing complexity and uncertainty, more individualization and social diversity, expanding economic and cultural uniformity, degradation of the ecosystem services upon which they depend and greater vulnerability and exposure to natural and technological hazards. Moreover, a huge amount of information is available to today’s citizens, having the tendency to increase significantly over time. All these conditions require creative and self-organized action as the complexity of such situations surpass basic problem-solving processes that go strictly according to plan. People must learn to understand the complex world in which they live. They need to be able to collaborate, speak up and act for positive change (UNESCO, 2015). These people are called “sustainability citizens” (Wals, 2015; Wals and Lenglet, 2016). In UNESCO (2017), a concrete set of key competences for sustainability is described. These are: systems thinking competence, anticipatory competency, normative competency, strategic competency, collaboration competency, critical thinking competency, self-awareness competency and integrated problem-solving competency. The sustainability key competencies represent what sustainability citizens particularly need to deal with today’s complex challenges. They are relevant to all SDGs and also enable individuals to relate the different SDGs to each other, according to the 2030 Agenda for Sustainable Development.

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The SDGs (Sustainable Development Goals) is a set of 17 goals introduced in the 2030 Agenda Framework, describing major development challenges for humanity. The aim of the 17 SDGs is to secure a sustainable, peaceful, prosperous and equitable life on earth for everyone now and in the future. The goals cover global challenges that are crucial for the survival of humanity. They set environmental limits and set critical thresholds for the use of natural resources. The goals recognize that ending poverty must go hand-in-hand with strategies that build economic development. They address a range of social needs including education, health, social protection and job opportunities while tackling climate change and environmental protection. The SDGs address key systemic barriers to sustainable development such as inequality, unsustainable consumption patterns, weak institutional capacity and environmental degradation. The 17 SDGs are enlisted in Table 1. For each one of the SDGs, UNESCO (2017) describes the specific learning objectives in the cognitive, socio-emotional and behavioural domains. The cognitive domain comprises knowledge and thinking skills necessary to better understand the SDG and the challenges in achieving it. The socio-emotional domain includes social skills that enable learners to collaborate, negotiate and communicate to promote the SDGs as well as self-reflection skills, values, attitudes and motivations that enable learners to develop themselves. The behavioural domain describes action competencies. Additionally, for each SDG, indicative topics and pedagogical approaches are outlined. Education must be strengthened in all agendas, programs, and activities that promote sustainable development. Sustainable development must be integrated into education and education must be integrated into sustainable development (UNESCO, 2014). ESD is holistic and transformational education that addresses learning content and outcomes, pedagogy and the learning environment. Thus, ESD does not only integrate contents such as climate change, poverty and sustainable consumption into the curriculum; it also creates interactive, learner-centred teaching and learning settings. What ESD requires is a shift from teaching to learning. It asks for an action-oriented, transformative pedagogy, which supports self-directed learning, participation and collaboration, problem-orientation, inter- and transdisciplinarity and the linking of formal and informal learning. Only such pedagogical approaches make possible the development of the key competencies needed for promoting sustainable development (UNESCO, 2017). ESD promotes the integration of critical sustainability issues in local and global contexts into the curriculum to prepare learners to understand and respond to the changing world. It aims to produce learning outcomes that include core competencies such as critical and systematic thinking, collaborative decisionmaking, and taking responsibility for the present and future generations (UNESCO, 2013). Traditional knowledge delivery seems to not be sufficient to inspire learners to take action as responsible citizens. Thus, ESD entails rethinking the learning environment, physical and virtual. The learning environment itself must adapt and apply a whole-institution approach to embed the philosophy of sustainable development. Building the capacity of educators and policy support at international, regional, national and local levels helps drive changes in learning institutions. Empowered youth and local communities interacting with education institutions become key actors in advancing sustainable development (UNESCO, 2013). Overall, ESD is about real-life problems, not to say future life problems. As such, they fully comply with the STEM approaches described in the previous section, providing context for STEM problems, but also complementing the competence cultivation through STEM approaches by providing ground for knowledge applicability. What is also important to note is the way of ESD delivery which is described in UNESCO (2017), which states that ESD is not only about teaching sustainable development and adding new content to courses and training. Educational entities should see themselves as places of learning and experience for sustainable development and should therefore orient all their processes towards principles 68

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of sustainability. They should reconsider and redesign themselves, rethinking the curriculum, campus operations, organizational culture, student participation, leadership and management, community relationships and research (UNESCO, 2014). Fig. 2 presents the “whole-institution” idea of UNESCO, which describes the interconnection of an educational entity or a training facility with the community, formal education and society. The MiniOpenLab idea is grounded on this approach, as it supports its connection with society both on a local and a global perspective. Table 1. The 17 Sustainable Development Goals (SDGs) SDG

Asynchronous E-Learning

1

No Poverty – End poverty in all its forms everywhere

2

Zero Hunger – End hunger, achieve food security and improved nutrition and promote sustainable agriculture

3

Good Health and Well-Being – Ensure healthy lives and promote well-being for all at all ages

4

Quality Education – Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all

5

Gender Equality – Achieve gender equality and empower all women and girls

6

Clean Water and Sanitation – Ensure availability and sustainable management of water and sanitation for all

7

Affordable and Clean Energy – Ensure access to affordable, reliable, sustainable and clean energy for all

8

Decent Work and Economic Growth – Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all

9

Industry, Innovation and Infrastructure – Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation

10

Reduced Inequalities – Reduce inequality within and among countries

11

Sustainable Cities and Communities – Make cities and human settlements inclusive, safe, resilient and sustainable

12

Responsible Consumption and Production – Ensure sustainable consumption and production patterns

13

Climate Action – Take urgent action to combat climate change and its impacts

14

Life below Water – Conserve and sustainably use the oceans, seas and marine resources for sustainable development

15

Life on Land – Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss

16

Peace, Justice and Strong Institutions – Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels

17

Partnerships for the Goals – Strengthen the means of implementation and revitalize the global partnership for sustainable development

RESEARCH METHODOLOGY What becomes apparent from the previous section of this chapter is that both STEM and ESD play a significant role in children’s cognitive and overall development, but also that they should be addressed properly from a very early age. The literature indicates the significance of familiarizing students with the UN’s 17 SDGs through also activities which are extended outside the typical classroom walls, connected with society on a local and global level.

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Figure 2. The whole-institution approach (UNESCO, 2014)

Source: UNESCO, 2014

However, the way children perceive and react to these 2 fields is generally different. Over the past few years, children have taken a great and genuine interest in SD and in some cases, they are even in the forefront of the battle for a more sustainable world. By contrast, STEM is still regarded as difficult and unattractive by the majority of children. Having this in mind, it seems beneficial to couple both these educational fields. If, on one hand, SD needs to look at science and technology for answers, on the other hand, STEM education can be made more interesting and appealing if applied to a specific field that gathers particular interest, like SD. Thus, the general interest in SD can be used to attract children to STEM. If coupling these areas of education might be beneficial, it is not enough to gather children’s interest if the learning methodologies don’t step up and respond to the needs of children. The dominant approach to STEM Education and Education for Sustainable Development in schools is still teacher-driven. This in part is responsible for the students’ lack of interest in pursuing STEM studies and careers and for not exploring to a greater length the genuine interest of children in SD topics. For these reasons, the idea of the MiniOpenLabs approach emerged within the consortium. Although a general idea was already formulated, a mixed-method research approach was applied within the first

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output of the MiniOpenLabs project in order to provide grounds for its development. On one hand a desk-research was carried out in order to identify and analyse similar approaches within the literature, including living laboratories, makers spaces, fablabs, etc. As the idea of the MiniOpenLabs extends learning also outside the typical classroom walls, other approaches were studied in order to identify structural and qualitative elements that could further enhance the approach. On the other hand, a qualitative research approach was designed in order to acquire insights from the potential end-users and experts on the corresponding fields (STEM and SD). This chapter reflects only upon this study. The participating teachers were mainly from Elementary School, as the project’s main target group is children aged 6 to 12 years old.

The Focus Groups In the MiniOpenLabs project 6 partners from 3 countries are involved, namely a school and a higher education or research institution. Overall it was decided to form 3 focus groups, one in each country, with at least 24 participants overall. The initial idea was to not have the focus groups meet only once, but as many times as needed in order to elaborate on the expressed ideas. Each focus group included a moderator from the higher education or research institution, an assistant and the participants. The Greek focus group comprised of 1 moderator, 1 assistant and 24 participants. The latter were school teachers (8), STEM instructors (10) and educational coordinators (6). The Spanish focus group comprised of 1 moderator and 10 participants, covering all the STEM areas as experts (university teaching staff and/or researchers) or school teachers. The Portuguese focus group comprised of 1 moderator and 6 participants, teachers, experts on the corresponding areas and policy makers (on a municipal level). Thus overall, 41 people participated in the 3 focus groups. A basic question structure was available for the conduction of the focus groups, starting from the participants’ perception of what STEM and SD are. Then, their perception of the community’s involvement, thus extending the corresponding teaching activities outside the school premises was examined, focusing on the significance, the way of realization and strategies of engagement. In the final part of the discussions, the idea of the MiniOpenLabs was brought up, asking the participants to freely express their ideas and perceptions of its infrastructure, function and overall contribution to both students and the community. The answers were transcribed and examined following a thematical analysis approach in order for them to be coded and correlated with the initial idea of the MiniOpenLabs concept. This approach allowed the consortium to further elaborate on this concept and reach its final and definite description which is presented in the corresponding section of this chapter.

Insights In this section, a brief overview of the insights provided by the participants of the focus groups will be presented, following a summative approach. Regarding their perception of STEM (or STEAM which is commonly used nowadays, also including Arts as the 5th constituent), most of the participants (but mainly the school teachers) intuitively provide the most common definition which is that STEM is the combination of the 4 constituent disciplinary areas. An indicative example was the statement “STEAM is an educational approach to learning that uses Science, Technology, Engineering, the Arts and Mathematics”. Another stated that “I think I do 71

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[know what STEAM is] but there is always something more”. This is an indication of the transversality of STEAM and the fact that not all people, even if they claim to be experts of a certain level on the topic, are fully aware of its complexity and applicability. Moreover, one participant stated that “STEAM is a cross-curricular educational approach which involves students’ active participation” and another that “[STEAM] … five subjects with a common goal to create knowledge as you face up with problems”. It is obvious that all the initial attempts to provide a definition which highlighted the participants’ understanding of what STEAM is were rather generic, although more or less correct. It is to be noted that throughout the focus groups and some more elaborative discussion, many of the participants leaned towards a more accurate definition of STEM which is “STEM is an approach for addressing realistic problems, utilizing competences from the Science and Math domains, following the Engineering approach of solving problems and making use of Technological means”. This was evident by statements such as “STEAM is about facing with problems which are to be solved by combining competences from several of the corresponding disciplinary areas”. Thus, a first conclusion from the focus groups is that it seems important within the MiniOpenLabs approach to highlight the need to introduce end-users in realistic (better said, real life) problems to be solved. Also it is important to facilitate the understanding that Engineering refers mainly to a process of analyzing and solving problems (through the Engineering Design Process) rather than referring to constructing artifacts, for example, which is a very common misconception. Indeed, the concept of the Engineering Design Process as a problem analysis and solving approach is not very easy for teachers and of course the students to acquire and utilize. This would further enhance by demonstration of its usefulness, the added value of STEM in real life situations In one of the focus groups (as there were minor differences in the final set of questions asked, based on the evolvement of each active discussion) was asked to comment upon the relevance of the proposed STEM model with Sustainable Development. The relevance was commented upon as obvious, especially focusing on the contextualization of STEM activities via SD. For example, one participant explained that he always found it difficult to “explain Physics concepts without children being able to actually touch anything”. This abstract way of teaching complex notions and concepts can be addressed by the meaning making that issues of sustainability provide, but also they seem to provide means of designing experiential learning activities as well. As the same participant clearly stated “… obviously that having tools of experimentation there will be numerous case studies numerous applications in the area of sustainability – whether at sea, whether environment or mobility or carbon or there is a lot of topics that can be addressed almost transversally – now what’s really critical is the ability to get our hands dirty and that’s the decisive aspect of this – and mini labs represent that.” Another participant explained how the local municipality designed and implemented learning workshops for children, through which they would develop what he referred to as scientific literacy; “… getting children to ask questions to develop a strategy, to collect data for the scientific questions that have to read the data and discuss the data and conclusions”. All these workshops were connected to issues related to sustainability (e.g. the sea life) which were also tightly connected to that country’s economy and tradition. Thus, it seems that the participants were able to visualize the synergy between STEM and SD within teaching activities. The participants were also asked about the ways in which the communities could be actively involved in STEM activities. Various interesting ideas emerged. As aforementioned, the local authorities (e.g. municipalities could play an active role by either designing or supporting such attempts, which would be characterized by their open nature. Openness refers mainly to accessibility. Another significant parameter 72

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was that of proper contextualization of the STEM activities and their connection to local areas of interest (e.g. economy, history, culture, tradition, nature, etc). In the case of the Portuguese focus group, more concrete examples were provided as the local municipality had been running similar open programs for their citizens, connecting them with elements of local interest such as the sea, the canning process of fish (especially sardines) or even more generic issues such as the turn to cleaner energy consumption by shifting to more electric devices, air pollution, ecology, etc. In other focus groups, the connection to the local environment was brought up for this matter with statements such as “real-world applications” or “the local community may share problems or questions to solve”. These statements refer to the realistic nature of the proposed problems to be solved and thus to a direct link to the local community by providing meaningful solutions for the students’ everyday life which would be better conceptualized experientially. Parents were mentioned within this perception as a fundamental part of a school-community collaboration to further extent STEAM education towards the community. Other interesting ideas regarding ways to open up to the community were mentioned, like STEM festivals, STEM marathon activities and open classes (which resemble the realized activities mentioned in the case of the Portuguese focus group). All these ideas describe open access activities for a wider target group, involving also parents and other stakeholders. Thus, the open approach which is proposed also by the MiniOpenLabs approach was raised as important and it is safe to conclude that openness is crucial. Also, a connection with the local community in matters of providing realistic context to the activities to by conducted via the MiniOpenLabs approach seems to be of importance, as it would provide added value to the concept and enhance the bonding with the local communities. It is understandable that such bonds lead to the adoption of open approaches by local communities, as they provide insights of “why is it useful to have something of this kind in our area” and further enhance visits and even expansion of the hosted activities. It refers to making meaning out of the existence of an OpenLab in an area which would also contribute to further bonding of the visitors to their community overall. The significance of connecting such a space with the community is also highlighted by statements which were made when the discussion focused on the subject, such as “…the subject of STEAM is based on the real world and has a goal to serve the community…”, “…they will gain a unique opportunity to solve local issues …”, “…STEAM connects theory [referring to school teaching] with practice, thus school practice with community reality” Thus the participants seemed to value this connection of the MiniOpenLabs with the community on multiple levels, although initially and intuitively they focused on typical teaching and learning. As another participant stated, a different strategy should be followed in this case in order to highlight this issue; “I would say that there has to be an exogenous thing ... it’s not bringing people in... the problem is to go there to people”. Thus, an important element seems to be how to demonstrate to the members of the community the significance of having a MiniOpenLab available and what the added value of that would be in their everyday lives. This issue is highlighted in the focus group discussions, as a lot of time was spent on describing teaching scenario and material examples in all three countries, focusing on the teacher who would then have more tools available for teaching STEM concepts. Thus, not all teachers and other types of end-users, at extent, are intuitively able to connect STEM practices and the wider community, since the experts in this focus group appeared to have some difficulties in doing so and that has to be stated clearly by the MiniOpenLab approach. Further examining the community aspect of the MiniOpenLabs approach, the participants were asked to reflect on the pros and cons of the community engagement in STEM activities. Regarding the cons, the issue of complexity was raised referring to the uneven background of the potential end-users. This, 73

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in a way, reflects again on the professional nature of the participants being educators, who often think as having to “teach”, although a teacher stated that “direct communication of students with professions of the local community” could be an interesting approach to follow. Thus, an interesting attribute for the MiniOpenLabs concept would be to demonstrate that STEM activities can be implemented in a simple way and that anyone can solve a problem despite of his/her social and cognitive capital, when the proposed activities are meaningful for the end-users and provide added value for them and the local community as a whole. Finally, the participants were asked to envision the MiniOpenLabs concept and reflect upon its structure and activities. Attempting to not replicate statements already made, it is important to note that the use of simple materials was mentioned, reflecting on a low cost of setting up such a space. Furthermore the space would have to be attractive (in the sense of being able to also have a fun time there), possibly portable, easy to replicate or move to other locations and provide coherent activities. Being able to hold teaching activities both inside and outside, in the natural environment, was also mentioned as an interesting aspect. Overall, the focus groups provided valuable insights for the design of the MiniOpenLabs concept, as they highlighted issues that need to be addressed beforehand (e.g. common misconceptions of the potential stakeholders), but also interesting ideas to be incorporated.

THE MiniOpenlabs CONCEPT Building upon the findings from the focus groups but also on those from an intensive desk research for existing approaches which have commonalities with the originally envisioned idea of the MiniOpenLabs, the consortium formulated a concrete description of them. Up to the point where this chapter was written, the final refinements were being made in order to finalize the conceptualization of the MiniOpenLabs, also by creating an activity book to accompany them. Since this is a bilateral connection, as the selected activities reflect on the required design and the materials to be used, until they are fully tested for the parameters set also during the focus groups (e.g. openness, fun, simplicity, of local community interest, etc), the MiniOpenLabs concept is dynamic and will be refined during the lifespan of the project. Thus, in this section a brief description of the basic elements is provided. To start with, the MiniOpenLabs are small laboratories, open to the local community, where children, under the guidance of teachers and other educators (including parents), may engage in STEM-based projects on Sustainable Development. Furthermore, these laboratories need to be actual functioning ones, but of small dimensions. This would contribute to their accessibility, portability and even replication if needed. The main target group for the MiniOpenLabs is students 6-12 years old and the initial spaces will be setup in schools. Regarding the conceptual basis of the MiniOpenLabs, this relies merely on the Agency by Design (AbD) model (figure 3), as proposed by Harvard University’s Project Zero research group (www.agencybydesign.org). This approach is divided into three strands, namely: literature review; interviews and site visits; concept development and action research. Thus far, the consortium finalized strand 1, is finalizing strand 2 and is initiating strand 3. The idea behind this approach is that in order to make empowerment one has to look closely, explore complexity and find opportunities. Making empowerment means to

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have a sensitivity to the designed dimension of the objects and systems along with the inclination and capacity to shape one ´ s world through building, tinkering, re/designing and/or hacking. According to the AbD, this definition focusing on the triad of sensitivity, inclination, and capacity, extends a concept of dispositional behavior developed at Project Zero (Perkins, Jay, & Tishman, 1993; Perkins & Tishman, 2006; Tishman, 2001) proposing that ability alone is not enough to ensure action. One has to have the ability to do something, the motivation to do it, and the sensitivity to appropriate occasions to do it. Looking closely is about observing the interconnection among elements (e.g. in our case the existing approaches and how they interact with the communities). Exploring complexity regards considering the people, interactions, and motivations associated with objects and systems. Finding opportunity is about noticing if and where there are opportunities for imagining how an object or system might be otherwise. Figure 3. The Agency by Design model Source: www.agencybydesign.org

Following this idea, the MiniOpenLabs approach seeks provide basic STEM knowledge, empower STEM related attitudes by highlighting their connection to real life problems, to the community, but also the applicability of acquired knowledge along with the underlying simplicity once the corresponding concepts are fully understood. The MiniOpenLabs concept includes the Lab’s mission, goals and learning areas. Although the general concept of the MiniOpenLabs is the same for all the partnership countries, each Lab may focus on specific SD areas to respond to local needs and will be highlighted in the mission and goals statement of each laboratory. A draft schematic of this concept is depicted in figure 4. The working framework (Figure 5) includes the Lab’s management structure, working schedule, basic resources, characteristics of the space, type of activities/services, safety rules, etc. The latter will be provided also in the form of guidelines for teachers mainly who will be the core facilitators of the laboratory activities. An additional activity book will be provided.

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Figure 4. The MiniOpenLabs model

Figure 5. The MiniOpenLabs working framework

As for the teaching/learning approach, the basic concept is that the MiniOpenLabs will be designed from a constructionism perspective, as Papert (1986) introduced. “From constructivist theories of psychology we take a view of learning as a reconstruction rather than as a transmission of knowledge. Then we extend the idea of manipulative materials to the idea that learning is most effective when part of an activity the learner experiences as constructing a meaningful product”. Connecting this with the AbD model, three key concepts are considered: a) Making which is about the active role construction plays in learning. The maker has a product in mind when working with tools and materials; b) Tinkering which is a mindset, a playful way to approach and solve problems through direct experience, iteration, experimentation and discovery; and c) Engineering which extracts principles from direct experience. It builds a bridge between intuition and the formal aspects of science by being able to better explain, measure and predict the world around us.

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Overall the principal of learning by doing will be incorporated, following the Maker-Centered Learning approach (Clapp et al., 2016). The main benefits of this approach are: 1. Primary benefits of maker centered learning a. Developing student agency i. Stuff making: finding opportunities to make things that are meaningful to oneself and taking ownership over that process of making ii. Community making: finding opportunities to make things that are meaningful to one ´ s community and taking ownership of that process of making, either independently or with others b. Building character i. Self making: building competence as a maker, building confidence in one ´ s maker abilities, forming a maker identity ii. General thinking dispositions: supporting various patterns of thinking that are perceived as being beneficial across domains 2. Secondary benefits of maker centered learning a. Cultivating discipline specific knowledge and skills i. Fostering the development of knowledge and skills within the STEM subjects and other disciplines b. Cultivating maker specific knowledge and skills i. Fostering the development of knowledge and skills with regard to maker specific tools and technologies ii. Fostering the development of knowledge and skills with regard to maker specific processes and practices Thus, the MiniOpenLabs will be a Makerspace that is “public workshop where makers can share tools and knowledge” (Taylor et al., 2016). This complies with the openness of the concept as already discussed. As Taylor et al. (2016) state “It is clear, then, that makerspaces are not just homes for 3D printers and laser cutters. Rather, they are public resources dedicated to creativity, learning and openness. This comes at a time when many communities do not have a community spaces and where civic life is often seen as being in decline”. Thus, a space such as this may also serve as a community meeting space which would facilitate socializing, apart from learning. Following this idea, the MiniOpenLabs approach also aspired to facilitate another community element, that of local history and tradition preservation through the designed activities. Throughout the human history, people crafted and made artifacts to serve specific actions and needs. However, eventually such crafts often came with a story, usually a cultural one which highlighted aspects of a localized community. Thus, stories are often told through objects and historical/social capital is preserved. Consequently, within the MiniOpenLabs activities, a concrete section of historical and social information will be included, in the form of “Did you know…” element. Regarding the structure of the MiniOpenLabs, various ideas are being considered. In the case of Spain, the proposal is to have them organized in two different blocks. The first block will regard Science and Mathematics. The second block will regard Engineering and Technology. The idea is to utilize 1st block activities for enabling students to create a solid conceptual base that will help them understand and be able to explain environment phenomena, such as the movement of the moon, the colour of the 77

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sky, the mechanism in a domestic device, etc. The 2nd block activities will make students apply all the concepts they have worked in Block 1. For example, they will have to use the concepts learnt in science to build a gadget related to a sustainability issue. The initial idea (to be tested) is for students 6-9 years old to focus more on block 1 and those 9-12 years old on block 2 activities. One of the four STEM areas will act as the conductive axis, the center of the experience and the rest of them will act as tools, or will be of secondary importance. For this reason the MiniOpenLabs were conceived as having two distinct blocks. Similar approaches will be followed in the other countries, adapted to their specificities. Regarding content, the Spanish MiniOpenLab intends to focus mainly on environmental issues, including fossil creation and studying. The Portuguese MiniOpenLab intends to focus on smart and sustainable cities, mobility and the ocean. The Greek MiniOpenLab intends to focus on renewable energy and environmental issues. Finally, each MiniOpenLab will incorporate an Activity Book which will include complete lesson plans with experiments. Children can investigate the world around them and learn mathematics and science in action. Using the technology, they will progressively resolve tasks (experiments) with increasing difficulty degree. Once the required concepts have been acquired by them, they will manage and develop novel engineering projects. The book will include helpful descriptions and explanations to clearly show how the experiments should be accomplished. Striking artwork and photographs will illustrate all of the projects with clarity. In addition, an index is included indicating the experiment sections: materials, methods and experimental procedure. The presentation of the Activity Books is out of the scope of this chapter, as the books are not yet finalized while this was being written.

DISCUSSION As already stated, ESD and STEM are 2 major EU priorities. Following the idea that both SD and STEM should be addressed from an early age, motivating children to acquire scientific knowledge but also cultivate competences related to that are in line with the UN’s SD Goals, the MiniOpenLabs concept emerged. On one hand sustainability is an issue tightly connected with everyday life. The mass media make use of terms related to sustainability constantly and practical implications of it are easier be understood, even by young children. On the other hand, STEM is still regarded as difficult and unattractive by the majority of children. Having this in mind, the MiniOpenLabs consortium attempts to couple both these educational fields so that SD looks at science and technology for answers and STEM education can be made more interesting and appealing if applied to a specific field that gathers particular interest, like SD. Thus, the general interest in SD can be used to attract children to STEM. The project MiniOpenLabs proposes to set-up and test a different methodology with a higher prevalence of experiential learning and relying on the collaboration between science and technology organisations, enterprises and civil society, to ensure relevant and meaningful engagement of all societal actors with science and increase the uptake of science studies, citizen science initiatives and science-based careers, employability and competitiveness. It follows the Makerspace approach, conceptualized under the Agency by Design model. The main goal of the project is to set-up and test an open community and hands-on approach to Sustainable Development and STEM Education of children (6-12 years old). To define this concept and working framework, partners conducted a benchmark analysis and focus groups with end-users

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and experts. The benchmark analysis mainly consisted of desk research to identify and analyse similar structures (e.g. living labs, makers spaces, fablabs, etc.) in order to learn from these experiences. The focus groups allowed to get insights from end-users and experts that are critical to create a new concept of MiniOpenLabs that responds to specific needs in SD and STEM education in each of the countries/local areas. In total 3 focus groups were formed, one in each country (namely Greece, Spain and Portugal). The focus groups were organized by a University partner and supported by a school partner in each country. Overall, the findings led to the conceptualization of the MiniOpenLabs are small laboratories, open to the local community, where children (6-12 yo), under the guidance of teachers or other educators (including parents), may engage in STEM-based projects or activities about sustainable development topics. The labs will be implemented within the partner schools’ facilities and will be stocked with basic equipment (e.g. laser cutter, 3D printer, minirobots) and materials (e.g. wood planks, electronic sensors, etc.). Both indoor and outdoor activities will be designed to be hosted in the MiniOpenLabs, focusing also on local community interest in order to provide a realistic environment for addressing STEM and SD issues. The overall goal is to offer both an educational but also a social environment where children will familiarize themselves in these fields in a meaningful way for the sociocultural environment in which they develop as citizens. This output is highly innovative as it promotes a hands-on and open/community approach to STEM education and Education for SD, as opposed to the more traditional and teacher- driven methodologies used in most of the classrooms in Europe. This will allow children to experience STEM and SD topics in an experiential and engaging way, making a stronger case for STEM studies and careers, especially in fields related to sustainability. The innovation also resides in the fact that the activities for an accompanying Activity Book will be co-created with the involvement of teachers, pupils and researchers, thus increasing for their feasibility and novelty. As this is an ongoing effort, more information can be hereinafter found on the project’s website (https://miniopenlabstem.com/), including the full specifications of the laboratories, the activity books and research-based results from their utilization.

ACKNOWLEDGMENT This work was co-funded by the Erasmus+ Programme of the European Union, Action KA2 for School Education, Project Νο: 2019-1-PL01- KA201-065695 “MiniOpenLabs”.

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ADDITIONAL READING Ansorger, J. (2020). STEM Beyond the Acronym: Ethical Considerations in Standardizing STEM Education in K-12. In B. Brown, V. Roberts, M. Jacobsen, & C. Hurrell (Eds.), Ethical Use of Technology in Digital Learning Environments: Graduate Student Perspectives (pp. 87–103). University of Calgary. https://openeducationalberta.ca/educationaltechnologyethics/ Arifin, N. R., & Mahmud, S. N. D. (2021). A Systematic Literature Review of Design Thinking Application in STEM Integration. Creative Education, 12(7), 1558–1571. doi:10.4236/ce.2021.127118

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Bevan, B., Gutwill, J. P., Petrich, M., & Wilkinson, K. (2014). Learning through STEM-rich tinkering: Findings from a jointly negotiated research project taken up in practice. Science Education, 99(1), 98–120. doi:10.1002ce.21151 Breiner, J. M., Harkness, S. S., Johnson, C. C., & Koehler, C. M. (2012). What is STEM? A discussion about conceptions of STEM in education and partnerships. School Science and Mathematics, 112(1), 3–11. doi:10.1111/j.1949-8594.2011.00109.x Bybee, R. W. (2013). The case for Stem education: Challenges and opportunities. NSTA Press. Clapp, E., Ross, J., O’Ryan, J., & Tishman, S. (2016). Maker-Centered Learning: Empowering Young People to Shape Their Worlds. Jossey-Bass. UNESCO. (2017). Education for Sustainable Development Goals: Learning Objectives. United Nations Educational, Scientific and Cultural Organization. UNESCO. (2018). Issues and trends in Education for Sustainable Development. United Nations Educational, Scientific and Cultural Organization.

KEY TERMS AND DEFINITIONS Constructionism: A theory of learning, teaching and design which supports that knowledge is better gained when students construct it by themselves while they construct artifacts that can be shared and probed to the world. Education for Sustainable Development: Education that encourages changes in students’ competences (defined as sets of knowledge, skills, values, and attitudes) to enable a more sustainable and just society for all. MakerSpace: Public workshop where makers can share tools and knowledge. MiniOpenLab: Small laboratory, open to the local community, where children (6-12 yo), under the guidance of teachers or other educators (including parents), may engage in STEM-based projects or activities about sustainable development topics. SDGs: Are 17 goals with 169 targets that all UN Member States have agreed to work towards achieving by the year 2030. STEM: An approach for addressing realistic problems, utilizing competences from the Science and Math domains, following the Engineering approach of solving problems and making use of Technological means. Sustainable Development: An organizing principle for meeting human development goals while also sustaining the ability of natural systems to provide the natural resources and ecosystem services on which the economy and society depend.

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Chapter 5

Computational Thinking and Robotics in Kindergarten: An Implemented Educational Scenario Evgenia Roussou Directorate of Primary Education of Piraeus, Greece

ABSTRACT Ever since technology became an integral part of human life, a range of new concepts have surfaced. Computational thinking (CT) has been extensively discussed in the last 15 years and has been gaining popularity in the educational world. Following an overview of the basic literature published on this evasive new concept, an attempt is made to outline the connection between computational thinking and programming with emphasis on tangible programming of educational robots. An implemented educational programme, which attests to the positive impact of robotics on the acquisition of computational thinking skills in early childhood, is presented and evaluated. The study took place in a typical Greek kindergarten in 2017 and focused on the development of particular aspects of computational thinking with the use of a programmable floor robot.

INTRODUCTION Technology is rapidly evolving and bombarding our world with inventions that change people’s lifestyles, requiring flexibility and constant adaptation of our skills. And while in everyday life, on an individual level, this flexibility is perhaps possible, education meets enormous difficulties: it takes copious study, effective planning, long-term research and pilot implementation of new programs before the official Curricula can be updated. However, current developments are cataclysmic therefore, the global scientific and academic community in collaboration with policy makers are making special efforts to speed up the process so that schools will provide students with the necessary 21st century skills. Collaboration, communication and thinking skills are at the heart of modern educational pursuits. Einstein’s famous view that we cannot solve problems using the same way of thinking we had when we created them, just DOI: 10.4018/978-1-6684-3861-9.ch005

Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

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highlights the need to expand and develop new aspects of human thought. This chapter aims to present an educational scenario which was designed and implemented in a typical kindergarten classroom, as part of a Master’s Thesis case study. A detailed description of all robotic activities, together with analytical information on student response and behavior is provided. Available research data indicate that using the robot in a developmentally appropriate, playful way leads to remarkable increase in the kindergartners’ targeted computational skills, which is consistent with the findings of similar international studies. Moreover, student observation offers interesting insights on the impact of an educational robotics program on young children’s social skills and interactions.

BACKGROUND Computational Thinking (CT) Prensky (2001: 1) proposed the insightful term digital natives to describe the “generation born and raised in an environment where digital media is ubiquitous” which results in fundamental differences in the way students think and process information; differences that educators are just beginning to comprehend. In 2006, Karl Fisch pinpointed one of the greatest challenges educational systems face nowadays: “We are currently preparing students for jobs and technologies that don’t yet exist in order to solve problems we don’t even know are problems yet”. His inspirational video has had more than 21 million views on YouTube and triggered spirited discussions among educators worldwide. Modern School Curricula around the world are gradually including the development of Computational Thinking (CT), a term coined by Wing (2006: 33) when she stated that “computational thinking involves solving problems, designing systems, and understanding human behavior, by drawing on the concepts fundamental to computer science”. Although CT has various definitions, it is widely accepted that it “encompasses a broad of analytic and problem-solving skills, dispositions, habits, and approaches used in computer science” (Sullivan & Bers 2015: 5). The British Royal Society (2012: 29) defines CT as “the process of recognizing aspects of computation in the world that surrounds us, and applying tools and techniques from Computer Science to understand and reason about both natural and artificial systems and processes”, based on Papert’s views (1980, 1991) that computers enable children to develop procedural thinking (i.e. CT) through programming and solving problems - by generating ideas, analyzing problems and explaining the relations between problems and their solutions. Scientists have since tried to further clarify the concept of CT but consensus has not been reached yet; nevertheless, there is academic agreement that CT is a thinking process, therefore not dependent on technology, and it involves specific problem-solving skills which can be used by a computer, a human or a combination of both (Bocconi, Chioccariello, Dettori, Ferrari & Engelhardt, 2016). According to Perković, Settle, Hwang & Jones (2010), CT also offers new ways of understanding natural and social phenomena and promotes creativity and innovation. Therefore, attempts have been made to introduce activities for the development of CT skills even in primary education as it is considered equally important with the traditional three R’s (reading, writing, arithmetic).

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Computational Thinking and Programming Since Papert’s groundbreaking work with LOGO, programming has been considered the most effective way to develop CT skills because it uses strategies such as algorithms, subtraction and debugging (Dede, Mishra & Voogt, 2013). Also, CT skills acquisition has been regarded, to some extent, as a fortunate ‘side effect’ of learning how to code: in addition to mastering programming languages, computer scientists have been found to possess high-level skills, applicable outside the field of computing (Howland, Good & Nicholson, 2009). Brennan & Resnick (2012) point out that educational activities focusing on design, and particularly interactive media programming, promote CT development among youngsters and children. Moreover, Kafai (2016) stresses that coding is a social and creative process: as members of a wider learning community, today’s children write software programs e.g. to create video games or interactive stories; their main motivation is the opportunity to create something they can share with others in an increasingly digital world. It seems that “CT is more than programming, in the same way that language literacy is more than writing; programming, like writing, is a means of expression and an entry point for developing new ways of thinking” (NRC, 2010: 13). It is widely accepted that speech both expresses and stimulates thinking; respectively coding and CT could be considered similarly interconnected. However, although programming is highly related to the acquisition of CT skills, a learning environment rich in age-appropriate educational tools, motivating activities and a collaborative classroom culture also play a key role (Allan et al., 2010). Research on programming for children began decades ago at the MIT Artificial Intelligence Lab (LOGO Lab), when Papert developed a floor turtle that children could control using the text-based LOGO programming language (Bers, 2008). Studies on the LOGO language showed that, when introduced in a structured way, programming enabled young children to improve their visual memory and number sense, as well as develop problem-solving techniques and language skills (Clements & Meredith, 1993). Papert (1980) believed that programming was instrumental to the development of children’s cognitive skills because he noticed that student programmers had integrated specific computational models into their thinking and way of learning thus increasing their academic potential and opportunities for professional development. More recently Resnick (2013: 1-2) highlighted that when children learn a programming language, they are not ‘‘just learning to code, they are coding to learn’’ because they don’t just learn about variables, conditionals or other mathematical concepts, they actually learn how to solve problems, design projects, create content and communicate their ideas using the digital media. International researchers (Grover & Pea, 2013; Fessakis, Gouli & Mavroudi, 2013; Portelance & Bers, 2015; Papadakis, Kalogiannakis & Zaranis, 2016) seem to agree on the positive influence of programming on the development of basic mental skills, e.g. related with the mathematical ability and the development of logical thinking among preschool and primary school children, because it requires structured thinking. In the UK, where teaching programming at pre-school became compulsory in 2013, there is a number of coding platforms and applications, such as Tynker, Hopscotch, aspiring to introduce children to programming in a way that is compatible with their developmental level. There is growing research evidence that even preschoolers have the ability to understand several basic programming concepts, name and comprehend commands, sequence events and also create simple programs to achieve hypothetical goals as long as age-appropriate educational activities are implemented (Brennan, 2011; Flannery et al., 2013; Kandroudi & Bratitsis, 2016) and robotics seem the ideal tool for such activities.

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Educational Robotics (ER) For decades, early childhood Curricula have focused on literacy and numeracy with some attention paid to science, particularly the natural world. While understanding the natural world is important, developing children’s knowledge of the human-made world is also necessary (Bers, 2008). Young children’s innate curiosity facilitates science instruction; their creative and inquisitive nature welcomes engineering instruction and technological literacy: most children enjoy designing and building things as much as they enjoy taking things apart to see how they work (Resnick, 2007). ER enables children to develop new ways of thinking, comprehend the connection between the real world and the digital one but also access concepts which are traditionally considered intellectually appropriate for adults (Resnick, 1996). Misirli & Komis (2014) stress that robotics can be integrated into a variety of educational contexts allowing children to implement problem-solving, exploration and experimentation strategies. Further research has shown that ER contributes to the development of young children’s spatial awareness, sense of direction, algorithmic thinking and early mathematical skills (Highfield, Mulligan & Hedberg, 2008; Highfield, 2010; Komis & Misirli, 2013; Kazakoff & Bers, 2014; Misirli, Komis & Ravanis, 2019). Researchers stress that ER involves imagination, collaboration, innovative design, Science, Technology, Engineering, Mathematics, even the Arts (STEM/STEAM) in an effective, playful learning context (Bers, Ponte, Juelich, Viera & Schenker, 2002; Johnson, 2003; Flannery & Bers, 2013). More recent studies concur that the interdisciplinary nature of robotics allows it to be successfully integrated into a variety of school subjects such as Science (Robinson, 2005; Ioannou & Bratitsis, 2017; Sullivan, Strawhacker & Bers, 2017), Language (Burke & Kafai, 2010; Karkani, 2017) even EFL teaching (Korosidou, Meditskou & Bratitsis, 2013; Alemi, Meghdari & Ghazisaedy, 2015) thus offering learners the possibility to reap all benefits of this innovative approach while developing important 21st century technological and social skills. Unlike usual computer activities, which often require sitting alone in front of a screen, robotic manipulatives promote collaboration and teamwork (Lee, Sullivan & Bers, 2013). Using objects to think and learn has been a longstanding, preschool tradition. As early as 1800, Montessori and Fröbel designed a number of wooden materials (e.g. pattern blocks, beads, etc.) to help children develop a deeper understanding of mathematical concepts. Robotics can easily become the modern generation of such learning manipulatives which facilitate children’s understanding of mathematical concepts and offer them the opportunity to participate in social interactions and learn to play / play to learn while being creative (Resnick, 2003). What is more, robotic technologies with a Tangible User Interface (TUI) are becoming increasingly popular as they minimize children’s exposure to screentime in accordance with pediatric advice worldwide (Pugnali, Sullivan & Bers, 2017). For more than a decade, TUI floor roamers – like the popular Bee-bot – have proved to be a powerful learning tool for the development of young children’s technological, programming and problem-solving skills as they motivate students to explore their potential while acquiring knowledge in a playful and meaningful way; they can make abstract ideas more concrete because children immediately see how their commands affect the actions of the robotic device, thus comprehending cause-effect relations (Markelis, Atmatzidou & Demetriades, 2009; Sullivan, Kazakoff & Bers, 2013). Furthermore, as João-Monteiro, Cristóvão-Morgado, Bulas-Cruz & Morgado (2003) rightly point out, robots literally have inexhaustible patience, which makes them ideal tools for learning through trial and error, a method essential for knowledge build-up. They give children endless opportunities to identify mistakes, backtrack and repeat the sequence of commands as many times as necessary to achieve 87

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their goal. Robots offer positive reinforcement on an emotional level since they are never judgmental or dismissive; moreover, during collaborative play, an older child (or the educator) can give explanations / instructions or demonstrate how to achieve the intended goal, thus acting within Vygotsky’s Zone of Proximal Development and contributing to progress that may not have occurred otherwise (Vygotsky, 1978). Additionally, age-appropriate educational activities involving children and adolescents have proved that ER contributes to the development of both metacognitive and computational thinking skills (La Paglia, Rizzo, La Barbera, & Cardaci, 2010; Atmatzidou & Demetriadis, 2016; Sullivan, Bers & Mihm, 2017). Significant research on ER and CT has been carried out in Tufts Univesity: Bers and her colleagues developed prototype devices which could be programmed haptically using especially designed wooden blocks which were developmentally appropriate for children aged 4 to 7 – the TangibleK program (Bers, 2010). Published findings indicate that, despite their young age, children who participated in research courses easily learned to build and program robots, thus exploring engineering, technology and computer programming while also developing their CT skills (Sullivan et al., 2013; Bers, Flannery, Kazakoff & Sullivan, 2014); more specifically, they became better at comprehending and expressing sequence, using conditionals and applying debugging strategies (Kazakoff & Bers, 2012; Sullivan & Bers, 2015; Elkin, Sullivan & Bers, 2016).

THE CASE STUDY As the aim of this chapter is to present a detailed educational scenario which brings ER to the center of the learning process, with respect to space limitations, only a short summary of the research work connected to this scenario is outlined here.

Research Focus Inspired by the above international research findings and aspiring to explore how CT is affected by educational robotics in authentic classroom settings in a typical public kindergarten in Greece, the case study was designed to focus on the acquisition of four key aspects of CT: 1. Comprehending causality - It is fundamental to programming because a program is a series of sequential commands executed by a computer / robot as instructed by the programmer, who knows exactly which command triggers which action/response. Lack of this understanding would lead to random computer / robot behaviors, thus revealing limited or non-existent programming skill. 2. Making and expressing hypotheses - It is connected to the ability to notice the possible relation between objects / actions / events in order to make deductions and decide on the appropriate course of action through checking – correcting – rechecking. 3. Understanding sequence and sequencing - objects or actions. It is highly important and directly related to basic concepts of time, such as before and after. Therefore, it is an integral part of the preschool Curriculum connected not only to mathematics but also to language, since sequencing phonemes and words leads to the development of speech and the acquisition of reading.

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4. Problem solving (Debugging) - It is considered a key computational practice as it focuses on understanding any malfunction by identifying causal relationships between events and deciding on corrective action. The process actually encompasses four steps (Bers et al., 2014): a. recognize that something is not working / meeting the stated goal. b. decide to keep the original goal or switch to a suitable alternative. c. generate a hypothesis about the cause of the problem d. attempt to solve it.

Research Tools The main research tool was a picture questionnaire (Roussou & Rangoussi, 2020: 37-38) consisting of 4 units which correspond to the four targeted CT aspects. It was administered individually, to all students, before the educational intervention to determine the existing level of the targeted CT skills and after the completion of the educational intervention to measure any changes in the level of the targeted CT skills among students. Throughout the intervention, ER activities were constantly video-recorded to provide the teacher/researcher with all information about student performance and behavior during the tasks; there was no research assistant or even teacher assistant in class during the activities so without the video, valuable evidence could easily go unnoticed. Daily analysis of the video recordings throughout the intervention and systematic completion of observation sheets provided interesting data on programming skills development, children’s linguistic and social interaction, their engagement and participation levels but also their emotional well-being during the activities. Prior to the beginning of the study, a formal parental consent concerning each child’s participation was obtained; it included parental approval of both the video-recording and the academic use of all data collected for the purposes of the research. Finally, individual semi-structured interviews were conducted with the students in order to reveal their views/ experiences about the implemented activities and with the parents in order to obtain further information about the impact of the robotics activities on their children.

Contribution and Findings The main contribution of this research lies in the fact that it was conducted in an authentic school environment and robotic activities involved all students daily for a period of 11 weeks whereas the majority of prior research was conducted in laboratory settings and/or for shorter periods of time. Furthermore, in contrast with most reported interventions which use ER as a motivating means to teach various subjects, this study focuses on children’s engagement with the robot in a playful but goal-oriented setting in order to determine if and how ER affects the development of children’s specific CT skills; the main hypothesis being that programming the floor roamer systematically for a respectable period of time would enhance children’s CT skills in correlation with existing literature. The analysis of the data collected (Roussou & Rangoussi, 2020: 40-42) indicates that student participation in the ER activities lead to notable increase of their tested CT skills; their improvement ranged between 11% and 42% in all 4 units of the picture questionnaire (post-test). The limited nature of this small-scale study does not allow for any generalizations but its findings are in accordance with prior research (e.g. Kazakoff & Bers, 2012; Bers et al., 2014; Elkin et al., 2016; Pugnali et al. 2017). Further, large-scale work in authentic classroom settings is required to reach conclusions which would be statistically significant; in that case, this educational scenario may prove useful for educators wishing to integrate ER in their class practices. 89

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EDUCATIONAL INTERVENTION Learning Objectives A plethora of traditional and technologically innovative activities aiming to develop mathematical thinking skills are available to kindergarten students; mainly because mathematics, alongside language development, are at the core of most early childhood educators’ pursuits. However, fully organized lesson plans aiming to develop CT skills via collaboration, creativity and ICT are scarce. CT skills are acquired and developed when children participate in age-appropriate activities designed to maximize experiential learning, game-based learning and learning by doing or by trial-and-error. The educational programme presented here was primarily designed to promote the development of specific CT skills by combining unplugged activities, such as fairy tales and roleplay, with robotic and coding technologies. On a secondary level, children worked on spatial concepts (more particularly distinguishing between right and left) and practised their reflection & self-evaluation skills. Equally, they had the opportunity to develop verbal communication and scientific skills (by observing and recording their experimentation) but also their social skills as they participated in group game-like activities which required following rules, behaving respectfully and acknowledging different perspectives. The core pursuits of this scenario are in full compliance with the Greek Kindergarten Curriculum (2014) which focuses on 21st century life skills and children’s full development and they include: • • • • •

digital literacy and creative thinking understanding basic functions of programmable toys and controlling them successfully using ICT to communicate and work together towards a common goal using technology to explore / experiment on / solve problems

Learning Environment: Skills Required This educational scenario was designed for a Greek kindergarten class consisting of 12 five-year-olds and 6 four-year-olds. Activities were implemented in plenary, in pairs and in small groups (3-4 children) in order to promote collaboration. The intervention began in the penultimate week of March and ended in the second week of June 2018 which is the end of the school year in Greece (see Table 1). Kindergartners had the opportunity to interact with the robotic device for about 60 minutes a day on average. All activities took place in a typical kindergarten classroom where a new learning center was created: the “Mouse House” where Colby, the mouse robot, took up residence (see Figure 1). While there is a significant number of robotic devices and educational robotic kits available (Misirli & Komis, 2014: 101-102), floor roamers (such as Bee-bot) are considered most appropriate for preschoolers. Therefore, the robot selected for this intervention was “Learning Resources - Code and GoTM Robot Mouse Activity Set” mainly because it is easy to use and affordable enough for the underfunded Greek kindergartens. The set contains sixteen (16) plastic tiles, which can easily be rearranged to create various paths, route cards of increasing difficulty and command cards, which depict the keys on Colby’s back. These cards can be used by the children while planning Colby’s trip to his ‘cheese’: they help them map out their thinking in order to program the robotic device more efficiently; the use of “a pseudo-language, through a series of graphical representation of commands on cards contributes to the visualization of program90

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ming procedures providing children with the opportunity to not only visualize a program but also reflect on it and correct its content” (Misirli & Komis, 2014: 110). Table 1. Activities calendar Week 1st

Date March 26-30

Description Pre-test in individual sessions.

March 31 – April 15: Easter Vacation 2nd

April 16-20

3rd

April 23-27

4th

April 30 – May 4

5

May 7-11

6th

May 14 -18

7th

May 21-25

8th

May 28 – June 1

9

June 4-8

10th

June 11-15

Robot Olympics.

11th

June 18-22

Post-test and evaluation interviews.

th

th

Robot tales and experiential role-play to acquaint children with the concept of programming (giving & receiving commands). Introducing the robotic device via individual play in plenary so that students learn how the robot works. Creating ‘Colby’s house’. Forming random teams to familiarize children with the device during free play at ‘Colby’s house’. Forming final teams to train for the games: daily group ‘practice’ with systematic track recordings.

Students were familiar with the classroom and its activity centers. Also, they had developed the social skills necessary to participate in the activities: they showed respect and a willingness to cooperate, they had learned to wait their turn and handle the educational material of the classroom carefully, following the instructions for use. As for the robotic device, they did not need any prior knowledge because the educational scenario already included familiarization activities with the robot and its operation. In fact, complete lack of any experience with robots and coding was desirable in order to keep the pre-test scores as uncontaminated as possible.

Lesson Methodology: Learner/Teacher Roles All activities in this intervention were experiential and playful; students were at the heart of the learning process, having the opportunity to learn through play and practice, which is in line with Dewey’s (1966) pedagogical theories of “learning by doing”. The children assumed control of the way and the pace at which they took part in the activities. Through trial and error, they built their own skills: not so much to operate the robotic device itself but mainly to achieve the goal of successfully completing each route and lead the mouse to its prize. In fact, as they worked in small groups, they could fully benefit from the collaborative method that Vygotsky described and their efforts were amplified by the help and advice of their team. Emotionally, the satisfaction they got each time they achieved their goal, despite the increasingly challenging paths, and the enthusiasm their team expressed, motivated them to continue their efforts thus practicing the target skills of this scenario.

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Figure 1. The Mouse House with Colby and its components

According to the Curriculum, the main teacher role is to assess the children’s learning needs, choose the appropriate tools that will facilitate each student to achieve his/her learning goals and to promote exploratory and experiential learning by creating the appropriate educational framework. In this scenario, the teacher initially presented the material and coordinated the children to use it. She stimulated reflection on the difficulties that groups encountered while interacting with the robotic device and encouraged children to engage in conversations with each other so as to draw on the experiences of their classmates who worked in other groups. She also acted as a guide and supporter whenever needed, with the ultimate goal of eventually becoming redundant when the children gained their independence and worked with the robot based mainly on the support of their team.

LESSON OUTLINE Stage 1: Unplugged Activities Fairy tale reading is at the core of kindergarten activities because stories can set behavioral patterns, promote friendship and cooperation and, of course, supplement any study topic. Seeking a playful introduction to robotics, Valerie Thomas’s tale “Winnie’s big bad robot” was selected. The children were fascinated by the adventures of the witch who brought a paper robot to life and struggled unsuccessfully to control it. The narration was followed by a discussion about the existence and role of robots in real life and their possible forms and characteristics, with the aim of exploring student views / prior knowledge on the subject. A poster presenting these views was posted in a prominent place in the classroom (see Table 2) and the following day, after a brief discussion about what a robot can do, the children were asked to draw a robot (see Appendix), name it and give it some special skills. Finally, students were given the opportunity to role play by ‘turning’ into robots and moving around in class to the sounds of electronic music.

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Table 2. Sample student views on robots before the intervention “What do you think a robot is?” Α1: Something like a remote controlled, my daddy can make robots. Α3: It is a device like a human but it is not real, that is, it does not eat. A4: They have some buttons on the remote control and you have to press a button and it goes where we take the remote control. Τ5: From a machine and all people make them with iron and set them up Τ6: They don’t move.

“What do you think a robot can do?” Α1: I would lie down and it sweeps and mops the floor and pretend to be a mermaid. Α3: Open the door, sweep and mop and do all the housework. Α4: Take me to school, serve my food, take off my clothes, iron, fix the TV when it breaks down, do laundry. Τ5: Put away all the toys and me, cook. Τ6: It can cook and I have a bath.

A few days later, Manos Kontoleon’s story “Me and my robot” was read; in it, an ordinary man buys a technologically advanced robot and tries it out. The story led to a discussion / reflection on the independence of robots from humans and their ability to act autonomously or make decisions. Kindergartners concluded that humans actually control the robot and determine its actions and movements. So, children were encouraged to play a game in pairs, in which one student would be the human and the other, the robot. The aim was for each ‘human’ to lead his ‘robot’ from point A of the class to point B, avoiding all obstacles. The ‘robot’ was blind-folded and relied completely on its human’s instructions as he/she could not see and act on its own. The ‘human’ was not allowed to touch his/her robot; he/she could only give verbal instructions: go forward / move to the (other) side / go back in order to guide the robot to the end of the designed path. Each command ‘translated’ to one robot step. The path was designed on the class floor using A3 paper (see Figure 2). The first paths were straight lines, easy and safe for the children, but as time went by and students got better at choosing the right commands and communicating, the paths became longer and more complex. Children loved this game and often played it during the week, so everybody had the opportunity to be both the ‘robot’ and the ‘programmer’ several times. Once they familiarized themselves with this roleplay and comprehended the connection between the command and the robot’s movement (response), the students were ready to welcome a real robot in class. Figure 2. Roleplay “The Programmer and the Robot”

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Stage 2: Robotic Activities in Plenary At the beginning of the 4th week, a box arrived and the children speculated on its content. When they learned it was a robot, they were encouraged to speculate about its form and features. Finally, the box was opened and the children got the chance to observe Colby, the robotic mouse, trying to guess how it works; then the teacher showed them how it receives instructions and how it moves. Colby’s square plastic tiles were arranged on the floor and partitions were used to create the first path: a simple straight line so that the children would have the satisfaction to complete it successfully. Then, the robot-mouse was placed at the beginning of the path and its cheese at the end and a student came forward for the first attempt; he/she was asked to select and press the appropriate buttons in order to lead the mouse to the cheese (see Figure 3). During the first days, the robot routes were straight lines so that kindergarteners could learn how to use the robot and rejoice in their successful attempts. Gradually, however, the routes became more complicated, providing the opportunity to introduce the programming cards and explain how they could help the children achieve their goal. Some students used them immediately, others ignored them trying to complete Colby’s route correctly without them. The teacher tried to highlight the usefulness of the programming cards by emphasizing their contribution to the successful effort of the children who had chosen to use them, but did not impose their use on the children who did not choose them, leaving them to decide for themselves, through trial and error, if they actually needed them or not (see Figure 4). In these first few days with Colby, all children were completely engaged in the activity, whether playing themselves or waiting their turn while others played. So, around the middle of the 5th week, after all the children had learned how to program the device, it was time to move the robot to its ‘house’ so that students could select it during free play. As expected, everybody wanted to play at Colby’s house, hence the need for a mini daily schedule: all interested students were asked to write their name on the list and they could take turns playing with Colby individually for a few minutes every day. Figure 3. First attempts to program the robot (straight routes)

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Figure 4. Programming the robot for more difficult routes using the programming cards (or not)

Stage 3: Robotic Activities in Groups During the 6th and 7th week, group play was introduced to allow children to devote more time to the robot. Groups of four were formed randomly, according to the order that names were written on Colby’s list daily. Each group was given approximately twenty minutes, during which children got the opportunity to interact with each other, observe their peers’ choices and offer improvement tips or optimize their own programming choices when it was their turn to play. At this stage the teacher: a. supported by giving advice/guidance when requested b. coordinated, ensuring that all students respect the allotted time, and c. encouraged students’ emerging collaboration skills by praising them when they gave or received advice/help from their classmates in order to program the robot properly. As expected, discussions in class about Colby were frequent because the robot fascinated students. They expressed great joy when Colby arrived at his ‘cheese’ and they realized how much better they were at programming the robot: day by day, they managed to complete more difficult routes, making fewer mistakes. Therefore, an idea was put forward: to hold an end-of-the-year robot championship where student teams would compete for the title of ‘Best Programmer’. The proposal was enthusiastically accepted and all children were eager to officially register for the championship, named “Robot Olympics”. The children selected their teammates and the next two weeks were dedicated to training: each team was given 20 minutes every morning to work with Colby systematically so that they could practise their coding and collaboration skills in order to get the best possible results in the Games. So, during the 8th and 9th week, the children worked intensively together trying to program the robot in order to complete increasingly complex routes without errors and with the fewest possible movements. They were encour-

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aged to think and plan collectively, using the programming cards, then try out their plan and record it on paper using color-coding (similarly to Colby’s buttons) in order to count the number of movements in each attempt and finally decide on the fastest/most effective itinerary. Once they found it, each team member had the opportunity to press the buttons and program Colby following the instructions of the ‘secretary’ who ‘read’ the commands recorded on paper. On average, each team managed to complete two routes a day during the time they had at their disposal (see Figure 5).

EVALUATION In all educational scenarios, evaluation activities are fundamental in order to determine whether the desired objectives are achieved and to reveal strengths/weaknesses for future improvement. The research tools, outlined earlier in the chapter, offered valuable evidence of children’s programming skills development and their enthusiastic participation in all activities. Additionally, comparison of their perceptions and drawings about robots before and after the intervention revealed cognitive changes concerning not only a robot’s nature and abilities but also its socialization aspect (compare Tables 2 & 4, see Appendix). During the intervention, formative evaluation was constant: through discussions and student interaction with the materials and with each other, the teacher systematically monitored each child’s development, planned improvement actions and / or redefined the type and level of difficulty of the proposed activities. Implementing this scenario depended on the reactions and educational needs of the students to whom it was addressed. The result of students’ work and interaction was constantly visible via the video recordings so, the teacher had a clear picture of the course of the activities and the evolution of their thinking. Figure 5. The teams are training for the Robot Olympics and rejoicing at their success. Notice the notes of the ‘secretary’ which are highlighted in red circles

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Evaluating Learners’ Programming Skills (Robot Olympics) Assessing the acquisition of basic programming skills could be determined by a simple individual programming task, however such a process is not considered developmentally appropriate for preschool children. Additionally, children’s work with the robotic device was overall a playful group activity and it should be evaluated as such. Therefore, the decision to give the form of Robot Games to the evaluation of the children’s programming skills aimed to keep this process in harmony with the social and playful nature of the whole intervention. Moreover, the element of competition, which was vital to the Games but completely lacking during training stages, added to student motivation and enhanced their engagement. The ‘Robot Olympics’ took place during the 10th week of the program in the form of a championship as each team had to face three (3) opponents in separate games so, in total, there were six (6) races per day on the same route though (see Figure 6). The first team to finish won five (5) points and the second team won three (3) points. Each team was entitled to three (3) attempts per game but each wrong attempt cost them one (1) point. For example, if a team finished first after one incorrect attempt, they gained four (4) points whereas if they finished second after one incorrect attempt, they gained two (2) points. If they did not manage to send Colby to the cheese after all three attempts, they just scored zero (0) points. All the points each team collected, were recorded on a special ‘Games Board” (see Table 3). At the end of the day, there was a class discussion about the course of the games and ideas were exchanged on how to deal with the difficulties encountered; also, the total score and the ranking order of each team were announced. At the end of the fourth day, when all races finished, after a public count of the total points collected, the final ranking of the winners was announced. All participants were deemed winners as long as their team had won at least one (1) point in the ‘Robot Olympics’; the only difference was in the ranking order written on the ‘Participation Certificate’. Medals and Cups were awarded to the children on the next day, which was the last of the school year. Figure 6. Teams competing against each other at the ‘Robot Olympics’

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Table 3. Each team’s score per day indicating successful attempts and race outcomes Team

Day 1

Day 2

Day 3

Day 4

“Superman”

1

4

0

5

5

5

5

3

3

2

2

3

“Run & Go”

0

0

3

1

4

5

1

5

5

4

2

3

“Strong”

4

3

0

0

3

5

4

4

5

5

5

5

“Butterfly”

0

0

0

0

3

0

3

2

3

5

3

5

Upon the completion of the intervention, there was a new discussion about the children’s views on robots and their role in our lives. Their responses were also recorded and compared to the ones given at the beginning of the programme, revealing the cognitive changes which occurred during this time. The main difference observed is that the majority of children verbally highlighted the feature of programming: that the robot is controlled by its operators (see Table 4). As for the drawings, the robot had taken a specific form (Colby’s, as expected) and it was mostly depicted among children which reflects the group nature of the activities and their recent experience from the ‘Robot Olympics’ (see Appendix). Table 4. Student views on robots after the intervention “What is a robot and what can it do in our lives?” Α1: It does what you tell it to do, it comes if you tell it so and it cleans. Α3: It does what we tell it to do and does all the work until it breaks down but you have to press the buttons to control it. Α4: If we tell it to dance, it will dance. If we tell it to sleep, it will sleep. If we tell it to open the curtains, it will open them. If we tell it to fall in the swimming pool, it will fall. If we tell it to come and bathe me, it will bathe me. A robot can do mom’s chores so mom can rest... it can set the table, make food... Τ5: You can program it to go right and left and forward and back, to go to work and when it returns to prepare, cook, make the bed and go to sleep. Τ6: They are a bit rhythmic and have a lot of wires and it is a bit electric and we always have to turn it off at night.

Evaluating the Intervention: Discussion Student interest in the robot remained high throughout the intervention. Only the youngest children showed signs of fatigue at the end of the first stage, when they played in plenary and had to wait their turn, which is expected because this activity greatly outlasted the maximum 20-minute attention span of 5-year-olds. This fatigue was actually what marked the end of the first stage. However, it is worth noting that most older children (5,5 – 6 years old) remained focused on each player, especially if he/ she was a good friend, and tried to help him/her make the right choices and achieve the goal. Especially the children who were the last to play often managed to complete each route without any mistakes, precisely because they had observed their classmates and identified which buttons they had to press. As days went by, an increasing number of students seemed to learn through ‘trial and error’ – their classmates’ errors, not their own. Therefore, although initially the first stage was considered a ‘necessary evil’ (all children needed to learn the robot function but waiting their turn was boring), finally it proved to be particularly important because it offered learners the opportunity to observe, think and discover the correct sequence of the programming commands for each route through the mistakes of their peers. Of course, this realization led to modifications of the second stage: the original idea was for each child 98

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to play in Colby’s corner individually but it became clear that group play might lead to better student performance. Moreover, the robot’s popularity led to the decision to play in small groups, based on the order of arrival at ‘Colby’s house’. Unfortunately though, most children remained at ‘Colby’s house’ until it was their turn to program the robot, but as soon as they finished, they left to play elsewhere. They watched their peers’ efforts but showed no interest in giving advice or learning from them. During this stage, nobody managed to complete a flawless command sequence after observing previous erroneous attempts. A possible explanation might be that learners only watched a limited number of attempts because groups consisted of 3-4 members and only spent 10-15 minutes on the activity whereas, in stage 1, they had the chance to watch around 20 attempts in 35-40 minutes. The random composition of each group seemed to have an additional inhibiting effect: more substantial interactions were observed when friends found themselves in ‘Colby’s house’ at the same time; they helped each other and rejoiced when their friends succeeded thus, they remained more engaged throughout the activity. Having noticed these group dynamics, for the next and most demanding stage of the program, it was decided that each group should consist of friends and be fixed throughout the rest of the activities. So, children had to decide which friends they would choose as their teammates for the Games. Indeed, creating teams of friends acted as a catalyst, increasing student interest and boosting their cooperation. Moreover, the thrill of the upcoming Games and the desire to win motivated most children to make conscious efforts in order to achieve effective and fast route-planning. There were certainly some initial difficulties before they understood how to use the programming cards together in order to plan the route more quickly, taking advantage of everyone’s suggestions especially about left/right turns which were most troublesome. Also, there were some conflicts over who would act as the team secretary and record their attempts or who would press Colby’s buttons. Some children tried to assume leadership and took initiatives that the rest did not approve of, while others attempted to monopolize all responsibilities and the rest of the team complained about not having the opportunity to make decisions or choices. Two teams (“Superman” and “Run & Go”) managed to reach a good level of cooperation during training, despite their disagreements and ‘power’ struggles as they consisted of dynamic members, while the other two teams (“Strong” and “Butterfly”) trained calmly and without much conflict, they finally developed a strategy based mainly on individual initiative rather than actual collaboration.

Group Dynamics and Social Skills During the Games, group dynamics within each team ultimately determined the outcome of the matches. It seems that the stress to quickly program the robot’s route and get victory points negatively affected the teams in a distinctive way. In the first days of the games, the teams consisting of members with strong personalities and high programming skills, who had managed to cooperate well in training and get excellent results, found it very difficult to finish in first place as they all tried to impose their own ideas: one member would often undo the other member’s right choices believing he/she could do it better. Thus, they lost valuable time or ended up failing an attempt, which cost them points. This is why they found themselves in 2nd and 3rd place in the final ranking.

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The “Butterfly” team, which consisted of quiet, low-key children, initially tried to implement the individual approach they had used during training: each member in turn attempted to program the robot once. They soon realized that this was not a good strategy since on the first day of the ‘Robot Olympics’ they did not complete any route correctly and remained at zero points. However, they gradually understood that working together had better results so, they started thinking collectively and discussing their choices, which allowed them to improve steadily and even achieve several victories, especially on the last day (see Table 3). An interesting fact is that they discovered the advantages of this collaborative approach during the Games. It is possible that the frustration caused by the initial consecutive failures combined with the desire for victory spurred them to discover the most effective approach and score winning points. Before the ‘Robot Olympics’, they were content with just planning and completing each training route on their own, no matter how much effort/time was needed. But when this behavior led to repeated defeats in the Games, they felt annoyed enough to reconsider their approach and motivated enough to explore various options and pursue victory. Therefore, it is safe to conclude that the Games were the key factor which enabled them to collaborate effectively. In contrast, the “Strong” team (which also continued implementing the individual approach they had chosen during training) finally ranked 1st, having achieved the most victories and the most flawless routes because its members actually chose not to cooperate at all: namely the two members (T1 and T2) recognized early on the highly developed programming skills of the third member (A2), so they selected him to take initiative and complete each route alone, keeping for themselves a supportive role and of course the joy of victory. When the other teams quarreled over who would select the cards and who would press the buttons and blamed each other for the mistakes and delays, the “Strong” team entrusted the whole game to A2 and then congratulated each other and celebrated the victory together.

CONCLUSION Students were enthusiastic about the robotics program; most of them preferred to ‘work’ with Colby or watch others do it rather than play in another activity center. The children always watched in suspense as Colby tried to reach its ‘cheese’ and every successful programming attempt was always met with applause and cheers, while mistakes lead to reflection, discussion, and a return to the programming cards for debugging and correction. Overall, the activities designed and implemented seem to have had a positive impact on all students and affect various learning areas. The related case study results indicate notable improvement of the target CT skills in all participants (Roussou & Rangoussi, 2020). Additionally, observation of student behaviour reveals significant development of several social skills, such as team work, collaboration, negotiation and compromise, which are fundamental to building meaningful social relationships. Discussion with students during the post-test sessions shows progress in language skills such as oral communication, use of conditionals, picture description and expression/justification of ideas. Last but not least, the kindergartners’ joy and commitment were consistently high and virtually undiminished throughout the activities with Colby which attests to the success of this educational scenario.

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Elkin, M., Sullivan, A., & Bers, M. U. (2016). Programming with the KIBO Robotics Kit in preschool classrooms. Computers in the Schools, 33(3), 169–186. doi:10.1080/07380569.2016.1216251 Fessakis, G., Gouli, E., & Mavroudi, E. (2013). Problem solving by 5-6 year-old kindergarten children in a computer programming environment: A case study. Computers & Education, 63, 87–97. doi:10.1016/j. compedu.2012.11.016 Fisch, K., & McLeod, S. (2007). Did you know? Available at https://www.youtube.com/ watch?v=pMcfrLYDm2U Flannery, L. P., & Bers, M. U. (2013). Let’s Dance the “Robot Hokey-Pokey!”: Children’s programming approaches and achievement throughout early cognitive development. Journal of Research on Technology in Education, 46(1), 81–101. doi:10.1080/15391523.2013.10782614 Flannery, L.-P., Kazakoff, E.-R., Bontá, P., Silverman, B., Bers, M.-U., & Resnick, M. (2013) Designing ScratchJr: support for early childhood learning through computer programming. In Proceedings of the 12th International Conference on Interaction Design and Children (IDC ’13), ACM. 10.1145/2485760.2485785 Grover, S., & Pea, R. (2013). Computational thinking in K-12: A review of the state of the field. Educational Researcher, 42(1), 38–43. doi:10.3102/0013189X12463051 Highfield, K. (2010). Robotic toys as a catalyst for mathematical problem solving. Australian Primary Mathematics Classroom, 15(2), 22–27. Highfield, K., Mulligan, J., & Hedberg, J. (2008). Early mathematics learning through exploration with programmable toys. Proceedings of the Joint Meeting of PME 32 and PME-NA XXX, 3, 169-176. Howland, K., Good, J., & Nicholson, K. (2009). Language-based support for computational thinking. IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC 2009), 147–150. 10.1109/VLHCC.2009.5295278 Institute of Educational Policy. (2014). Kindergarten Curriculum (revised edition). Author. Ioannou, M., & Bratitsis, T. (2017). Teaching the Notion of Speed in Kindergarten Using the Sphero SPRK Robot. 17th IEEE International Conference on Advanced Learning Technologies (ICALT). 10.1109/ICALT.2017.70 João-Monteiro, M., Cristóvão-Morgado, R., Bulas-Cruz, M., & Morgado, L. (2003). A robot in kindergarten. Proceedings Eurologo’2003 – Re-inventing technology on education. Johnson, J. (2003). Children, robotics, and education. Artificial Life and Robotics, 7(1/2), 16–21. doi:10.1007/BF02480880 Kafai, Y. (2016). From computational thinking to computational participation in K–12 education. Communications of the ACM, 59(8), 26–27. doi:10.1145/2955114

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Kandroudi, M., & Bratitsis, T. (2016). Διδάσκοντας προγραμματισμό σε μικρές ηλικίες με φορητές συσκευές μέσω του παιχνιδιού Kodable και του ScratchJr: Mελέτη περίπτωσης [Teaching programming at an early age with mobile devices through Kodable and ScratchJr: Case study]. In T.A. Mikropoulos, A Tsiara, & P. Chalki (Eds.), Proceedings 8th Panhellenic Conference «Διδακτική της Πληροφορικής» (pp 133-140). ETΠE. Karkani, E. (2017). H εκπαιδευτική ρομποτική ως αφόρμηση για τη διδασκαλία γλωσσικών μαθημάτων στην πρωτοβάθμια εκπαίδευση [Educational robotics as an impetus for the teaching of language courses in primary education]. Proceedings of 5th Panhellenic Conference «Ένταξη και Xρήση των TΠE στην Eκπαιδευτική Διαδικασία», 604-614. Kazakoff, E., & Bers, M. (2012). Programming in a robotics context in the kindergarten classroom: The impact on sequencing skills. Journal of Educational Multimedia and Hypermedia, 21(4), 371–391. Kazakoff, E. R., & Bers, M. U. (2014). Put your robot in, Put your robot out: Sequencing through programming robots in early childhood. Journal of Educational Computing Research, 50(4), 553–573. doi:10.2190/EC.50.4.f Komis, V., & Misirli, A. (2013). Étude des processus de construction d’algorithmes et de programmes par les petits enfants à l’aide de jouets programmables [Study of the processes of construction of algorithms and programs by small children using programmable toys]. Dans Sciences et technologies de l’information et de la communication (STIC) en milieu éducatif: Objets et méthodes d’enseignement et d’apprentissage, de la maternelle à l’université. Korosidou, E., Meditskou, E. & Bratitsis. (2013). Παραγωγή και λήψη οδηγιών κίνησης στο χώρο κατά την εκμάθηση της Aγγλικής ως ξένης γλώσσας με το ρομπότ BeeBot. Proceedings 3rd Panhellenic Conference «Ένταξη και χρήση των TΠE στην εκπαιδευτική διαδικασία». La Paglia, F., Rizzo, R., La Barbera, D., & Cardaci, M. (2010). Using robotics construction kits as metacognitive tools: Research in an Italian primary school. Annual Review of Cybertherapy and Telemedicine. Advanced Technologies in the Behavioral. Social Neuroscience, 154, 110–114. Lee, K., Sullivan, A., & Bers, M. U. (2013). Collaboration by design: Using robotics to foster social interaction in kindergarten. Computers in the Schools, 30(3), 271–281. doi:10.1080/07380569.2013.805676 Markelis, I., Atmatzidou, S., & Demetriadis, S. (2009). Introduction of educational robotics in primary and secondary education: reflections on practice and theory. In D. Alimisis, K. Papanikolaou, S. Frangou, & M. Kantonidou (Eds.), Lessons Learnt from The TERECOP Project and new Pathways into Educational Robotics Across Europe (pp. 25–26). Academic Press. Misirli, A., & Komis, V. (2014). Robotics and Programming Concepts in Early Childhood Education: A Conceptual Framework for Designing Educational Scenarios. In C. Karagiannidis, P. Politis, & I. Karasavvidis (Eds.), Research on e-Learning and ICT in Education. Springer. Misirli, A., Komis, V., & Ravanis, K. (2019). The Construction of Spatial Awareness in Early Childhood: The Effect of an Educational Scenario-Based Programming Environment. Rev. Sci. Math. ICT Educ., 13, 111–124.

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National Research Council. (2010). Committee for the Workshops on Computational Thinking: Report of a workshop on the scope and nature of computational thinking. Washington, DC: National Academies Press. Available at https://www.nap.edu/read/12840/chapter/3#13 Papadakis, S., Kalogiannakis, M., & Zaranis, N. (2016). ‘Developing fundamental programming concepts and computational thinking with ScratchJr in preschool education: A case study’, Int. J. Mobile Learning and Organisation, 10(3), 187–202. doi:10.1504/IJMLO.2016.077867 Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. Basic Books. Papert, S. (1991). Situating constructionism. In I. Harel & S. Papert (Eds.), Constructionism (pp. 1–11). Ablex. Perković, L., Settle, A., Hwang, S., & Jones, J. (2010). A framework for computational thinking across the curriculum. In Proceedings of the 15th annual conference on Innovation and technology in computer science education. ACM. 10.1145/1822090.1822126 Portelance, D.-J., & Bers, M.-U. (2015). Code and tell: assessing young children’s learning of computational thinking using peer video interviews with ScratchJr. In Proceedings of the 14th International Conference on Interaction Design and Children (IDC ’15). ACM. 10.1145/2771839.2771894 Prensky, M. (2001). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6. doi:10.1108/10748120110424816 Pugnali, A., Sullivan, A., & Bers, M. U. (2017). The impact of user interface on young children’s computational thinking. Journal of Information Technology Education: Innovations in Practice, 16, 171–193. doi:10.28945/3768 Resnick, M. (1996). Programmable bricks: Toys to think with. IBM Systems Journal, 35(3 & 4), •••. Resnick, M. (2003). Playful learning and creative societies. Educator’s Update, 8(6). Resnick, M. (2007). Sowing the seeds for a more creative society. Learning and Leading with Technology, 35(4), 18–22. Resnick, M. (2013, May). Learn to Code, Code to Learn. EdSurge. Robinson, M. (2005). Robotics-Driven Activities: Can They Improve Middle School Science Learning? Bulletin of Science, Technology & Society, 25(1), 73–84. doi:10.1177/0270467604271244 Roussou, E., & Rangoussi, M. (2020). On the Use of Robotics for the Development of Computational Thinking in Kindergarten: Educational Intervention and Evaluation. In M. Merdan, W. Lepuschitz, G. Koppensteiner, R. Balogh, & D. Obdržálek (Eds.), Robotics in Education. RiE 2019. Advances in Intelligent Systems and Computing (Vol. 1023, pp. 33–44). Springer. doi:10.1007/978-3-030-26945-6_3 Royal Society. (2012). Shut down or restart: The way forward for computing in UK schools. Available at https://royalsociety.org/topics-policy/projects/computing-in-schools/report/ Sullivan, A., & Bers, M. U. (2015). Robotics in the early childhood classroom: Learning outcomes from an 8-week robotics curriculum in pre-kindergarten through second grade. International Journal of Technology and Design Education, 26(1), 3–20. doi:10.100710798-015-9304-5

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Sullivan, A., Bers, M. U., & Mihm, C. (2017). Imagining, Playing, & Coding with KIBO: Using KIBO Robotics to Foster Computational Thinking in Young Children. Proceedings of the International Conference on Computational Thinking Education. Sullivan, A., Kazakoff, E. R., & Bers, M. U. (2013). The wheels on the bot go round and round: Robotics curriculum in pre-kindergarten. Journal of Information Technology Education: Innovations in Practice, 12, 203–219. doi:10.28945/1887 Sullivan, A., Strawhacker, A., & Bers, M. U. (2017). Dancing, drawing, and dramatic robots: Integrating robotics and the arts to teach foundational STEAM concepts to young children. In Robotics in STEM Education: Redesigning the Learning Experience. (pp. 231-260). Springer Publishing. Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press. Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35. doi:10.1145/1118178.1118215

ADDITIONAL READING Aho, A. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832–835. doi:10.1093/comjnl/bxs074 Barr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community? ACM Inroads, 2(1), 48–54. doi:10.1145/1929887.1929905 Nickerson, R. S. (1982). Computer programming as a vehicle for teaching thinking skills. Thinking: The Journal of Philosophy for Children, 4, 42–48. Wing, J. (2016). Computational thinking, 10 years later. Microsoft Research Blog. Available at https:// www.microsoft.com/en-us/research/blog/computational-thinking-10-years-later/

KEY TERMS AND DEFINITIONS Activity Center: It is also called learning ‘corner’. A specific area in the classroom equipped with educational materials targeting specific skills. For instance, the writing learning corner is at a quiet spot and offers a selection of writing materials (i.e., pencils, papers, letter shapes, picture-letter flashcards, etc.) to any child who feels like working with letters. Compromise Skills: The ability to accept that one’s suggestions are not adopted (or desires are not met) by their team and still work to achieve goals without shouting, pouting, undermining others, leaving the group, or looking to the teacher for mediation. Free Play: The kindergarten Curriculum allocates specific time during the day when children are allowed to choose which activity center they want to play at, alone or with their friends.

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In Plenary: Tasks, discussions or games which are addressed to all the students. They take place at the designated classroom area that is equipped with seats for everyone so that they can present work, express ideas, share experiences and make decisions as one group. Negotiation Skills: The ability to discuss differences by respectfully presenting own views and trying to convince others to adopt them. For instance, saying “I believe it would be better to press the orange button because Colby must go left here! If we press the purple one, it won’t go correctly” instead of the usual behavior of shouting, pouting, grabbing the object of disagreement or looking to the teacher for mediation. Preschooler/Kindergartner: A child who attends the official pre-primary school programme at a school. In Greece, these children’s age ranges aged between 4 and 6 years. Tangible (or Haptic) Programming: The programmer uses available keys/buttons or blocks to create the desired code. It is closely connected with robotic devices, and it does not require any kind of screen.

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APPENDIX Table 5. Children’s drawings about robots Robot Before the Intervention The robot is mostly depicted in human form and it is usually alone.

Robot After the Intervention The robot is depicted in mouse form – it mostly looks exactly like Colby (blue with colored buttons on its back) and it is usually surrounded by children.

Robot Games

Robot Games

continues on following page

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Table 5. Continued Robot Before the Intervention

Robot After the Intervention

Robot Games

Robot Games

Robot Games

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Chapter 6

Control Technologies as Mind-Tools:

Emerging Mathematical Thinking Through Experiential Coding Activities in the Preschool Classroom Spyros Kourias University of Thessaly, Greece

ABSTRACT In mathematics education, especially in early childhood that is considered the most formative period in children’s lives, there is an always growing need to design, test, and validate tools and activities that take advantage of recent pedagogical and technological advancements but still focus on the creative learning process, instead of quantifying the outcomes and emphasizing numerical data and performance. Educational robotics as a context for interdisciplinary problem-solving scenarios in preschool education can be an interesting starting point, since modern control technologies are usually thought to provide a rich variety of mind-tools that encourage active learning and children’s creative thinking. Such activities may stimulate students to “do” mathematics in a seamless, creative, playful way in order to solve meaningful and appealing (for them) problems. The study tries to explore and validate emerging preschoolers’ opportunities to unconsciously “mathematize” their environment in everyday playful robotics activities in the context of brief teaching experiments.

INTRODUCTION Educational Robotics (ER) is a rather recent learning approach that is known mainly for its effects on scientific (academic) subjects such as Science, Technology, Engineering, and Mathematics (STEM). Interest in educational applications of robotics has risen sharply in the last 20 years or so, culminating in the most recent decade, mainly thanks to the advent of more advanced, affordable devices and specialized software. The increased and more complex possibilities offered as well as the wider availability of DOI: 10.4018/978-1-6684-3861-9.ch006

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 Control Technologies as Mind-Tools

new tools and applications based on “open architecture” and cheaper material resources, allow further experimentation and dissemination of the “makers” philosophy and practices to a wider age base of users. The use of robotics and programming has a long-standing history in mathematics education as well with tools such as “turtle” geometry or Logo explored in classrooms for almost 50 years (Papert, 1980). In the late 1960s, Papert and his floor turtle “launched” the field of educational robotics based on tangible tools and artefacts, giving children the ability to not only process materials and create structures, but also to define and control their behavior. Since then, a new kind of hands-on material, either tangible or digital (digital manipulatives) has made its appearance and is constantly evolving, offering the opportunity to kids and their teachers to experiment with dynamic ideas and affordances that other traditional tools, actually, have never been able to offer (Moyer- Packenham et al., 2015; Skoumpourdi, 2010). It should be mentioned, however, that the use of artificial intelligence and robotic devices and constructions implies a connection with tangible tools that, since the time of Fröebel and Montessori, still support learning through exploration and experiential practices (Brosterman & Togashi, 1997). There also seems to be a direct link with Resnick & Rosenbaum’s (2013) “tinkering approach” which refers to activity that engages children in a playful, experiential and iterative way of doing things with or even without the aid of advanced technology. For the above reasons, the trend of ER deliberately focuses on a range of control-technology educational tools in a variety of fields, addressing a variety of learning objectives (Keren & Fridin, 2014; Benitti, 2012 Eguchi, 2010; Nugent et al. 2010) and outcomes such as improving problem-solving skills (Alimisis, 2013; Benitti, 2012), cultivating cognitive flexibility and metacognitive practices in early and late childhood (Mioduser & Levy, 2010; Sullivan, 2008) as well as encouraging a positive attitude towards the STEM field (Lindh & Holgersson 2007; La Paglia et al, 2011) etc. In addition, recent studies have assessed the effects of robot programming on cognitive and learning processes, such as decisionmaking, self-awareness, problem-solving, and computational thinking (La Paglia et al., 2011; Kazakoff and Bers, 2014; Atmatzidou et al., 2018; Tuomi et al., 2018; Atmatzidou & Demetriadis, 2016 · Eguchi, 2014 · Keren & Fridin, 2014 · Alimisis, 2013 · Bers et al., 2014). In this chapter, through our research work, we intend to point out that teaching experiments based on ER in preschool classrooms, are indeed capable of generating an infinite variety of tangible representations and mediators that encourage experimentation with mathematical concepts and facilitate mathematical thinking in its whole. Our aim is to investigate how ER contexts can potentially lead to concrete mathematical constructs which can retain their dual role either as tools that model real world processes and events, or as means of (logical) reasoning. Our study explores emerging preschoolers’ “mathematizing opportunities” in everyday robotics play activities in the context of brief teaching experiments. Building on an ethnomethodological and multimodal discourse analytic framework, we suggest that mathematics (i.e. representations, spatiality, spatial reasoning, basic arithmetic operations such as addition, subtraction and even multiplication etc.) are expressed and actualized in children’s verbal and embodied interaction with their peers, material environment and more “experienced others”. We argue that new understandings and powerful ways of reasoning become possible on the basis of culturally mediated mathematical constructs produced in the context of creative and collaborative play of preschoolers with robots (floor turtles and more complex kits), coding and open-ended scenarios. As an additional supportive tool, the multiple implications of Vygotsky’s theoretical work, and especially the approaches that have emerged concerning the analysis of classroom interaction, such as the work of Rogoff (2003) and Kumpulainen & Wray (2002) can clearly complement teachers’ concerns and work. Basic concepts and pillars of our

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interpretive framework are the importance of the “more experienced other” in the contextualization of knowledge, the dynamics of interactions, the social framework, the tools for “mediating” thinking and cognitive processes.

BACKGROUND In our experiments we consider modern control technologies as the most “up-to-date” learning tools and their implementation context as a sophisticated “mathland” even more effective and close to children’s playfulness and needs than even Papert -who coined the term in his seminal book “Minstorms” (1980)had ever imagined. Creating from scratch or deploying ready-made “mathlands”, means that children get the opportunity to collaboratively experiment with mathematical phenomena in their real-world environments using tangible objects in ways that afford situated learning, embodied interaction and playful constructionism. Current programmable kits and coding environments, through the advanced capabilities they offer, highlight new opportunities for learning, including different ways to promote creativity, cognitive development and social interaction (Kozima et al., 2009) and encourage a stronger understanding of concepts and processes that surround children. Regarding preschool, a field that is of particular concern to our own research, we stress the fact that the lack of extensively documented research focusing on young children (4-6 years old) may be due to the complexity of mainstream robotics kits (eg EV3, Mindstorms, Arduino, etc.) that is associated with richer cognitive experiences and skills usually expected from children over 7-8 years old. However, it seems that during the last decade, interest has increased sharply and significantly based on the notion that “early robotics” and easily accessible robotic toys can be associated with an almost “effortless”, playful and unconscious interaction of preschoolers with a variety of processes and powerful STEM ideas (Bers et al. 2014; Kazakoff et al. 2013; Chronaki & Kourias, 2012). Therefore, it is argued that ER as a modern manipulative, can help make abstract ideas more specific, as the child can observe directly the impact of his/her programming commands on the immediate actions of the robot (Bers, 2008). Moreover, interaction with this type of control technologies seems to be appropriate for preschool children (Bers et al., 2014), as they are engaged in processes that activate and improve the innate tendency to explore, fine motor skills, embedded experience in the environment, observation and mathematical logic (Frye et al., 1996) without engaging in static interaction exclusively with the computer environment in front of a screen. In particular, Bers et al. (2014) and Kazakoff et al. (2013) verify the improvement of children’s procedural thinking and classification skills as well as sorting, measuring and recognizing patterns. Besides, classification is a component of design and involves placing objects or actions in the correct order (Zelazo et al. 1997) such as representing a story in a logical sequence, placing numbers in the correct order, and understanding the sequence of activities. of a day. Sequences, along with sorting, measuring, and recognizing patterns, are considered the “building blocks” of a child’s emerging logical thinking that begins to examine the world around him/her in the light of mathematics (Sarama & Clements, 2009). This seems to be further confirmed by other research studies as well, in which children along with adults in a collaborative effort to program and control a robot seem to come “effortlessly” in contact with mathematical ideas such as representation, symbolization, and modeling of movement (Chronaki & Kourias, 2012). Elkin et al. (2016) emphasize the evolution of children’s knowledge in relation to fundamental programming concepts through tangible programming

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blocks. Last but not least, Di Lieto et al. (2017) suggest that the engagement of preschool children in ER activities leads to a significant improvement in both the retention of information in short-term spatial memory and the development of algorithmic thinking and programming skills.

EDUCATIONAL ROBOTICS AS MIND-TOOLS THAT MEDIATE LEARNING AND ENCOURAGE CONCEPTUALIZATION AND ENGAGEMENT WITH POWERFUL IDEAS The contribution and added learning value of ER especially for young children is mainly about active participation, immediate interaction with the environment and the relations that it encompasses, as well as the feedback that it generates and the processes that encourage the development of mental models. Following Piaget’s constructivist theoretical model which implies that learning is indeed an active process of constructing experience-based knowledge, as well as Vygotsky’s theory on socially “crafted” learning, Papert envisioned coding, robotics and educational computing in general as a “next-generation” kind of mind-tools, as “objects-to-think-with” (Papert, 1980). The central insight of Papert’s constructionism is that when learning takes place in a meaningful and playful context, the learner is expected to recur to the direct feedback and outcome that is generated from the environment in relation to the intended goal, in order to improve their reactions and work out a better solution without the need for further external guidance or extrinsic teacher intervention (Laurillard, 2012). Papert also seems to share one of Vygotsky’s fundamental ideas regarding the importance of physical (tangible) and mental engagement with educational tools in order for the cognitive development processes to be facilitated. According to Vygotsky (1978), (mental) tools are able to significantly improve the learning behavior of the individual as well as to play a key role in his/her mental development. The importance of (educational) tools in teaching and learning processes seems to emerge more and more recently (Meira, 1998) and is often associated with supporting effective classroom communication (Mercer & Sams, 2006), the development of critical thinking, computational skills and practices (Jacobs & Kusiak, 2006) and the exploration of new ideas (Pimm, 1995). Learning processes are based on spontaneous, often temperamental motivations that can be structured and organized more effectively with the help of tools that lead to a more “responsible”, autonomous learning model with future references and extensions. For this reason, the absence of tools is considered to have long-term consequences in relation to learning because they are able to deeply affect the level of understanding of abstract concepts on the part of children. Without such tools, many children may interpret and reformulate several scientific phenomena, but they will result unable to transfer and apply existing knowledge to other problems and related fields (Bodrova & Leong, 1996). Moreover, according to Vygotsky (cited in Cole et al., 1978), mental tools are equally important and useful with physical-mechanical tools because they can be invented ad lib, used, reused and taught to be used by others. Following this, a child needs to actively explore, sense the environment and its components, make comparisons, discuss, relate, design and redesign the arrangement of objects until he/she builds his/her own knowledge and understand concepts before integrating them into their pre-existing cognitive load. In any case, every educational object or material does not automatically reveal its “tool status”, which it acquires if and when the individual himself/herself becomes able to integrate it meaningfully into his/ her activity through the creation of new mental shapes or its attachment to pre-existing ones. Within this “tooling” or “tool genesis” process, as it is called by Zbiek et al. (2007), the individual interacts with 112

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artefacts and builds “fresh” knowledge in order to achieve specific goals. According to Pimm (1995), however, the selection and integration of even the theoretically most appropriate mind-tool into a learning practice does not automatically lead to the understanding of concepts and learning. In the “dialectical” relationship with the environment and (educational) artefacts, it is necessary to frame activities that will be meaningful for children and will be enhanced by the discreet support and feedback of the teacher who will scaffold the whole process. Skoubourdi (2010) considers that educational materials can be turned into useful mind-tools for learning especially mathematical concepts as long as their integration undergoes careful planning coupled with good knowledge of both their “hidden” features and potential connections to concepts and (mathematical) ideas. In addition, to ensure the prospect of turning an object into a useful mind-tool in the hands of children, it is important to be aware of the possibilities it provides for supporting gradual movement towards abstract thinking. In the context of the present study, we suggest that (mind)tools like those generated in ER and control technology contexts, help children to form their motor, cognitive and emotional behaviors, to react to processes based on specific patterns, to design, solve problems and activate their memory and in general take on the role of “mediator”, more like a cognitive amplifier and “intellectual partner”. We argue that ER acts like a rich context that is able to empower children to discover or invent mind-tools since it frames similar principles through the design-thinking process in which participants have to reflect on a problem, collaboratively design meaningful projects, manipulate objects, tinker, reflect, test and validate solutions as well as associate concepts through cause-effect relations. Moreover, ER and especially more recent and open-architecture oriented tools (e.g. Arduino, Makey Makey etc.) go a step beyond by emphasizing real world processes and making practices out of the computer screen and without the need for testing and validating outcomes exclusively in digital environments. As Mikropoulos & Bellou (2013) suggest, working with robots, students shorten or even eliminate the distance between the “objects of the world” and the “computational objects” such as variables. The existence of robotic artefacts as physical and concrete objects offers the tangible tool to the children to work with and construct their mental models more easily and effectively. We firmly believe that educational robots bring into effect the constructivist and constructionist principles as a result of the combination of both their tangible (hardware) and intangible (software) components. Resnick and Silverman (2005) also suggest that control technologies that engage children in tinkering with objects and materials, empower the exploration of the ideas and concepts that underlie their creations and for this reason they should be regarded as powerful mind-tools (Bers et al., 2013).

METHODOLOGY: DESCRIPTION OF THE EXPERIMENTS Our research consists of different episodes that we have collected at different times between 2012-2019 in various kindergarten schools located in typical urban settings (Volos, central Greece). It is clearly influenced by the sociocultural theoretical framework (Cole, 1978; Rogoff, 2003; Kumpulainen & Wray, 2002) within which, the dominant elements are those of peer-to-peer learning, tangible, hands-on experience, scaffolded exploration and understanding of the environment and the relationships that emerge within it as well as the importance of mental tools that mediate concepts and processes. The research involves -gradually and equally distributed in groups/sessions- 90 children, (50) boys and (40) girls aged between 4.5-6 years and their selection was always done randomly with no personal opinion of the researcher or suggestion of the teachers to be taken into account. Each time, the teach113

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ing experiment was implemented in four distinct stages, each of which was designed to lead to data that could potentially answer our research questions. The complete flowchart of the research process with the individual phases and their connection with the research protocol, is fully reflected in figure 1. Stage 1 served as an introductory meeting with the children and at the same time as a preparatory activity for the class to get acquainted with the research tools. In Stage 2, a semi-structured individual interview was conducted in combination with spatial micro-tasks with each child separately. The aim was to explore any previous experiences and mental patterns of children in relation to both space and the use of technologies and programmable systems before the implementation of the main group activities. Stage 3 was actually the teaching intervention per se, that lasted, each time, two days and a total of four teaching hours with each of the groups of children. Stage 4 resulted to the final semi-structured individual assessment interviews through which we had the chance to understand if and how children could transfer and apply newly acquired spatial knowledge and skills in open-ended spatial challenges in a digital environment (Lightbot application). Figure 1. Teaching experiment workflow

The broader organization of our teaching experiments is based on the importance of the social context as a significant factor that contributes to defining cognitive practices and strategies but also as an “enhancer” of potential Zones of Proximal Development (Cole et al., 1978). Therefore, the approach of learning in this light, influences both the design of the teaching experiments and the activities that are expected to facilitate the development of children’s mathematical thinking and tangible experience of space, the emergence of the dynamics of mental tools (pre-defined or emerging) and (verbal, symbolic, graphic, etc.) representations as mediating conceptual means. The same applies to the qualitative analysis and interpretation of our research data which is based on an ad-hoc analysis tool that draws its inspira-

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tion from Rogoff’s “Three Foci of Analysis” (1998) and Kumpulainen and Wray’s theory on analyzing classroom interaction (2002). Following this theoretical framework, emphasis is placed on the utilization of ER not as an “enhancer” of techno-centric skills but as a means of creating multifaceted representations of space and collaborative construction of mathematical concepts. More specifically, our research aims to identify mainly which spatial skills and “powerful ideas” and under what conditions can be encouraged and enhanced with the aid of modern control technologies, while trying to make sense of the dynamics contained in the combined and representational rich use of relevant tools mainly through tangible programming and code synthesis in mixed environments (physical and digital). All this grounded in a broader qualitative approach and more specifically in the teaching experiment practice which is already widely tested in the field of mathematics education and allows the micro-ethnographic recording and interpretation of “events” within the classroom community (Kelly & Lesh, 2012 · Glasersfeld, 2006) Cobb et al., 2003) putting an emphasis on communication events rather than strictly on the final (quantitative) performance of children. In each teaching experiment, the problem-solving practice was rather “modular”, as the engagement with the research tools concerned individual action initially, went on with work in pairs and ended up with group work. The activities were all open-ended based on the use of programmable devices (Bee-Bot, Lego NXT) in different - robot design and movement coding- scenarios in the context of a small-scale model that represented an urban environment. In the first stage, based on a short story, we asked each team to program their robot to reach a specific point in the model. Each child should study and draw with a marker on a worksheet a suggested route and then present it to the rest of the group for discussing, comparing and picking the most appropriate-shortest route. At a later stage, children had to represent the same route, this time using tangible, puzzle-like code-blocks. In essence, it all goes down to a sort of visual programming processes through the use of print-out cards, each of which represented simple movement and activity commands (“go straight”, “go backwards”, “turn right”, “turn left”). The final results (visualized movement scripts) of each preschooler’s work represented a step-by-step route plan of the robot’s movement and could expose children both individually and collaboratively in conditions of open solution of a spatial problem until the selection of the optimal choice. In each stage of our research, for the first-encounter activities, we used the “Bee-Bot” programmable “floor turtle” while for the rest of the experimentation, we resorted to a pre-constructed simple Lego NXT robotic vehicle and the appropriate accompanying software which implies processes of pseudocode design and development for programming the behavior and movement of our experimental robots in a small-scale model. The Bee-Bot roamer is directly linked to the philosophy of use and affordances of the early Logo turtle. It is considered (DeMichele et al. 2008, Stoeckelmayr, 2011) suitable for either familiarizing children aged 5-7 years old with basic aspects of computational thinking or encouraging spatial thinking. As can be seen in Figure 2, it is essentially a device that is being programmed through its 7 built-in keys, each of which has a different and representative symbol of movement or activity and corresponds to a specific command each time (forward-backward direction, right-left turn, pause of one second, clear memory, program execution). The width of each step of the Bee-Bot is 15 cm and to facilitate the procedures of measuring and estimating distance on the part of children, it is equivalent to the length of a standard marker. In addition, it is almost equivalent to the length of its own body, which is especially useful in overlapping measurement scenarios. It does not need to be connected to a computer to be programmed and it is based on the LOGO commands logic, however the execution of pseudocode, i.e. the movement

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is a process that is not visualized in a dedicated screen but gets executed in a real environment, thus seems more abstract. Figure 2. Bee-bot: one of the teaching experiment’s educational robotics tools

For the activities of the second day of our teaching experiments, we resorted to the use of one fully programmable, pre-constructed (earlier from us) Lego NXT robot vehicle with its corresponding software that clearly refers to programming processes through blocks (images) and concerns the planning and execution of movement in space and beyond. The accompanying programming interface is a flowchart-based environment that allows the user to code using icons representing all data types and basic commands and programming structures in a symbolic format without the use of conventional commands. The coding practice is rather understandable since it requires only dragging and dropping of each block from the command palette (bottom of the screen) to a dedicated coding grid. We made sure that the NXT robot had a total length as much as the Bee-Bot (15 cm) and therefore exactly as much as each quarter of the surface of the small-scale city model. This was done in order to enable children to develop mental shapes and strategies for managing movement and space with common references to both of the aforementioned tools. Therefore, in the same light, we made sure that each step of the NXT robot was equivalent to 15 cm, which is the same as the step of Bee-Bot and the quarters of the floor on which it would perform the respective movement. For this reason and in order not to engage children in complex and frustrating programming processes, we decided to provide pre-configured movement commands whose icons were replaced by custom representations that resembled the ones children would use to represent Bee-Bot’s movement. Our intention was for these to be immediately understood without further misinterpretation.

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It is necessary to point out that the choice of the two main tools (Lego NXT & Bee-Bot) of the teaching experiment, which are also based on different ways of interaction between children and each device, aimed at highlighting the different approach required for movement planning every time. It therefore concerns the different strategies that children had to develop in order to perceive and deal with space around them. Therefore, the emerging multiplicity of mediators and the diversity of the symbolic code that emerges through the planning processes of the movement and functions as a “scaffolding” were equally important to us. Regarding the special features of both basic tools that we chose, we could say that in the case of NXT, the ease of composing a program using the mouse and simply placing icons on the screen was of particular importance, even if we had to adapt the tools to the range of skills of preschool children. On the other hand, in the case of Bee-Bot, an important feature was its resemblance to toys familiar to children (shape, colors, figure, etc.) as well as the “safe” tangible interaction required to plan its movement.

THE EFFECTS OF DEPLOYING EDUCATIONAL ROBOTICS AS MIND-TOOLS Encouraging Preschoolers’ Mathematical Thinking In our teaching experiments, we thought that the context of planning and coding the correct route of a robot in a given small-scale three-dimensional urban landscape model would clearly encourage children to think out of the box in a collaborative way, to explore, invent and reinvent a variety of mind-tools while resorting to mathematical thinking for solving simple spatial problems. Besides, movement is a way to interact with the external world and the physical placement of a body or an object (programmable or not) in space as well as the mental and sensational feedback associated with movement are keys to how humans shape, perceive and interpret their surroundings and what mediators they make use of in order to better understand spatial interactions. The robotics-enhanced learning environments that we have devised in the context of our research not only gave to children access to (mental) tools that favor the development of spatial thinking and orientation skills through planning, testing and verifying routes but they also opened up significant opportunities for “mathematizing” their environment on the basis of spatial processes, crucial for solving problems related to the movement of a floor turtle such as Bee-Bot or a robotic construction like NXT in a given small-scale space. All this leads to the use of environment and context elements as informal tools for measuring and comparing distances as well as resorting to simple operations such as addition, subtraction etc in a natural and seamless way. In some of the episodes that we singled out, it seems that the value of involving children in such spatial experiences and interactions lies exactly in the visualization of a rather abstract activity (movement in space) and its perception as a single process which however consists of several intermediate steps that are often “invisible” to preschoolers unless they are intrigued to explore them. It is therefore obvious that during the initial planning of such activities it is rather necessary for children to be engaged in a discussion regarding the semiotics of movement in space in order for them to explore how people move through their surrounding and interact with objects. One of the most efficient ways to encourage such a discussion was the coding sequences (coding cards and drawings) that we asked children to create in an “alternative programming canvas” that would act in parallel as a graphical representation and visualization of their decisions and thoughts about specific movement in space. At a later stage this very “pseudocode” should be transferred to the “brain” of both Bee-Bot and the NXT in order for it to be 117

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executed in the model environment. Moreover, especially the nature of a Bee-Bot, which contains the tangible programming buttons on its body while it totally lacks a screen in which to display the children’s “coding” options, in contrast to the NXT, led us to the need to represent the steps in an alternative way so that they become visible in case of trial-error and debugging processes. For that reason, children were asked to plan the robot’s movements by putting together flow-charts based on card-based sequences that represented the robot’s step-by-step route which would later on be “executed” by Bee-Bot (sequence of button pressing) or NXT (sequence of code-blocks in a programming environment). According to what we observed throughout our experiments, in episodes just like the one that follows next, when we ask from children to design and test their “movement diagram/sketch-up” of choice, this usually acts as a powerful “mental tool” since it favors at the same time both the process of children’s reflection on space and the “evolution” of the tool itself granted it is gradually improved -through trial and error processes- regarding its efficiency in achieving the final goal of the route. It may be the most important mental aid among those we have indirectly suggested to the children to use as, each time, it triggered the emergence of practices necessary for solving a (spatial) problem, namely observation and debugging (visualization and easier highlighting of the error), collaborative renegotiation of concepts of space, reorganization of sequences, pattern discovery, argumentation and perception of movement as a single serial process consisting in separate but interconnected steps. RESEARCHER (R): Let’s see!! Did he do it right? DANAE (D): Yes!! He went forward-forward-forward-turn-forward-forward-forward-turn-forwardforward-turns and “Go”. (At the same time, she shows the icons with her hand meaning that she tries to provide explanation, representation of an idea but also self-evaluation) R: Let us check the program again for a while! Did we forget anything? ... D: Oops, now I found it! (After thinking about it for a while and after observing the coding cards) R: What should we do? D: We have to follow this! (She shows us the “coding flow-chart/representation” in order to express her point of view which emerged after observation. Danae begins to reorganize the steps carefully observing the “coding script” but at the point of the second left turn, due to her different point of view, she stops and thinks about it. This is where Nico helps by pointing the right step with his finger). R: Fine!! Let’s see! Shouldn’t she turn here? (We try to point out the point of confusion with a reinforcing question) D: Oh, come on! We should use an arrow like this. (Indicates direction but confuses “straight” and “turn” icons) NICO (N): Wait a minute! We did something wrong! Here it must turn. (changes the direction of the straight-line icon so as to lead to a right turn). There have also been certain scenarios in which the teacher invited the children to choose the shortest of the routes for the robot to take in order to reach its destination. As a means of preventing the temperamental and mainly egocentric way of thinking of children, which at an early stage lacks any rational justification and is dictated mainly by enthusiasm, competition and dominant roles within the group, we asked them to explain the differences between the suggested paths. This way we encouraged children to indirectly explore, compare, discover and perceive the existence of any informal tools of measurement and comparison that would naturally lead to the “mathematization” and quantification of an otherwise temperamental and abstract- process, through operations of addition and subtraction. Such operations 118

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seemed to encourage comparative processes regarding relations of inequalities, e.g. “greater than vs less than”, “farther vs nearer”, “faster vs slower” and so forth, exactly as it is reflected in the following episode. RESEARCHER (R): Think about it, how did we measure the bee’s steps yesterday? Think about which of the routes is the fastest? CHRISTINE (C): This one! R: Well, yes, but without counting? Thanos, how many steps does our robot have to take up to here? THANOS (T): 4, up here. 1 … 2 .... 3 .... 4 ... (Counts while pointing his finger on the floor plan) NEFELI (N): It needs 5. R: 5 eh? Let’s see! How did you measure them Nefeli? N: I started off with this box. R: This one is the starting point though! It should be left out. Well…. N: Hmm, 1 .... 2 .... 3 .... 4 .... 5 .... (Counts following the steps with her finger on the floor plan) E: OK, 5! But what if we leave out this box? N: Then it is 4!! R: This route has 4 steps, this one too!! George’s route, how many steps does it have? (We attempt to compare works that will trigger mathematical thinking and further discussion) C: 1 ... 2 ... 3 ... 4 ... 5 ... 6 ... 7 ... 8 ... (Counts following the steps with her finger on the floor plan) R: 8! Christina, let’s see. Christina, how many steps does it take to get here? C: It will be 4!! R: Why do you say that? What made you think something like this? C: She did what Nefeli did! R: Aaah, then it is the same route? C: Yes! Q: Fine, which one do you suggest we should choose? Remember that we need a fast route. C: Thanos’ route. R: Why’s that? C: Because it has 4 and is the shortest. Such informal measuring tools were the Bee-Bot programming command cards (which represented individual steps and quantified movement into measurable units as well as comparable numerical sets), the NXT code-blocks (in the digital programming environment) as well as the quadrants of the smallscale model that deliberately marked the surface on which the robots moved around as we can see in figure 3. In the next episode, based on such “seamless” measuring and calculation tools, it was possible to create the appropriate framework for all those mathematical operations and processes that in turn led the children to find solutions to the respective spatial-programming problem of the “missions” that they were assigned to them. Our main effort with children was to inspire them with the importance of a logical quantification of the elements that were at the same time part of the correct programming process as well as to draw comparative conclusions based on operations and reasoned calculations and not on random, abstract thinking. RESEARCHER (R): I want you to measure the steps our robot needs to take. Do you remember how we measured the steps? THEODORE (T): Oh yes! With the arrows. 119

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R: The arrows or something? ATHENA (A): Maybe with the computer? T: 7, 7!! (He looks at us with great confidence and we noticed him counting the steps as we formulated the question) R: How did you count them? Can you show me? T: 1...2..3..4..5..6..7! (Counts while indicating the squares-steps to be taken based on the suggested route suggested) R: Let’s look here on the map to get a little more help. I want you to tell me if you can notice here (on the surface of the model) how we can count the steps. NASIA (N): Me sir! 6! R: 6? How did you count it? N & A: 1.2.3.4.5.6 (They count the steps in the model using their fingers) A: I have 4! T & N: 1.2.3.4.5.6 R: What does Athena say? See, what could we measure? A: Maybe we should put 5. (Renegotiation through observation). R: How did you think of that, Athena? A: 1...2..3..4 ..5. (She counts the quadrants of the floor-plan of the small-scale model) R: Wait a minute. What did you measure in order to tell us that it is 5? A: Look, these. One “box”, another box and another and another.... (She clearly refers to the quarters of the model’s floor-plan) R: Well, nice idea. So, count the “boxes” and then write the number on your sheets. (After comparing everybody’s suggested routes in relation to the final destination of the robot, the children end up with “5”) We rather think that the emerging development of children’s ability to decide upon routes and identify various spatial relationships by quantifying the environment through spontaneous invention and use of informal and/or pre-designed (by the researchers) tools, should be considered of high learning value. The majority of the recorded episodes concern an absolutely quantitative approach through the use of informal and ad lib measuring instruments and this probably implies a significant frequency of practices that favor the experiential and multifaceted approach of mathematical thinking. We firmly believe that without these practices, children would find it particularly difficult to develop the correct “coding scripts” for route planning since a necessary component for defining complete and correct movement in the smallscale model environment was initially the numerical correlation of the steps-commands (programming block) with the respective quarters into which the floor route was evenly divided. We had already taken into account the division of the route into “boxes” of dimensions equal to the step of both Bee-Bot and the NXT, a fact that made it “obvious” but also necessary to quantify the whole process on the part of the children. This is exactly what is also reflected in the short episode that follows and was recorded in the context of the 1st day of one of the teaching experiments and in a phase when children got to know the tools and the activities of the teaching experiment. Throughout the interaction with children, it is obvious that their behavior shifts from abstract reasoning to the use of solid argumentation that can adequately explain both the way they thought and their final choices in the movement planning process.

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Figure 3. Tangible, hand-drawn and digital movement flow-charts that trigger mathematical thinking

RESEARCHER (R): Let me ask. How did you measure the steps? CHRIS (C): We saw the road. (Without further explanation) R: Is there a way to measure this? C: Yes! R: How? C: By measuring .... With the ruler. (Spontaneously recalling the use of a formal tool) R: That is, if we do not have a measure, how else can we count how many steps the Bee should take? C: Eight!!! R: Eight? How did you figure this out? C: I counted the arrows and the boxes. (Chris and Thanos count the command-icons with their fingers. It seems that our question triggered exploration)

Encouraging Preschoolers’ Spatial Thinking Spatial thinking is a rather complex process related to the use of spatial code, reasoning (finding paths, spatial correlations, creating representations, discovering spatio-temporal relationships, etc.) and transformations (change of perspective, orientation, change of size and scale, transformation of shapes, etc.)

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especially for preschoolers (Piaget & Inhelder, 1967; Everett, 2000) although it seems that such difficulties can be potentially tackled with the use of ER (Francis et al., 2016). Based on the analysis of group activity episodes, it seems that our teaching experiments address a broad variety of mental tools that encourage spatial thinking. In the following episode, our group of preschoolers is still at the beginning of both designing the BeeBot movement and “negotiating” key space concepts. At the same time, the researcher tries to help them either understand the ways and strategies of representing position in space, or how to make connections with experiences already developed in similar recent activities. The children are asked to design an ad hoc map that graphically depicts the environment of the 3D model. After providing explanations on the objective of such an activity, we try to make them correlate the value of such a tool with the movement “script” we would develop later on in order for the Bee-Bot to move successfully toward its destination. From our introductory question addressed to the group, it is obvious that the attempt is to trigger collaboration as well as help recall previous experiences both individually and collectively. On the other hand, the attempt is to invite children to focus on a new solution (map design) and to refer to the use of tools (plan) that act as reference points in the context of giving exact directions to someone else (coding instructions, Bee-Bot). At a later stage, when the researcher tries to elicit detailed explanations for the proposed routes, the children’s descriptions seem to drift away from the mere use of gestures to a combination of gestures and correlation of the environment with their own drawings and maps. It is quite interesting that the process of maps and route plans design and then the attempt of children to explain their drawings, kicks off a dialogue which completely lacks spatial descriptions and vocabulary at least at this initial stage. However, it activates them significantly in the field of perception of space with the help of intense use of non-verbal elements such as gestures and the use of the body as a point of self-reference and comparison with other reference points in space. In addition, it seems to encourage meaningful opportunities for the correlation of a real-world environment (3D model) with its graphic representation (2D map drawing) and the position of the individual in relation to both. Such patterns now serve as reference points and correlations of the abstract with visible and tangible elements (Steinbring, 2000). RESEARCHER (R) How can we help Bee-Bot to get where we want since it does not know the way? Daphne: She can go this way and that way. (shows the route over the model with her hands.) R: Yes, but you know the way! The Bee-Bot doesn’t. What do we do when we get lost? Do we need any maps? .... Would you like to draw one and help our little bee remember the road? (We hand out blank pages and crayons in order for children to draw the map of the suggested route… (R): Let’s see Alexia. Can you explain to me what you have done here? ALEXIA: The bee goes from here and turns and here it turns again. (As she speaks, she follows with her finger the path she has drawn. She uses non-verbal means and gestures, but always in relation to the ad lib map and the 3D model environment.) R: Giannis, what have you done? GIANNIS: She goes there, then there, then there and there. (while talking, he follows the path with his finger) R: What about you Danae? Where does the bee start from? DANAE: From here, it goes straight, then it turns, straight again. (Uses non-verbal means and gestures but leaves the description incomplete)

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Figure 4. Route planning patterns prior to coding

On one of the first days of the teaching intervention children come in contact with the Bee-Bot for the second time, but in this case, they are able to make use of additional tools. In the episode that follows, they understand how to use the directional keys/buttons not in an abstract and casual way but in combination with the route pre-planning (maps) and the representation of the potential movement with the help of coding cards as per figure 4. At this stage they seem to realize the functional value of the coding cards but also their importance as an informal measurement unit as they help to estimate and accurately calculate the distance from the starting point to the final destination we have defined in the context of the mission. Figure 5 contains a fine example of such practice.

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RESEARCHER (R): But do we have to learn to talk a little better with the bee? Can we help her understand your map? What do you say; Do you want us to show her some cards? ALL TOGETHER: Yes!! R: Do you remember the bee buttons? Daphne (D): Right-Left-Up-Down (shows the buttons on the back of the Bee-Bot) R: Would you like me to give you these cards? How can you tell the bee where to go following these cards? D: This here is the same with that. (shows us two directional arrows) Nick (N): This is different. Modestus (M): I want a “5”! (Obviously Modestus implies that he will have to get as many cards as the steps of Bee-Bot) R: So there are numbers here or arrows? A “5”? M: Numbers… .arrows… Q: Is her house far or near here? N: Far. D: Very near!! Q: How do we know if it is far or near? How can you figure it out, is there a way? N: From the “squares”. (He means the quadrants of the surface of the small-scale model environment, each one of which is equivalent to a complete Bee-Bot step) D: We make the road and help the bee. Then we use the arrows… Figure 5. The environment as a generator of mind-tools

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In the following episode, one of the groups gets to use for the first time our NXT robotic vehicle. We feel that since movement and coding is mediated for the first time by a digital environment, thus the software that is needed for developing actual code, it is useful to remind to the team about the new way of “human-robot” interaction” and the more complex programming processes. The significance of such a reminder lies in the fact that the “new” processes of interaction with the NXT are no longer based on direct tangible coding (by the press of a button) but on the use of the mouse and the transfer of digital code from the software screen to a real environment. As part of the group engagement process, we ask children to explain us if they understand how important computer mediation is in the NXT movement processes and how this fits with the “coding cards” planning we have already done while actually planning the robot’s possible routes. Alexia is activated from the beginning in the use of the computer and the relevant software in order to create a first executable script which acts as a basis for discussion with the rest of the group. Following is a continuous and evolving effort by the team to optimize and identify the pre-designed route (representation with cards) and the rest of the accompanying tools (maps and plans designed by the children themselves) with the digital coding interface of the NXT software and finally with the movement of the NXT itself in the small-scale space of the model. RESEARCHER (R): Listen, I want us to send our robot to refuel. What should we do, just think about it? ELENI (E): I know…Turn, go from here, go from here and then refuel. R: What do you mean? Do you want to show us with a program? (Children gather around the computer) ALEXIA (A): I know! (Alexia has tried to create the executable script in the coding app while we try with the team to explore possible routes) R: Not there, not on the computer. Work with the cards first. We have the cards. A: I did it sir! R: Let me see! Is the code correct? KEVIN (K): Oh, no!! A: Should we try it? (Meanwhile, the robot executes the script) K: What? (Kevin expresses his surprise) A: She had to turn! (Alexia finds out for herself by observing the NXT while it moves) K: Alexia, you did it wrong! MARIA (M): Let’s delete it!! R: Fine! Listen for a while. We said that we must first create a script with the cards. Why don’t you all come over here and help. E: Here is a turn! (Eleni passes a right turn icon) M: Where, here? Hmm, I know what is needed. There! Give me another “turn”! (Maria asks for and places another icon to complete the “executable script”) E: Yes, I found it! K: Thank God! E: Okay! R: And after she turns, how many more steps does she have to take to turn to the gas station? (As we speak we represent the movement of the NXT with our hand to help children understand better) K: One more step. M: Give it to me. Here! R: Now, let me ask something? Look here. She turns right, takes a step. How many steps does it take to get to the corner here? One? 125

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M: Yes, one. K: Two! Q: Eleni? What do you think? E: 1..2..3..4..5 .. (Eleni counts all the steps until the end of the route) K: Another one maybe? R: So something is missing here? E: Yes! R: And that is? E: One step forward! Q: Okay, let’s try it then. The variety of so many representational tools almost in parallel seems to give the group but also to each child individually the “safety” and confidence for effortless experimentation and implementation of their ideas (trial-error process) in real-world environment until they approach an optimal solution. In addition, the coexistence of multiple tools that essentially serve the same purpose of understanding, visualizing and organizing movement, especially through actual collaborative coding practices -as depicted in figure 6- offers children the ability to appreciate the value of (pre) planning strategies and debugging practices that favor both justification and comparison as well as the importance of a trialand-error strategy towards the right solution to a (mathematical, spatial) problem. Figure 6. Peer-to-peer coding

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CONCLUSION The inspiration and starting point for our research is the traditional “LOGO turtle geometry”, which aimed to introduce mathematical concepts in the context of coding processes and was to change the way we talk today about young children build knowledge and their ability to be actively involved in the experiential classroom culture. Our findings highlight the affordances of ER regarding the development of skills that allow children to recognize and describe, directly or with the aid of various forms of feedback, topological/spatial relationships in the environment that surrounds them (inside, out, left, right, next, between, close, far, round, front, back, side by side, down / over, etc.). In addition, the ability to approach and measure spatial relations by quantifying space and topology through the invention and use of informal and ad lib tools, is clearly demonstrated thanks to the exploitation of “coding” practices required for developing efficient pseudocode (e.g. use of programming cards and blocks in software environment, justification of choices by matching each step of the robot with every single programming command etc.). Other elements that emerge from the data analysis of our research work are the development of skills of understanding and deploying spatial code as well as orientation skills in space when different points of reference exist, through embodiment-based strategies. In addition, one more interesting finding, which mainly concerns the strategies for solving a spatial problem, is that most children in many cases have gone through self-assessment processes and redefined the solution to each problem, adapted to new data, altered their initial attempts and often moved between other-self-regulation as a natural consequence of the above processes. Based on the research experience so far (DeMichele et al. 2008, Chronaki & Kourias, 2011), the suggestion of the mind-tools and practices of our research is considered suitable for supporting familiarization with the broader computational practices as well as encouraging the development of spatial and wider mathematical thinking of children aged between 5-6 years old. It also seems that the provision of basic visible and tangible tools (route plan, small and large cards with directional representation, photo-plan of the small space) as well as the initially guided visualization of spatial concepts and processes in a way that emerges through free play leads to the spontaneous invention of new tools and the emergence of multiple representational means of the environment (eg the quadrants and landmarks of the model, the correlation of the 3D environment with its 2D representation, the body position and orientation etc.) during the course of activities. The non-serial, uncompromised and almost random interplay of tools scaffolds cognitive evolution and exploration and supports children’s mathematical improvisation and spatial thinking through peer-to-peer trial-error processes. We could also argue that children perceive experientially the value of trial-error strategies, the importance of both existing or ad lib powerful tools, the usefulness of the combined and near-parallel utilization of multiple representational media as well as the central role of the use of our own body not only as a means of egocentric perception of space but also as a kinesthetic tool for drawing experiential conclusions through comparisons and correlations of environmental elements.

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A Proposal for Creating Mixed Reality, Embodied Learning Interventions Integrating Robotics, Scratch, and Makey-Makey Stefanos Xefteris https://orcid.org/0000-0003-2448-4970 University of Western Macedonia, Greece Ioannis Arvanitakis https://orcid.org/0000-0002-3024-6007 University of Western Macedonia, Greece

ABSTRACT In current research we observe a clear trend that calls for novel teaching practices that involve multidisciplinary approaches that integrate information and communication technologies (ICT) into “traditional” workflows, employing embodied affordances in multimodal learning interventions. The educational process can therefore be augmented and transformed making use of available tools like educational robotics, tinkering with electronics (such as Makey Makey), and programming environments like Scratch to produce gamified versions of teaching sequences in a mixed reality context that “physicalizes” abstract concepts and improves both “21st century skills” and knowledge of traditional classroom material. Under the embodied cognition framework, the authors make use of robots as tangible agents in a gamified mixed reality setting. In this chapter, they provide a proposal for creating educationally effective, immersive, and engaging learning environments, as well as primary results from experimental application in various multi- and transdisciplinary teaching interventions.

DOI: 10.4018/978-1-6684-3861-9.ch007

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 A Proposal for Creating Mixed Reality, Embodied Learning Interventions Integrating Robotics

INTRODUCTION Human cognition has been shown to be inextricably linked with the manifestation of objects around us. How we act directly influences the way we think and the way we interact with physical objects directly shapes our perception and understanding of concrete or abstract notions. From the time of the abacus to the era of virtual and augmented reality, embodied interaction has been consistently proved a fertile ground on which to build learning interventions that provide learners with conceptual anchors. The STEAM (Science, Technology, Engineering, Arts Mathematics) approach to learning employs interdisciplinary concepts from the Natural Science, Engineering, Technology, Arts and Mathematics as a base for developing and honing 21st century skills such as critical thinking, creativity, communication and cooperation in a framework that facilitates inquiry based experiential learning. Using a creative process (Nemiro, Larriva, & Jawaharlal, 2017), the STEAM approach enables students to develop their problem solving skills, engage in the design and evaluation process -facilitating design based thinking (Alimisis, Moro, & Menegatti, 2017; Jaipal-Jamani & Angeli, 2017; Khanlari, 2016), and advance their computational intelligence skills while cooperating and engaging in science-based dialogue. The ultimate goal of employing STEAM learning scenarios is that students are familiarized with both concrete and abstract notions from engineering (simple and complex machines), advance their ability to think algorithmically (programming devices), design and build robots that perform a variety of tasks (Bers, Flannery, Kazakoff, & Sullivan, 2014). In recent years, the virtual deluge of novel advancements in ICT has greatly improved our fundamental grounds of developing single- or multimodal and more importantly multidisciplinary teaching interventions. Mixed and augmented reality applications (Fleck, Hachet, & Bastien, 2015), virtual models and 3D representations (Sun, Lin, & Wang, 2010), tangible manipulatives and ubiquitous interfaces (Mpiladeri, Palaigeorgiou, & Lemonidis, 2016) as well as educational robotics (Alimisis et al., 2017; Karim, Lemaignan, & Mondada, 2015), have consistently proven to be great tools for leveraging conceptual change (Bonito & Almeida, 2016; D de la Hera, Sigman, & Calero, 2018). Deploying ICT tools to develop multimodal and multidisciplinary teaching scenarios has been consistently providing highly praised outcomes, there has been so far a specific vital aspect that many applications miss, due to the nature itself of the employed mediums: Tangibility. More often than not, recent research has been shown to employ intangible representations of concepts, thus -not failing, butlimiting access to the full potential the availability of multiple and ubiquitous technologies offers to us. The use of physical manipulatives which the learner can use, tinker, build and feel, the use of embodied learning affordances can greatly and further advance the creation of conceptual anchors: The physicalization and operalization of processes, turns abstract, and possibly inaccessible from our POV. concepts (such as Earth’s trajectory) to concrete instances with which learners can interact. In this context, this chapter proposes the integration of multiple technologies, combined to provide a rich ground for the design, development and evaluation of STEAM learning scenarios. Mixing educational robots as tangible agents and interfaces with the digital world, Scratch programs to provide a gamified background and Makey-Makey hubs to facilitate interaction, this chapters aims at describing a concept of developing learning interventions where physical objects merge with digital representations to provide natural interaction, on which learners can build new knowledge (Xefteris, 2019; Xefteris & Palaigeorgiou, 2019a; Xefteris, Palaigeorgiou, & Zoumpourtikoudi, 2019). The proposed frame of operation has been tested in multiple experiments, with 4 of them having been published in conferences and journals and others having been tested only unofficially during the 133

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undergraduate course “STEAM scenarios using educational robotics” in the Elementary education department of the University of Western Macedonia, Greece. In the published experiments the examined variables for the learning interventions covered multiple aspects: The researchers conducted pre- and post-cognitive tests to assess the efficacy of the learning paradigm and usability/user acceptance questionnaires to assess ease of use, user stimulation and identity, autotelic experience etc.

LITERATURE REVIEW According to the framework implemented under the embodied cognition theory, there is an unbreakable bond between our actions and our thoughts (Abrahamson & Lindgren, 2014). Our perception of space, of objects and even abstract notions depends on our bodily interactions, our tangible contact with them. We formulate and sustain mental representations after interacting with the world with our body, with all our senses, not just our vision. Full body interaction has been shown to support learning by involving participants at different mental and corporeal levels, such as the affective aspect, the cognitive aspect, as well as the whole sensorimotor experience the user of a framework gets. Thus, building new knowledge has been shown to be influenced by students who create “conceptual anchors” while acting out and “physicalize” relationships between abstract and concrete notions and operations (Lindgren, Tscholl, Wang, & Johnson, 2016). New ICT tools, facilitating improved Human-Computer interaction technologies, with ubiquitous interfaces serve as conceptual leverage (Lindgren et al., 2016). The development and integration of novel modalities in teaching interventions, making use of embodied affordances, plays a vital role in the transformation of the teaching paradigm and the development of novel frameworks that improve learning. learning environments created under the embodied cognition framework aim to facilitate the creation of embodied experiences that represent abstractions as concrete instances or transform inaccessible -to the point of view of the participants- phenomena and actions to tangible, physicalized representations. Novel ICT tools such as mixed reality (Kazanidis, Palaigeorgiou, & Bazinas, 2018), tangible interfaces (Xefteris, Palaigeorgiou, & Tsorbari, 2018) and educational robotics (Eguchi, 2015) provide us nowadays with new opportunities to develop teaching interventions combining many disciplines under the common umbrella of a gamified and immersive experience. The creation of such interventions is an emerging area in recent research and to our knowledge not yet fully systematized. There are three main research domains that underlie the creation of the proposed framework of operation: 1. Creating STEAM learning scenarios 2. Tangible maps and ubiquitous human computer interfaces and 3. Educational robotics and the use of robots as tangible agents linking the physical world with a digital one in a mixed reality setting. Considering tangible maps recent literature suggests that maps in both forms electronic and paper do provide learning opportunities and advantages but also induce sometimes barriers in the honing of spatial thinking skills (Collins, 2018). The transformation from the three dimensional world we live in to the two dimensional world of a projected or printed map does induce barriers in the mental representation of topographical details by making learners perform mental representations in order to create new knowledge (Li, Willett, Sharlin, & Sousa, 2017). The addition of ubiquitous digital interaction 134

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with printed or projected maps, their transformation into tangible 3D maps has been shown to improve to improve learning especially in the context of disciplines such as geography in an embodied framework (Palaigeorgiou, Karakostas, & Skenderidou, 2017). In other disciplines, such as history, literature suggests that including ICT tools to create tangible interactions in mixed reality settings in the design of teaching interventions, augments motivation and engagement and makes the learning process more enjoyable for students. Through the use of gamified mixed reality learning scenarios we can facilitate the development of not only 21st century skills but also transform the experience of learning to a more constructive and inquiry based one (Blanco-Fernández et al., 2014). There is significant traction in the use of virtual worlds and augmented reality in the development of teaching scenarios for disciplines ranging from astronomy to history and from mathematics to language learning (Mpiladeri et al., 2016;Xefteris et al., 2018;Xefteris et al., 2019; Xu & Ke, 2016). From depictions of historical battles, ancient sites and cities to representations of number lines or the solar system, the teaching paradigm faces a specific shift from the usual static representations to interactive virtual ones. Gamifying the learning experience, inducing affective factors, inquiry based methodologies and role playing capabilities has been shown to enhance immersion, motivation and engagement and transform the learning process enhancing efficacy and helping students to create end retain knowledge (Blanco-Fernández et al., 2014; Cai, Liu, Yang, & Liang, 2019; Huang et al., 2019). But although digitally enhanced experiences in virtual or augmented teaching spaces are being constantly deployed buy schools public installations or museum there are so far few examples of embodied learning in mixed reality settings with tangible interfaces (Savenije & de Bruijn, 2017). For example, in the context of history learning the FingerTrips paradigm was deployed as an augmented 3D tangible model of a historical site in a learning scenario where students could interact and learn historical content through a virtual field trip. In this application the intervention was evaluated by 26 6th grade students who’s answers revealed improved motivation and engagement as well as better immersiveness and creation of new knowledge while being made to feel as active participants in the historical events presented (Palaigeorgiou, Karakostas, et al., 2017). Moving on from tangible interfaces and 3D augmented maps, the inclusion of educational robotics affordances into everyday teaching practices can facilitate educators to implement seamlessly multiple educational approaches to the creation of their teaching sequences: competition based learning (Sklar, Eguchi, & Johnson, 2002), inquiry based learning, problem solving (Alimisis, Frangou, & Papanikolaou, 2009), and discovery learning (Sullivan, Sullivan, & Moriarty, 2009). So far in recent research, educational robotics is used and viewed as a tool mostly related to facilitating the development of 21st century skills such as computational thinking algorithmic thinking and design based thinking (Khanlari, 2016). And albeit truly significant for these aspects, using educational robotics affordances in a slightly different framework can provide teachers with a specific dynamic to enhance and induce multidisciplinary learning capabilities in a STEAM context, while of course retaining the dynamic for the development of computational thinking etc. From the creation of a catapult for the enactment of a historical battle or a water dam in the area they inhabit, to the creation of an orery or a model to ascertain the gravity acceleration coefficient educational robotics offers a rich ground on which to build learning scenarios. There are also examples of integration of robots and drones in teaching scenarios alongside mixed or augmented reality environment and wearables (Palaigeorgiou, Malandrakis, & Tsolopani, 2017). There is thus a rising trend to develop teaching scenarios integrating multimodal and ubiquitous tangible interfaces with technologies such as robotics, in mixed reality settings in order to create authentic and immersive learning experiences under the precepts of experiential learning (Xefteris & Palaigeorgiou, 135

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2019b). Digital worlds provide students especially elementary school students with a fascination rarely found in a regular teaching sequence in an everyday classroom. Through the integration of multiple technologies for inducing ubiquitous human computer interaction with tangible interfaces, through the use of robotics in mixed reality settings, we have the ability to create exciting and immersive learning experiences, although this paradigm is right now for sure somewhat far away from every day classrooms. Mixed reality, virtual reality and augmented reality applications are highly interactive and very attractive to modern children whose everyday routine is saturated with technological advancements. The addition of tangible interactivity in virtual words, in the context of an interactive gamified storytelling experience, manipulating familiar- or less familiar- physical objects can facilitate the merging of multiple technologies and the transformation of different modalities of ICT tools into novel teaching scenarios. This framework enables students to become inherent and integral parts of the mechanisms and operations they are examining, become actors in the story that is unfolding in the learning scenario and have the opportunity to both monitor and evaluate vendor lying relationships of the domain they are studying (Wang et al., 2010).

FRAME OF OPERATION As indicated in the literature review, lack of tangibility is a consistent issue with many aspects of employable ICTs. Educational robots on the other hand, solve the issue of tangibility but are mainly focused on developing computational thinking skills and not -more often than not- used as representations or “tangible agents” to facilitate the physicalization of non-programming or computational thinking related concepts. In this chapter the proposed framework aims at providing a mixed reality background employing educational robotics, Makey-Makey and Scratch, designed on the following axes: 1. Implement and deploy embodied learning concepts through the creation of tangible objects and ubiquitous interfaces. 2. Create a mixed reality background environment to improve immersion and employ gamified scenarios where problem solving skills, scientific thinking and inquiry learning are combined. 3. Employ educational robots as tangible agents, merging the digital with the physical world in seamless interaction with the mixed reality environment. The proposed integration of technologies is designed so that the produced learning environments are easily reproducible, with hardware and materials available publicly and to a great measure easily affordable by schools or university departments. The fundamental hardware for creating the learning interventions include a canvas (dimensions usually at 1.7mx2.0m), a projector (short throw capabilities usually best for our purposes), a laptop with Scratch (installed or web-based), a Makey-Makey board and an EV3 robot, as well as regular sundries for hand crafting extra props, some extra cables, tape etc. The projector is placed perpendicular to the floor, so that it projects downwards, and under it we place the canvas, where a Scratch game is projected, thus creating an “augmented floor”, as seen in Figure 1. The canvas is riddled with Makey-Makey “touch bases” in specific “places of interest”. When the robot reaches each base, the Makey-Makey interface is triggered, sends a key message and the Scratch program responds accordingly.

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Figure 1. The basic framework setup

The canvas “game floor” is rigged with Makey-Makey connected touch-pads which, when pressed, act as buttons that interact with Scratch, to advance the learning scenario. The Scratch game is programmed so that it is partitioned into “questions” that correspond to the learning plan’s activities. So, for example in Activity 1, the robot should reach Base 1. If Base 1 is reached, then Makey-Makey sends the letter “A” which is the correct response to the question posed in activity 1. If any other base, or no base is reached then Scratch prompts the user to try again, re-programming the robot to reach its intended destination, beginning from its original starting place. Thus, the gamified scenario can support multiple activities, each corresponding to a “touch base” on the canvas and each one corresponding to a single, specific trigger key that enables the game to continue The learning scenario is thus built around a series of “missions” that hide knowledge assessment, knowledge acquisition, inquiry-based learning, experimentation and evaluation and depending on the scenario, competition between teams. An EV3 robot acts as the protagonist of the scenario, with students programming it to perform tasks that correspond to the game missions. In this context, students not only perform programming tasks to achieve their goals, but also use the robot as a tangible simulation agent to hypothesize, experiment on and verify or disprove their theories. Depending on the underlying learning topic (or topics) and the design of the game, the deployed intervention implements various combinations of aforementioned tasks. Honing computational thinking skills, algorithmic thinking and facilitating the learner’s contact with programming tasks is usually in the background of the proposed interventions, with other disciplines and learning subjects taking the foreground. In Table 1 a short description of so-far deployed experiments based on the proposed framework can be found, briefly highlighting the aforementioned concept. All interventions tackle elementary education level lessons

EXPERIMENTAL APPLICATION AND RESULTS As seen in Table 1, there have been so far 8 distinct deployments of teaching interventions under the proposed guidelines of the specific framework, with four of them having already been published in conferences and journals and one more publication, describing the course design for the undergraduate

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course that gave birth to these instances (Xefteris, 2019; Xefteris & Palaigeorgiou, 2019a; Xefteris, Palaigeorgiou, & Zoumpourtikoudi, 2019, Xefteris, Palaigeorgiou, & Tsorbari, 2018) Table 1. Deployed interventions using the mixed reality framework #

Learning goals

Published results?

1

• Astronomy – The day/night cycle – seasons

• Yes, experiments on elementary school students conducted, in 8 gaming sessions of two participants

2

• European History/ Geography [Double setup with FingerTrips board]

• Yes, experiments on 23 undergraduate students of Elementary education department

3

• Mathematics - Fractions

• Yes, but only as a teaching scenario approach due to COVID19 measures that prohibited contact

4

• English as a second language – Giving directions vocabulary

• Yes, but only as a teaching scenario approach due to COVID19 measures that prohibited contact

5

• Traffic education

• No, implemented as final assignment

6

• Greece’s music history / Coding notes with colors

• No, implemented as final assignment .

7

• The legend of Theseus / The Minotaur’s maze / Cretan artifacts

• No, implemented as final assignment

8

• Catapults and sieges

• No, implemented as final assignment

The Day/Night Cycle and Seasons This implementation aims at helping elementary school students recall previous knowledge and bring forth and clear misconceptions regarding the day/night cycle and the seasonal change on Earth. The Scratch game is deployed on a background displaying the space between Earth and the Sun. There is also a natural model of the Sun and an EV3 robotic model of the Earth, capable of performing four programmable movements and one “stealth” movement using five motors: Rotation (around itself), circumnavigation (around the Sun), tilting of the axis and the “stealth” movement which keeps the axis stable with respect to the Sun. The specific setup is depicted in Figure 1 and Figure 2. The scenario also makes use of a tangible interface built with Makey-Makey board -instead of touch pads on the canvas-. During the scenario the students in pairs of two are asked to answer questions through the touch interface, hypothesize and test them through programming the earth to rotate around itself and revolve around the Sun to experimentally verify their preconceived notions about the day/night cycle. During the game, a virtual assistant and info-pop ups guide the students on how to perform their experiments or point out clues that can aid them make better ones. In the final and more difficult assignments of the scenario, students test different axial tilts of the Earth and find out that the northern hemisphere -where they liveis actually closer to the Sun during winter, but what makes it colder, is the axial tilt of the Earth not the absolute distance from the Sun. The scenario narrator introduced the basic concepts of the examined phenomena: The Earth’s position relative to the Sun, its movements around itself and on its trajectory around the sun, as well as why we have seasons. Then the learning sequence begins and students have to participate in twelve activities of increasing difficulty. The activities examine every aspect of the day/night cycle, ranging from the direction of the earth’s rotation to complex notions on which they harbor naïve knowledge and misconceptions,

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such as the different time zones and the height of the Sun at noon during seasonal change. The students are called to hypothesize on how much the Earth should turn according to the posed question, and then program the robot-Earth to move as much in order to verify their hypotheses. Thus, the students are facilitated to perform mathematical calculations on abstractions they have difficulty in grasping, such as the representation of the 24 hour cycle with decimals and fractions and link them to absolute hours duration, or fractions of the earth’s rotation (i.e 12 hours = half a day=half a rotation = 0.5 rotations in the programming block). In order to put more weight in the main teaching goals, “myblocks” instances were used to reduce the complexity of the needed programming. Thus, students only had to perform mental calculations and input only the final amount of rotations instead of configuring speed or blocks that would add unnecessary complexity to the operation. Figure 2. The scenario setup with the Earth robot and the model sun

Figure 3. The Earth at the “Summer” position with correct axial tilt. The scenario instructor is visible at the right

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In this experiment the participants were 16 elementary school students of the fifth and sixth grade, with two per session. This intervention was evaluated using pre and post/cognitive tests, an attitude questionnaire examining the students’ perception on usability and the environment’s design, as well as semi-formal interviews. Summarily, there was a significant statistical difference in pre- and post-cognitive tests with questionnaires and interviews consistently showing the students’ vocal preference to the setup and design of the intervention as well as their perception of the scenario’s efficacy. Comprehensive results can be found in the relevant publication (Xefteris, Palaigeorgiou, & Zoumpourtikoudi, (2019).

Teaching European History and Geography In this study the mixed reality framework was deployed in a learning scenario to teach European history, geography as well as basic programming skills, making use of EV3 vehicles. This approach made use of two augmented spaces which were conceptually linked and students swapped between them as the scenario progressed: The game begins with two teams of two students, on a tabletop augmented map built using the FingerTrips approach as seen in Figure 4: Students here “travelled” on the map tracing their fingers over the relief of an embossed geomorphological path. In a treasure hunt scenario, students move from city to city passing over mountain ranges. Figure 4. The FingerTrips augmented space

Each session began on the FingerTrips augmented 3D map, where all participants interact as one team. The first station is Corfu, and students had to travel through 6 of the major European cities, with their fingers tracing routes over the embossed map relief, which was studded with Makey-Makey touch points, along major geographical features such as mountain ranges and along the way find clues that point to the next major station. During these trips the game prompted students with questions answered by all participants via tangible interface.

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As soon as students arrived at a major point on the embossed map, they needed to break down into two teams and compete against each other hunting for possession of the next clue with their robots on the floor based track. There, the robots acted as competing adventurers who searched for hidden clues in historical sites across Europe (Valle dei Tempi in Sicily, the Colosseum and the baths of Caracalla, piazza San Marco in Venice, etc.). in each of these stations the robot adventurers had to follow a projected route and reach their destination first in order to collect their reward. The program tasks where of increasing difficulty, ranging from introductory actions such as simply moving forward and backward to more advanced actions that require the use of distance or color sensors in four separate substages. The robotics track who was equipped with Makey-Makey “touch-bases” detecting if and when each robot reached its destinations, as seen in Figure 5. During each assignment, programming instructions were provided in the form of preprinted hint cards. this intervention integrated a multimodal continuous exchange of activities from traveling through Europe on the fingertips map to traveling on the augmented robotic track with robots, employing a challenge-based learning scheme. The intervention sequence can be seen in Figure 6, and the two augmented floors together in Figure 7.

Figure 5. Example levels of the robotics track

Figure 6. The game sequence

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Figure 7. Combined view of the augmented spaces

This intervention was conducted on 23 undergraduate students of the Elementary Education department and each session comprised two teams of two. The evaluation was conducted with the same methodology as the previous one (pre- and post- cognitive tests, attitude questionnaires and semi-formal interviews). Consistent with the Day/Night cycle experiment, the results showed significant statistical difference in pre- and post- cognitive tests, high perception of efficacy, motivation and engagement, and vocal affirmation of the intervention’s usefulness and practical application (Xefteris, Palaigeorgiou, & Tsorbari, 2018)

Teaching Fractions This implementation along with the next one, was published only as a teaching scenario proposal in a Greek conference without experimental results on actual students, as the CoVid19 pandemic quarantine prohibited all possible contact between researchers and students. Nonetheless, based on previous findings and following the same core precepts, researchers postulate that this also would elicit similar experimental results. In this instance, the augmented space takes the form of a fantasy kingdom, where a princess is abducted. The noble prince mounted on his EV3 horse, must solve a series of puzzles on fractions, calculate results and program the horse to travel on projected number lines to reach the intermediate stations of his hunt where the next clue of the princess’s location is found. This educational scenario is addressed to 6th grade students. Based on the school textbook, it deploys concepts included various chapters: In the 19th chapter: Fractions of the same name and heteronyms “What creature is this… fraction”, in the 20th: The fraction as an exact quotient of division “Who will help me in the division”, in the 21st: Equivalent fractions “I can I say the same in other words! “, and in the 22nd: Comparison-arrangement of fractions” How will we get in order?” “Whatever he does, I will multiply.” It is therefore aimed exclusively at students with this level of knowledge. The narrator and backstory is implemented in Scratch. Students listen to the narrative, which describes the story of Prince Christopher and Queen Emelia. Evil Monica managed to kidnap Queen Emelia and now Christopher with the help of little mathematicians must free her. The students are asked, based on the story, to program the robot by following the orders of the evil Monica, in order to help Prince Christopher reach Emelia. What students have to do is listen carefully to the commands from the narrative and then plan and check if they have executed each command correctly. The robot in this case is used not only as a programming learning tool, but also as a tool for learning and dealing with concepts of fractions (fraction operations, equivalence etc.)

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In the sequence, students are called to calculate how much the robot-prince will move on the number line to reach each intermediate station. So, to calculate how much the robot will have to move, they take into account the actual distance on the track, then do the fractional operation and then find how many turns of the robot wheel correspond to this distance. In the script, the robot is used as a “simulator” and its role is to confirm the calculations that children perform. When students make a mistake and do not reach their goal, or over-calculate and move further, they return to the start line of each station and re-calculate, trying again to fulfil their assignment. Figure 8. The intervention augmented board setup with a projected number line (screenshot from Scratch)

Teaching English as a Second Language: Directions Vocabulary Concurrently with the previous intervention, another one was designed, concerning teaching English as a second language, and more specifically, teaching directions in two dimensional, three-dimensional space and cardinal points. It also included a drone apart from the robot. The scenario here concerns a Robot (an EV3 Riley Rover model)that wants to fly, so the students must program the hero of the story to navigate in the city, until it reaches the Inventor’s Shack, were the inventor turns it into a drone. Students here program the robot initially to perform basic movements, while learning the relevant vocabulary. Then when in drone form, students are called to program the drone to fly up, down, tilt and turn, and land again. Since this intervention also coincided with the CoVid19 pandemic, it was also published as a teaching scenario proposal, without experimental findings. The teaching sequence concerned 5th grade elementary school students and incorporated the section “Unit 3, Places” and more specifically lesson 2, “How can I get to…?”. The narrator asks the students questions (in English), and they answer using a Makey-Makey interface. The path they have chosen is displayed on the floor and if it is the correct one, they are asked to program the robot to execute the commands that they gave through the interface. The game is designed so that the interface selects a sequence

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of commands if needed (e.g. Go straight, Turn left, go straight, turn right, turn around). To simplify the teaching sequence and to focus only on the directions, the track was created with calculated distances and “myblock” was used in the EV3 environment, which contained only the direction expressions. The plan was divided to 10 activities of increasing difficulty. In the first 6, the robot, prompted by the narrator, travels to different destinations in the city. In these activities students get familiar with the vocabulary related to directions (turn, right, left, forward, backwards). In the last 4, the robot arrives in the garage and turns into a drone, so we proceed to learn directions in 3d space, programming through Scratch 2.0 the drone Tello to perform take-off, landing and already programmed maneuvers such as “Flip”. The vocabulary covered here includes expressions related to the flight (fly / up, down, land, take off). Figure 9. The scenario augmented space, with the robot and the drone

The rest of the implemented scenarios were built as final assignments of an undergraduate courses and have been presented in a publication describing the curriculum (Xefteris, 2019).

Traffic Education A scenario where students built an augmented floor with a city, through which the robot must navigate and obey to traffic signs, avoid pedestrians (physical objects-distance sensor), stop at traffic lights (color detection), and park at specific spots (color detection). In thus scenario the augmented space was depicting a city, with various points in it harboring Makey-Makey interfaces that were used as triggers to prompt the sequence of the assignments. Appropriately color coded squares were put on the map, depicting either assigned parking spaces (blue) or traffic lights (green-red). Traffic light changes were implemented with just changing the colored squares, since a changing light source could not be easily integrated on the augmented floor.

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Figure 10. The traffic education assignment

Greece’s Music History: Coding notes with Colors A scenario in which the robot must gather encoded pieces of a melody in the form of printed squares of color, travelling through various locations in Greece, birthplaces of Greek composers. When the final piece of the melody is gathered, the students program the robot to play it, by assigning the 7 recognizable colors by EV3 to each note of the octave. The scenario follows the style of a treasure hunt too. In this one, students are informed that the notes of a well known melody have been hidden in the homes where Greek composers were born. After finding out the city on which each one was born, the robot adventurer must go from city to city and reach the Makey-Makey touch bases. Then, a short clip is played with information about each composer, a famous melody of his as well as a short musical quiz that examines knowledge on music history, or music itself (notes, octaves, scales etc). As soon as students have responded, the next melody note is presented, along with its assigned color, and students are given a printed square with it. As soon as they have collected all notes and their color assignments, they build the musical sequence -which is actually the song “Twinkle little star”, which occupies one octave, so the EV3 detected colors are adequate. Afterwards, by adding the color sensor on their robot, they program it with the colors and the corresponding notes, and “play” the melody with the robot moving over the sequence and playing each note as soon as each color is detected.

The Minotaur’s Maze: Cretan Artifacts A scenario in which Theseus rides a robot through the Labyrinth and with it discovers clues and solves puzzles regarding Minoan Artifacts to follow the fabled String of Ariadne and escape from the Minotaur. The hero is placed at one edge of the Labyrinth and has to pass through various intermediate stations where he has to answer riddles (questions from Greek mythology) and identify artifacts with multiple choice questions. After each riddle or question is answered, a short clip is played on the maze, with the narrator making clarifications and instructing students how to program their robot to reach its next goal.

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Figure 11. The Greek music history assignment (Translation: did you know that Manos Hadjidakis is from Xanthi?)

Figure 12. The Labyrinth assignment

Catapults and Sieges In this scenario, students were called not only to simply program, but to also research and build a “fantasy” trebuchet with line following capabilities, that would travel from Venice to Constantinople and lay siege on the walls of the city. The students engaged in a design phase, with various pre-printed cards given to them, highlighting the construction challenges and various implementations of catapults and siege engines. In this scenario, the main focus was thus the engineering aspect of the construction, as well as tests and experiments on various designs of catapults, taking into consideration the practicality of the design, its effectiveness, its maneuverability, and of course its attacking result. Moreover, students engaged in experiments testing how far the catapult stone would fall, or what were the limits of the catapult’s weight lifting ability-trying different counterweights, or different “projectiles”. The most successful experiment was one using the EV3 smart brick itself as a counterweight, following a complicated but

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effective standard “trebuchet” mode. It was taken into account that this specific scenario could not possibly be used in the context of a history course, especially targeting elementary school students, in order to avoid creating confusion with historical fact. The scenario would be mainly used as a background to evaluate different catapult designs and build a “smart” catapult that would avoid obstacles and detect enemy walls, stop at the right distance and fire. Figure 13. The Catapults and sieges assignment

DISCUSSION The integration of multiple ICT technologies in mixed reality environments to deploy successful teaching interventions apart from opportunities for great results and transformation of learning paradigm, also presents specific caveats: Researchers and educators always face the danger of misusing technology and ending up distracting students with impressive environments but missing out on teaching effectiveness. In the design process of the proposed framework, educators should always keep in mind the learning goals and match the scenario activities to them, avoiding to just mix and match ICT tools in order to motivate their students. In this era, even elementary school students have been brought up in a highly technological environment, some are even skilled users of multiple ICT tools already. Thus, if the content itself fails to address the underlying teaching goals, “simple” immersiveness and engagement are not adequate.

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CONCLUSION In this chapter a proposal for creating multimodal and multidisciplinary teaching interventions using robotics, Makey-Makey and Scratch in mixed reality environments was presented. Based on recent research on the practical use of integrating various ICT’s in STEAM education scenarios, it is postulated that this proposal may indeed provide novel ideas in the creation of learning scenarios and more efficient achievement of teaching goals. The preliminary experimental outcomes of the deployment of teaching interventions built in this frame, have proven that this approach can become a significantly helpful canvas that can aid educators in creating a multitude of different scenarios. The conducted experiments have clearly shown that students both think that tangible interactions, educational robotics and mixed reality can positively affect their performance, with cognitive test metrics corroborating their interview answers. Thus, considering the available evidence so far, such learning interventions can indeed provide a solid background for effectively conveying new knowledge, reassessing old one and facilitating the development of 21st century skills. The combination of robotic tangible agents, Makey-Makey and Scratch in mixed reality scenarios seems to provide an interesting and effective background on which researchers can build novel and multidisciplinary teaching experiments and interventions.

ACKNOWLEDGMENT The authors would like to thank Dr. George Palaigeorgiou, former Assistant professor in the Elementary Education Department of Florina and the director of CrInTe lab, professor Tharrenos Bratitsis in the department of Early Childhood Education of Florina. We would also like to thank the Elementary Education and Early Childhood Education departments of University of Western Macedonia for providing continuous and substantial support to the creation and development of the CrInTe Laboratory.

REFERENCES Abrahamson, D., & Lindgren, R. (2014). Embodiment and embodied design. The Cambridge Handbook of the Learning Sciences, 2, 358–376. Alimisis, D., Frangou, S., & Papanikolaou, K. (2009). A constructivist methodology for teacher training in educational robotics: The TERECoP course in Greece through trainees’ eyes. Proceedings - 2009 9th IEEE International Conference on Advanced Learning Technologies, ICALT 2009, 24–28. 10.1109/ ICALT.2009.86 Alimisis, D., Moro, M., & Menegatti, E. (2017). Educational Robotics in the Makers Era (D. Alimisis, M. Moro, & E. Menegatti, Eds.). doi:10.1007/978-3-319-55553-9 Bers, M. U., Flannery, L., Kazakoff, E. R., & Sullivan, A. (2014). Computational thinking and tinkering : Exploration of an early childhood robotics curriculum. Computers & Education, 72, 145–157. Advance online publication. doi:10.1016/j.compedu.2013.10.020

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Blanco-Fernández, Y., López-Nores, M., Pazos-Arias, J. J., Gil-Solla, A., Ramos-Cabrer, M., & GarcíaDuque, J. (2014). REENACT: A step forward in immersive learning about Human History by augmented reality, role playing and social networking. Expert Systems with Applications, 41(10), 4811–4828. doi:10.1016/j.eswa.2014.02.018 Bonito, T., & Almeida, A. (2016). The Role of ICT to change misconceptions of some astronomy concepts in children of primary school. Electronic Proceedings of the ESERA 2015 Conference. Science Education Research: Engaging Learners for a Sustainable Future, Part/Strand. Retrieved from https://www. researchgate.net/profile/Antonio_Almeida16/publication/301659892_Bonito_T_Almeida_A_2016_ The_Role_of_ICT_to_change_misconceptions_of_some_astronomy_concepts_in_children_of_primary_school_In_O_Finlayson_R_Pinto_Co-editors_Learning_science_Conce Cai, S., Liu, E., Yang, Y., & Liang, J.-C. (2019). Tablet-based AR technology: Impacts on students’ conceptions and approaches to learning mathematics according to their self-efficacy. British Journal of Educational Technology, 50(1), 248–263. doi:10.1111/bjet.12718 Collins, L. (2018). The Impact of Paper Versus Digital Map Technology on Students’ Spatial Thinking Skill Acquisition. The Journal of Geography, 117(4), 137–152. doi:10.1080/00221341.2017.1374990 de la Hera, D. D., Sigman, M., & Calero, C. I. (2018). Social interaction and conceptual change in children: Paving the way away from misconceptions about the Earth. Retrieved from https://osf.io/djsva/download Eguchi, A. (2015). Educational Robotics as a Learning Tool for Promoting Rich Environments for Active Learning (REALs). In Human-Computer Interaction (pp. 740–767). doi:10.4018/978-1-4666-8789-9.ch033 Fleck, S., Hachet, M., & Bastien, J. M. C. (2015). Marker-based augmented reality. Proceedings of the 14th International Conference on Interaction Design and Children - IDC ’15, 21–28. 10.1145/2771839.2771842 Huang, K. T., Ball, C., Francis, J., Ratan, R., Boumis, J., & Fordham, J. (2019). Augmented versus virtual reality in education: An exploratory study examining science knowledge retention when using augmented reality/virtual reality mobile applications. Cyberpsychology, Behavior, and Social Networking, 22(2), 105–110. doi:10.1089/cyber.2018.0150 PMID:30657334 Jaipal-Jamani, K., & Angeli, C. (2017). Effect of Robotics on Elementary Preservice Teachers’ SelfEfficacy, Science Learning, and Computational Thinking. Journal of Science Education and Technology, 26(2), 175–192. doi:10.100710956-016-9663-z Karim, M. E., Lemaignan, S., & Mondada, F. (2015). A review: Can robots reshape K-12 STEM education? 2015 IEEE International Workshop on Advanced Robotics and Its Social Impacts (ARSO), 1–8. 10.1109/ARSO.2015.7428217 Kazanidis, I., Palaigeorgiou, G., & Bazinas, C. (2018). Dynamic interactive number lines for fraction learning in a mixed reality environment. South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference, SEEDA_CECNSM 2018. 10.23919/SEEDACECNSM.2018.8544927 Khanlari, A. (2016). Teachers’ perceptions of the benefits and the challenges of integrating educational robots into primary/elementary curricula. European Journal of Engineering Education, 41(3), 320–330. doi:10.1080/03043797.2015.1056106

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Li, N., Willett, W., Sharlin, E., & Sousa, M. C. (2017). Visibility perception and dynamic viewsheds for topographic maps and models. ACM Reference, 9, 39–47. doi:10.1145/3131277.3132178 Lindgren, R., Tscholl, M., Wang, S., & Johnson, E. (2016). Enhancing learning and engagement through embodied interaction within a mixed reality simulation. Computers & Education, 95, 174–187. doi:10.1016/j.compedu.2016.01.001 Mpiladeri, M., Palaigeorgiou, G., & Lemonidis, C. (2016). Fractangi: A Tangible Learning Environment for Learning about Fractions with an Interactive Number Line. International Association for the Development of the Information Society. Nemiro, J., Larriva, C., & Jawaharlal, M. (2017). Developing Creative Behavior in Elementary School Students with Robotics. The Journal of Creative Behavior, 51(1), 70–90. doi:10.1002/jocb.87 Palaigeorgiou, G., Karakostas, A., & Skenderidou, K. (2017). FingerTrips: Learning Geography through Tangible Finger Trips into 3D Augmented Maps. Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017, 170–172. 10.1109/ICALT.2017.118 Palaigeorgiou, G., Malandrakis, G., & Tsolopani, C. (2017). Learning with Drones: Flying Windows for Classroom Virtual Field Trips. Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017, 338–342. 10.1109/ICALT.2017.116 Savenije, G. M., & de Bruijn, P. (2017). Historical empathy in a museum: uniting contextualisation and emotional engagement. doi:10.1080/13527258.2017.1339108 Sklar, E., Eguchi, A., & Johnson, J. (2002). RoboCupJunior: Learning with Educational Robotics. Lecture Notes in Artificial Intelligence, 2752, 238–253. doi:10.1007/978-3-540-45135-8_18 Sullivan, F. R., Sullivan, F. R., & Moriarty, M. A. (2009). Robotics and Discovery Learning: Pedagogical Beliefs, Teacher Practice, and.... Journal of Technology and Teacher Education, 17(1), 109–142. Sun, K.-T., Lin, C.-L., & Wang, S.-M. (2010). A 3D virtual reality model of the sun and the moon for e-learning at elementary schools. International Journal of Science and Mathematics Education, 8(4), 689–710. doi:10.100710763-009-9181-z Wang, C.-Y., Chen, G.-D., Chen, C.-H., Wu, C.-J., Chi, Y.-L., & Lee, J.-H. (2010). Constructing a Digital Authentic Learning Playground by a Mixed Reality Platform and a Robot. Retrieved from https://www. researchgate.net/publication/228991052 Xefteris, S. (2019). Developing STEAM Educational Scenarios in Pedagogical Studies using Robotics: An Undergraduate Course for Elementary School Teachers. Engineering, Technology & Applied Science Research. Xefteris, S., Palaigeorgiou, G., & Zoumpourtikoudi, E. (2019). Educational Robotics For Creating Tangible Simulations: A Mixed Reality Space For Learning The Day/night Cycle. In Interactive Mobile Communication, Technologies and Learning. Springer. Xefteris, S., & Palaigeorgiou, G. (2019a). Mixing Educational Robotics, Tangibles and Mixed Reality Environments for the Interdisciplinary Learning of Geography and History. International Journal of Engineering Pedagogy, 9(2), 82–98. doi:10.3991/ijep.v9i2.9950

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Xefteris, S., & Palaigeorgiou, G. (2019b). Mixing Educational Robotics, Tangibles and Mixed Reality Environments for the Interdisciplinary Learning of Geography and History. International Journal of Engineering Pedagogy, 9(2), 82. doi:10.3991/ijep.v9i2.9950 Xefteris, S., Palaigeorgiou, G., & Tsorbari, A. (2018). A learning environment for geography and history using mixed reality, tangible interfaces and educational robotics. International Conference on Interactive Collaborative Learning, 106–117. Retrieved from https://www.researchgate.net/profile/George_Palaigeorgiou/publication/328417221_A_learning_environment_for_geography_and_history_using_mixed_ reality_tangible_interfaces_and_educational_robotics/links/5bcd10e8299bf17a1c661739/A-learningenvironment-for-geo Xu, X., & Ke, F. (2016). Designing a Virtual-Reality-Based, Gamelike Math Learning Environment. American Journal of Distance Education, 30(1), 27–38. doi:10.1080/08923647.2016.1119621

ADDITIONAL READING Alimisis, D. (2013). Educational robotics: Open questions and new challenges. Themes in Science and Technology Education, 6(1), 63–71. Garcia-Ruiz, M. A., Santana-Mancilla, P. C., & Gaytan-Lugo, L. S. (2018). Integrating microcontrollerbased projects in a human-computer interaction course. Int. J. Comput. Inf. Eng, 12(10), 946–950. Hsu, Y. C., Ching, Y. H., & Baldwin, S. (2018). Physical computing for STEAM education: MakerEducators’ experiences in an online graduate course. Journal of Computers in Mathematics and Science Teaching, 37(1), 53–67. Keengwe, J., & Tran, Y. (2020). Handbook of research on equity in computer science in P-16 education. IGI Global. Mikropoulos, T. A., & Bellou, I. (2013). Educational robotics as mindtools. Themes in Science and Technology Education, 6(1), 5–14. Papadakis, S., & Kalogiannakis, M. (2020). Handbook of Research on Using Educational Robotics to Facilitate Student Learning. IGI Global. Yamamori, K. (2019). Classroom practices of low-cost STEM education using scratch. Journal of Advanced Research in Social Sciences and Humanities, 4(6), 192–198.

KEY TERMS AND DEFINITIONS Computational Thinking (CT): A set of problem-solving methods that involve expressing problems and their solutions in ways that a computer could also execute. It involves automation of processes, but also using computing to explore, analyze, and understand processes (natural and artificial). Educational Robotics: A discipline designed to introduce students to Robotics and Programming interactively from a very early age.

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Embodied Learning: An educational method that has been around for a while in (primary) education. In this method, one does not only offer an intellectual way of teaching, but also involve the whole body. One can think of doing mathematics while throwing small bags of sand to each other. ICT: Information and communications technology (or technologies), is the infrastructure and components that enable modern computing. Makey-Makey: MaKey MaKey lets you transform everyday objects into computer interfaces. Make a game pad out of Play-Doh, a musical instrument out of bananas, or any other invention you can imagine. It’s a little USB device you plug into your computer, and you use it to make your own switches that act like keys on the keyboard. Mixed Reality: A blend of physical and digital worlds, unlocking natural and intuitive 3D human, computer, and environmental interactions. Scratch: Scratch is the world’s largest coding community for children and a coding language with a simple visual interface that allows young people to create digital stories, games, and animations. STEAM Education: An approach to learning that uses Science, Technology, Engineering, the Arts and Mathematics as access points for guiding student inquiry, dialogue, and critical thinking.

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Chapter 8

Preparing Teachers for the 21st Century:

A Mixed-Methods Evaluation of TPD Programs Under the Lens of Emerging Technologies in STE(A)M Education Stavros Pitsikalis https://orcid.org/0000-0002-3051-2555 University of the Aegean, Greece Ilona-Elefteryja Lasica https://orcid.org/0000-0001-6842-9901 University of the Aegean, Greece

Apostolos Kostas https://orcid.org/0000-0002-1567-2649 University of the Aegean, Greece Chryssi Vitsilaki University of the Aegean, Greece

ABSTRACT This chapter provides an overview of (1) the current situation concerning teacher professional development (TPD) programs through studies referring to existing challenges; (2) the TPD programs under discussion that have been implemented during the last three years (2018-2021) in the context of European projects, including their structure and descriptions of the educational content; (3) teachers’ views and feedback concerning the TPD program they attended, based on a specific evaluation framework, with focus on issues relevant to emerging technologies. The researchers provide directions towards an effective framework for horizontal TPD programs targeting large numbers of teachers, aiming to allow them to gain the appropriate knowledge and skills in order to integrate emerging technologies as concepts in interdisciplinary STE(A)M-based instructional scenarios, especially in the levels of Secondary general (Gymnasium and Lyceum in Greece) and (post)secondary vocational education (EPAL and IEK in Greece).

DOI: 10.4018/978-1-6684-3861-9.ch008

Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

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INTRODUCTION This chapter aims to provide practicing educators, teacher trainers and researchers in the field of educational science with directions for designing TPD programs for integrating emerging technologies, such as Augmented Reality (AR), in interdisciplinary STE(A)M based instructional scenarios, especially in the level of Secondary general (Gymnasium and Lyceum in Greece) and (Post)Secondary Vocational Education (EPAL - Vocational Lyceum) and IEK (Institution of Vocational Training in Greece). The suggested directions arise as a result of the evaluation process of specific components of TPD programs, where the authors have been involved in the evaluation process. The chapter begins with an overview of the current situation concerning the trends for transformation and evolution of teaching practices through innovative pedagogical approaches and emerging technologies (Adnan & Tondeur, 2018; Darling-Hammond, 2017; Ramírez-Montoya, Andrade-Vargas, Rivera-Rogel, D & Portuguez-Castro, 2021; Tarling & Ng’ambi, 2016). Changing teaching practices is proving difficult to achieve, while it seems that many teachers (at least at European level) remain unprepared to effectively employ technology-enhanced teaching practices. This is a fact that has been highlighted in many studies (Cochran-Smith & Maria Villegas, 2015; Dotong, De Castro, Dolot & Prenda, 2016; Kaufman, 2014) and has recently emerged, during the global situation of the pandemic COVID-19 (Whalen, 2020; Winter, Costello, O’Brien & Hickey, 2021), where critical issues have raised concerning the need for ready-to-instruct teachers in the 21st century. Teachers attend numerous training programs on a variety of topics, including STE(A)M education, ICT in education, interdisciplinarity in education, 21st century skills etc. As a result, they gain fragmented knowledge having difficulties in connecting it and bringing it to practice (Santos, Franco, Leon, Ovigli & Donizete Colombo Jr, 2017). The main question that still needs to be answered is whether nowadays teachers are appropriately prepared to support their students to strengthen their 21st century skills and become human resources responding to the demands of the modern labor market. Teachers face challenges in deploying smart learning environments, since the development pace of information and communication technologies (ICT) and devices that could be applied in education, far exceeds the development pace of educational studies concerning the effectiveness of each technological innovation integration within the educational process (Lasica, Meletiou-Mavrotheris & Katzis, 2020a). Emerging technologies as well as any innovative tool introduced into the educational process, should be treated as a concept, taking into consideration numerous factors, rather than a sole technological tool offering new teaching and learning opportunities (Vitsilaki & Pitsikalis, 2017). It is critical not only for teachers, but also for those involved in the educational process (researchers, designers and developers of educational content, decision makers in education, school administrative staff etc.) to have opportunities for adequate training. Taking the above mentioned into consideration, existing TPD programs have been evaluated, in which authors of the current chapter were involved during the design, development, implementation and/or evaluation phases, including: (a) “train the trainer” programs, targeted to teacher trainers in the context of the National Project “Training of teachers/trainers in Apprenticeship topics” (Pitsikalis, Lasica & Roussos, 2020) in Greece, (b) a TPD in the context of a European project (i.e. Enlivened Laboratories within STEM Education – EL-STEM), targeted to Secondary Education teachers from Greece, Cyprus and Estonia (Mavrotheris, Lasica, Pitsikalis & Meletiou-Mavrotheris, 2018). It is important to declare that the current research is part of the wider studies, implemented in the context of the relevant projects, including internal and external evaluations, as well as qualitative and quantitative data. The current chapter focuses on the book’s main topics towards practical approaches to integrating ICTs in 154

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STEAM education and the authors’ perspectives through their experience and involvement in the TPD programs. The TPD evaluation process is based on Guskey’s (2002a) and the Merchie, Tuytens, Devos and Vanderlinde (2018) evaluation frameworks, applied through the different data collection methods. The TPD programs under investigation, focused on applying emerging technologies in education and supporting the educational process through blended approaches. More specifically, the TPD programs in Greece were open to teacher trainers, that were expected to train teachers in the context of the National Project “Training of teachers/trainers in Apprenticeship topics”, i.e. Secondary general and (Post)Secondary Vocational Education and Training, aiming to support the integration of Augmented Reality, as well as other collaboration tools (i.e. MS Teams), suggested by the Ministry of Education and Religious Affairs during the pandemic COVID-19. The EU project’s TPD program focused on the technology of Augmented Reality for Secondary Education teachers with students of specific age groups (12-15). All TPD programs were provided both synchronously and asynchronously, allowing the attending teachers to study the available educational material on their own pace and at the same time, promoting immediate communication with the instructors and other participants through face-to-face or online meetings. The educational material was structured in relevant units, including theoretical content, practical content (tutorials and workshop activities), suggested additional content, as well as collaboration activities, where teachers were encouraged to discuss their experience and share their work with others, creating a digital community and exchanging best practices between them. The TPD programs treated the suggested technologies as concepts rather than individual tools, taking into consideration other aspects and correlations, such as the Content Knowledge (CK), Pedagogical Knowledge (PK), and Technological Knowledge (TK) (TPACK) (Chai, Koh & Tsai, 2010). In addition, the successful completion of the TPD programs under discussion was accompanied with the submission of an educational scenario, in which the teachers were asked to integrate the emerging technologies into interdisciplinary scenarios. The chapter contributes to the existing work by applying a suggested Extended Teachers’ Professional Development evaluative framework (Merchie et al, 2018), specifically for programs towards integrating emerging technologies into the educational process. Through this evaluation, directions for high quality TPD programs derive, which could be taken into consideration during the design of a similar program.

BACKGROUND Considering issues like “what it entails to teach in the 21st-century?” in the context of embracing Fourth Industrial Revolution (4IR) by education professionals, there is a need to understand that teacher profession is evolving towards new innovative and responsive teaching methods, capable of preparing students for the 4IR as well (Naidoo, 2021). 4IR is explained as the assimilation of the physical and virtual world, where Internet of Things (IoT), robotics, artificial intelligence (AI) and mixed reality (XR) are rapidly evolving and transforming societies. And it is evident, that the 4IR involves advanced proficiencies for people and machines and signifies new means in which technology becomes entrenched within society (Schwab, 2016). To succeed within the 4IR embracement, educational sector ought to adapt (Naidoo, 2021); students would need to be exposed to and be stimulated to learn through technology-enabled pedagogy and tools, and teachers would also need to be proficient in using technology-enabled pedagogy and tools, as well. To prepare the required capacity for this upcoming pedagogical and digital transformation, educational settings ought to adapt quickly since the demand for remote and virtual pedagogy globally is increasing 155

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and progressing and teachers are required to possess critical skills to achieve success within the 21stcentury educational environment. These skills include critical thinking, communication, collaboration, problem-solving and creativity (Fadel, 2008). Moreover, this transformation ought to consider that including technology-based tools within the educational environment is not adequate to supplement a transformed pedagogy, but instead, the educational environment needs to be flexible to inform best practices, and tangible learning spaces need to be restructured to support interactive educational environments (Boothe & Clark, 2014). Catering and supporting interactive educational environments also require curriculum reforms and curriculum material ought to link content knowledge to real-world applications and problems that enable students to perceive how their learning relates to real world and what it is relevant and realistic for them (Beers, 2011). Education needs to integrate content for various subjects and disciplines as well as skills for the 21st century including critical thinking, creativity, collaboration, communication, information literacy, media literacy, technology literacy and flexibility (Beers, 2011; Fadel, 2008). Thus, curriculum revision needs to include content material that links crucial knowledge and skills for the 21st century to relevant real-world problems and applications, so that students may envision the importance and relevance of what they are learning with aspects of their lives and the real world (Beers, 2011). But, to use revised curriculums effectively in the 21st-century educational contexts, teacher development needs to be encouraged. The 21st-century teacher needs to be competent with using innovative technologies, since this is an integral part of successful teaching and learning (Jan, 2017), because technology can enhance student’s achievement if used suitably (Sarkar, 2012). Thus, teacher development is essential to ensure that teachers are aware of curriculum revisions and emerging technologies, capable of supporting teaching and learning in the 21st century. The role of the teacher as a guide or facilitator is vital within these new educational arrangements like flipped or blended classrooms, a combination of the traditional teaching approach with the integration of technology-based tools and resources within the classroom environment (Jan, 2017). Teachers need to guide students’ “learning by-doing” and sustain a supportive and safe classroom environment that encourages collaboration and supports problem-based learning (Murphy, 2010). The notion of problembased learning is vital to incorporate within 21st-century teaching and learning as this is an essential approach for developing independent thinking among students. Thus, teachers need to make teaching relevant and authentic by promoting thinking skills, encouraging communication and collaboration, tackling misconceptions, and making efficient and purposeful use of technology (Tican & Deniz, 2018). Conclusively, teachers ought to be comfortable with the use of technology-enabled pedagogy within their educational environments, and they need to be proficient at using 21st-century skills and knowledge within their teaching. The 21st-century teacher needs to be adept at conveying critical skills and knowledge to their students to better prepare them for work and life in the future. Teaching in the 21st-century while acknowledging the notions of the Fourth Industrial Revolution brings about exciting opportunities and experiences. Teachers need to partake in professional development initiatives (formal and informal) that demonstrate how technology may be integrated into authentic educational environments and cultivate their own personal learning environments (PLEs) via peer networking, to share 21st-century pedagogic strategies with other colleagues and expand their personal technology skills and practices (Kaufman, 2013).

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Teachers’ Professional Development Initiatives Any successful TPD program, besides a grounded training needs analysis, presupposes a clear understanding of what is “teacher professionalism” and its contextual characteristics, considering postmodernism, 21st Century skills initiative and digital transformation of education. Profession as a concept reflects key features both at professional and personal level and entails the key concepts “professionalism” and “professionalization”. Professionalism reflects teacher’s professional identity, competence, and capacity to operate in terms of quality and sense of duty, while professionalization states teachers’ profession upgrade in terms of self and social perception (Hargreaves, 2000). According to Hargreaves (2000), teachers’ professionalism is now traversing the fourth evolution phase (postmodernism 2000-today), characterized by digitization, convergence, and globalization. The differences that have occurred in the organization of social subsystems, and therefore of the educational subsystem, are currently forming a new dialogue around teacher professionalism, which is subject both to timeless changes (society, economy, institutions) and contemporary factors, such as the use of digital technologies in education, the need for teachers to develop digital skills, to expand school community beyond its narrow boundaries and cultivate one’s individual, social and scientific background (Whitehouse, McClosky & Ketelhut, 2010). Now, being a teacher is more than just “teaching in the classroom”, as they own a collective responsibility, work with parents and the local community, evaluate, and adapt their teaching practice by analyzing the learning needs of their students and actively participates in Lifelong Learning. However, at the same time, the transition from “old” to “new” professionalism obliges in-service teachers to conform to the needs for continuous professional development, a concept which is ambiguously defined reflecting upon the various attempts for its conceptual delimitation (Helleve, 2010). According to Darling-Hammond (2017) TPD is a continuous developmental process of strengthening the teacher’s professional status through cultivation of the awareness and cognitive background. Kelly (2006) approaches TPD (a) through the lens of “learning as a cognitive process” implying that training is the appropriate method for professional development and (b) through the lens of “situated learning”, where teacher’s development is strengthened through reflective, collaborative, and inclusive activities. Bell & Gilbert (1994) prefer the term “learning” arguing that the term “development” reflects a passive process, when in fact it is an ongoing process, on a personal, professional, and social level. Schlager & Fusco (2003) refer to TPD as the process of learning how to relate knowledge to practice through active involvement in the practice itself within peer-to-peer communities. Helleve (2010) states that professional development is a continuous reflective learning process where teachers and educators are involved in learning how to adapt their teaching to the learning needs of their students. Professional development, as a complex process, depends on various factors, such as teacher’s decision-making ability, perception of its professional identity, self-perception, work environment and cultivation of a self-learning culture. These factors potentially influence teachers’ attitudes towards self-improvement. Thus, it has been observed that while initially the participation of teachers in TPD activities is based on in-service formal obligations, or some type of accreditation/certification, finally it is guided by internal motivations as a means of self-improvement, professional satisfaction, knowledge acquisition, status, hierarchical development (Beijaard, Verloop & Vermunt, 2000; Guskey, 2002b). Finally, successful TPD needs to be continuous and reflective, problem-solving oriented, provide opportunities for collaboration, bring together innovation, technology and teaching practice and promotes creation and sharing of learning resources (Ifanti & Fotopoulou, 2013). 157

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Teachers’ professional development programs could entail numerous activities, such as workshops, seminars, trainings, thus, there are many approaches in the literature, towards this direction (Goodson, 2002; Hendriks, Luyten, Sleegers & Steen, 2011; Kulshrestha & Pandey, 2013; Ur, 1997; Vermunt, 2014) depending on the training’s characteristics including: • • • • • • •

teachers’ status (e.g. pre-service, in-service), motivation (e.g. imposed from the Ministry of education, initiated by the teacher), expected results (e.g. aiming to strengthen teachers’ cognitive background in a specific field, aiming to enhance specific skills), program structure (e.g. pre-determined structure, structure determined through the training process), program syllabus (e.g. externally determined by experts, teachers in collaboration with their trainers co-shape the syllabus), evaluation (e.g. self-evaluation, strict evaluation process, in case the training leads to an accreditation and/or certificate), formality (e.g. formal training provided by the Ministry of Education and/or other authorities, informal training provided by any training provider).

In the context of this chapter, the authors refer to Teachers’ Professional Development programs, provided in Greece, in the context of specific projects, targeting in-service teachers (without excluding pre-service) self-motivated to attend, aiming to enhance specific skills, with ta pre-determined structure, where the teachers could intervene in the syllabus in collaboration with their trainers, without a strict evaluation process, but providing teachers with feedback concerning the educational scenarios developed at the end of the programs.

Teachers’ Professional Development Evaluation Frameworks The research literature identifies a number of frameworks for evaluating TPD initiatives, as it is of additional value to gain a deeper understanding of the results of such programs and guide reform efforts, towards increasing effectiveness and attractiveness for the teachers addressed (Guskey, 2000). These frameworks, usually have some common axes, since most of them focus on particular factors before, during and after the completion of a TPD program, sometimes also taking into consideration other factors (contextual factors, personal characteristics etc.) that could affect the effectiveness of a program (Merchie et al, 2018). One of the most cited frameworks is Guskey’s Five Levels of Professional Development evaluation (Guskey, 2000; Guskey, 2002a). These evaluation levels are hierarchically arranged and the process of gathering data gets more complex from one level to another (Guskey, 2002a), thus, multiple data collection tools should probably be applied to enhance levels of validity and reliability. Moreover, each level suggests questions that could be addressed in the context described. Level one refers to teachers’ reactions concerning the TPD program. Questions of this level should address teachers’ satisfaction with the training experience in total, including questions about the instructors, the learning sessions, the training material, even details concerning the training location, such as coffee breaks. Level two should include questions concerning teachers’ learning, thus, the knowledge, skills and attitudes gained during the TPD program. At level 3, the focus shifts from the teachers to the organization, the provider of the 158

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training. Questions should refer to organizational issues, time plan, policy etc. Level four consists of a critical level, as it returns the focus to teachers and their intention to apply/ use the new knowledge and skills in their real classrooms, laboratories etc. It has been highlighted in the literature (Vermunt, 2014) that although teachers attend TPD programs, they tend to strengthen their theoretical backgrounds but hesitate to apply new knowledge in the educational process. Thus, evaluating the future application in the educational process, as well as the challenges towards this direction, could be of additional value for the topics of a TPD program. Finally, level five refers to students and changes on the learning outcomes and/or their behavior (e.g. interest towards the educational process, motivation to attend), when actually a teacher applies the new knowledge and skills gained during a TPD program, in a real classroom. A more recent TPD evaluation framework has been suggested by Desimone (2009) and illustrates interactive relationships between four main dimensions, affected by contextual factors (curriculum, educational policy, school administration, socioeconomic factors, school autonomy etc.) and teachers’ personal characteristics (gender, age, educational level, technological background, previous experience, personal motivation etc.). These dimensions include: (a) features of professional development, such as content, structure, duration, even provider of the training program and trainers’ quality, (b) increase of teacher quality (knowledge, skills and changes in attitudes/beliefs), (c) change in teaching behavior (instructional strategies, practices, as well as behavior among teachers and behavior towards students) and (d) improvement of students’ results (knowledge, skills and changes in attitudes/beliefs). Parallels have been drawn between Guskey’s (2000) and Desimone’s (2009) models, thus, an extended model has been suggested by Merchie et al. (2018), which unites views on important components in TPD evaluation and evaluation models and methods of professional development. The extended evaluative framework is illustrated in Figure 1 (Merchie et al., 2018), including detailed descriptions and sub-categories for each component of the initial framework by Desimone (2009). In the context of this chapter, the authors applied the Merchie et al. (2018) extended evaluative framework, as the main pathway to guide the evaluation process and enhance the presentation of the relevant results, focusing on issues relevant to the integration of emerging technologies into the educational process.

Pedagogical Frameworks in TPD Programs Different pedagogical frameworks for TPD programs focused on technology integration have been proposed in the literature (Desimone, 2009; Lawless & Pellegrino, 2007). One such framework is TPACK, suggested by Mishra and Koehler (2006), which has been extended by Phillips (2013). TPACK consists of a deep understanding that emerges from the interactions among Technology, Content and Pedagogy Knowledge, as well as all possible individual correlations between all aspects, such as the Content Knowledge (CK), Pedagogical Knowledge (PK), Technological Knowledge (TK) and Content Pedagogical Knowledge (CPK). Phillips (2013) also focused on the contexts in which the TPACK framework is implemented, including sociocultural influences on pedagogical technology practices and on identity transformations, adding the key role of the place where the TPACK framework is implemented. Similarly to Merchie et al. (2018) in their evaluation framework, Phillips (2013) in his pedagogical framework, highlights the importance of the context. In this chapter, the authors refer to the Phillips (2013) extended pedagogical framework, applied as the main pathway to guide the design and implementation process of the TPD programs’ structure under discussion, focusing on issues relevant to the integration of emerging technologies into the educational process. This approach allows description of

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specific directions for designing TPD programs, especially when focusing on the expected impact on teachers’ knowledge. Figure 1. Extended teachers’ professional development evaluative framework (based on Desimone 2009; Guskey, 2000) Source: Merchie, Tuytens, Devos & Vanderlinde, (2018)

Teachers’ Professional Development Programs’ Description The following sections provide detailed descriptions of the TPD programs implemented in the context of this research and the evaluation applied, through the data collection and analysis processes, based on the background already described above.

“Train the Trainer” Programs Targeted to Teacher Trainers in the Context of the National Project “Training of Teachers/Trainers in Apprenticeship Topics” in Greece The TPD programs under investigation, focused on the “train the trainers” (multipliers), specifically those trainers that were going to take over topics in their fields in the context of the National Project “Training of teachers/trainers in Apprenticeship topics” (Pitsikalis et al., 2020) in Greece, and train other teachers/trainers on apprenticeship issues, aiming to support the “Apprenticeship Year” and lead to its smooth implementation, responding to the needs of the modern labor market.

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The educational content for the TPD program has been developed by experts in the relevant fields (Table 1), following the specifications prepared by the project’s scientific team at the Institute of Educational Policy for face-to-face (Mavrikakis, Sirigos & Farantou, 2018a) and online educational content (Mavrikakis, Sirigos & Farantou, 2018b). Trainers were provided with the official educational content for each module; thus, the main aim of their training was to enhance them with the necessary knowledge and skills on how to teach the specific content in their field through a blended approach and of course, how to integrate innovative technologies in VET and Apprenticeship. Focusing on the integration of emerging technologies, the main objective of this TPD program was to encourage the trainers and prepare fertile ground to apply emerging technologies - such as digital realities (Virtual, Augmented, Mixed Reality), Internet of Things, Artificial Intelligence, etc., putting emphasis on Augmented Reality - in their classrooms and/or laboratories. Through this program, participants got familiarized not only with concepts of the emerging technologies as individual tools (Vitsilaki & Pitsikalis, 2017), but also, integrated in the context of innovative teaching and training approaches (e.g. inquiry-based learning, game-based learning, project-based learning), 21st century skills necessary to support nowadays demanding labor market and interdisciplinarity, as an authentic approach to deal with real-life situations and professional challenges. As far as the Augmented Reality software/ tools are concerned, trainers got familiarized with HaloAR, Doodle Lens, Metaverse, CoSpace, ARloopa, ZapWorks, BlippAR and Unity/ Vufora, among others that they chose to investigate on their own. Module 9 initially included only Big Blue Button (BBB) as a tool for synchronous training, but since the pandemic of COVID-19 (February 2020), the circumstances changed radically, and the Hellenic Ministry of Education and Religious Affairs, included among others, the MS Teams platform, as a strong suggestion for synchronous online meetings. Table 1 summarizes the modules of the “train the trainers” programs. Modules M1-M7 addressed trainers depending on their field and the topic they were expected to teach (e.g. the apprenticeship framework, the relevant curriculums, principles of adults’ education, innovation in teaching and training and safety issues), while modules M8-M10 addressed all participants.

Table 1. TPD topics Module

Description

M1

Institutional framework for Apprenticeships

M2

Apprenticeships Curriculums

M3

Health and safety at work

M4

Basic Principles of Adult Education/ Innovative Teaching Approaches in Vocational Education and Training

M5

Counselling and Career Guidance and Information

M6

Entrepreneurship

M7

Best Practices – Preparing Didactical Scenarios

M8

Using Moodle for asynchronous training

M9

Using BigBlueButton - MS Teams for synchronous training

M10

Applying emerging technologies in VET and Apprenticeship, with emphasis on Augmented Reality

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The specific “train the trainers” programs’ duration was thirty (30) hours, three for each module. However, since there was a high interest on specific topics, including emerging technologies (M10), trainers were encouraged to attend wider programs (220 hours), deepening on the module’s topics and concepts. A blended approach has been designed and adopted (at least as an initial approach, before COVID-19 affected the training circumstances). Face-to-face training workshops encouraged communication, allowed the development of a personal connection with the participants and practical familiarization with Augmented Reality technology, supported by mobile devices. Online modules offered trainers time flexibility and ease of access to additional educational content (articles, videos, tutorials etc.). Since the TPD program targeted teachers and trainers in a national level, the online modules enhanced attendance from different regions, overcoming location difficulties, such as islands, isolated areas etc., as well as restrictions that emerged due to COVID-19 protection measures. The specific “train the trainer” program has been repeated four (4) times between 2018-2021, equally to the number of implementation cycles of the National Project “Training of teachers/trainers in Apprenticeship topics”. More than two hundred trainers were trained as multiplies, training in their turn more than three thousand teachers/ trainers of VET. The first two times, as already mentioned, were based on a blended approach. However, the last two implementations, took place during 2020 and 2021, when restrictions due to COVID-19 arose (Viner et al., 2020). Thus, both the “train the trainer” and the National Project programs, took place exclusively online.

The EL-STEM TPD Program The EL-STEM project, targeted students of secondary general education, aiming to (Mavrotheris et al., 2018): (a) attract those who might not be interested in STEM related studies/careers and enhance the interest of those who have already chosen this field of studies/careers, and (b) improve performance in courses related to STEM education. The TPD program, designed and developed in the context of this project, aimed to motivate Secondary general Education teachers (Gymnasium and Lyceum in Greece and Cyprus) of STEM-related courses on effectively integrating AR with core STEM curricular ideas to transform their classrooms and/or laboratories into a smart-learning environment both by (a) using existing AR Learning Objects (LOs) and (b) creating their own AR LOs and Lesson Plans (LPs) with appropriate tools (Lasica, Meletiou-Mavrotheris, Katzis, Dimopoulos & Mavrotheris, 2018). The theoretical approach of the TPD program as well as the educational content have been developed by the project consortium’s experts in the relevant fields (Table 2), following the TPACK framework (Lasica et al., 2018), under the concepts of Problem-Based Learning and Inquiry-Based and Contemporary Learning Approach, promoting scaffolding and collaboration in STE(A)M education (Pedaste et al., 2015). Focusing on the integration of emerging technologies, the main objective of this TPD program was to encourage teachers and prepare fertile ground to apply emerging technologies in their classrooms and/or laboratories, with specific emphasis on Augmented Reality. Through this program, teachers got trained on how to implement inquiry-based learning LPs supported by AR in their STEM-related courses and got familiarized with different software/ tools for developing AR LOs, such as HP Reveal, ARTutor, ZapWorks, EON Experience, Scratch and Unity (Lasica, Meletiou-Mavrotheris & Katzis, 2020b). Table 2 summarizes the modules of the EL-STEM TPD program. A blended approach has been designed and adopted of a total duration of thirty (30) hours, including fifteen (15) hours of workshops and about fifteen (15) hours for the online training, depending on each teacher’s pace and degree of depth into each topic. Face-to-face training workshops provided ample op162

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portunities for interactive and collaborative training through the use of Augmented Reality and related equipment, encouraged authentic collaborative educational activities and allowed the development of a personal connection between the trainers and the participant teachers (Lasica et al., 2020b). Online modules offered trainers time flexibility and ease of access to additional educational content (articles, videos, tutorials etc.), allowing participating teachers to share content, ideas, and instructional strategies and deepen their knowledge. Table 2. EL-STEM TPD topics Module

Description

M1

Introduction to the EL-STEM project

M2

Enlivened Laboratory Methodological Guidelines (ELMG) (Part 1 - Who, Where, Why)

M3

Enlivened Laboratory Methodological Guidelines (Part 2 - What)

M4

Enlivened Laboratory Methodological Guidelines (Part 3 - How)

M5

Using the EL-STEM Platform

M6

Evaluating the Augmented Reality STEM Teacher

M7

Getting Ready for the Pilot AR/MR STEM Laboratories! (guided-field practice)

The face-to-face trainings with teachers have been repeated many times in the consortium countries (Greece, Cyprus, Estonia, Finland, Portugal), while in Greece they took place twice, during 2019 and 2020 (just before COVID-19 pandemic affected schools’ operation). More than fifty teachers have been trained in the context of the EL-STEM TPD program, acting as multipliers in their schools and engaging even more teachers in the technology of Augmented Reality.

METHODOLOGY The current chapter focuses on the book’s main topics towards practical approaches to integrating ICTs in STEAM education and the authors’ perspectives through their experience and involvement in the TPD programs. The TPD evaluation process is based on Guskey’s (2002a – Table 3) and the Merchie, Tuytens, Devos and Vanderlinde (2018 – Figure 1) evaluation frameworks, applied through the different data collection methods. The researchers of this study focus on qualitative research, as they have observed part of the TPD programs and collected data from interviews with the teachers, open-ended questions of the TPD programs’ evaluation questionnaires and open-ended discussions (face-to-face and forum discussions), between the teachers and the researchers. Quantitative data have also been collected; however, they are not discussed in the context of this chapter (e.g. as descriptive statistics), due to extent restrictions. It is important to mention that the current research is part of the wider studies, implemented in the context of the relevant projects, including internal and external evaluations, as well as both qualitative and quantitative data. The total number of the participant teachers was fifty-five (55), including only those that have provided at least one reply in the open-ended questions and/or have attended at least a discussion and/or have designed/ implemented an educational scenario supported by Augmented Reality. In order to strengthen

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the research evidence, the authors have also included in their evaluation data, parts of the educational scenarios that were designed and submitted by the teachers.

Data Collection and Analysis Methods The following sections provide details about the method implemented by the authors to evaluate the TPD programs described in this chapter. Gall, Gall and Borg (2007) have identified five (5) tools for collecting both qualitative and quantitative data within an educational research, including questionnaires, self-reports, interviews, performance assessments, and observations. Merchie et al. (2018), based on their extended evaluative framework, suggest a consistent set of data collection methods and instruments to apply the evaluation of TPD programs in a focused systematic way. These include rubrics, observations (video or audio recorded), questionnaires, interviews, digital logs, knowledge sets, self-reports, portfolios, policy documents, school and/or other records, etc., and could be applied in each of their framework’s component individually, partially or in total, depending on the available resources (Merchie et al., 2018). Taking the above mentioned into consideration, the current research focuses on qualitative data, collected from open-ended questions of the TPD programs’ evaluation questionnaires, interviews conducted, open-ended discussions (face-to-face and forum discussions), observations by the researchers as well as evaluation data, i.e. parts of the educational scenarios that were designed and submitted and/or implemented by the teachers. The data collected have been triangulated to enhance the levels of validity and reliability of the research. Moreover, concurrent, parallel, iterative and retrospective analysis was undertaken, with the purpose of triangulation and expansion (Guest, 2013). The total number of the participant teachers was fifty-five (55), including only those that have provided at least one reply in the open-ended questions and/or have attended at least a discussion and/or have designed/ implemented an educational scenario supported by Augmented Reality. It is important to mention that the current data were collected as part of wider studies in the context of the relevant projects, including internal and external evaluations, as well as qualitative and quantitative data. The current chapter focuses on the book’s main topics towards practical approaches to integrating ICTs in STEAM education and the authors’ perspective through their experience and contribution to the TPD programs.

Questionnaires All teachers/trainers participating in the TPD programs described, were asked to complete an anonymous online questionnaire for the program’s evaluation. The questionnaires have been developed with the Lime Survey tool and have been distributed online, to enhance the data analysis process. Referring to the questions, the authors applied Guskey’s levels (Table 3) to design and develop the core structure for each TPD program’s evaluation questionnaire (Guskey, 2002a). Since the TPD programs were implemented more than once, they were similar but not identical, due to characteristics that differentiated them, such as implementation by different trainers, during periods with specific characteristics (e.g. COVID-19 pandemic), with different targeted teachers, and in some cases, with different educational content (e.g. M8 in the “train the trainers” program). Table 3 displays the five levels of the questionnaires described and main focus of the relevant questions. As already mentioned, in the context of this study, quantitative data from open-ended questions have been collected.

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Table 3. Levels of questions for each TPD program’s evaluation questionnaire Level (Guskey, 2002a)

Questions’ Focus

1. Teachers’ reactions/ feedback

Teachers’ reactions concerning the TPD programs’ trainers, learning session(s), educational resources, workshops’ location (if applicable) and online course.

2. Learning Results

Knowledge, skills gained and possible changes in attitudes achieved during the TPD program.

3. Support by the Training provider

Sufficient support by the training provider, concerning technical issues, the educational material provided, the implementation process etc.

4. Application of knowledge/ skills gained

Intention to apply the knowledge and skills gained, in their classrooms/ laboratories etc. Possible change in technology (i.e. Augmented Reality) acceptance.

5. Students

Impact on students’ learning results and behavior, including interest towards the educational process, motivation etc.

Interviews and Open-Ended Discussions Additionally to the questionnaires, semi-structured interviews with open-ended questions were conducted with teachers/trainers, who expressed their willingness to share their experience concerning the TPD programs. Semi-structured interviews are flexible and allowed the researchers to focus on specific issues, especially patterns that emerged concerning emerging technologies (Cohen, Manion & Morrison, 2013). The interviews took place either face-to-face, at the TPD workshops’ locations, or online, through BBB or MS Teams. All interviews were anonymous and conducted in Greek, to encourage the feeling of comfort and trust to the researchers and allow expressions without possible language restrictions (Cohen et al., 2013). Moreover, open-ended discussions have been included in the data collection, such as discussions developed through emails with feedback (including both positive and negative comments), forum discussions (in the online educational platforms) and finally, face-to-face discussions during the TPD programs, where teachers felt more comfortable and replied spontaneously.

Observation and Evaluation Data (Educational Scenarios) Observation involves active looking, informal interviewing (mini-interviews) and taking detailed notes (Kawulich,2005). Researchers of this study participated some of the TPD programs as evaluators, thus, with a discrete presence without intervening the training process. Desimone’s (2009) evaluation framework has been applied as a guide to address the topics under investigation, focusing on emerging technologies. Finally, evaluation data, specifically the educational scenarios designed, developed and in some cases, implemented by teachers in their real classrooms, have been collected, to strengthen the research discussion and relevant conclusions.

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Data Analysis The collected data were analyzed both retrospectively and simultaneously while being collected (Schoonenboom & Johnson, 2017). The data analysis process begun with equal attention given to all data collected, while it gradually focused on the emerging themes, patterns, correlations and theoretical properties (Guest, 2013). Simultaneous analysis occurred mainly during the observation, where on-the-spot ideas raised. Interviews were analyzed both during and shortly after their implementation. It is important to mention that the current data were analyzed as part of wider studies in the context of the relevant projects, including internal and external evaluations, as well as qualitative and quantitative data. The current chapter focuses on the book’s main topics towards practical approaches to integrating ICTs in STEAM education and the authors’ perspective through their experience and contribution to the TPD programs.

RESULTS In order to present the results of this research, the Merchie et al. (2018) extended evaluative framework has been applied as the main pathway to guide the discussion and enhance the presentation of the relevant results (see Figure 1). Authors of the current research focus on issues relevant to the integration of emerging technologies into the educational process. Thus, the suggested directions follow in the table below (Table 4), framing an innovative approach of designing TPD programs for integrating emerging technologies, such as Augmented Reality (AR), in interdisciplinary STE(A)M based instructional scenarios, especially in the level of Secondary general (Gymnasium and Lyceum in Greece) and (Post) Secondary Vocational Education (EPAL - Vocational Lyceum) and IEK (Institution of Vocational Training in Greece).

Features of the TPD Program As far as the features of the TPD program are concerned, and specifically, the core content, emerging technologies should be treated as concepts rather than individual technological tools, thus, be accompanied with relevant educational approaches, highlighting the pedagogical added value of the technological tool under study. Enhancing students’ 21st century skills is of high importance, however, teachers of this study focused on the category of digital skills, usually underestimating the rest of the 21st century skills, such as problem solving, creativity, critical thinking etc. It is also critical for the teachers to understand that there are already real examples and use cases, thus, emerging technologies in education and training are not a science fiction scenario. Engagement in the development of educational content, could enhance the familiarization with a technological tool. For example, there are numerous tools, that could be applied by teachers without programming skills, to develop an Augmented Reality learning object. Through this process, they could more easily understand the way the specific technology works and could support the educational process.

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Table 4. Directions for designing TPD programs for integrating emerging technologies Component

Directions

Features of the TPD program

Core content - Treat emerging technologies as concepts rather than individual technological tools - Include real examples and use-cases, even in demo modes - Engage teachers in the design and development of educational content, supported by emerging technologies (if possible) Structure - The duration of TPD program should consist of a motivation (e.g. accredited professional development experience) - Enhance collaboration between teachers of different fields and interdisciplinarity - Enhance active learning, teachers should get in touch with the emerging technologies under - Allow trainings at the teachers’ schools, instead of other locations to strengthen confidence Trainers’ quality - Prefer trainers with previous experience on emerging technologies - Prefer trainers with portfolio on developing interactive educational content - Update and provide specific instructions on how to author innovative educational content (format, digitalization specifications etc.)

Teacher Quality

Expected impact on: (a) Knowledge - Content Knowledge (CK – teachers’ knowledge on a subject to be taught or learned) - Pedagogical Knowledge (PK – teachers’ knowledge on the methods, practices and processes to teach and learn), - Pedagogical Content Knowledge (PCK – teachers’ knowledge of the pedagogy applicable to the teaching of a specific subject) - Technological Knowledge (TK - the ways a teacher thinks or works with any technological tool and resource) - TPACK – a combination of all the above mentioned (b) Skills - Attend workshops to get familiarized with the technology under study - Gain general digital skills to enhance self-confidence and independence when applying an innovative technology (c) Attitudes/ Beliefs - Understand the additional educational value of the emerging technology under study - Strengthen the intention to apply emerging technology in education and training

Teaching Behavior

When teachers in their turn, teach in their classroom, they need to have been prepared on how to: - Treat emerging technologies as concepts rather than individual technological tools - Adapt pedagogies applicable to the teaching of a specific subject - Feel confident with integrating emerging technologies - Collaborate with other teachers

Students’ Results

Expected impact on students’: - domain specific knowledge - digital skills, specifically focusing on the technology under study - 21st century skills, including problem solving, creativity, critical thinking, collaboration etc. - intention to apply emerging technologies - response to the modern labor market

Referring to the structure of a TPD program, the duration seems to be a factor of high value. For example, a duration that is officially recognized and could be included as previous professional development experience seems to affect teachers’ intention to attend a TPD program. In Greece, depending on the case each time, programs longer than 300 hours or nine months could offer additional scoring in the teachers’ CVs, while programs shorter than 25 hours, usually do not count in the total training time. Thus, teachers prefer long TPD program, accredited as previous training experience. Another more flexible alternative that teachers mentioned was the choice to attend a total of shorter TPD programs (jigsaw programs) that could consist of a wider one (e.g. five programs of sixty hours, which could lead to a wide certification of 300 hours). As mentioned by a teacher “such TPD programs are more feasible

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in a manner of time and budget”. In Greece, especially in the level of Secondary general (Gymnasium and Lyceum in Greece) and (Post)Secondary Vocational Education (EPAL - Vocational Lyceum) and IEK (Institution of Vocational Training in Greece), the teaching fields are individual and only limited interaction between teachers of different fields exists. One of the characteristic statements, among others, that highlight the necessity of collaboration between teachers of different fields during a TPD program, was “Why should I know what are they (here: students) doing during their Computer Science lesson? I am teaching Physics; they don’t need Word or Excel to study Physics”. This teacher treated the Computer Science lesson as an independent one, focused on using office software, completely irrelevant to Physics. This was probably not surprising, since most of the existing TPD programs for teachers, also address target groups of the same specialty. Thus, interdisciplinary approaches in the structure of a TPD program, should be applied, aiming to lead to similar practices when teaching. This is also closely related to active learning, thus, teachers should be introduced to emerging technologies in real-life situations and issues, their students are expected to face in their future works, instead of being trained in theory and hypothetical applications. Finally, some teachers mentioned that they felt more confident when a training concerning innovative technologies took place at their school, instead of another location, since they could test their existing infrastructure (e.g. Wi-Fi connection, school computers, other devices) and ensure the functionality of the technology under study.

Teacher Quality Trainers also consist of a core feature of the TPD program, thus, their quality, including communication skills, familiarization with emerging technologies as well as previous experience on developing interactive educational content, seem to affect a TPD program’s quality. Many teachers mentioned that they prefer to attend TPD programs with activities and interactive content, while getting feedback from an “active” trainer is also motivational, however, such programs are much more time consuming to be successfully completed. Teachers with weaker technological backgrounds, seemed quite hesitant to attend more interactive programs, and preferred “traditional” trainers, providing educational content in text format, so that they study on their own pace. In turn, teachers’ trainers mentioned about the quality of the educational content, that they usually get specific instructions on how to develop it, however, these instructions still refer to word files specifications, additional content such as videos and external readings and educational content in format of the “past decades”. “I never follow these instructions, if I did, we wouldn’t now discuss about innovation in education”, a teacher mentioned, highlighting the fact that creating innovative educational content is closely related to the trainer’s quality. Teacher quality is the second component that needs to be treated with attention, to achieve positive impact on the gained knowledge, skills and attitudes. When designing a TPD program, especially a program focused on emerging technologies, TPACK could be a guide to develop the relevant content and the teachers’ evaluation process. A teacher should definitely be aware of the subjects to be taught (CK), for example, in order to teach the Tower of Pisa as a STEAM topic, each teacher (Maths, Physics, History, Arts etc.) should have deep knowledge of their fields and of course, realize how they integrate in a single subject. Pedagogical knowledge (PK) is critical; a number of this study’s participating teachers, mentioned that they applied innovative methods and practices (e.g. problem solving, inquiry-based learning), however, during the observation it was noticed that they kept seated on the teachers’ desk giving a lecture. In addition, they mentioned that they taught STEAM topics in collaboration with other teachers, but they actually taught their individual lesson, in the context of a wide STEAM topic (e.g. in 168

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the case of the Tower of Pisa, the Physics teacher taught the concept of gravity during the physics hour, the mathematics teacher taught the concepts of angles, etc., keeping separately the different dimensions). Thus, moving on to the Pedagogical Content Knowledge (PCK) and the pedagogy applicable to the teaching of a specific subject, it would be of additional value for the teachers to be taught specific subjects with the method they are expected to apply in their classroom (active learning). Finally, as already mentioned before, the technological knowledge should be integrated as a concept in the educational process combining an emerging technology with the content and pedagogy to be applied. Referring to teachers’ skills, there is an obvious need to attend workshops, aiming to get teachers into touch with the technology under study and get familiarized with the usage of relevant equipment, software, applications etc. Moreover, the need to enhance digital skills in general arose in this research, as a number of teachers mentioned that “I feel more confident when I have the support of the Computer Science teacher”. Thus, it would be of additional value to include modules for teacher of any technological background, to enhance self-confidence and independence when applying an innovative technology in their classroom.

Teaching Behavior Moving to the third component, changing teaching behavior after having successfully completed a TPD program is important. As already mentioned, when teachers in their turn go back to their classroom, they need to feel confident with integrating emerging technologies, they should have been prepared on how to treat an emerging technology as a concept rather than an individual technological tool, adapt in action pedagogies applicable to the teaching of their subjects and collaborate with other teachers.

Students’ Results The teachers’ interventions in their real classrooms consist of a validation method of a TPD program’s impact on students’ results. These results should not only be evident on students’ specific knowledge in a domain, but also, digital skills focusing on the technology under study (e.g. in the case of Augmented Reality, what is this technology, which tools can be used to apply it, how can students deal with technical issues) and 21st century skills in general (problem solving, creativity, critical thinking, collaboration etc.). Moreover, the impact could be measured through the students’ intention to apply emerging technologies in learning, training and other activities, apart from entertainment, responding to the needs of the modern labor market.

Other Components Finally, as mentioned by Merchie et al. (2018), contextual factors and teachers’ personal characteristics could affect a TPD (esp. focused on integrating emerging technologies) program’s success. This research highlighted among other contextual factors: compatibility with the curriculum standards, policy directions, the TPD program provider, school administration and support, school facilities and equipment, implementation time during the school year (e.g. exam period), financial resources and teachers’ appraisal. As far as the teachers’ personal characteristics are concerned, this research revealed: age, gender, technological background, motivation, internal motivation for personal development, time restrictions, personal issues (e.g. family) and health issues.

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FUTURE RESEARCH DIRECTIONS As highlighted through this study, there is a need to understand that teacher profession is evolving towards new innovative and responsive teaching methods, capable of preparing students for the Fourth Industrial Revolution (4IR). Thus, teachers need to participate in professional development initiatives that promote technology integration into authentic educational environments and cultivate their personal teaching approaches to expand their technological skills and practices. The specific chapter aims to contribute to the core book’s theme of “Practical Approaches to Integrating ICTs in STEAM Education”, by providing directions for an effective framework for horizontal TPD programs targeting large numbers of teachers, aiming to allow them to gain the appropriate knowledge and skills, in order to integrate emerging technologies as concepts in interdisciplinary STE(A)M based instructional scenarios, especially in the levels of Secondary general (Gymnasium and Lyceum in Greece) and (Post)Secondary vocational Education (EPAL and IEK in Greece). Future research opportunities could focus on teachers of all educational levels in different countries, conducting both qualitative and quantitative research with large scale data. Moreover, a generic evaluation framework, accompanied with suggested methods and tools to measure the expected impact of a TPD program towards integrating emerging technologies, could be of additional value for TPD providers, to re-frame their programs and provide high quality training, responding to the need for 21st century ready-to-teach teachers.

CONCLUSION This chapter provides an overview of the current situation concerning TPD programs, highlighting the need for initiatives towards the effective integration of emerging technologies into education and training. Moreover, specific TPD programs in the context of European projects are described, including their structure and evaluation process. The researchers provide directions towards horizontal TPD programs, aiming to allow teachers to gain the appropriate knowledge and skills, in order to integrate emerging technologies as concepts in interdisciplinary STE(A)M based instructional scenarios, especially in the levels of Secondary general (Gymnasium and Lyceum in Greece) and (Post)Secondary vocational Education (EPAL and IEK in Greece).

ACKNOWLEDGMENT This study was partially supported by the EU, under the Erasmus+ Key Action 2 program [Enlivened Laboratories within STEM Education (EL-STEM)—Motivating EU students to choose STEM studies and careers and improving their performance in courses related to STEM education/Project No.2017-1CY01-KA201-026775]; and by the European Social Fund (ESF) within the framework of the Operational Programme “Human Resources Development, Education and Lifelong Learning 2014-2020” [MIS 5008057]. Any opinions, findings, and conclusions or recommendations presented in this paper are those of the authors and do not necessarily reflect those of the EU or the relevant organizations/ institutions.

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Schlager, M. S., & Fusco, J. (2003). Teacher professional development, technology, and communities of practice: Are we putting the cart before the horse? The Information Society, 19(3), 203–220. doi:10.1080/01972240309464 Schoonenboom, J., & Johnson, R. B. (2017). How to construct a mixed methods research design. KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie, 69(2), 107–131. doi:10.100711577-017-0454-1 PMID:28989188 Schwab, K. (2016). The Fourth Industrial Revolution. World Economic Forum. Tarling, I., & Ng’ambi, D. (2016). Teachers pedagogical change framework: A diagnostic tool for changing teachers’ uses of emerging technologies. British Journal of Educational Technology, 47(3), 554–572. doi:10.1111/bjet.12454 Tican, C., & Deniz, S. (2018). Pre-service teachers’ opinions about the use of 21st century learner and 21st century teacher skills. European Journal of Educational Research, 8(1), 181–197. doi:10.12973/ eu-jer.8.1.181 Ur, P. (1997). Teacher training and teacher development: A useful dichotomy. The Language Teacher. https://jalt-publications.org/old_tlt/files/97/oct/ur.html Vermunt, J. D. (2014). Teacher learning and professional development. In Teachers’ professional development (pp. 79–95). Brill Sense. doi:10.1007/978-94-6209-536-6_6 Viner, R. M., Russell, S. J., Croker, H., Packer, J., Ward, J., Stansfield, C., Mytton, O., Bonell, C., & Booy, R. (2020). School closure and management practices during coronavirus outbreaks including COVID-19: A rapid systematic review. The Lancet. Child & Adolescent Health, 4(5), 397–404. doi:10.1016/ S2352-4642(20)30095-X PMID:32272089 Vitsilaki, C., & Pitsikalis, S. (2017). Modern Curricula in Higher Education and Training supported by the technologies of Augmented and Mixed Reality: Overview and Recognition of Research Issues. Proc. of 9th International Conference in Open and Distance Learning (ICODL). Whalen, J. (2020). Should teachers be trained in emergency remote teaching? Lessons learned from the COVID-19 pandemic. Journal of Technology and Teacher Education, 28(2), 189–199. Whitehouse, McClosky, & Ketelhut. (2010). Online Pedagogy Design and Development: New Models for 21st Century Online Teacher Professional Development. In Online Learning Communities and Teacher Professional Development: Methods for Improved Education Delivery (pp. 247-262). New York: IGI Global. Winter, E., Costello, A., O’Brien, M., & Hickey, G. (2021). Teachers’ use of technology and the impact of Covid-19. Irish Educational Studies, 40(2), 1–12. doi:10.1080/03323315.2021.1916559

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ADDITIONAL READING Astuti, A. P., Aziz, A., Sumarti, S. S., & Bharati, D. A. L. (2019, June). Preparing 21st century teachers: Implementation of 4C character’s pre-service teacher through teaching practice. Journal of Physics: Conference Series, 1233(1), 012109. doi:10.1088/1742-6596/1233/1/012109 Compen, B., De Witte, K., & Schelfhout, W. (2019). The role of teacher professional development in financial literacy education: A systematic literature review. Educational Research Review, 26, 16–31. doi:10.1016/j.edurev.2018.12.001 Heap, T., Thompson, R., & Fein, A. (2021). Designing teacher professional development programs to support a rapid shift to digital. Educational Technology Research and Development, 69(1), 35–38. doi:10.100711423-020-09863-5 PMID:33223780 Malik, R. S. (2018). Educational challenges in 21st century and sustainable development. Journal of Sustainable Development Education and Research, 2(1), 9–20. doi:10.17509/jsder.v2i1.12266 Oke, A., & Fernandes, F. A. P. (2020). Innovations in teaching and learning: Exploring the perceptions of the education sector on the 4th industrial revolution (4IR). Journal of Open Innovation, 6(2), 31. doi:10.3390/joitmc6020031

KEY TERMS AND DEFINITIONS Augmented Reality (AR): An emerging technology where the real world is supplemented with digital objects (usually 3D objects superimposed on the top of real objects) and the user can interact with them while still remaining in contact with the real world. Emerging Technologies: New technologies under continuing development, such as Virtual/Augmented/Mixed Realities, Internet of Things, Artificial Intelligence, 3D printing, etc. EPAL: The acronym for Epaggelmatika Lykeia (Vocational High Schools) in Greek language. EPALs belong to Secondary Vocational Education for students until the age of 18, while the Post-secondary year – Apprenticeship Class (Metalykeiako etos – Taksi Mathiteias) belongs to Post-Secondary NonTertiary Education. Fourth Industrial Revolution (4IR): Refers to the current period of rapid technological growth, which is fundamentally changing our everyday life. IEK: The acronym for Institouta Epaggelmatikis Katartisis (Vocational Training Institutions) in Greek language. They belong to Post-Secondary Non-Tertiary Education. Mixed Reality (MR/XR): An emerging technology where the real world meets the digital world in a completely integrated way, as real and digital objects cannot be distinguished. STEAM: Is the acronym for Science Technology, Engineering, Arts, and Mathematics. In this study, it refers to the integrated way of teaching and learning, no matter which individual subjects are included in the educational process.

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Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning Manolis Kousloglou Aristotle University of Thessaloniki, Greece Anastasios Zoupidis https://orcid.org/0000-0003-3097-9451 Democritus University of Thrace, Greece Anastasios Molohidis Aristotle University of Thessaloniki, Greece Euripides Hatzikraniotis https://orcid.org/0000-0002-9516-4037 Aristotle University of Thessaloniki, Greece

ABSTRACT STEM education promotes scientific inquiry and engineering design, including mathematics, incorporating appropriate technologies. Portable technologies motivate active learning of students and enable accessing to learn resources, facilitating cross-disciplinary designing tasks. This chapter initially presents theoretical approaches of STEM education, mobile learning, and inquiry-based learning, and then it describes an inquiry-based short-term intervention that took advantage of portable digital devices in a STEM class. The aim of the intervention was to study its affection on students’ motivation about physics. Results indicate that students who participated in the activity had higher motivation scores than their classmates who attended lessons with conventional teaching methods. The findings also show that the students involved in a guided inquiry-based process became more profoundly engaged in STEM than their classmates who followed a structured inquiry process. Other factors, such as grade point average (GPA) and gender, did not seem to affect student motivation.

DOI: 10.4018/978-1-6684-3861-9.ch009

Copyright © 2022, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

 Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning

INTRODUCTION Education in the 21st century has been driven by teaching and learning processes regarding STEM approaches that provide students with skills in integrating all aspects of learning. STEM education leads students to easily gain knowledge of concepts in authentic problems, using technology, deploying scientific knowledge, managing data by mathematical reasoning, and practicing engineering (Prasongsap et al., 2020). As ICT competency is an important skill that should be developed as one of the 21st century skills, any form of integration in today’s situation is incomplete without the digitalization of classrooms (Deák et al., 2021). Especially, mobile technology, namely tablets, smartphones, or wireless sensors, motivates an active, exploratory, and inquiry-based learner-centered learning, as well as collaborative work and creativity (Prasongsap et al., 2020). Although increasing attention on the importance of STEM education has been worldwide stated, difficulties related to lack of time, resources and trained instructors greatly hinder the potential of developing and implementing STEM activities. Thus, it is suggested that ICT, especially mobile technologies, could overcome these difficulties and complement the practice of different activities under formal and informal learning settings (Yeung & Sun, 2019). We could define Inquiry-based learning as a process in which students propose questions, formulate hypotheses, investigate, and test experiments or observations (Pedaste et al., 2015). Inquiry-based learning is a self-directed learning process which emphasizes active participation and students’ responsibility for discovering knowledge (Wilhelm & Beishuizen, 2003). The future of pedagogy in STEM classrooms will be governed by how efficiently educators can present their content knowledge in collaboration with e-learning tools and develop inquiry-based learning in classrooms (Deák et al., 2021). Mobile technologies in inquiry-based STEM learning can give observable benefits to the learning process of students in several aspects and their achievement (Yeung & Sun, 2019). Mobile inquiry-based learning (mIBL) aims to exploit mobile technology to aid the inquiry process, exchange information, and motivate learners to obtain knowledge building and sharing procedures (Yang et al., 2020). Thus, in this framework, motivation can be defined as an individual’s desire to learn concepts or complete learning tasks in mobile Inquiry-based Learning (mIBL). Especially in a science-learning context, the motivation is a crucial issue as it could be described as an internal state that stimulates, conducts, and assists science-learning behavior (Glynn et al., 2011). MIBL should be used with appropriate technology support and teaching strategies, as STEM education, in order to promote students’ motivation (Yang et al., 2020). In this book-chapter we start by a brief Literature Review on the concepts of Inquiry-Based Learning (IBL), Mobile Learning (m-Learning), Mobile technology-supported Inquiry-based Learning (mIBL), STEM education and especially their integration and its advantages. Then a STEM-driven mIBL intervention held in the 3rd High School of Kavala, in Greece, and its effect on student motivation will be presented and analyzed.

BACKROUND The Background consists of a brief literature survey on the various aspects of STEM education and Inquiry-based Learning in the Mobile Area and on the methods for enhancing the students’ motivation.

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STEM and Inquiry in the Mobile Era The literature survey can be depicted as a set of three inter-sectioned circles, one for STEM, one for IBL and one for m-Learning. The literature survey will cover the main circles and their intersections (figure 1). Figure 1. The framework of the literature survey

STEM Education STEM education refers to teaching and learning in the fields of science, technology, engineering, and mathematics with the aim of improving students’ ability and skills to apply cross-disciplinary knowledge effectively in order to solve problems. Besides the well-known terms “Science” and “Maths”, the acronym STEM includes Technology, which is the utilization of knowledge to develop products out of the given resources and Engineering that refers to the use of mathematical and scientific knowledge to develop and modify the three fundamental resources that humankind has available for the benefit of mankind: energy, materials, and information (Tantu, 2017). According to Deák et al. (2021), the last two decades’ trends in article publications about STEM show a significant rise in approaches towards integration on pedagogy and subjects in STEM education. However, it is stated that designing STEM activities as well as proposing innovative learning tools or technologies in STEM education remain a challenge (Hwang, 2020).

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STEM education is more than a simple integration of its four disciplines. It encompasses real-world, project-, problem- or inquiry-based learning that integrates the disciplines through active teaching and learning approaches. STEM programs also have explicit course objectives, content domains and learning indicators. They provide student-centered learning experiences, stress the connection and integration of STEM knowledge, and cultivate high-level thinking such as logical thinking, problem solving, and critical thinking (Lai, 2018). The students learn how the concepts, principles, and techniques of the four STEM’s disciplines are used in the development of products, processes, and systems used in everyday life. In this way, STEM education prepares students for the challenges of the 21st century, namely Digital Age Literacy, Inventive Thinking, Effective communication, and High productivity (Hwang, 2020; Mutambara & Bayaga, 2020; Yuliati et al, 2018). Daher & Shahbari (2020) mention four levels of integration among the subjects in STEM education: In the first level, STEM activities involve just two subjects, where the first is the dominant one, while the second subject’s concepts support the emergence of concepts from the first one. The second level is similar to the first, but STEM activities are the combination of three subjects or more, from which one subject is dominant, while the other two support the emergence of concepts from the dominant one. The third level involves two equivalent subjects, the concepts of which emerge as a result of their integration. The fourth level is similar to the third, but involves at least three subjects, where concepts from at least two of them emerge together, while the rest of the subjects support these emergences (figure 2). Figure 2. The four levels of integration among the subjects in STEM education

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Inquiry-Based Learning (IBL) Inquiry-based learning (IBL) is a constructivist approach in which students are placed in the position of scientists by developing their own questions, formulating appropriate hypotheses, designing activities and experiments to test them, analyzing, understanding, and explaining the results from their experiments, drawing conclusions, and finally reflecting and communicating their findings. Thus, they conduct investigations creating new knowledge based on the collected evidence (Liu et al., 2021; Tijani at al., 2021; Yuliati et al, 2018). There are four main levels of IBL outlined in Table 1. The levels, form a continuum of guidance that students are provided by their teacher: a) confirmation, at which teacher provides the questions, procedures and solutions or conclusions in a predefined-prescribed way, b) structured inquiry, at which teacher provides the questions and procedures, c) guided inquiry, at which teacher provides only the questions, and d) open inquiry, at which the students develop their own questions, design the procedures and generate the solutions (Liu et al., 2021). Table 1. The four levels of IBL according to students’ guidance Level of IBL

Confirmation

Structured inquiry

Guided inquiry

Open inquiry

Question

Given

Given

Given

Open

Procedure

Given

Given

Open

Open

Solution

Given

Open

Open

Open

Many researchers have agreed on the positive effect of inquiry-based learning on students’ conceptual understanding, their problem-solving and collaborative abilities, as well as their Higher-Level Thinking Skills, such as discovering information, and making decisions. Inquiry-based learning has the potential to engage students in an actual scientific discovery process, by giving them an idea of classroom learning achievement making learning more joyful, and thus it is recommended as a critical element in science pedagogy (Deák et al., 2021; Hwang, 2020; Tijani at al., 2021).

Mobile Learning (m-Learning) Mobile learning could be defined as learning in multiple contexts, through social interactions, but also content, using personal digital mobile devices (Crompton, 2015). Mobile learning refers to the use of mobile technology, such as smartphones, laptops, and tablet devices to facilitate learning. Many concepts are related to m-Learning, such as (Hwang, 2020; Liu et al., 2021; Tantu, 2017; Thongsri et al., 2020;): • • • •

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ubiquitous learning which refers to the notion “learning anywhere and at any time”, context-aware ubiquitous learning which emphasize the use of mobile technologies to support learning across contexts, authentic learning that targets real-world problems to make attractive learning environment, customization of access to information in order to build new skills and meet specific educational goals,

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• •

personalization of accessing knowledge, collaboration among learners, interactivity and seamless bridging between contexts in both formal and informal learning.

Mobile-Learning changes a teacher-centered approach to a learner-centered one, which can stimulate deep holistic learning experiences (Mutambara & Bayaga, 2020). Natural sciences, by their very nature, are based on the exploration of the physical world, and digital mobile devices are considered appropriate to support this exploration (Suarez et al., 2018) since they offer the tools to make it more accessible but also ubiquitous (Crompton et al., 2017).

Mobile Inquiry-Based Learning (mIBL) Mobile technology-supported inquiry-based learning (Mobile Inquiry-based Learning - mIBL) aims to employ mobile technologies to facilitate inquiry process and motivate learners to build and share their knowledge (Looi, 1998). Scanlon et al. (2011) state that mIBL improves IBL in terms of mobility and rapidity of feedback and has a positive impact on interaction among students and teachers. Liu et al. (2021) identified five main types of mIBL: authentic scientific inquiry, abductive scientific inquiry, collaborative inquiry, collective whole-class inquiry, and inquiry with a game component (figure 3). Authentic scientific inquiry (AUI) occurs when, among others, students take advantage of mobile technology to conduct hands-on investigations collecting and analysing data and making conclusions towards real-life problems. Abductive science inquiry (ABI) refers to inquiry activities where students develop plausible hypotheses based on theories and observation and offer explanations using critical thinking with assistance of mobile technology. In collaborative inquiry (CAI), students work in groups/ pairs engaging in investigations of problems. They collect and interpret data and try to answer questions by generating evidence-based explanations. Collective whole-class inquiry (CEI) involves students as a whole class in working for a common goal and developing community knowledge based on each other’s ideas with the assistance of mobile Inquiry. In an inquiry with game component process (GCI) students participate using a game as learning material and conduct investigations for addressing a problem with the assistance of mobile technology. Also, the benefits and constraints of mIBL can be divided into three main groups: micro, meso and macro levels, under which different themes emerge. At the micro level, themes include efficiency, effectiveness, learnability, perceived usefulness, and cognitive load. At the meso level, themes focus on attitude, attention, motivation, learning performance, group work and cognitive processes, while the macro-level theme focuses on motivation (Liu et al., 2021). As m-Learning has an immense potential to promote learning in inquiry-based designed environments (Thongsri et al., 2020), mIBL is one of the most popular pedagogical approaches utilized in secondary mathematics and science education. Nevertheless, there is a lack of understanding of mIBL in secondary science education. More evidence-based insights are needed into how using handheld devices might facilitate the engagement of students in various levels of inquiry and enhance their science learning (Liu et al., 2021).

STEM Education and IBL STEM activities can be categorized into project-based tasks and inquiry-based tasks (Hwang, 2020). According to Deák et al. (2021), the future of pedagogy will be defined by how efficiently instructors present their knowledge in collaboration with e-learning tools and develop inquiry-based learning (IBL), 181

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Figure 3. The five main types of mIBL

especially in STEM classrooms. Scholars suggest that IBL should be used to promote technology exploration and strengthen the effect of STEM teaching (Lai, 2018). Deák et al. (2021) state that IBL could be the torchbearer approach to teaching higher education STEM-based research in science and technology and bridge the big knowledge gap between knowing (Ideas – Conceptualization) and doing (Actions – Analysis with expert opinions). In STEM education, inquiry-based methods have enormous potential in deepening students’ knowledge and skills, while the activities can be supported by technologies which provide new forms of inquiry and research (Yeung & Sun, 2019). It has been shown that IBL is an effective method for raising students’ motivation in STEM subjects, influencing their concept achievement as well as their scientific literacy, enhancing their creative and critical thinking skills, directing the attention and motivation to learn concepts and skills through cognitive processes and resulting in a deeper understanding of real-world phenomena (Daher & Shahbari, 2020; Tijani at al., 2021; Yuliati et al, 2018). Sutoyo et al. (2019) developed a 6-phase model for Inquiry integrated with STEM, in order to explain the students’ training for critical thinking skills. In phase 1 (Initiation), interpretation skills, motivation and concept mastery are developed. Phases 2 (Selection) and 3 (Formulation) trains students’ interpretation skills. Phase 4 (Collection) trains students’ analysis skills. In phase 5 (Presentation) students are trained about critical thinking skills in analysis, inference, and explanation indicators. Finally, phase 6 (Assessment) gives chance to train critical thinking skills and deepens students’ concept understanding. Daher & Shahbari (2020) suggest that the design of STEM activities could take into consideration two aspects, namely the inquiry level in the activity (confirmation, structured, guided, and open) and the integration type of the activity: combination of two subjects with one dominant subject, combination of at least three subjects with one dominant subject, combination of two dominant subjects, and combination of at least three subjects, where two of them are dominant.

STEM Education and m-Learning In the last few years there has been an increase in attention on the importance of STEM Education. However, difficulties are reported in the full integration of STEM activities in normal setting classes,

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due to lack of time, resources, and trained manpower. Hence, it is suggested that mobile technologies can support the practice of different activities under informal learning settings (Yeung & Sun, 2019). Mutambara & Bayaga (2020) state that poor-performing education systems, poor quality of teaching, lack of STEM teaching and learning resources, and lack of science laboratories are the main reasons for the emergence of m-learning, due to its potential to improve the quality of STEM education in rural areas. Besides, STEM education and mobile learning share similar pedagogies such as, student-directed, problem-based, authenticity-based, and collaborative learning (Schuck et al., 2018). Publications about the integration of mobile technology in STEM education has been increasing over the decades, as this technology can support students’ learning anytime and anywhere and can lead to a pedagogy that support the learning of Science, Technology, Engineering, and Mathematics (Prasongsap et al., 2020). For instance, mobile technologies provide supplementary materials to science learners whenever they need to observe in the field. Moreover, in mathematics and engineering courses, several mobile apps can guide learners to implement a task, or to control a device via programming. Therefore, the benefit of mlearning has significant potential in facilitating STEM learning (Hwang, 2020). Considering the above affordances of mobile technologies, it is important for a STEM educator to employ mobile devices for any educational intervention (Tantu, 2017).

Enhancing Students’ Motivation Social cognitive theory considers students’ learning as most effective when it is self-regulated, which among others, means that students control their motivation and behavior. In this theory, motivation is described as an internal state that stimulates, conducts, and assists a behavior which is goal oriented (Glynn et al., 2011). According to Prasongsap et al. (2020), many researchers intend to integrate mobile technology into STEM education, as a way to enhance students’ learning. Liu et al. (2021) in their systematic review find that students are motivated towards science learning when they have an enjoyable learning experience using mobile technology. Data visualization and collaborative opportunities foster students’ interest in science, create feelings of excitement in their learning, leading as a consequence to enhanced engagement in addressing inquiry problems. The autonomy that students enjoy in their mIBL activities permits them to be more participative in science learning process. Furthermore, the psychological need to develop competence, and engagement in a relevant inquiry problem, motivates students to perform mIBL activities, while only a small number of studies report on students finding mIBL boring or tiring. For instance, Nouri et al. (2013) in their study about collaborative scaffolding and performance in mIBL observed that students participated in interesting context-related discussions, which is an indication of a higher reflection on the school subject, generated by an intrinsic motivation. Yang et al. (2020) also declare that mIBL can increase learners’ motivation or participation more than traditional approaches by providing opportunities such as interaction between learners and their peers or their instructors, via the use of mobile devices. Novak & Krajick (2006) articulate that motivating investigative techniques, such as probes, modeling, Web 2.0, mobile technology, and visualization tools, which are used in the inquiry process enhance the effectiveness of laboratory practices Motivation must be considered as a complex multidimensional construct that interacts with cognition to influence learning (Salta & Koulougliotis, 2014). Motivation’s components are intrinsic motivation, which is defined as learning science for its inherent satisfaction rather than for some separable consequence; self-determination, which refers to the ability students believe they must manage their learning of science; self-efficacy, which refers to students’ belief in their capacity to achieve well in science; and 183

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extrinsic motivation, which involves learning science as a means to an actual end, such as a career or a grade. Extrinsic motivation can be divided into two factors, grade motivation and career motivation, which target more precisely the actual ‘‘ends’’ on which students focus. For instance, grades are important short-term goals because they are a criterion of learning accomplishment and part of the entry criteria for many careers (Glynn et al., 2011).

MATERIALS AND METHODS Rationale and Research Questions The rationale of the intervention described in this paper is displayed in Figure 4. The students in the Science class were involved in a STEM intervention, which focused on the design of an experimental setup for the study of Friction. They worked in small groups, applying elements of M-learning. The process was conducted in the pedagogical context of inquiry-based learning. Figure 4. The rationale of the intervention

In our research, the effect of mIBL STEM activities on students’ motivation towards science was explored. The research questions are whether the mIBL STEM activities enhance the students’ motivation towards science, and the correlation between the motivational characteristics. It is crucial to mention that, in Greece there has been no systematic research so far which address the students’ motivation to learn physics.

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 Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning

The Participants The research methodology follows the control - experimental group scheme. Both groups come from Northern Greece; the experimental group from the city of Kavala, and the control group from New Peramos (a small city in the district of Kavala). The participants were secondary school students of the 8th grade, aged 13-14 years old. The control group consists of 70 students who have followed a traditional teaching for friction, whereas the experimental group consist of 71 students who have been taught the same subject with STEM-oriented mIBL activities, described below. The distribution of students in the two groups in terms of their grade point averages in Science was tested and found to be similar. Both the students and their parents were informed about the aim of this research and students in both groups participated voluntarily.

The Tools In this study, the motivation of secondary school students to learn physics in school was investigated, from the perspective of social cognitive theory. We have chosen the Science Motivation Questionnaire II (SMQ II), developed by Glynn et al. (2011). It is a broadly accepted questionnaire, based on a theoretical formulation of motivational constructs, it functionalizes the motivational construct with a range of indicators, and it demonstrates various psychometric properties (Salta & Koulougliotis, 2014). SMQ-II can serve to investigate students’ motivation to learn science, the correlation between motivational characteristics, and can be used in relating the students’ motivation with instructional methods. The original questionnaire consists of 25 items, which are grouped into five factors: grade motivation (GM), self-efficacy (SE), self-determination (SD), career motivation (CM) and intrinsic motivation (IM). Originally, the SMQ-II was developed to assess the motivation of college students, both science majors and non-science majors, and the scales were found to be useful. In our case, the questions related with factor CM were omitted, since we believe that is too early for students on the 8th grade to have a clear view on whether Physics would help them to get a better job, advance their career and if their future job would involve Physics. Therefore, we consider that students might reply by a pure guess in these items. The SMQ-II questionnaire used in this study was translated, adapted, validated, and applied by Salta & Koulougliotis (2014) for the domain of chemistry. The translation and adaptation process were conducted taking into consideration the Hambleton comments on International Test Commission (ITC) guidelines. The selected questionnaire was validated via Confirmatory Factor Analysis (CFA), a procedure that provides evidence for the validity of SMQ-II, as well as for configural, metric and scalar invariance, and hence allows relevant comparisons between groups. The students of both schools anonymously completed the translated SQM-II questionnaire. Their answers to all items were assessed using a 5-point Likert scale: never (0), rarely (1), sometimes (2), often (3), always (4). The Statistical Program for the Social Sciences, version 17.0 (SPSS, Inc., 2008), was used for the statistical analysis of the findings, while the CFA was performed with JASP, an opensource project supported by the University of Amsterdam.

The STEM-Oriented mIBL Intervention In Greece, science teaching starts at the 5th grade. The science courses include some experiments, inquiry-based learning is limited in the classroom, while STEM is practically not applied in the Greek 185

 Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning

curriculum. The students in the experimental group performed hands-on friction experiments using both conventional setups and mobile devices, i.e., mobile phones with their embedded sensors as part of the measurement setup and tablets to record and analyze the results. These hands-on experiments adopted an Inquiry based Science Learning methodology (mIBL), according to the following phases: Orientation, Conceptualization, Investigation, Conclusion & Reflection (Pedaste et al., 2015). During the same period, the students in the control group have been taught the same topic with traditional teaching methods (chalk and blackboard or PowerPoint-type lecture with simple demonstration experiments). The experiments were designed within the STEM framework, as they combine Science (friction), Technology (conventional experimental setups and smartphones’ sensors), Engineering (designing experimental setup using laboratory equipment) and Mathematics (data analysis their tablets). From the perspective of subject’s integration in STEM education (Daher & Shahbari, 2020), the students participated in a second level STEM activity, as four subjects were involved, from which one subject (physics) was dominant, while the other ones supported the emergence of concepts from the first. As part of STEM education, students were expected to participate in processes and tasks similar to those faced by engineers. They had to ask questions to identify the engineering problem, to design many solutions, to set criteria for a solution that will be considered successful, and to identify limitations. Following procedures similar to those of scientists, they conducted data collection research that would help them determine design criteria to test their designs. In this way, they had to identify the relevant variables, decide how to measure them, collect and analyze data. In conducting their research, the students used models to analyze the proposed solutions, in order to identify possible shortcomings and thus identify the strengths and limitations of their designs. Such an approach provided students with a way to practice, applying their understanding of how science, technology, and engineering are interconnected. Concisely, the steps followed by the students were: (a) Research the need, (b) Develop possible solutions, (c) Select the best possible solution, (d) Construct a prototype, (e) Test and evaluate the solution, (f) Communicate the solution. A discussion between the students of all groups and the teacher has followed, aiming to evaluate the different ideas and designs, and altogether ended up selecting the laboratory setup that could check all the factors (variables) that probably influence friction.

The Implementation of the STEM-Oriented mIBL Activities The Inquiry-based STEM activities are shown schematically in Figure 5. They follow the five-stage inquiry-based learning: Orientation, Conceptualization, Investigation, Conclusion and Reflection (Pedaste et al., 2015). The laboratory activities lasted 3 weeks and were developed into six teaching-sessions, each one lasting one class hour. The first teaching-session corresponds to the “Orientation & Conceptualization”, the next three ones to the “Investigation”, and the last two sessions to the “Conclusion & Reflection” phases of the Pedaste scheme. Students worked in small groups of 4 or 5, with the aid of worksheets, which were structured and were designed taking into account students’ limited experience in group work, in conducting experiments, in inquiry-based learning, and in Mobile Learning applications. The 1st teaching-session aimed in the orientation & conceptualization of the problem. The worksheet in the orientation phase, started with a fictional story from everyday life for stimulating the students’ curiosity and addressing a learning challenge:

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 Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning

Figure 5. The six teaching-sessions of the laboratory activities

In our house, on a chair, there were various objects, such as a cup, a booklet-calorie counter, a kettle … even our mobile phone! We lift the chair from one side so that our father can pull the carpet underneath and… great damage: Some objects were slipped on the chair and fell to the floor Students were guided to form testable questions, related to the fictional story and generate hypotheses regarding the stated problem. This corresponds to the conceptualization stage of the Pedaste model, i.e., the process of stating theory-based questions or hypotheses. The 2nd teaching session aimed in exploring the fictional story. This is the first of the three investigation sessions, where curiosity that has been developed in the orientation stage, was turned into action in order to respond to the stated research questions or hypotheses. Students were prompted to test their questions experimentally using their smartphones. The objective was to determine the maximum coefficient of static friction. At the beginning, the students discussed and recorded their predictions about the sliding behavior of their smartphones, placed on an inclined chair. Then, test measurements were performed to familiarize the students with the lab activity and make the experimental data more reliable. Finally, the experiment took place by handling smartphones and exploiting the Phyphox software (https://phyphox. org/). Each group of students performed the experiment storing the data in .xls format on Google Drive through the “export data” capability of Phyphox. The aim of this activity was to further analyze the data, using their tablets, and share the data with other groups. When the procedure was completed, the groups announced and compared the results of their measurements. Students were surprised to notice the wide range of angles that the smartphones began to slip. When the smartphone was left to slide with the case, the values range from 11o to 49o, while without the case they range from 4o to 16o. Therefore, the students were introduced to the necessity of a systematic study of the friction, before they would explore the factors that affect it. Students with low lab-experience were thus trained in observation as

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 Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning

well as in developing thinking and analytical skills. More details for the smartphone experiment can be found on Kousloglou et al. (in press). In the next two teaching-sessions students studied experimentally the phenomenon of friction (3rd session) and the factors that affect the friction (4th session), using conventional lab equipment. In these two investigation sessions, the findings of the previous session and the necessity of a more systematic study of the friction refined the questions to be explored. Students explored/observed, changed variables, made predictions, and interpreted outcomes. Experimentation involved the design and implementation of the investigative activities, and an intermediate outcome was the design of the experiment. During these two teaching-sessions, students, worked either with the Structured or with the Guided Inquiry scheme. In both types of inquiry, the teacher poses the problem to be investigated; in Structured Inquiry the students follow a prescribed experimental procedure, whereas in Guided Inquiry the students select and design appropriately the procedure themselves. The basic experimental setup for the determination of the maximum static friction (session 3) consists of a wooden block on a horizontal melamine desk, as depicted in Figure 6. The block is attached on a laboratory spring scale, which acts as a force sensor. The other end of the spring scale is attached on a suspended weight, an empty bottle, which students gradually fill with water, and observe the threshold value of the force needed to produce the motion of the block. The experimental setup is easily modified for session 4, adding weight on the block, changing the contact surface area and consequently the surface roughness, by attaching several materials (sandpaper, velvet cloth, plastic sheet, etc.) on it, using double sided scotch tape. The students then formulated hypotheses in terms of the testable question “which are the factors that affect friction” that they had previously put forward: The friction may depend on (a) the roughness/ smoothness of the surface, (b) the surface area of the contact, and/or (c) the mass of the sliding body. In the 4th teaching session, the students were prompted to choose the appropriate lab equipment, that was available in the school’s lab, and design an experimental setup to check their hypotheses. In other words, the students were engaged in engineering-practice by designing and constructing a proper experimentation setup within the STEM framework. Due to the large amount of experimental work required to test all hypotheses, students were divided into smaller groups and each group chose one of the variables to investigate. Students were introduced to the control-of-variables strategy, by changing one variable (the one they have chosen), keeping all other variables constant. Similar to the 2nd teaching-session, students used their tablets to record and analyze the data, and at the end of the experimentation, all groups announced the results of their measurements and compared them in plenary. Finally, in the last two teaching-sessions the students analyzed and evaluated their data and communicated their results in the class receiving feedback and comments from their peers. The procedure was accomplished by the comparison of the results to the initial hypotheses and the formulation of the conclusions. During the entire process, the students reflected on the procedure, evaluated the experimental setup, and completed their reflection report at home. Reflection has been mainly focused on the inquiry-based learning process (What did I do and why?), while communication has been focused on the experiment-related outcomes (What did I find?). Summarizing the process, first the students were oriented through a fictional story from everyday life; Then they experimented and observed that when they lifted a chair the mobile phones placed on it slide with different inclination angles of the chair. So, they questioned themselves what factors influence the slide. The next step was to hypothesize possible answers to their questions and to record their hypotheses for further investigation. Afterwards, they designed an experimentation setup with their 188

 Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning

teacher’s support, and they experimented, investigating their hypotheses. Then, the students analyzed their data with their tablets and recorded their overall conclusions about Friction. They also evaluated the process (design, errors, experimental setup, suggestions for improvement, etc.). Finally, they discussed and came up with communicating their research to their peers and schoolteachers. During the whole lab activity, they completed a Reflection Report at home. Figure 6. The basic setup for the friction experiment (schematic and in classroom conditions)

RESULTS The Results on the Intervention As already mentioned, during the phases of the STEM intervention the students in the experimental group used their smartphones as well as conventional equipment (Technology) in order to find the solution to a hypothetical problem, related to the phenomenon and the factors which affect friction (Science). The students were prompted to design and implement an experimental setup using the lab equipment (Engineering) and proceeded with data analysis applying mathematical formulation (Math). Each of the investigation phases consists of three steps of experimentation, namely, the design and setup of the experiment, the measurements, and the conclusion. Obviously, the time devoted in each of the steps is related to the guidance provided. In order to investigate this, during the third phase, half of the students (group1) in the experimental group followed a Structured Inquiry process, while the other half (group2) applied a Guided Inquiry process. In the fourth phase, all students followed the Guided inquiry process. Figure 7 shows the comparison of the two groups (Structured & Guided Inquiry), performing the same experiment in 3rd phase. The graph shows the time spend during the experimental procedure, divided in the three stages: the time required to complete the design & setup of the experiment, the time for the

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 Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning

measurements and the time for the students to draw the conclusion. As can be seen, in Figure 7a, the total time is practically the same for both groups, however with different distribution between the various steps of experimentation. As expected, the amount of time devoted in the “design & setup” step, is much larger in the group which followed the Guided Inquiry process, since in this process, students had to design the experiment themselves. On the other hand, for the group that followed the Structured Inquiry process, a considerable amount of time has been devoted in taking the measurements, while this time is much less for the group which followed the Guided one. It seems that the total time is “balanced” between these two steps, and time for “measurements” is less when students design the experiment themselves. Figure 7. (a) Duration of experimentation procedure and (b) Student verbal interaction Time (3rd Phase)

The verbal interaction of the students within the group for the two types if inquiry process is presented in Figure 7b. The time for student-talking was increased from 20 min for the Structured Inquiry subgroup to 30 min for the Guided Inquiry one, for the same experiment. As can be seen, the time for both groups for the measurement & conclusion steps are identical, while the 50% more time in the Guided inquiry process, is due to the more time required by the students for the design stage. During the Guided Inquiry process the students were much more active in talking, and apparently dealt more deeply with the Engineering part of STEM (design & setup) than their schoolmates who followed a Structured inquiry process and student-talking was almost limited in setting up of the experiment.

The Results on Motivation The administrated questionnaire is presented in the Appendix. The questionnaire was checked for the internal reliability with Cronbach-α. A significance of p=0.05 was accepted as a conventional level. One-way ANOVA analysis was applied to identify any significant difference. The correlation coefficient was interpreted in terms of its statistical significance, indicate that the results are unlikely to have occurred by chance. Table 2 shows the values of Cronbach-α for each factor, for both groups. The values range from 0.68 to 0.86 per factor in the two groups. When the two samples are added together (N=141) the Cronbach-a is increased, ranging from 0.77 to 0.85. According to DeVellis (2003), a coefficient above 0.80 is “very

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 Enhancing Students’ Motivation by STEM-Oriented, Mobile, Inquiry-Based Learning

good,” 0.70 to 0.80 is “respectable,” 0.60 to 0.69 is “undesirable to minimally acceptable,” and below 0.60 is “unacceptable”. The total Cronbach-a of the whole questionnaire is considerably high, and invariant from one school to the other. The similar values are recorded for both groups, indicate that the questions were perceived in the same way by both groups, and therefore the groups may be added together for further analysis. Table 2. The values of Cronbach-α for each factor’s set of questions, for both schools Reliability of internal consistencies - Cronbach’s alpha Factor (questions)

Factor name

Control Group N = 70

Experimental Group N = 71

Total (n = 141)

F1 (2,4,8,20,24)

Grade Motivation (GM)

0.74

0.79

0.77

F2 (9,14,15,18,21)

Self-Efficacy (SE)

0.81

0.88

0.88

F3 (5,6,11, 16,22)

Self-Determination (SD)

0.85

0.74

0.80

F4 (1,3,12,17,19)

Intrinsic Motivation (IM)

0.81

0.68

0.81

0.91

0.92

0.92

Total

Performing Confirmatory Factor Analysis (CFA) with the JASP software, on the questionnaires from both groups (N=141), we verified the model presented by Glynn. CFA is a statistical technique which allows to test the existence of a specific relationship (model) between the observed variables (questions) and their underlying latent constructs (factors). Circles in Figure 8 represent the unobserved latent factors and squares the observed variables. Single-headed straight arrows represent the impact (the loading) of one variable on another, and double-headed bended arrows represent covariance between a pair of variables [Byrne, 2005]. In our case, CFA depicts that: • •

•

There are four factors indicated by circles, labeled as GM (Grade Motivation), SE (Self Efficacy), SD (Self Determination) and IM (Intrinsic Motivation). The 4 factors are intercorrelated as indicated by the 6 two-headed arrows. There are 20 observed variables (questions), which load on the factors in the following pattern: the factor GM groups the students’ responses on the questions 02, 04, 08, 20, and 24; the factor SE on the questions 09, 14, 15, 18, and 21; the factor SD on the questions 05, 06, 11, 16, and 22; and the factor IM on the questions 01, 03, 12, 17, and 19. Each observed variable loads on one and only one factor. Errors associated with each observed variable are uncorrelated, i.e., there are no double-headed arrows connecting any two error terms.

To access the “goodness of fit” we examine the fit indices. For example, the Comparative Fit Index (CFI) is found 0.9, the Tucker-Lewis Index (TLI) is 0.8, the Root Mean Square Error of Approximation (RMSEA) index is 0.09, and the Standardized Root Mean Square Residuals (SRMSR) index is 0.09, which are marginally below the acceptable limit, and are due to the small size of the sample (Leite & Stalpeton, 2011). The acceptable values are CFI>0.9, TLI>0.9, RMSEA 0.95) in addition to its five independent sections (a> 0.72). Due to the number of questions, 37 questions among the first four sections and 112 items from the pre and post tests were subjected to Principal Components Analysis (PCA) in order to reduce a larger set of variables into a smaller set of “artificial” variables called principle components which account for most of the variance in the original variables. Factor analysis by the PCA with varimax rotation method was performed to detect any correlations among factors, where loadings above 0.40 were recorded as significant. The Kaiser (1974) criterion (KMO = 0.873> 0.8, p 0.8, p .05), and there was a homogeneity of variances, as determined by Levene’s test for equality of variances (p = .134), as shown in Table 2. According to the results from Table 1, the attitudes were slightly improved in the experimental group (M = 0.22, SD = 1.19) than the control group (M = 0.16, SD = 1.64), but without a statistically significant difference, M = 0.06, 95% CI [-0.87, 0.74], t(54) = -0.156, p = .877. Table 1. Students’ attitudes Var S (Science), Var TE (Technology and Engineering), Var M (Mathematics)

Var S Var TE Var M

Team

N

Mean

Std. Deviation

Std. Error Mean

Control

34

,1569

1,63601

,28057

Experiment

22

,2200

1,18756

,25319

Control

34

,2326

1,15277

,19770

Experiment

22

-,6372

1,05521

,22497

Control

34

,1746

1,26850

,21755

Experiment

22

,1517

1,10720

,23605

Table 2. Independent samples test – students’ attitudes toward science, technology and engineering and mathematics Levene’s Test for Equality of Variances

Var S

Var TE

Var M

Equal variances assumed

Sig.

t

df.

Sig. (2-tailed)

Mean Difference

Std. Error Difference

Lower

Upper

2,315

,134

-,156

54

,877

-,06312

,40437

-,87383

,74760

-,167

53,196

,868

-,06312

,37792

-,82107

,69484

2,849

54

,006

,86986

,30531

,25775

1,48199

2,904

47,812

,006

,86986

,29949

,26763

1,47210

,069

54

,945

,02284

,33062

-,64001

,68570

,071

49,224

,944

,02284

,32101

-,62218

,66786

1,056

,309

Equal variances not assumed Equal variances assumed Equal variances not assumed

95% Confidence interval of the Difference

F

Equal variances not assumed Equal variances assumed

t-test for Equality of Means

,691

,409

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 Use of STEM Intervention Teaching Scenarios to Investigate Students’ Attitudes Toward STEM Professions

An independent-samples t-test set out to determine any differences in students’ attitudes towards Technology and Engineering. There were no outliers in the data, as per the Boxplot analysis. Engagement scores for each group were normally distributed, as confirmed by the Shapiro-Wilk’s test (p > .05), and there was a homogeneity of variances, as determines by Levene’s test for equality of variances (p = .309), as shown in Table 2. According to the results from Table 1, the attitudes differ significant in the pre- and post-surveys for the experimental group (M = -0.64, SD = 1.06) compared to the control group (M = 0.23, SD = 1.15), with a statistical difference, M = -0.87, 95% CI [0.26, 1.48], t (54) = 2.849, p = .006. To determine if the experimental group showed greater improvement in their attitudes compared to the control group, a unilateral test was performed. Since t> 0 and seeing that we set out to determine if there was a difference between the two groups, p = (1-0.006)/2=0.497> 0.05 hence no statistically significant difference between the groups. An independent-samples t-test set out to determine any differences in students’ attitudes towards Mathematics. There were no outliers in the data, as per the Boxplot analysis. Engagement scores for each group were normally distributed, as confirmed by the Shapiro-Wilk’s test (p > .05), and there was homogeneity of variances, as determined by Levene’s test for equality of variances (p = .409), as shown in Table 2. According to the results from Table 1, the attitudes of the experimental group (M = .15, SD = 1.11) against the control group (M = 0.17, SD = 1.27), did not show a statistically significant difference, M = -0.02, 95% CI [-0.64, 0.68], t (54) = 0.069, p = .945

Changing Students’ Attitudes Toward Self-Evaluation in 21st Century Skills and Science, Health, and Environmental Careers An independent-samples t-test set out to determine any differences in students’ self-evaluations of 21st century skills. There were no outliers in the data, as per the Boxplot analysis. Engagement scores for each group were normally distributed, as confirmed by the Shapiro-Wilk’s test (p > .05), and there was a homogeneity of variances, as determined by Levene’s test for equality of variances (p = .674), as shown in Table 4. According to the results from Table 3, the self-evaluation of the 21st century skills was improved in the experimental group (M = 0.37, SD = 1.03) as opposed to the control group (M = -0.19, SD = 1.14), with a statistically significant difference, M = 0.56, 95% CI [-1.16, - 0.04], t (54) = -1.860, p = .068. Table 3. Students’ attitudes Var SK (21st Century Skills), Var SCIENCE (Careers in Science Professions), Var HEALTH (Careers in Health Professions), Var ENVIRONMENT (Careers in Environment related Professions)

Var SK Var SCIENCE Var HEALTH Var ENVIRONMENT

352

Team

N

Mean

Std. Deviation

Std. Error Mean

Control

34

-,1867

1,14173

,19581

Experiment

22

,3725

1,102763

,21909

Control

34

-,1645

1,40963

,24175

Experiment

22

-4847

1,10094

,23472

Control

34

,0716

1,21914

,20908

Experiment

22

,6517

,93494

,19933

Control

34

-,1550

1,46280

,25087

Experiment

22

,5391

,91120

,19427

 Use of STEM Intervention Teaching Scenarios to Investigate Students’ Attitudes Toward STEM Professions

Table 4. Independent samples test – students’ attitudes toward self-evaluation in 21st century skills and science, health and environmental careers Levene’s Test for Equality of Variances

Var SK

Var SCIENCE

Var HEALTH

Var ENVIRONMENT

Equal variances assumed

Sig.

t

df.

Sig. (2-tailed)

Mean Difference

Std. Error Difference

Lower

Upper

,0179

,674

-1,860

54

,068

-,55919

,30064

-,1.16194

,04356

-1,903

48,325

,063

-,55919

,29384

-1,14989

,03151

,901

54

,371

,32016

,35525

-,39206

1,03239

,950

51,969

,346

,32016

,33695

-,35599

,99632

-1,898

54

,063

-,54011

,30570

-1,19300

,03277

-2,008

52,234

,050

-,568011

,28887

-1,15969

-,00053

-2,141

54

,037

-,74808

,34939

-1,44856

-,04760

-2,358

53,955

,022

-74808

,31729

-1,38423

-,11194

1,408

.241

Equal variances not assumed Equal variances assumed

1,902

,173

Equal variances not assumed Equal variances assumed Equal variances not assumed

95% Confidence interval of the Difference

F

Equal variances not assumed Equal variances assumed

t-test for Equality of Means

5,555

,022

An independent-samples t-test set out to determine any differences in students’ attitudes toward careers in the Hard Sciences. There were no outliers in the data, as per the Boxplot analysis. Engagement scores for each group were normally distributed, as confirmed by the Shapiro-Wilk’s test (p > .05), and there was a homogeneity of variances, as determined by Levene’s test for equality of variances (p = .241), as shown in Table 4. According to the results from Table 3, the attitudes of the experimental group (M = -0.48, SD = 1.10) compared to the control group (M = -0.19, SD = 1.14), did not show a statistically significant difference, M = -0.32, 95% CI [-0.30, 1.03], t (54) = 0,901, p = .371. An independent-samples t-test set out to determine any differences in students’ attitudes toward career pathways in Health. There were no outliers in the data, as per the Boxplot analysis. Engagement scores for each group were normally distributed, as confirmed by the Shapiro-Wilk’s test (p > .05), and there was a homogeneity of variances, as determined by Levene’s test for equality of variances (p = .173), as shown in Table 4. According to the results from Table 3, the attitudes of the experimental group (M = .65, SD = 0.93) compared to the control group (M = 0.07, SD = 1.22), did not state a statistically significant difference, M = 0.58, 95% CI [-1.19, 0.33], t (54) = -1.898, p = 0.063 in the pre and postsurvey, however a unilateral test was performed and since t < 0 and seeing that we set out to determine improvement in the experimental group compared to the control group a significant difference was recorded, p = 0.063/2 = 0.032. An independent-samples t-test set out to determine any differences in students’ attitudes toward career pathways in the Environmental Sciences. There were no outliers in the data, as per the Boxplot analysis. Engagement scores for each group were normally distributed, as confirmed by the Shapiro-Wilk’s test

353

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(p > .05), and there wasn’t a homogeneity of variances, as determined by Levene’s test for equality of variances (p = .022), as shown in Table 4. According to the results from Table 3, the attitudes of the experimental group (M = 0.59, SD = 0.91) compared to the control group (M = -0.16, SD = 1.46), showed a statistically significant difference, M = 0.75, 95% CI [-1.38, - 0.11], t (54) = -2.358, p = .022.

Improving Students’ Self-Evaluation in Mathematics and Physics A Mann-Whitney U test set out to determine any differences in the self-evaluation scores between the control and experimental groups in Mathematics. Distributions of the self-evaluation scores for the control and experimental groups were similar, as assessed by visual inspection (Figure 1). As shown in Table 5, Self-evaluation scores were not statistically significantly different between the control (Mdn = 28.59) and experimental (Mdn = 28.36) groups, U = 371, z = -0.052, p = .959, after using an exact sampling distribution for U (Dineen & Blakesley, 1973). Figure 1. Students’ self-evaluation score in Mathematics

Table 5. Man-Whitney U Test – mathematics self-evaluation across groups

354

Total N

56

Mann-Whitney U

371,000

Wilicoxon W

624,000

Test Statistic

371,000

Standard Error

57,990

Standardized Test Statistic

-,052

Asymptotic Sig.(2-sided test)

.959

 Use of STEM Intervention Teaching Scenarios to Investigate Students’ Attitudes Toward STEM Professions

A Mann-Whitney U test set out to determine any differences in self-evaluation scores between the control and experimental groups in Science. Distributions of the self-evaluation scores for the control and experimental groups were similar, as assessed by visual inspection (Figure 2). As shown in Table 6, Self-evaluation scores were statistically significantly different between the control (Mdn = 24.91) and experimental (Mdn = 34.05) groups, U = 371, z = -0.052, p = .959, after using an exact sampling distribution for U (Dineen & Blakesley, 1973). Figure 2. Students’ self-evaluation score in science

Table 6. Man-Whitney U Test - science self-evaluation across groups Total N

56

Mann-Whitney U

496,000

Wilicoxon W

749,000

Test Statistic

496,000

Standard Error

57,229

Standardized Test Statistic

2,132

Asymptotic Sig.(2-sided test)

,033

DISCUSSION The aim of the study was to investigate changes in Junior High School students’ attitudes toward STEM subjects, and future careers when introducing STEM teaching interventions, in particular programming, robotics as well as STEM activities and scenarios developed by the ESA. In particular, the teaching

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intervention was based on the 5E Instructional Model and the science-based scenarios completed by the experimental team were “Introduction to Arduino”, “Plants on Mars” and “Hello, am I speaking to planet Earth?” which provided students with multiple opportunities to build, plan and solve authentic problems relevant to the natural sciences, mathematics, technology and engineering. The results showed that the two groups (control and experimental) while initially showed similar attitudes, differed on some variables after the teaching intervention: the experimental group showed greater self-evaluation improvement as well as attitude change toward STEM careers in the health and environmental sectors, also confirmed by the research of Nugent et al. (2008). Additionally, after the teaching intervention the experimental group showed improved self-evaluation in science subjects, similarly demonstrated by Hurley’s study (2008). With regards to changes in attitudes toward STEM subjects, no differences were observed between the two groups, similar to Koskey’s (2018) research. Throughout the teaching intervention, students developed numerous skills as they engaged in electronic circuits and programming, enhanced their interaction and teamwork abilities and gradually students fulfilled, in turn, the requirements of the teaching intervention scenarios as also demonstrated by the research of Wilensky (2011). According to post-intervention teacher interviews, improvements were observed in formulating ideas, where students explained concepts with a greater ability to argue and negotiate. Students were also exposed to materials and technologies, which they had not come in contact with until the teaching intervention. This exposure sparked their curiosity, increased their interest and triggered feelings of creativity and enjoyment, as was the case in the research of Sherin (2001). Students shared that interaction and the means through which they created this interaction were the method with which they wanted to acquire knowledge because they felt that they were in control of their own discovery and creativity, and that the knowledge built held a firmer foundation and would more sustainable in the long term. Through classroom discussions, critical thinking and metacognition skills were observed since the student-built knowledge, at any given stage, could be used to solve new problems or construct more complex mechanical structures with greater ease and speed. Improving students’ attitudes toward STEM careers, as well as their self-evaluation in STEM subjects, through STEM related activities administered to a greater number of students or implemented in all schools, can reverse the downward trend observed from the PISA indicators, and grant Greek students with broader perspectives to find effective solutions to 21st century challenges.

FUTURE RESEARCH DIRECTIONS The study presents several limitations that could be addressed in future research. The teaching intervention took place from January 2020 with students in their final year of Junior High School. The study’s expected end date was April 10, 2020, but school closures in early March 2020 to prevent the spread of the pandemic did not allow for the study’s fruitful completion. An end to the lockdown period allowed to complete the teaching intervention and therefore the post-test surveys were not handed to students until mid-May 2020 once schools had reopened. Consequently, the post-test surveys were answered more than two months after the teaching intervention. To our knowledge, non-completion of all teaching scenarios as well as students’ late post-test responses resulted in distorted research results. An attempt to repeat the study and re-evaluate the results is a worthy consideration. Even better would be to avoid convenient sampling but assign the sample to entire classrooms throughout the program’s duration to 356

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further increase the reliability of results. It would also be useful to implement the instrument across more schools from different parts of Greece in order to assess the overall usefulness of STEM actions.

CONCLUSION Greece’s educational system is shifting from a traditional environment that focuses on the teacher as a provider of knowledge, to a modern one centered on students and their needs, where knowledge is built with the teacher as a guide and mentor. Encouraging students to engage in STEM activities is a step in this direction. Constructivism (Papert & Harel, 1991) together with an applied 5E Instructional Model generates results as demonstrated empirically, and the STEM-based scenarios in the teaching interventions were suitable for Year 3 students of Junior High School. The cost of materials was insignificant, and the software used in the intervention was open source, therefore free of charge. Additionally, these science-based scenarios could very well be used in computer science classes or science laboratories with senior high school students. They are simple for the teacher to administer and increase interest among students while building essential knowledge and life skills.

REFERENCES Barrows, H. S. (1996). Problem-based learning in medicine and beyond. In L. Wilkerson & W. H. Gijselaers (Eds.), New directions for teaching and learning. Bringing problem-based learning to higher education: Theory and practice (pp. 3–13). Jossey-Bass. Benitti, F. B. V. (2012). Exploring the educational potential of robotics in schools: A systematic review. Computers & Education, 58(3), 978–988. doi:10.1016/j.compedu.2011.10.006 Burke, L., Francis, K., & Shanahan, M. (2014). A horizon of possibilities: a definition of STEM education. In STEM 2014 Conference (pp. 12-15). Academic Press. Bybee, R. W. (2019). Using the BSCS 5E instructional model to introduce STEM disciplines. Science and Children, 56(6), 8–12. doi:10.2505/4c19_056_06_8 Bybee, R. W., Taylor, J. A., Gardner, A., Van Scotter, P., Powell, J. C., Westbrook, A., & Landes, N. (2006). The BSCS 5E instructional model: Origins and effectiveness. BSCS, 5, 88–98. Casner-Lotto, J., & Barrington, L. (2006). Are they really ready to work? Employers’ perspectives on the basic knowledge and applied skills of new entrants to the 21st century US workforce. Partnership for 21st Century Skills. Dave, V., Blasko, D., Holliday-Darr, K., Kremer, J. T., Edwards, R., Ford, M., Lenhardt, L., & Hido, B. (2010). Re-enJEANeering STEM Education: Math Options Summer Camp. The Journal of Technology Studies, 36(1), 35–45. doi:10.21061/jots.v36i1.a.5 Dori, Y. J., Mevarech, Z., & Baker, D. (2018). Cognition, metacognition and culture in STEM education. Springer. doi:10.1007/978-3-319-66659-4

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Edelson, D. C., & Reiser, B. J. (2006). Making authentic practices accessible to learners: Design challenges and strategies. In K. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 335–354). Cambridge University Press. English, L. D. (2016). STEM education K-12: Perspectives on integration. International Journal of STEM Education, 3(1), 3. doi:10.118640594-016-0036-1 Faber, M., Unfried, A., Wiebe, E. N., Corn, J., Townsend, L. W., & Collins, T. L. (2013, June). Student attitudes toward STEM: The development of upper elementary school and middle/high school student surveys. Proceedings of the 120th American Society of Engineering Education Conference. Feldhausen, R., Weese, J. L., & Bean, N. H. (2018). Increasing Student Self-Efficacy in Computational Thinking via STEM Outreach Programs. Proceedings of the 49th ACM Technical Symposium on Computer Science Education, 302–307. 10.1145/3159450.3159593 Honey, M., Pearson, G., & Schweingruber, H. A. (Eds.). (2014). STEM integration in K-12 education: Status, prospects, and an agenda for research (Vol. 500). National Academies Press. Jonassen, D. H. (2007). Learning to solve complex, scientific problems. Lawrence Erlbaum Associates. Kelley, T. R., & Knowles, J. G. (2016). A conceptual framework for integrated STEM education. International Journal of STEM Education, 3(1), 11. doi:10.118640594-016-0046-z Koskey, K. L., Ahmed, W., Makki, N., Garafolo, N., Kruggel, B. G., & Visco, D. P. (2018, June). Board 154: Zipping to STEM: Integrating Engineering Design in Middle School Science. 2018 ASEE Annual Conference & Exposition. 10.18260/1-2--29957 Moore, T. J., & Smith, K. A. (2014). Advancing the state of the art of STEM integration. Journal of STEM Education: Innovations and Research, 15(1), 5. National Academies of Sciences, Engineering, and Medicine. (2019). Science and Engineering for Grades 6–12: Investigation and Design at the Center. The National Academies Press. doi:10.17226/25216 Nugent, G., Barker, B., & Grandgenett, N. (2008, June). The effect of 4-H robotics and geospatial technologies on science, technology, engineering, and mathematics learning and attitudes. In EdMedia+ Innovate Learning (pp. 447-452). Association for the Advancement of Computing in Education (AACE). Palincsar, A. S., & Herrenkohl, L. R. (1999). Designing collaborative contexts: Lessons from three research programs. In A. M. O’Donnell & A. King (Eds.), Cognitive perspectives on peer learning (pp. 151–177). Erlbaum. Papert, S., & Harel, I. (1991). Situating constructionism. Constructionism, 36(2), 1–11. Psycharis, S. (2018, September). Computational thinking, engineering epistemology and STEM epistemology: A primary approach to computational pedagogy. In International Conference on Interactive Collaborative Learning (pp. 689-698). Springer. Psycharis, S., Kalovrektis, K., Sakellaridi, E., Korres, K., & Mastorodimos, D. (2018). Unfolding the Curriculum: Physical Computing, Computational Thinking and Computational Experiment in STEM’s Transdisciplinary Approach. European Journal of Engineering Research and Science, 19-24.

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Psycharis, S., Kalovrektis, K., & Xenakis, A. (2020). A Conceptual Framework for Computational Pedagogy in STEAM education: Determinants and perspectives. Hellenic Journal of STEM Education, 1(1), 17–32. Rennie, L. J., & Heard, M. R. (2012). Scientists in Schools: Benefits of Working Together. 2nd International STEM in Education Conference. Roschelle, J., & Teasley, S. (1995). The construction of shared knowledge in collaborative problem solving. In C. E. O’Malley (Ed.), Computer supported collaborative learning (pp. 69–97). Springer-Verlag. doi:10.1007/978-3-642-85098-1_5 Sengupta, P., & Wilensky, U. (2011). Lowering the learning threshold: Multi-agent-based models learning electricity. In Models and Modeling (pp. 141–171). Springer. doi:10.1007/978-94-007-0449-7_7 Sherin, B. L. (2001). How students understand physics equations. Cognition and Instruction, 19(4), 479–541. doi:10.1207/S1532690XCI1904_3 Trilling, B., & Fadel, C. (2009). 21st century skills: Learning for life in our times. John Wiley & Sons. Vasquez, J. A. (2014). Developing STEM site-based teacher and administrator leadership. Exemplary STEM Programs. Vasquez, J. A. (2015). STEM-Beyond the Acronym. Educational Leadership, 72(4), 10–15. Vasquez, J. A., Sneider, C. I., & Comer, M. W. (2013). STEM lesson essentials, grades 3-8: Integrating science, technology, engineering, and mathematics. Heinemann. Verner, I. M., & Revzin, L. B. (2017). Robotics in school chemistry laboratories. In Robotics in education (pp. 127–136). Springer. doi:10.1007/978-3-319-42975-5_12 Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.

ADDITIONAL READING Alimisis, D. (2013). Educational robotics: Open questions and new challenges. Themes in Science and Technology Education, 6(1), 63–71. Alimisis, D., & Kynigos, C. (2009). Constructionism and robotics in education. Teacher Education on Robotic-Enhanced Constructivist Pedagogical Methods, 11-26. Breiner, J. M., Harkness, S. S., Johnson, C. C., & Koehler, C. M. (2012). What is STEM? A discussion about conceptions of STEM in education and partnerships. School Science and Mathematics, 112(1), 3–11. doi:10.1111/j.1949-8594.2011.00109.x Crippen, K. J., & Antonenko, P. D. (2018). Designing for collaborative problem solving in STEM cyberlearning. In Cognition, metacognition, and culture in STEM education. Springer.

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English, L. D. (2017). Advancing elementary and middle school STEM education. International Journal of Science and Mathematics Education, 15(1), 5–24. doi:10.100710763-017-9802-x Khine, M. S. (2017). Robotics in STEM Education: Redesigning the Learning Experience. Springer. doi:10.1007/978-3-319-57786-9 Psycharis, S. (2016). The Impact of Computational Experiment and Formative Assessment in Inquiry Based Teaching and Learning Approach in STEM Education. Journal of Science Education and Technology, 25(2), 316–326. doi:10.100710956-015-9595-z Wang, H. H., Moore, T. J., Roehrig, G. H., & Park, M. S. (2011). STEM integration: Teacher perceptions and practice. Journal of Pre-College Engineering Education Research, 1(2), 2.

KEY TERMS AND DEFINITIONS Attitude: A positive or negative feeling toward a particular subject or object (e.g., STEM education, Information and Communication Technologies). Education: The process of facilitating learning, or the acquisition of knowledge, skills, values, beliefs, and habits. ESA: The European Space Agent is an intergovernmental organization dedicated to the exploration of space. Intervention: A set of skills-building activities which the student completes during a portion of the school day to help improve academic abilities such as reading, writing, or math. Perception: The process by which a person combine knowledge and idea has gained as a result of having an experience in relation to a topic. Principal Component Analysis (PCA): A statistical procedure that is used to identify which items or factors in a questionnaire are highly correlated with each other. Problem-Based Learning: A learning approach in which learners inquire into real problems about important questions and issues that have no clear answers. STEM: A teaching philosophy that integrates all four disciplines (Science, Technology, Engineering, Mathematics) into a single, cross-disciplinary program which offers instruction in real-world applications and teaching methods.

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A Teaching Sequence Proposal Using Microcontrollers Programmed With BASIC Thomas Francis Hartley Independent Researcher, Australia

ABSTRACT This chapter presents three electronics-based projects at increasing levels of sophistication. Two of the projects use the PIC microcontroller-based MicroMite chip. One uses the new Raspberry Pi PICO microcontroller board. All three deliver base level units that monitor atmospheric pressure (Projects 1 and 2) and ambient light levels (Project 3). All three communicate bidirectionally with an app on an Android mobile phone via the popular and well supported Bluetooth protocols. In the final technical section of the chapter, the content of those Bluetooth communications are ‘pushed’ onto a local IoT intranet design. The chapter closes with a brief summary of the STEAM initiatives in Australia plus a brief discussion of the importance of electronics in contemporary life which arguably justifies their inclusion in STEAM curricula content.

INTRODUCTION In the current age, it is indisputable that Information and Communication Technologies (ICT) have permeated our lives and are ubiquitous in every aspect of our daily routine. Since the early 20th century, technology has been envisioned as and promised to be a perfect tool that will transform the way we interact with learning material, change the way we learn and make teaching sequences more interesting, immersive and successful. In the course of integrating technology with learning sequences there have been many successful stories, but this integration also ended in quite a few disappointments. Students nowadays are “digital natives” and significantly familiar with many aspects of ICT. It is clearly important for this generation, to acquire the so-called 21st century skills (Geisinger, 2016).

DOI: 10.4018/978-1-6684-3861-9.ch017

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 A Teaching Sequence Proposal Using Microcontrollers Programmed With BASIC

Science, Technology Engineering Arts and Mathematics (STEAM) education affordances have been increasingly integrated in modern curricula, aiming to provide students with not only “core” knowledge from the various disciplines but also teach them problem solving skills, critical thinking, creativity, communication skills and in general digital and information literacy (Khine & Areepattamannil, 2019; Taylor, 2016; Xefteris, 2019). The STEAM framework has been shown to be instrumental in reconceptualizing instructional strategies and models, focusing educators and students on “learning how to think and learning how to learn” (Ge, Ifenthaler, & Spector, 2015). The framework is targeted towards transdisciplinary and multimodal contexts of presenting learning material, combining different learning areas and uncovering hitherto “hidden” relationships among different disciplines (Hayman, 2017). In this context, the introduction of programming activities in curricula is a promising and highly versatile tool that enables educators to formulate the sought-after transdisciplinary and highly engaging learning activities. There are many approaches and different formulations of courses using microcontrollers or micro PCs to engage students in project based activities under a STEAM framework, tackling different aspects and using one or more modalities such as educational robotics, Arduino, Raspberry Pi etc. (de Souza & Elisiario, 2019; Zhong & Liang, 2016). In this chapter a teaching sequence is proposed, based on the use of microcontrollers that are programmed using ‘Basic’. The core materials of the presented projects include the new Raspberry Pi Pico board and the PIC microcontroller based MicroMite chip. The teaching sequence consists of three projects at increasing levels of sophistication. Projects 1 and 2 deliver an atmospheric pressure monitor and project 3 delivers an ambient light level monitor. All projects communicate bidirectionaly with an Android mobile app via a Bluetooth connection. In the final section, measurements are pushed onto a local IOT intranet. The teaching sequence aims at inducing a problem based learning activity, emphasizing on evaluation of results.

BACKGROUND STEAM Education in Australia The Australian Science Curriculum outlines perspectives on how to engage students with material that facilitates basic uni-disciplinary knowledge and skills but also highlights the significance of the acquisition of higher-order skills for functioning in a highly and constantly evolving technology saturated environment. In this, the Australian Science Curriculum provides a roadmap that urges educators to create learning sequences that make use of multiple modalities and engage students in developing inquiry skills through the conceptual acquisition of scientific concepts (“The Australian Curriculum,” 2021) In this context, Australia’s chief scientist has called for educational reforms that facilitate the students’ engagement with STEM disciplines, in order to future-proof Australia’s high tech digital workforce (Taylor, 2016). Although STEAM education aspires to be Australia’s nationwide focus for innovation and for arming students with much desired 21st century skills, including the ability to “think smart and creatively, solve problems, take risks, have strong digital skills and collaborate effectively” (PriceWaterhouseCoopers, 2015) it seems there is much to be desired for considering the state of education in the nation’s schools, especially at the secondary level, where STEAM based curriculum resources are scarce. A report by

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(Deloitte, 2015) outlines that educators need to embrace and add the “A” in STEM in order to foster the students’ creative design and performance. The uptake of the STEAM initiative in Australia is at an early stage. The two largest States – Victoria and New South Wales – have documentation on their Educational Department websites around the need for STEM to become a reality in their Years K to 12 curricula(“About STEM education in Victoria,” 2021; “STEM Education in New South Wales,” 2021). The documentation tackle issues around the migration from existing science and mathematics curricula to a STEM focus and the pedagogical arguments for the migration. State based activities for trainers to up skill in this area are also covered. Unfortunately, it would seem that the Coronavirus Pandemic which started in 2019 meant that such events did not proceed. So at this point in time there does not appear to be an across the board position statement that one could make about STEM in Australia, with the “A” of STEAM largely missing from online. Following on from this position that there is a ‘foundation’ skills requirement, the approach in this Chapter has been to provide launch pads for the students’ ideas. It just so happens that they are all electronic but in reality, so much in contemporary life now revolves around an ‘electro-mechanical device’ of some sort. Explicit developments or even suggestions as to how the Project Boards can be used have purposely been avoided. Commentary was made in the previous paragraph that documentation around STEAM is still embryonic at the ‘Educational Departmental’ level but this does not mean there is none available in the Australian environment. For example, the company LAPtek which is based in Mount Waverley, Victoria Australia have ten titles in their ‘Victorian Curriculum Design and Technologies STEM-D and STEAM (Years 5 – 10)’ series(“Victorian Curriculum Design & Technologies Stem-D and STEAM (Years 5 to 10),” 2021). These are all written in formats that match the conventional teaching and learning outcomes required by educators. Everton Park State High School in Queensland, Australia, have posted their powerpoint on STEAM into STEM: Linking to the Australian Curriculum online (STEAM into STEM: Linking to the Australian Curriculum, 2021). In Australia there are two magazines that can be considered good resources for students. DIYODE magazine (“DIYODE Magazine,” 2021) has been publishing hard copy and e-copy since July 2017. They intentionally publish items that are relevant to electronics in STEAM at all levels. Content in each issue tends to be rather mixed but given that they have nearly 5 years of back issues students should be able to locate several items of interest and/or assistance. SILICON CHIP is more technical magazine that covers a broader range of amateur and professional electronic topics and projects. They have been publishing since November 1987 and have an extensive archive of back issues (“Silicon Chip Online,” 2021). They also produce printed circuit boards for almost all of their projects which means that a student could very quickly get a head start with a project built on a proven and stable baseboard.

Teaching STEM With Microcontrollers In the recent years, there is a significant trend for educators using microcontrollers in teaching sequences integrating a veritable plethora of modalities: IOT, game design and robotics, Arduino, Raspberry, Micro:Bit etc are used to create novel and highly interesting educational sequences (Fidai et al., 2019; Tsai, Hsiao, Yu, & Lin, 2021; Yasin, Prima, & Sholihin, 2018). Lately, microcontrollers manufacturers have been steadily focusing on the premise that “the application is more important than the program”. That the end result, the solution to the problem, is more significant for the learning experience of the students than simply learning a programming language. To get an insight into this one only has to review how microcontroller manufacturers have supported the educational sector around the World with 363

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literature and user forums which are definitely biased towards applications. For example, the distributors of the PICAXE microcontroller (picaxe.com), which is popular in the UK and Europe, provide support educators and forums for users. The PICAXE is programmed in their version of BASIC via a conventional text based editor and compiler, but they have also provided a visual programming environment ‘Blockly for PICAXE’. Visual programming portals were launched originally by Google in an attempt to make programming more approachable. Visual programming moves the programmer away from having to master a ‘language’ and instead approach programming as a construct of interlocking modules. These initiatives have now been taken under the umbrella of various prestigious organisations with the most prominent being the Massachusetts Institute of Technology (MIT) which has developed Scratch, ScratchJr, StarLogo and Godot. The BBC micro:bit is another microcontroller popular in the UK and Europe. Their website (“Lessons | micro:bit,” 2021)provides a wealth of ‘lessons’ that provide a well balanced curriculum of coding and applications. Visual programming is also possible with the micro:bit; their recommended visual programming application is Microsoft’s Make Code. The Arduino which is more of a microcontroller board than a bare bones microcontroller has a huge international following and educational resources that cover students from 11 years old to tertiary. Because of its long history in the market place the Arduino is predominantly programmed using a text based IDE but it can also be programmed using the visual programming tools - Scratch and Snap!. Finally mention has to be made of Raspberry Pi. This was brought onto the market with the intention of providing an alternative to the Arduino. This has not happened because the Raspberry Pi is a microcomputer board which has been purposely fitted with multiple digital and analog input pins to give it the appearance of a microcontroller. In reality it is a fully fledged Linux computer running a version a of Debian Linux called Raspian. Another reason it has not surpassed the Arduino is that the cost has ballooned out to approximately five times the cost of an Arduino. Raspberry Pi are also fully committed to educators (“Teach computing and digital making – Raspberry Pi,” 2021; Zhong & Liang, 2016)but the majority of their focus is on information technology. To offset this higher end focus, there are other simpler Raspberry Pi hardware devices and in this chapter their ‘lowest specification’ device marketed to date, the Raspberry Pi Nano, is included as it truly is a bare bones microcontroller module. The chapter aims at providing a highly detailed teaching sequence in tutorial form, avoiding overcomplicated designs on circuits boards that more often than not end up in “birds nest” wiring that frustrates novice students from further using the paradigm, as seen in Figure 1.

DESCRIPTION OF THE PROPOSED TEACHING SEQUENCE Educational Objective The aim of the proposed teaching sequence is to introduce students to the PIC family of microcontrollers with the minimum prerequisites for high level construction or programming skills. The prime objective is to facilitate the students’ engagement through the implementation of a “real life” problem to be solved, minimizing the “conceptual clutter” of intricate construction, wiring and highly complicated programming, emphasizing on the evaluation of the end result.

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Figure 1. An example of an Arduino based breathalyzer circuit implementation

Desirable Pre-Existing Skills Reasonable manual dexterity and some familiarity with handling integrated circuits and soldering simple components like resistors to Veroboard. Students with some intention tremor may find soldering more of a challenge in which case some relief can be achieved by using larger pieces of circuit board and spacing the components further apart. In Project 1 the items are firmly located by gluing them to Leg bricks with double sided mounting tape. This approach is recommended for younger students and those with dexterity problems. Soldering items that are mechanically stable and easily accessible are significantly easier to work with.

Intended Learning Outcomes Because the construction aspects of the projects are simple, they can be completed in short periods of time. This will leave the students with more time to concentrate on the important tasks of: • • •

IOT sensor sensor selection and location design, microcontroller programming beyond the basic capabilities of the three projects described in this chapter deployment of mechanically and programatically sound IOT devices.

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Material Requirements The basic equipment list for the implementation of the proposed projects is as follows: 1. Materials ◦◦ Access to a Windows or Linux PC ◦◦ Access to an Android mobile phone with a Bluetooth serial terminal app. ◦◦ A soldering iron ◦◦ Small hand tools including a Veroboard copper track cutting tool ◦◦ Alkaline cell batteries ◦◦ Integrated circuits: ◦◦ MicroMite PIC integrated circuit chip ◦◦ USB-TTL converter module ◦◦ HC-05 Bluetooth module ◦◦ Real Time Clock module ◦◦ Atmospheric Pressure module ◦◦ Light Dependent Resistor (LDR) module ◦◦ Low voltage power supply module ◦◦ Solid core hookup wire ◦◦ Screw Terminal blocks ◦◦ Lego style baseboards and bricks ◦◦ Small pieces of Veroboard ◦◦ 10X magnification hand lens 2. MicroMite and the Raspberry Pi Pico The MicroMite was invented by Geoff Graham. He pioneered the porting of the BASIC programming language interpreter into the protected memory space of a PIC microcontroller. His objective was to make it simpler for users to program the PIC microcontroller using a high-level programming language which has been in use since the very early days of personal computers. He has added commands that make it simple to access the analog, digital and serial I/O pins of the chip. The other significant advantage of his solution is that there is absolutely no requirement for the user to load additional software onto their computer in order to work with these chips. All that is required is a conventional VT100 terminal emulator program – TerraTerm for Windows PCs and PuTTY for Linux, Several versions of PIC microcontrollers can be used in this way. This chapter is restricted to the 28 pin DIL package: PIC32MX150F128B-50I/SP. The Raspberry Pi PICO when loaded with Geoff Graham’s MMBASIC interpreter is referred to as the PicoMite. The MicroMite is programmed in a version of BASIC that is almost identical to Microsoft’s original GWBasic of the 1980’s. Additional commands have been added by the developer, Geoff Graham, so as to facilitate programs to interact with the pins on the microcontroller. In addition, there are additional commands and functions that facilitate the use of sensors that communicate via an I2C protocol, the 1-Wire protocol or the SPI protocol. The projects described in this chapter use an atmospheric pressure sensor and a real time clock module that both communicate with the microcontroller using the I2C protocol.

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The MMBASIC interpreter that Geoff Graham has developed for the Raspberry Pi PICO has gone even further and the version of BASIC that can be loaded onto that hardware has extended the commands to make it particularly suited to graphical displays.

THE PROJECTS Project 1: A Simple MicroMite Based Design The objective of this project is to demonstrate that the MicroMite can be used as a simple and inexpensive standalone IOT device. This has been achieved by programming a MicroMite 28 pin chip via the conventional PC USB connection to the Editor. Then disconnecting it from the PC and transmitting the MicroMite’s terminal output data stream over Bluetooth into an Android App running on an inexpensive mobile phone. The required components for the project are: • • • • • • • • • • • •

MicroMite 28 pin PIC Controller chip preloaded with MMBASIC and a tantalum capacitor as recommended by Geoff Graham. An HC-05 Bluetooth module preferably one with an ‘Enable’ push button key. A USB to TTL converter A BMP180 atmospheric pressure sensor A short USB male to female converter cable. A 4 X AA battery holder modified by tapping the output voltages at 3V and 4.5V. (The fourth battery is not needed and that position can be left empty.) A small piece of Veroboard. A Veroboard copper track cutting tool. Short strips of Arduino style header pins Hook up wire An Android mobile phone with the Bluetooth Terminal App by Kai Morich Installed There are three groups of tasks to complete:

• • •

Construct the core circuit board that contains MicroMite PIC controller chip. Select a suitable VT100 serial terminal emulator to run on your PC. For Windows users TeraTerm appears to be the most favoured. For Linux users PuTTY SSH Client is recommended. Construct a simple circuit to set the correct baud rate etc. for the HC-05 Bluetooth Module Add the USB-TTL converter, HC-05 Bluetooth module and the BMP180 Atmospheric Pressure module at optimum positions around the core circuit board. Type in the BASIC program read and decode all the data stream from the BMP180 sensor. Load the Bluetooth Terminal App onto an Android mobile phone to view the sensor’s output without needing any physical connection to a PC.

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Task 1: In this task the PIC microcontroller preloaded with the MicroMite BASIC interpreter is mounted on a small rectangle of Veroboard and wired up so that it forms the core circuit board versatile enough to be relocated into other MicroMite based projects. Refer to Figure 2 during this task. It will assist in understanding the how the components are best located. Refer to Figure 3 and Figure 4 to understand which pins on the MicroMite controller are being referred to. Select a small piece of Veroboard; 16 holes wide by 20 holes long is the minimum size. The copper tracks should be parallel to the short edge. Insert the MicroMite chip 3 rows down from the short edge; (these three rows will be referred to later as rows {a}, {b}, and {c}). The small semicircular indentation in the MicroMite chip should be closest to this same edge of the Veroboard. Carefully solder each leg of the MicroMite chip to the copper tracks underneath. Using the Veroboard track cutting tool cut the 14 tracks between the legs of the MicroMite chip so that the legs of the chip are not shorted to each other. 2 rows away from the legs of MicroMite chip solder two strips of 14 Arduino style header pins with their long leg pointing up from the non-copper strips side of the Veroboard. Solder these two strips to the copper tracks underneath. Solder 2 more pins adjacent to pin 11 and 12 of the MicroMite chip. The MicroMite chip is usually supplied with a 47 µF tantalum capacitor and this should be soldered across pins 19 and 20 of the MicroMite chip. Note that the capacitor is polarised i.e. it has a positive and negative wire. Ensure that the positive wire of this capacitor is soldered to pin 20’s copper track. The following point to point wiring is required: {b} {a} {a} {a} {b} {b} {a} {b}

to to to to to to to to

MicroMite pin 8 MicroMite pin 13 MicroMite pin 1 MicroMite pin 28 MicroMite pin 19 MicroMite pin 27 the +ve 3V tapping in the battery pack the -ve point in the battery pack

The core circuit board is now complete. A suggestion is that it is now glued to some Lego blocks using double sided mounting tape and the assembly located at a convenient point on a piece of Lego base board. Firmly mounting items in this way is particularly suited to younger students because it locates the items firmly while soldering wires between them. Task 2: In this task the HC-05 module is setup before mounting it onto the Project 1 Lego baseboard and wired to the core circuit board. The HC-05 has to be setup so that it runs at the correct baud rate for the MicroMite chip. The USB-TTL converter module is wired to the core circuit board. Install a VT100 compatible terminal software onto a PC. Follow the instructions provided by the serial terminal software publisher that apply to that PC’s hardware and operating system. The HC-05 Bluetooth module has many similarities to a modem. The first step is to supply the module with the appropriate commands to set up the baud rate etc. These are sent as ‘AT’ commands. To do this you have to connect the module to your computer as per the diagram in Figure 5. Because this circuit is not permanent a convenient solution is to use double end female Arduino patch leads. The 5V supply required for the HC-05 module can often be picked up from the USB-TTL converter but if that is not possible a battery will have to be used as shown in Figure 5.

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Figure 2. Topside view of the Project 1 board

Figure 3. The 28 Pin DIL PIC32MX150F128B-50I/SP Micromite Chip and Wiring for the Project 1 Core Board

Startup your terminal program on your PC and plug the USB to TTL converter into a convenient USB port on your PC using a short USB male to female USB cable. The terminal software will require information about which USB port it should connect to. This is done in Windows using the device manager. In Linux, when there are no other USB devices plugged into the computer, then the usual USB designation usually defaults to /dev/ttyUSB0. If other USB devices are already plugged into the PC then this address could be anything between ttyUSB0 and tyUSBN where N is the number of USB ports on the PC minus one.

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Figure 4. Project 1 wiring diagram

Figure 5. Circuit Required to Communicate with the HC-05 Module During Setup

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Hold down the button on the HC-05 module and turn the switch on the battery box to the ‘ON’ position. If the battery box is not being used then unplug the USB-TTL converter – HC-05 combination and then while holding the button on the HC-05 module plug the combination back in. Wait a couple of seconds before releasing the button. The red LED on the HC-05 module should flash slowly. Now type in AT on the computer terminal program and the module should respond with OK. If it does not then there is probably a baud rate mismatch so check that the terminal is communicating with the HC-05 at 9,600 baud, 8 bits, No parity, 1 stop bit, no flow control. Also the Enter Key on your PC needs to be mapped as a carriage return plus line feed usually signified in the terminal software as CR/ LF. The other baud rate to try is 38,400. Different manufacturers have different default baud rates on first use so it may be necessary to consult the device manufacturer’s data sheet for that item. Once you have an OK on the PC’s screen then proceed to enter these two commands: AT+UART=38400,1,0 AT+NAME=MMITE01

If both commands have been successful then then an OK should have been received after each one. Check that the required settings have been recorded into the module by typing in AT+UART which should get the response 38400,1,0 AT+NAME which should get the response MMITE01

Dismantle the HC-05 module from the temporary wiring. Take a six way long legged header socket and glue it to a suitable sized Lego brick using double sided mounting tape. Place that brick at a suitable location on the Lego baseboard e.g. as shown in Figure 2. Plug the HC-05 into that header. Use a self adhesive label to mark out the pin names in their correct positions and stick that to the header. Proceed to use short lengths of hook up wire to connect: • • • •

HC-05 Rx to MicroMite Pin 11 core circuit board HC-05 Tx to MicroMite Pin 12 core circuit board HC-05 GND to Row {b} core circuit board HC-05 Vcc to +4.5V wire from the Battery Pack

The procedure for wiring the USB-TTL module to the core circuit board is similar. Take a six way long legged header socket and glue it to a suitable sized Lego brick using double sided mounting tape. Place that brick at a suitable location on the Lego baseboard e.g. As shown in Figure 2. Plug the USBTTL module into that header. If the pin assignments are not visible from the topside use a self-adhesive label to mark out the pin names in their correct positions and stick that to the header. Proceed to use short lengths of hook up wire to connect: • • •

USB-TTL Rx MicroMite Pin 11 core circuit board USB-TTL Tx MicroMite Pin 12 core circuit board USB-TTL GND MicroMite Pin 8 core circuit board

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The Project Board should now closely resemble the arrangement in Figure 2 but without the BMP180 module in place. At this point the battery pack can be glued to the underside of the Leg base board and the Project powered up. Connect the USBTTL module to the PC running the VT100 terminal emulation program. Press the CTRL and C keys simultaneously on the PC keyboard and the terminal program should then display the MicroMites’ “>” command prompt symbol. If not refer to the debugging section for this Project 1. Task 3. This section describes the wiring up of the BMP180 Atmospheric Pressure sensor module to the core circuit board followed by the programmatic setup for that sensor. The procedure for wiring the BMP180 module to the core circuit board is similar to that already described above. The schematic can be seen in Figure 6. Figure 6. Inter connections of the modules in project 1

Take a six way long legged header socket and glue it to a suitable sized Lego brick using double sided mounting tape. Place that brick at a suitable location on the Lego baseboard e.g. As shown in Figure 2. Plug the BMP180 module into that header. If the pin assignments are not visible from the topside use a self-adhesive label to mark out the pin names in their correct positions and stick that to the header. Proceed to use short lengths of hook up wire to connect: • • • •

BMP180 SDA to MicroMite Pin 18 core circuit board BMP180 SCL to MicroMite Pin 17 core circuit board BMP180 GND to Row {b} core circuit board BMP180 VCC to Row {a} core circuit board

The BMP180 sensor is an I2C device and this means that it is a serial communications device that sends and receives information via special format of ‘words’. At this point it is not necessary to understand that format but just to load and edit the the program written by Jim Rowe which is available free of charge from the Silicon Chip Shop webpage [ http://www.siliconchip.com.au/Shop/Download/4521/8992 ].

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Edit out all lines which pertain to formatting and/or displaying information on the LCD screen that is presumed to be connected to the MicroMite in that program. Replace all of that detail with simple Print commands. Run the program and confirm that it all performs correctly in the usual PC ‘RUN’ terminal mode. Shutdown the PC terminal and unplug the Project 1 board from the PC’s USB port. Install the Bluetooth Terminal App on your mobile phone. Power up the Project Board. Notice that the red LED on the HC-05 module is flashing rapidly. Follow the instructions for connecting a bluetooth device to the Bluetooth Terminal App on your phone. The steps involve registering the HC-05 with the phone’s Bluetooth devices list. It will first show up as a alphanumeric address similar to an IP address but segmented into several pairs of hexadecimal characters. Once you provide the password of 0000 or 1234 your HC-05 should then appear on the list as MMITE01. Return to the Bluetooth Serial App on the phone and select MMITE01 as the required device to connect with. Successful connection to the HC05 will be detectable by the flashing LED having slowed down considerably. The App should also be displaying exactly as has been observed previously seen on the PC’s terminal screen. If not then turn the battery power to the Project 1 board off and on again. Whenever the Project 1 board is powered down and up the the Bluetooth Terminal App will report it has lost the connection. Tap on the connect icon in the App and connection should be re-established without any further need for user inputs or adjustments. A typical screen on the mobile phone is shown in Figure 7. Figure 7. Example of bluetooth connection to micromite via the android phone app

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This particular App has a data Log option so all input and output communications can be recorded for later reference and use e.g. pasting into Excel and plotting graphs. There is also another advantage from using this particular Bluetooth Terminal App – it adds the current date and time to every line of data received thereby making it unnecessary to build a RTC module into Project 1. In fact, now that the data is resident in the mobile phone there are now opportunities to exploit the computing capabilities of the mobile phone by downloading or writing Apps that work with these data. When the MicroMite is programmed to AutoStart it does so before the HC-05 has had time to complete its communication stream with the Bluetooth serial terminal app on the Android mobile phone. As a result, it appears as though there is no communication with the project. In fact, the communication is probably all OK and a stop and restart of the MicroMite will resolve this problem. To stop the MicroMite send a CTRL-C combination from the Bluetooth terminal program on the mobile phone. If the recommended serial terminal app is being used then it possible to program a macro key (M1) to store the CTRL-C code under that location; see Figure 8. Figure 8. Programming a macro key on the android Bluetooth serial terminal app

Project 2: A more Versatile MicroMite Based Design This project takes the design in Project 1 to a more permanent and versatile configuration by adding a dual voltage power supply, a real time clock and a terminal strip that brings many of the useful interface pins of the MicroMite to the edge of the circuit board. Sensors can then be quickly and easily connected via fly leads to this terminal strip. That also means that the placements of the IOT sensors

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are not confined to the circuit board and, for example, can now be arranged in appropriate positions on some scientific apparatus being used in a STEAM experiment. The real time clock provides for true time and date data for your programs. The timer available under MMBASIC can only provide the elapsed time since the onboard program was first started. Robust IOT data logging applications need access to the true time and date in order to add a timestamp to readings as and when they are collected. (Under MMBASIC it is possible to set the date and time within the program but if the requirement is for the program to autostart without a pause for an operator to input the current date and time, then a real time clock module is essential.) The design requires some additional components to those required for Project 1: • • • • • • •

Veroboard style copper track board: 95mm wide by 152 mm long with holes spaced 2.5 mm apart. This board has holes that occupy 60 columns by 34 rows. A Real Time Clock module PCB mount style terminal strip A Breadboard style power module 3- and 6-way stackable headers; pins should be approximately 11 mm long. A 4 X AA battery holder with an on/off switch and a short cable terminated with DC connector – centre pin positive.

The circuit is simple and is shown in Figure 9. The objective is to build it in such a way that all components are connected via ‘point to point’ wiring above the strip board. One of the major causes of wiring errors in electronics projects is that the circuit diagram is a topside view of how the components are connected. When under board wiring is used it is very easy to get disorientated; if you tip the circuit board in a ‘bottom to top’ direction then what is ‘bottom’ on the circuit diagram is now ‘top’. The foolproof solution is to create a printed circuit but that is beyond the scope of these projects. Our objective is to get circuits built as quickly as possible so that more time can be devoted to the intended application. Hence the ‘point to point’ above board wiring up approach has been followed here. Figure 9. Project 2 Circuit Diagram

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Task 1: The power supply module is designed to easily plug into a breadboard and in order to make it mechanically stable when plugged into the breadboard it has three pins per voltage rail. In this project the power supply is being used in a different orientation from that intended by the manufacturer so eight of these pins have to be cut off before soldering it to the strip board. The correct pins to cut off when viewed from below and the power module on the right-hand upper corner are described in Table 1 Table 1. Underside of the power module Underside of the Power Module 3.3 Volt Output End

5 Volt Output End

x

x

5V

x

3.3 V

x

x

x

x

GND

x

GND

Push the pins into the strip board in the top left hand position as shown in Figure 10. Check that the 4 X AA battery pack intended for connection to the power supply has the correct design of plug to match this power supply module and that the centre of its plug is at +ve 6 volts. When switched on the LEDs on the module should light up and the voltages on the strip board should be +3.3 volts and +5 volts. If there are 5 volts on both strips then that indicates either incorrect wiring/pin removal or that the voltage selector on the power module has been switched across to the 5V position. The latter is easily corrected. Figure 10. Project 2: Topside view of the completed board

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Figure 11. Project 2: Underside view

Task 2: Turn off the battery pack and unplug it from the power module. Carefully bend the pins on the three long pin headers selected for use with the modules. Then solder them into convenient locations on the strip board; Figure 9 indicates suitable positions on the recommended size of strip board. Solder the 28-way DIL socket into a convenient position near the centre of the strip board. Solder the 15-position terminal strip as close as practical to the right had edge of the strip board. Solder in the tantalum capacitor across pins 19 and 20 of the DIL socket taking care to observe the polarity requirement – refer to Figure 3. Task 3: Plug in the three modules into their respective headers. Figure 4 and Figure 10 show the pin assignments on the three modules used by the author. Be aware that these pin assignments are not universal, and they should be checked against the actual pin assignments on the locally supplied modules. Task 4: Turn over the strip board and cut the copper strips according to the recommended plan shown in Figure 11 and schematically in Figure 12. This can be done using a 1/8-inch twist drill bit but is best done using the Veroboard track cutting tool designed for this purpose. Complete all the point to point above wiring according to that shown in Figure 9 and Figure 10. If wiring differences have been identified during Task #3 then ensure that these are implemented correctly. Task 5: The HC-05 bluetooth module needs to be programmed as previously described in Task 2 of Project 1. Once that has been completed plug the HC-05 module, the USB – TTL module and the real time clock into their headers. Plug in the 4 X AA battery pack with switch into this project board and then turn the power on. The LEDs on these three modules should light up if all is correct. Turn the power off. Carefully insert the MicroMite microcontroller into the DIL socket taking care to ensure that it is in the correct orientation; the semicircular indentation on the top of the chip needs to be at the top closest to the power module.

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Figure 12. Project 2 Copper track cutting guide

Plug the male / female USB cable used in Project 1 into the PC and into this project board. Power up the project board and start the terminal program on the PC. The > prompt should appear on the terminal. If not send a CTRL-C key combination from the terminal. Task 6: The Real Time Clock (RTC) needs to be setup. Because this uses the I2C protocol it is not as straight forward as the HC-05 module setup. It should be completed via the MicroMite MMBASIC command line and simple MMBASIC programming. The first task is to identify the I2C address of the real time module. This has been set by the manufacturer of the module and can vary from supplier to supplier. To interrogate the module for its address program #2 in the Appendix. needs to be run. (This is a useful program to keep in mind whenever a new I2C device is connected to this Project Board. Run the program before connecting the new device, note all the occupied addresses. Plug in the new module and run it again and note the additional addresses that have been detected. Those will be required in the programs written to access the new module.) The Project 2 Board is now ready for use with sensors; the same program as shown in Table 1 for Project 1 will run on this setup. Additional lines can be added that read date and time from the RTC and report them via the Bluetooth App.

Project 3: Project 1 Implemented on the New Raspberry PI Pico At the time of writing the Raspberry Pi Pico had only been available for a matter of months. This project was designed to provide a comparative alternative to the MicroMite board described in Project 1. The end point is a small self-powered board that is ready for the connection of the sensors required for the student’s project. In Section 2a the additional commands available in MicroMite BASIC were highlighted.

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The Raspberry Pi Pico is supplied as a 20 X 20 Dual in Line (DIL) package with pin spacings at 2.5 mm. This makes it compatible with breadboards and Veroboard. Overall dimensions are 51mm x 21mm. It can be supplied with or without header pins soldered on. For this project, the board without headers is required. This is because the reverse side of the DIL package has all the pins clearly labelled as to their function. This makes it almost impossible to make mistakes when coming to nominate pin numbers and their functional assignment in a design specification. The design requires some additional components: • • • • • • • • • • • • • • • • •

A Raspberry Pi PICO module without presoldered header pins A small piece of Veroboard, 95 X 75 mm. Two rows Arduino style female header strip, each 20 sockets long Two rows of Arduino style header pins, each 20 pins long One three pin long leg stackable header One six pin long leg stackable header An HC-05 Bluetooth Module A Light Dependent Resistor (LDR) module A red LED and a 330 ꭥ resistor A micro Momentary Single Pole Single Throw (SPST) switch A nine-way terminal strip; (usually supplied in sets of three ways). A small mobile phone power bank, 5000 mAh will be adequate A short mobile phone USB charging cable Hook up wire A small breadboard, one with 30 rows will be adequate. A copy of the MMBASIC interpreter for the PICO which should be downloaded from and its contents extracted into a dedicated folder on your PC. An Android mobile phone with the Bluetooth Terminal App by Kai Morich installed, as for the previous two projects. There are seven tasks:

1. Select a suitable VT100 terminal emulator to run on your PC. For Windows users TeraTerm appears to be the most favoured. For Linux users PuTTY SSH Client is recommended, Task 1. 2. Construct a simple circuit to set the correct baud rate etc. for the HC-05 Bluetooth Module, Task 2. 3. Load the MMBASIC Interpreter into the Raspberry Pi PICO, Task 3. 4. Assemble the electronics onto a small piece of Veroboard. There are nine steps ((a) to (i)) involved in this, Task 4. 5. Load the Bluetooth Terminal App onto an Android mobile phone. 6. Confirm all components are functioning correctly on first power up. 7. Enter the BASIC program necessary to monitor the light levels detected by the LDR. Task 1 and Task 2 are as for Project 1. Task 3: This step presumes that the MMBASIC interpreter has been downloaded as a .zip file and stored in a dedicated folder on your PC. 379

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Take the Raspberry Pi PICO module as received from the supplier and plug in the short mobile phone USB charger cable. With the PICO in the student’s left hand they need to hold down the tiny button labelled BOOTSEL on the topside of the PICO with their thumb; (this will put the PICO into USB drive mode as designed by the manufacturers). With the student’s right hand holding the other end of the USB cable plug that into a convenient USB port on your computer. Release the BOOTSEL button and place the PICO on a piece of paper (the unmounted PICO circuit board should always be placed on non electrically conducting surfaces). Open a File Finder application on the PC and locate an entry for a USB drive on the USB port that the PICO has been plugged into; on Linux it appears as /media/sandfly/RPI-RP2. Copy and paste the PicoMiteV5.07.00b22.uf2 MMBASIC interpreter file into the PICO. Unplug the PICO, pause for 5 seconds before plugging it back into the same USB port. Open the VT100 terminal program on the PC and attempt to connect to the PICO. At the time of writing the PICO modules currently in circulation appear as a ttyACM0 USB device; in Linux it usually appeared as dev/ttyACM0 but it could be another number because the USB ports are numbered from zero to N where N is the number of USB ports on your PC minus one. Connection parameters are 38400 baud, 8 bits, 1 stop bit, No parity, No flow control. Once the correct connection parameters are in place the “>” prompt should be visible and typing in       > Print “HELLO”

should produce the response       HELLO

Task 4: This design of this Project is shown in Figure 13 and has been built on Veroboard. The suggested layout is shown in Figure 14. Veroboard layouts do not accommodate ‘point to point’ wiring as easily as does plain perforated circuit board but it does make for tidier looking end products. The thing to keep in mind when using Veroboard is that paths to circuit elements have to follow paths that have right angles in them. The recommended sequence of construction is: 1. Solder Header Pins onto the Raspberry Pi PICO module. Start by placing two rows of 20 header pins into a small breadboard spaced so that the PICO module sits topside down and exactly on top of them. Placing the PICO module topside down makes it very easy to see the pin allocations because they are silk screened onto the circuit board. It does, however, make it more difficult to access the BOOTSEL push button switch. Because the MMBASIC interpreter has already been loaded under Task 3 there will be no need to access this button again. Remove the PICO with its soldered on pins from the breadboard and push two rows Arduino style female header strips, each 20 sockets long, onto the pins. This assembly will be referred to as the ‘mounted PICO’. 2. The piece of Veroboard used in this construction had 29 holes (columns) along the short side and 34 holes (rows) down the long side. The copper tracks should be running parallel to this short side. Place the mounted PICO so that it is at right angles to the short edge of the Veroboard with its USB connector facing outwards. The left hand row of PICO should be inserted at row 10 along the short side of the Veroboard. Turn the Veroboard over and solder the mounted PICO unit to the Veroboard. 380

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Figure 13. Project 3:Design of project 1 implemented on the new Raspberry Pi Pico microcontroller

Figure 14. Veroboard layout diagram for Project 3

3. Take the six pin long leg stackable header and plug the HC-05 Bluetooth module into it. Carefully bend each of the six long legs at right angles so when inserted into the Veroboard the ST pin of the module goes into the hole located at column 5 row 22. Temporarily keep the module and its socket in place by using a piece of BluTac or similar. Turn the board over and solder the socket in place. Trim off any excess pin lengths. 381

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4. Take the three pin long leg stackable header and plug in the LDR module. Carefully bend each of the three long legs at right angles so when inserted into the Veroboard the GND pin of the module goes into the hole located at column 5 row 32. Temporarily keep the module a its socket in place by using a piece of BluTac or similar. Turn the board over and solder the socket in place. Trim off any excess pin lengths. 5. Use solid core hookup wire to make all the connections shown in Figure 15 and Figure 16. Use a short piece of rainbow cable to connect the GP pins of the mounted PICO module to the terminal strip. The selection of PICO pins taken over to the terminal strip are a suggestion. Depending on the intended use of the Project Board other pins may have been more appropriate to take across to the terminal strip. Figure 15. Topside view of completed project 3

6. Use some double-sided tape or a small drop of adhesive to secure the micro Momentary Single Pole Single Throw (SPST) switch to the edge of the Veroboard. Solder pieces of hookup wire to the RUN track and the GND track two rows below the RUN track. 7. Figure 14 has small crosses to indicate where the Veroboard’s copper tracks underneath must be cut so as to complete the circuits correctly between the components. Remember this is a topside view. To ensure that the correct track is cut using the Veroboard Track Cutting tool it is suggested that a piece of wire is poked through at each location so that when the board is turned over to view the copper tracks side it is obvious where the track targeted for cutting is.

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Figure 16. Underside view of completed project 3

8. Figure 15 and Figure 16 show the topside and underside of the Project completed according to these suggestions. Note that the the LED and resistor were located in a position that was mechanically more convenient than in the schematic. These two components are not critical – they are there to provide a dummy load for the small mobile phone power bank. These power banks are designed for use with mobile phones and have built in circuitry that detects the current flow. If that flow falls below a certain limit then the unit disconnects. There are suggestions that some units can have this overridden by holding their power on button for a significant length of time. Experience has proven this to be unreliable and the reliable solution is to provide a dummy load. If spontaneous power down proves to be a problem then add another LED resistor circuit to increase the current drain. 9. Take a 10X magnifying glass and check every soldered point for completeness and re-solder any that look dubious. Check every copper track for accidental solder bridges between tracks; cut them with a sharp blade or mounted needle tool. Task 5: Install the Android Bluetooth Terminal App onto an Android mobile phone as in Project 1. Task 6: Plug the completed project board into the mobile phone power bank via the USB connector on the mounted PICO module. The PICO’s green LED should flash continuously, the dummy load LED should shine steadily and the LED on the HC-05 should flash rapidly indicating that it has not paired with a Bluetooth device. Turn on the Bluetooth Terminal App on the mobile phone, scan for the Project module and pair with it usually by typing in 0000 or 1234.

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Task 7: Unplug the project board from the power bank and plug it back into the PC that is used to program the PICO. Once the Terraterm or Putty serial terminal program is up and running enter the following after the > prompt symbol: OPTION AUTORUN

This will ensure than any program saved from this point onwards will automatically restart on powering up Project 3. Enter the program in Table 3 and save it. This is a simple script that reads the voltage from the LDR once every second for ten repeats. If this all runs as expected then the Project 3 board is ready for use in other projects. Remember that an AUTORUN program is unlikely to start in such a way that the Android Serial Terminal App gets an intelligible response on the first powering up of the Project 3 board. Re-read (f) in the construction notes to understand why after first power up it is necessary wait 10 seconds and then to push the momentary SPST switch. The program should then restart and intelligible messages etc. will appear on the phone running the Android Serial App.

Using Project Sensors as IOT Devices In this section, the project sensor data is broadcast into a private intranet, in an IOT framework. To achieve these objectives students will have to be prepared to install the TINY webserver on their Android mobile phone and also program a simple Python script using the Android App Pydroid 3. Figure 17 illustrates the functional arrangement of the basic building blocks required for this intranet based IOT network. The tasks required to get this up and running are as follows: Task 1: Making the Connections Install the Tiny Web Server App. Open the App and change the default page to storage/emulated/0/Android/data/de.kai_morich.serial_bluetooth_terminal/files

To do this in the correct place, open the top left hand menu in the App and select Settings then Misc. Settings then Save + log folder. Turn on the mains powered WiFi Router. Turn on WiFi on the mobile phone and ensure it connects to the mains powered WiFi Router. Tap the Start Server button on the Tiny Web Server App. That should connect it to the mains powered WiFi Router directly. Success can be detected by observing that the IP address in the Tiny Web Server changes to a subnet IP address of the router e.g. 192.168.1.101 Write this down and take it to any PC connected to the same router as the mobile phone. Open a browser on that PC and type in that IP address with the addition of:8080 at the end e.g. 192.168.1.101:8080 The browser should display the files in the directory that was defined under (a) above. eg. Index of / Name                          Size

joiner.py                     543 B

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serial_20211207_160006.txt 1 KB LRusso WebServer/3.6 (Android) Server at 192.168.1.101 Port 8080

Figure 17. Functional diagram of basic IOT intranet

The content shown will vary according to whether or not the Logging feature on Serial Terminal App has been used before. Notice that the Serial Terminal App automatically creates filenames in the following format serial_yearmonthday_hourminutesecond.txt Install the Pydroid 3 App and use it to create the following script: print(“THIS PROGRAM ADDS HTML TAGS TO THE START AND END OF BLUETOOTH TERMINAL LOG FILE SO THAT IT WILL DISPLAY PROPERLY IN YOUR BROWSER \n”) print(“Name of Log File you wish to process ?”) LOGFILE=input()

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header = “\n” footer = “\n\n” fileIN = open(LOGFILE, “r”) logdata = fileIN.read() print(logdata) fileIN.close webfile = header + logdata + footer webfilename = LOGFILE + “.html” fout = open(webfilename, “w”) fout.write(webfile) fout.close() print(webfile) print(“Done.........”)

Save it in the same directory on the phone as has already been defined under (a) above and name it joiner.py. Task 2: Running the IOT system. These operations need to be followed at each data logging session. • • • •

Turn on the mains powered WiFi Router. Turn on the Project board. Turn WiFi on on the phone. And ensure it is connected to the correct WiFi Router. Turn on the Serial Terminal App and ensure it is communicating properly with the Project board via Bluetooth. Turn on the Tiny Web Server App and start the server. Turn Data Logging on on the Serial Terminal App.

• •

Task 3: Closing off the Data Logging and create the web page. • • •

Turn Data Logging off on the Serial Terminal App on the phone. Open the Pydroid 3 App on the phone and load the joiner.py script that resides in the phone directory specified in Task 1 (a). It will ask for the filename of the logging session – enter the full filename including the ‘.txt’ . Go to the PC as defined above in Task 1 (e) ie. that PC connected to the same router as the mobile phone. Presuming it is still running the same page in the browser press the F5 key on its keyboard to refresh the page. The page should show the extra webpage file just created by the Python ‘joiner.py’ script eg.

Index of / Name                          Size

joiner.py                     543 B serial_20211207_160006.txt.html      1 KB

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serial_20211207_160006.txt 1 KB LRusso WebServer/3.6 (Android) Server at 192.168.1.101 Port 8080

Double click on that new file ie. the one like serial_20211207_160006.txt.html and it should open up as a easy to read web page. In Appendix 1 we can see an example of the webpage displayed in Opera browser on a PC running Linux Mint version 1.9. The complete codes for the proposed projects can be are publicly available in the author’s website : http://medlabstats.com/IGI/HartleyCode.html

CONCLUSION As previously discussed, the uptake of STEAM teaching practices in Australian curriculum is gaining traction but educators still in many cases lack appropriate insights and material that will help them integrate STEAM based activities in their teaching practice. In this chapter a highly detailed description of a teaching sequence using highly available microcontrollers has been presented, in three projects of mounting difficulty. This exhaustive tutorial is meant to be both a detailed description of a teaching sequence that will aid students in building, programming and evaluating three projects, but also function as a springboard on which educators can build upon and further exploit the microcontrollers’ capabilities, to foster their students’ engagement with highly interesting and practical projects.

REFERENCES About STEM education in Victoria. (2021). Retrieved February 19, 2022, from https://www.education. vic.gov.au/about/programs/learningdev/vicstem/Pages/about.aspx de Souza, T. L., & Elisiario, L. S. (2019). Educational robotics teaching with Arduino and 3D print based on STEM projects. 2019 Latin American Robotics Symposium (LARS), 2019 Brazilian Symposium on Robotics (SBR) and 2019 Workshop on Robotics in Education (WRE), 407–410. 10.1109/LARS-SBRWRE48964.2019.00078 Deloitte. (2015). The fusion of business and IT. Author. Diyode Magazine. (2021). Retrieved February 19, 2022, from https://diyodemag.com/ Fidai, A., Kwon, H., Buettner, G., Capraro, R. M., Capraro, M. M., Jarvis, C., . . . Verma, S. (2019). Internet of things (IoT) instructional devices in STEM classrooms: Past, present and future directions. 2019 IEEE Frontiers in Education Conference (FIE), 1–9. Ge, X., Ifenthaler, D., & Spector, J. M. (2015). Moving Forward with STEAM Education Research. In X. Ge, D. Ifenthaler, & J. M. Spector (Eds.), Emerging Technologies for STEAM Education: Full STEAM Ahead (pp. 383–395). doi:10.1007/978-3-319-02573-5_20 Geisinger, K. F. (2016). 21st Century Skills: What Are They and How Do We Assess Them? Applied Measurement in Education, 29(4), 245–249. doi:10.1080/08957347.2016.1209207

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Hayman, S. L. (2017). Investigating STEAM: Integrating Art and STEM to Spark Innovation. Academic Press. Khine, M., & Areepattamannil, S. (2019). Steam education. Springer. doi:10.1007/978-3-030-04003-1 Lessons | micro:bit. (2021). Retrieved February 19, 2022, from https://microbit.org/lessons/ PriceWaterhouseCoopers. (2015). A smart move : Future-proofing Australia’s workforce by growing skills in science, technology, engineering and maths. STEM. Silicon Chip Online. (2021). Retrieved February 19, 2022, from https://www.siliconchip.com.au/ STEM Education in New South Wales. (2021). Retrieved February 19, 2022, from https://education. nsw.gov.au/teaching-and-learning/curriculum/key-learning-areas/stem Taylor, P. C. (2016). Why is a STEAM curriculum perspective crucial to the 21st century? Academic Press. Teach computing and digital making – Raspberry Pi. (2021). Retrieved February 19, 2022, from https:// www.raspberrypi.org/teach/ The Australian Curriculum. (2021). Retrieved February 19, 2022, from https://www.australiancurriculum.edu.au/ Tsai, F.-H., Hsiao, H.-S., Yu, K.-C., & Lin, K.-Y. (2021). Development and effectiveness evaluation of a STEM-based game-design project for preservice primary teacher education. International Journal of Technology and Design Education, 1–22. Victorian Curriculum Design & Technologies Stem-D and STEAM (Years 5 to 10). (2021). Retrieved February 19, 2022, from https://www.laptek.com.au/store/Victorian-Curriculum-Design-&-TechnologiesStem-D-and-STEAM-Years-5-to-10-c14025473 Xefteris, S. (2019). Developing STEAM Educational Scenarios in Pedagogical Studies using Robotics: An Undergraduate Course for Elementary School Teachers. Engineering, Technology & Applied Science Research. Yasin, A. I., Prima, E. C., & Sholihin, H. (2018). Learning Electricity Using Arduino-Android Based Game to Improve STEM Literacy. Journal of Science Learning, 1(3), 77–94. Zhong, X., & Liang, Y. (2016). Raspberry Pi: An effective vehicle in teaching the internet of things in computer science and engineering. Electronics (Basel), 5(3), 56.

ADDITIONAL READING Kurkovsky, S., & Williams, C. (2017, June). Raspberry Pi as a platform for the Internet of things projects: Experiences and lessons. In Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education (pp. 64-69). 10.1145/3059009.3059028 Robinson, A., & Cook, M. (2013). Raspberry Pi Projects. John Wiley & Sons.

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Shovic, J. C., & Shovic, J. C. (2016). Raspberry pi IoT projects. Apress. doi:10.1007/978-1-4842-1377-3

KEY TERMS AND DEFINITIONS Blockly: A client-side library for the programming language JavaScript for creating block-based visual programming languages (VPLs) and editors. A project of Google, it is free and open-source software released under the Apache License 2.0. It typically runs in a web browser, and visually resembles the language Scratch. It is also being implemented for the mobile operating systems Android and iOS, though not all of its browser-based features will be available on those platforms. Computational Thinking (CT): A set of problem-solving methods that involve expressing problems and their solutions in ways that a computer could also execute. It involves automation of processes, but also using computing to explore, analyze, and understand processes (natural and artificial). ICT: Or information and communications technology (or technologies), is the infrastructure and components that enable modern computing. IoT: The internet of things (IoT) refers to a system of interrelated, internet-connected objects that are able to collect and transfer data over a wireless network without human intervention. Micromite: The Micromite is a Microchip PIC32 microcontroller programmed with the free MMBasic firmware. Raspberry Pi: A tiny and affordable computer that you can use to learn programming through fun, practical projects. STEAM Education: An approach to learning that uses Science, Technology, Engineering, the Arts and Mathematics as access points for guiding student inquiry, dialogue, and critical thinking. Veroboard: A brand of stripboard, a pre-formed circuit board material of copper strips on an insulating bonded paper board which was originated and developed in the early 1960s by the Electronics Department of Vero Precision Engineering Ltd (VPE). It was introduced as a general-purpose material for use in constructing electronic circuits - differing from purpose-designed printed circuit boards (PCBs) in that a variety of electronics circuits may be constructed using a standard wiring board.

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STEAM and Sustainability: Lessons From the Fourth Industrial Revolution Dinesh Sharma Steam Works Studio, LLC, USA Bob Eng Advisors for Good, USA Amartya Sharma George Washington University, USA

ABSTRACT The educational challenge of sustainability remains unexplored in the development of children in the K-12 curriculum in the United States and potentially in the educational curriculum of many of the member states of the United Nations. Using a case study method, this chapter shows how sustainability can be an educational value and a public good, transmitted to students through everyday instruction. By conducting a regional analysis in specific cultural groupings, using fieldwork and applied research methodology, students can demonstrate competence for sustainable education on a whole host of issues relevant for the Sustainable Development Goals (SDG 2030). With younger age groups consisting of students in middle and elementary school, the chapter examines an activity-based approach for socializing young children to issues of sustainability and preparing them for what is known as “the fourth industrial revolution.” Finally, it is imperative that corporations adopt a socially responsible approach towards investing that is environmentally conscious of long-term governance impact.

INTRODUCTION When the UN (United Nations) announced the SDGs in 2015, mostly economists and diplomats or country representatives and ambassadors immediately grasped the importance of the goals for future generations. Most educators still struggle with how to make the direct connection between STEM eduDOI: 10.4018/978-1-6684-3861-9.ch018

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cational goals and the concepts entailed in the multilayered construct of sustainability. STEM focuses explicitly on Science, Technology, Engineering, and Math to introduce innovation in the educational system in mostly the Western countries that are facing post-industrial or post-manufacturing decline; while sustainability suggests that there is more to STEM than just tinkering with recent technology tools, social media, robots, and gadgets. STEM outlines the educational principles for a scientifically literate and technologically advanced society in the 21st century. Sustainability on the other hand suggests the scientific models of the previous centuries, fueling the growth of the industrial age and the spread of globalization -- with unlimited horizons for labor and markets -- have been falling short for most of the populations around the world. Can these two visions, one of STEAM education and the other of sustainability, meet on a common ground or do they inherently clash? In this paper, we argue that the recent upsurge in the STEM and STEAM educational curriculum -- the added emphasis on Arts and Humanities is critical -- and the global emphasis on sustainability are the two faces of the same coin related to the post-industrial decline in the West and the failures of the neo-liberal vision of society, culture, and environment. For science education to fully embrace the challenges of the 21st century, STEAM would have to be integrated with sustainability. Likewise, the business and investor class would have to join with government and non-government sectors to transform our society. The educational pathways to STEAM curriculum can also be confusing to children and parents if it is not fully clear what STEAM truly stands for.  Like other science education programs, STEAM can stop short of its best manifestation without a full implementation. STEAM should be an integrated approach to learning; there must be intentional connections between standards, assessments, and lesson design. Multiple standards of assessment and experience can be used to foster learning in subjects focused on Science, Technology, Engineering, Math, and the Arts. Techniques and assessment can be conducted in and through different modes of inquiry, with an emphasis on process-based learning where students are allowed to work across disciplines. Process learning and “making” is at the heart of the STEAM approach. Thus, utilizing and leveraging the integrity of the arts, history, humanities, and culture is essential to an authentic STEAM initiative. On the other hand, sustainable development has been defined as development that meets the needs of the present without compromising the ability of future generations to meet their own needs. Sustainable development calls for concerted efforts towards building an inclusive, sustainable, and resilient future for the people and the planet. For sustainable development to be fully achieved, it is crucial to harmonize four core elements or the 4E’s: Economic growth that is fair; Equality or social inclusion; Education or universal literacy; and Environmental protections against climate change. These elements are interconnected and all four are crucial for the well-being of individuals, societies, and our planet. As outlined by the UN goals, the 4E’s are crucial for any society to advance into the 21st century: Economy, Equality, Education, and the Environment. Eradicating poverty is related to economic development; this is another significant goal of the UN mission, originally part of the MDG (Millennium Development Goals) universal goals, in all its forms and dimensions is an indispensable requirement for sustainable development and significantly correlated with the 4E’s mentioned above. To this end, there must be promotion of sustainable, inclusive, and equitable economic growth, creating greater opportunities for all, reducing inequalities, raising basic standards of living, fostering equitable social development, and promoting integrated and sustainable management of natural resources and ecosystems. How we handle these challenges will reshape our past and determine our future.

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Post-industrial decline and the rise of STEAM and sustainability are interconnected. As humanity lurches towards what has been called the “Fourth Industrial Revolution” (Schwab, 2017) we need to take stock of where we have been, where we stand today, and how we can navigate the future. The previous century witnessed a massive rise in incomes, health, and well-being, but also a huge rise in inequality in the last quarter century (Milanovic, 2016; Pinker, 2018; Sachs, 2015). As the globe’s population reaches 9 billion by mid-century, we need ideas of sustainability to manage and drive the future. Thus, key ideas of STEAM education for sustainability must be to balance growth, inclusiveness, and climate action. As Jeffrey Sachs (2015) of Columbia University’s Earth Institute has said, we want growth that is fair, leaves no one behind, and based on clean energy that protects the environment. Thus, both the ideas of STEAM and sustainability are correlated with the post-industrial decline in the developed world with implications for our new global reality. The dawning of STEAM education has been to fight against the post-industrial decline in education standards in the US and EU. As economies move away from industrial growth to information technology, new ways of constructing and transmitting knowledge are needed even as the very same recent technologies have made this transition possible and accelerated the building of global information networks, connecting cultures and people together. Joseph Murphy, Dean of Vanderbilt University, has argued convincingly that American education model that has been in place since the age of industrialization is now feeling pressures from within the education system (i.e., high dropouts, excessive costs etc.) and from external forces (i.e., global competition) challenging us to transform the very nature of education (Murphy, 2021). He suggests we went through a similar systemic change in the education system when Americans moved from farm families to urban communities. As scientific and technological change grips our lives in an immediate and personal way through social media and personalized tools, we need to prepare for total change in the value chain and distribution of the educational goods we impart to the younger generation. There is the issue of justice in education. Due to the post-industrial policies and changes in many urban areas hit with blight and migration, sustainability has become a mantra for development experts and economists. The planet cannot support endless growth at the expense of environmental degradation and the downward spiral in the lives of everyday folks. Thus, STEAM must be focused on providing solutions for saving the planet and its everyday inhabitants, while spreading the benefits of the Fourth Industrial Revolution to the mass of humanity. Moreover, in most of the underdeveloped world, where we still struggle to fight for literacy – reading, writing and numeracy – STEAM needs to incorporate the STREAM curriculum with the added emphasis on the “R” for reading and writing. Just as digital literacy can be central to navigating in the world of social media and the emerging digital workplace, in the economically underdeveloped world the added emphasis on digital literacy initiatives can lead to changes in the economy and the workforce sector including the expansion of the working and middle classes. The recent report from the Bureau of Labor Statistics points out that American society is caught amid the technological change demanding high STEAM skills. There has been concern regarding the dearth of STEAM workers to meet the demands of the information economy. While many experts have also asserted the evidence of STEAM labor surplus in specific industries. “A comprehensive literature review, in conjunction with employment statistics, newspaper articles, and our own interviews with company recruiters, reveals a significant heterogeneity in the STEM labor market: the academic sector is generally oversupplied, while the government sector and private industry have shortages in specific areas” (Bureau of Labor Statistics, 2015).

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CASE STUDY 1: STEAM AND SUSTAINABILITY IN AMERICAN EDUCATION There is a silent revolution taking place in action-based learning and project-based approaches to holistic education or what has also been called the portfolio learning and assessment tools, driven partly by the personal technology revolution, graphic design, and some of the advances in social media. Similarly, the makers-movement invites children to avoid screen time and start building with their imagination, minds, and hands – tinkering with the engineering tools of today and emerging technologies – which will take them much further in individual development as well as potentially in the evolutionary scale of human development. The maker’s movement has significant implications for education in terms of deploying: 1) contemporary digital tools, prototyping methods and computer platforms that make project development easier to manage and execute; 2) infrastructural resources including online communities, in-person spaces and events; and 3) the mindset that engages and cultivates making, with certain aesthetic appeals and habits of mind that are valued within the communities of interest. According to Harvard’s Project Zero, “Students learn a tremendous amount through maker-centered learning experiences, whether these experiences take place inside or outside of makerspaces and tinkering studios. There is no doubt that students learn new skills and technologies as they build, tinker, re/ design, and hack, especially when they do these things together. However, the most important benefits of maker education are neither STEM skills nor technical preparation for the next industrial revolution. Though these benefits may accrue along the way, the most salient benefits of maker-centered learning for young people have to do with developing a sense of self and a sense of community that empower them to engage with and shape the designed dimension of their world” (Project Zero, 2015). Data from projects conducted at Tufts University suggests that even with noticeably young children, robotics modules can transform the children’s early understanding of coding, programming, and building. When children were assessed on their knowledge of basic robotics and programming concepts upon completion of the structured curriculum, children were able to demonstrate basic robotics and programming skills even in pre-kindergarten. Older children were able to demonstrate increasingly complex concepts using the same robotics kits in the same amount of time. This has clear implications for developmentally appropriate design of technology, as well as structure and pace of the robotics curriculum for young children at home or in school. In her work with children Umaschi Bers describes coding as a playground, a place where language games and creative problem solving can take place. It offers “many opportunities for learning and personal growth, exploration and creativity, mastery of new skills, and ways of thinking” (Bers, 2017). We do not always take children to the playground. Skills may be developed using other tools and methods. Coding can be a developmentally appropriate space to enhance certain concrete and abstract skills. Bers argues from the framework of positive technological development, where developmental milestones and playful learning experiences can lead to developing computational thinking and exploring powerful ideas. Coding as play can turn children into producers, and not merely recipients in our technologically rich world. The playground dimension of coding moves the conversation forward. The traditional view of coding as a technical skill is limited when it comes to children’s development. Coding is a form of literacy, which invites new ways of thinking. Coding carries the ability to produce an artifact detached from its creator, with its own meaning. In terms of ownership, children when they are coding can be producers with an intention; their passion and desire to communicate can lead to new discoveries. Coding is like writing; it is a medium of 393

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human expression. Through this expressive process, children can learn to think, feel, and communicate in new ways. Problem solving is only one aspect of teaching young children to code. Instead, coding can support personal expression and style. Technologically, young children create their own projects to communicate ideas and express who they are when they are coding. They need developmentally appropriate tools like Scratch Jr. (Scratch, 2021), or We Do 2.0 (LEGO, 2021), or a coding script with games and modules. As they engage in problem solving and storytelling, they acquire sequencing skills and algorithmic thinking. They learn about the design process from an early idea, concept development, beta testing and generating a final product. Psychologically, they also learn how to manage failures, frustration, and the process of finding a solution, rather than giving up they learn to find solutions to a challenge by trial and error. They may learn to test their projects and refine strategies for debugging. They learn teamwork; to collaborate with others they learn new skills of communication. If children have fun while learning their hearts and minds will continue to grow. They can fail several times and learn to start all over again. Coding teaches children stamina in the process of working. In terms of computer science, the coding playground offers children powerful ideas that can be useful for future programmers and engineers, but also other types of scientists. Coding can be seen to achieve literacy in the 21st century, not unlike reading and writing in the earlier era. When started early, it can be a multiplier. Today, those who can produce digital technologies, and not only consume them, will oversee their own destiny. Literacy is a medium of human power. Those who know how to read and write can assert their voices. Those who do not are disfranchised. Will this be true for those who cannot code? For those who cannot think computationally. Thus, the digital divide highlights the need for bridging the educational and technological gap. In terms of adaptation, it is our responsibility to introduce children to coding and computational thinking when they are young. We know that as a form of literacy coding can open doors. We also know that these young coders are still children, who are learning new skills every day. It is not enough to simply copy codes or use models of computer science education developed for elementary or high school students. It is important that programming languages are age-appropriate and enhance children’s early development. As teachers, we need technologies and curriculum specifically designed for young children that take into consideration their cognitive, social, and emotional needs. This is novel territory. Therefore, these children are our best collaborators, as they can guide us through the complexity of their thinking. As researchers, we need to explore the developmental stages of learning to code, and the learning trajectories associated with computational thinking. We must understand what is truly happening when a four-year-old programs her robot to dance the Hokey Pokey, and a five-year-old makes an animation. While there is a growing movement towards STEAM—science, technology, engineering, arts, and mathematics—education and research methodologies from those disciplines, we also look at research on literacy to elucidate some of these learning processes. Coding can be studied not only as a problemsolving mechanism, but as a process that allows the creation of a shareable product of human expression. As teachers all over the world begin to incorporate coding and computational thinking in early childhood education, we need information to understand how educational technology can be integrated into early childhood educational practices. We need to see children in their totality -- as individuals with their own voices and stories to tell -- and not simply as cognitive agents or problem solvers. We need to encourage and support their playfulness as a way of learning. In our applied work as an instructor and manager of a STEAM education learning center, we have observed hundreds of children using STEAM based robotics technology at an early age, without the 394

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excessive screen time, while actively engaged with robotic projects, coding simple or complex programs, and establishing wireless communication between objects using programming code. We have found pre-k, first and second graders to be very adaptable and quick to learn basic procedures and coding instructions of building basic robotics objects. Each child tends to display different aptitudes for a different skill set: coding, programming, building robotics, graphic design, applied sciences, gaming, digital storyboarding and film animation, web design and internet technology. All the children are enamored by innovative technology, drawn in by the allure of new toys; attractive-looking technological gadgets make children think about manipulating objects with their own hands and minds. But each child has a special ability or their own way of playing with code or building robotic objects. Based on their inherent strengths and weaknesses, each child develops a deep sense of individual learning for STEAM skills and sustainability. In the process of transferring STEAM skills, we can stimulate the children to think about sustainable projects: solar, wind, alternative sources of energy, and green technology. For example, working on the WeDo 2.0 projects students can build windmills, solar panels, and smart city designs. Through scaffolding we can provide children with exposure to concepts of sustainability. When we ask children to convert a LEGO based WeDo 2.0 cooling fan into the windmill, the children can explain what they did – add additional blades to the cooling fan, make the windmill taller and longer, or give the windmill additional horsepower – aimed to convert it into an object that approximates the shape and size of a windmill. With first and second graders we might get a fuller description of what a windmill does and how it generates energy, which can be later used for repurposing a wind farm. While pre-k children may not be able to provide a fuller description, first and second graders are able to explain why we need more windmills for energy conservation. Based on actual hands-on learning experience, children may explore and develop a rich scientific understanding of the energy grid that relies on wind as a source of power. When contextualized within a lesson plan, with detailed information about the power of windmills, students can begin to critically think about the strengths and weaknesses of wind power. At this stage, we provide children with an actual windmill kit. Children can assemble a wind turbine complete with an electric generator and adjustable rotor blades. The blades are designed with complex aerodynamic curves to look and work like modern-day wind turbine blades. We ask them to conduct experiments with their wind turbine, including experiments to optimize its performance by adjusting the angle of the blades and the placement of the turbine. They use the wind turbine to light up a LED bulb and charge a rechargeable battery; and convert the wind turbine into an electric fan by using the electric generator as a motor. They are able to build additional models with the parts included: electric car, electric helicopter, and electric truck. Observational data suggests that the discussion about sustainability is not only relevant, but beneficial towards building deep scientific knowledge and adaptive skills for everyday problem solving related to our current environmental challenges. For example, one of our eight years old students, who is in third grade and has been involved in the First Lego League challenge, wanted to build an underwater robotics project to present at a science fair. She took interest in this project from her own initiative; she had researched the process of building robots for underwater exploration and wanted to build a home-made device that can clean the debris in the oceans. This is of course a uniquely bright student, very driven and motivated towards acquiring STEAM skills, but may not be atypical as we advance towards a sustainable society. During the online research process, she learned that there are different underwater robots: Remotely operated vehicles (or ROVs) are connected to a cable that allows a human to control the robot from a ship or boat on the ocean surface or from within the robot. Autonomous underwater vehicles (or AUVs) 395

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are controlled by computers on board the robot and can operate without being connected to the surface. Because both ROV and AUV robots contain computers and electronic equipment, underwater robots need to be waterproof. This means that water cannot damage the equipment because it is inside a covering that prevents water from coming in. In this robotics engineering project, she built an underwater robot, an ROV that moves up and down using a motor, propeller, and a plastic clothes hanger. Before she started the project, she figured out how and where to test the robot. She tested it in a large container of water. If you decide to test the robot in a large container, make sure that the container is deep enough and large enough to hold the clothes hanger. Since the motor is a piece of electrical equipment, you will have to waterproof it by using a balloon to cover the motor and making sure that the edges of the balloon are glued to the surface of the motor (you can learn more about electricity from many online science resources). After putting these pieces together, you will have a cool robot that works underwater and is lots of fun to experiment with. Thus, she learned about the engineering design process: how to use a DC volt motor; how to waterproof the motor; and by attaching it to a plastic coat hanger she was able to get the robot to move in a pool of water. She presented the underwater robot at a local science fair and was recognized for her skills and inquisitiveness. Another group of students have been working to build a space mission to the moon, again as part of a FIRST Lego League competition (FIRST, 2021). Their challenge has been to settle the moon as a livable environment, and what sources of energy would they need to make that work for human habitation? What do you need to know about the Moon to live there? What will you eat and drink? How will you get energy? How will you breathe? What will you do for fun? What other problems will you have to solve? Guided by adult coaches, the team explored a real-world solution to the moon challenge. Then they created a science poster that illustrated their journey of discovery and introduced their team. They also constructed a motorized model of what they learned using LEGO elements. In the process, teams learned about teamwork, the wonders of science and technology, and the FIRST Core Values (FIRST, 2021), which include respect, sharing, and critical thinking. At the close of each season, teams come together at Expos to strut their stuff, share ideas, celebrate, and have fun! The group of students researched NASA websites for energy sources they would need to work on the moon and how the conditions on the moon can be challenging for human settlement; where will they get the water resources, where will the daily source of food and supplies come from, where will they go to have fun and rest. By engaging these questions, students expand their horizons for exploration in science and technology. Students worked together as a team for a year to build their solutions to survive on the moon. They were able to present their project at three different events and expos, with added dimensionality and details. By working as a team, they learned the skills of project management and leadership. They learned how a project over an extended period of time can be refined and built in an iterative process. Their final project was much improved and fully developed, reflecting their improvement. In all these challenges (windmills, underwater robot, moon mission) by engaging questions about the environment in a holistic manner students can learn about the opportunities to explore their immediate environment and the biosphere, and the constraints placed on them by the limited resources in their environment. By directly engaging questions of technology use, ocean life, and life on the moon students are asking deep questions about human nature as well and its malleability. Initiatives at the state level to enhance and integrate sustainability education are showing encouraging promise. In our home state of New Jersey, its 581 local school boards, 87 charter school boards of 396

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trustees with almost 5,000 members studied steam and sustainability in the state-wide schools. These school boards govern public schools, which educate approximately 1.4 million students ages 3 to 21. Prior to 2011, one could not find sustainability measures in New Jersey schools. As a handful of schools began to pioneer sustainability initiatives over the past decade, the advantages became clear. The schools were able to: 1) lower their operational costs, 2) redirect those savings to other educational priorities, 3) recognized the potential opportunity and impact that sustainability initiatives could have, and 4) learned how to manage challenging economic times and increased state mandates. Key decision-makers began to incorporate processes used by schools and districts that had successfully incorporated sustainability into their short and long-term planning. With additional training in 2011, as a critical first step, board members increased their “understanding of how to integrate sustainability throughout school operations into areas such as finance, buildings and grounds, curriculum, policy and other areas involved in the day-to-day and long-term functions of a school” (NJSBA, 2021). As more systematic data was needed to support and justify sustainability efforts, the state’s education boards undertook an extensive study. Given there was little accessible information on greening existing schools, particularly regarding the leadership decisions that facilitated change and how connections to the classroom, if any, impacted teaching and learning, the New Jersey Sustainable Schools Project was created to address a single, guiding question: “Is sustainability a factor in contributing to the success of New Jersey schools?” The intent of the project was to document the impact that sustainability has on schools, capture the process for implementing sustainable practices, and provide the results to district decision makers throughout New Jersey. Implementing sustainability is not a one-size-fits-all process. Data from multiple types of schools — inner city, urban, suburban, and rural — was needed to accurately capture the variety of methods that were successful, as well as those that did not work. Numerous detailed success stories, as well as reports about challenges were key components of this project. Sustainability does positively impact the success of New Jersey schools, in both the academic and the financial arena. Innovative sustainability measures resulted in cost savings, enabling funds to be used for other educational purposes. Sustainability measures also resulted in healthier learning environments.

CASE STUDY 2: SUSTAINABILITY IN SOUTH ASIA The United States and Europe have been at the forefront of the Industrial Revolutions over the last two and a half centuries. All Asian countries, except Japan, were latecomers to these revolutions. Nevertheless, many of them, including the Big-7 economies in Asia (China, South Korea, Singapore, Hong Kong, Taiwan, India, Indonesia, and Malaysia) made considerable progress by the end of the Third Industrial Revolution. What follows is a brief description of the involvement of the South Asian region at the beginnings of the Fourth Industrial Revolution, wrestling with the challenges of sustainability. STEAM education, new social media tools and AI (Artificial Intelligence) have risen to the forefront of public discourse in recent years. This breakthrough has generated a development path that has further propelled innovations in innovative technologies, including cloud computing, big data, Internet of Things, and virtual reality. As a convergence of a widening spectrum of frontier technologies, STEAM, new social media, and AI has garnered the potential to bring new possibilities for global development and societal change. The transformative power of the new tools crosses all economic and social sectors, including the education sector. STEAM education, social media tools and AI have the potential to 397

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accelerate the process of achieving Sustainable Development Goal 4, quality education. It promises to reduce barriers to access education, automate management processes, analyze learning patterns, and optimize learning processes with a view to improving learning outcomes. However, the penetration of AI in education comes with concerns about ethics, security, and human rights. Without policy intervention, the commercial deployment of AI will also exacerbate digital divides and deepen existing income and learning inequalities, as marginalized and disadvantaged groups are more likely to be excluded from AI powered education. In South Asia, with the demographic dividend of younger people and the growing STEAM graduates, sustainability education is an emerging issue. South Asia is one of the most densely populated geographic regions in the world, with one third of the entire world’s population living together in harmony. The South Asian region is filled with several natural resources, ranging from minerals to spices to tea. With an enterprising population and numerous natural resources, South Asia has been able to sustain a growing economy in the past few decades. The entire region has a significant geopolitical and economic location, and it has historically been extorted for its natural resources. Will the region grow along the path of sustainability? It remains to be seen. Today, South Asia has established itself as one of the booming economic centers of the world. Dubbed the “world’s fastest growing region” (World Bank, 2016), economic growth in the region is forecasted to gradually accelerate to 6.3 percent in 2023. Like several regions in the world today, South Asia has a small elite harboring most of the wealth and power along with a growing middle class driving the change. The economic inequality in South Asia is particularly alarming, given the region harbors half of the entire world’s poor. In 1997, the Human Development Center called the region “the poorest, the most illiterate, the most malnourished, and the least gender-sensitive--indeed the most deprived--region of the world”v (UNDP, 1998). Plagued with problems, such as, lack of sanitation, gender inequality, and extreme poverty, the economic inequality in the region has gotten only worse. The newly articulated Sustainable Development Goals (SDGs) can help the South Asian region focus on specific goals to reduce income inequality and improve gender equality, leading to better living standards. In many ways, the region is ideal for building STEAM educational resources and sustainable development goals. The United Nations established the Millennium Development Goals (MDGs) in 2000, eight goals each with its specific targets as a way for the international community to eradicate inequalities together. The SDGs, 17 unique goals, some taken from the MDGs, were created in 2015 as a replacement for the MDGs. The SDGs were designed to advance the global goals MDGs were unable to accomplish. Throughout this section, we will discuss the effects of the MDGs in furthering economic equality in South Asia, the limitations of the MDGs, why we believe the SDGs may be more effective set of goals, and how the UN should act as a facilitator of the global goals, rather than the enforcer, which can lead to more local success in countries adopting the SDGs. As per the UN official report in 2015, the MDGs made great achievements in some areas, but increased efforts are needed in many other areas. The level of extreme poverty in South Asia dramatically decreased from 52% to 17% from 1990 to 2015, with the rate of reduction only increasing from 2008 onwards (UNESCAP, 2015). India has played a significant role in the reduction of poverty in the region. Women’s representation has also increased in South Asia. Gender parity regarding primary and secondary education could also be seen in South Asia, with 103 girls enrolled for every 100 boys. Additionally, from 2000 to 2015, the proportion of seats held by women in single or lower houses of national parliament increased from 7% to 18%. When women work, economies can further expand; and women

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can only get in the labor force through literacy and education. Women’s representation in the labor force is key to faster economic growth and equality; the two-work hand in hand. The MDGs, however, lacked in several ways. There are millions of people in South Asia who are still suffering from extreme poverty. More than half the population in South Asia still lacks access to improved sanitation. There is still a severe problem with regards to discrimination against women, though there is an increase in their education and parliament representation. Looking towards the SDGs is the only way to move forward. The SDGs are a more thought-out and well-structured set of goals. The eight goals chosen by the MDGs were not chosen in a thorough analysis of the current global economic situation. The complexity of world stability and sustainability was not reflected in the MDGs. The SDGs provide a full framework of all the areas needed to work on the 17 distinct, yet correlated and intertwined goals. The necessity to take a comprehensive approach is present within the SDGs, and to look at the bigger picture of long-term sustainable development is something the MDGs have lacked. With a large population at-risk, South Asians cannot afford to be left behind in the race for a sustainable planet. South Asia’s success is key to the SDGs success; they are one in the same. The South Asian countries are a mix of different populations, economies, and developmental constraints; they are all developing countries but have remarkably varied challenges. Five of those countries have unique development needs. Maldives is a Small Island Developing State (SIDS). Bangladesh is a least developed country (LDC). Afghanistan, Bhutan, and Nepal are landlocked least developed countries (LLDC). When we rank countries by GDP, GDP per capita and population size, South Asia can be grouped into various clusters of countries (see Figure 1). Figure 1. Size of the South Asian economies and income levels. Source: UNESCAP based on World Development Indicators, World Bank (accessed on 17 July 2016). Notes: LLDCs = Landlocked Developing Countries, LMICs = Lower-middle income countries, SIDS= Small Island Developing States

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Based on income, GNI classifications, South Asia has low-income and lower-middle income countries; Maldives being the exception to the rule. The range of average per capita incomes vary between $6670 for the Maldives to only $630 for Afghanistan, with the mean around $1533 in 2015. As suggested earlier, South Asia faces fundamental gaps in sustainable development goals in meeting basic needs and services. The SDGs can provide South Asia a timely opportunity to make its economic growth more inclusive and sustainable; closing the development gap between rich and poor people, and majority versus minority populations is a worthy ambition. The SDG agenda represents culmination of several years of consultation and review at the localsocietal level, national, regional, sub-regional and global goal setting process among 193 member states to be examined for the next fifteen years. Civil society, business and industry have also added to the global goals. The goals consist of a cross-matrix review of economic, social, and environmental domains. The 17 SDGs consist of 169 targets adopted by the world leaders on Sep 25, 2015, to be tracked through the year 2030. As mentioned above, some of the goals are carried over from the MDGs, but the emphasis on environmental goals is new. SDGs 1 to 7 focus on providing basic needs and services to the underserved populations that began with the MDGs. Given South Asia has the largest concentration of poverty, hunger, and deprivation in the world, we still have a long way to go. Unlike MDGs, SDGs aim “to leave no one behind” (see Figure 2). Figure 2. Sustainable Development Goals – Source Wikimedia Commons: https://bit.ly/3v4dlNJ

SDGs 8 to 10 focus on the drivers of change that are interoperable across economic, societal, and environmental domains: jobs and decent work; infrastructure and sustainable industrialization; and promoting income equality. South Asia faces huge problems in infrastructure development, but there is political will and popular support for investment in these development projects currently. Thus, SDGs provide an ideal context for policy makers to piggyback on the global goals.

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SDGs 11 to 15 work to enhance conservation and sustainability across various dimensions of the biosphere: make cities more resilient; enhance sustainable consumption and production; promote climate action; conserve ocean life; and conserve life on land. As South Asia embraces greater industrial reforms, ensuring long-term sustainability would be paramount. Finally, SDGs 16 and 17 foster exchange and partnerships for harnessing sustainability between agencies and NGOs (Nongovernment Organizations).

Ending Hunger In South Asia one out of every five persons is in malnourished condition (Goal 2); given the large population size, the region is the largest hunger hotspot on the planet, 281 million undernourished (16% of the population). With improved infrastructure (Goal 9), South Asian countries can improve food productivity and distribution. However, reduction in anemia, zinc, and vitamin A deficiency, common in the region, can only occur with better health policies (Goal 3) (World Hunger, 2015). Given agriculture employs more than half of the population, any improvements in the agriculture sector will impact hunger directly. Better technologies in sustainable agribusiness, with better seeds and irrigation methods, can have a positive impact on poverty reduction (Goal 1), job creation (Goal 8) and equality (Goal 10).

Sharing in the Growth While South Asia has shown remarkable improvements in reducing inequality, the recent growth in the economy has not been broadly shared across different socioeconomic and rural-urban segments. According to UN data, South Asia remains one of the least inclusive sub-regions in the Asia-Pacific countries (UNESCAP, 2017). For example, India’s billionaire community has increased 12-fold in the last 15 years, and they have twice the monetary resources to eliminate extreme poverty (Goal 1), but the wealth has not been shared and it has not trickled down (Goal 10). As Jeffery Sachs states, in his recent book The Age of Sustainability, “Ours is a world of fabulous wealth and extreme poverty: billions of people enjoy longevity and good health unimaginable in previous generations, yet at least 1 billion people live in such abject poverty that they struggle for mere survival every day” (Sachs, 2015).

Access to Education and Health South Asia met the MDG targets for universal primary education. Yet, at 59% the region lags the global average of 65% primary education enrollment (Goal 4). Pakistan and Afghanistan have exceptionally low rates of primary education for girls, and children in lower socioeconomic segments also lag significantly behind children from other regions. Investments in universal primary education are sorely needed; public expenditure in Bangladesh is 2% of the GDP, 3.8% in India, 2.5% in Pakistan, and 1.6% in Sri Lanka, which is much lower than the recommended 6%. Similarly, in terms of health outcomes 67% reduction in maternal mortality has been significant, but South Asia still lags the MDG target of 75% reduction in maternal mortality (Goal 3) (UNESCO, 2016).

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Gender Equality While South Asia reached gender parity in primary education between boys and girls, as per the MDG targets, the region still lags on multiple measures of gender equality (Goal 5). On three key measures of gender equality, South Asia shows a significant lag: Global Gender Gap produced by the World Economic Forum, Gender Development Index and Gender Inequality Index produced by the Human Development Report. The Global Gender Gap Report also provides gender inequality scores on countries’ performance against four sub-indices, namely education, health, political empowerment, and economic participation. Sri Lanka has the best ranking among the South Asian countries, while Afghanistan and Pakistan find themselves at the bottom of these indices (World Economic Forum, 2021).

Decent Jobs and Wages It is indeed significant South Asia has emerged as the fastest growing sub-region in Asia-Pacific economically; however, it is yet to scale the high economic growth rate witnessed before the onset of the global fiscal crisis in 2008. Economic growth has been central to the 2030 SDG agenda, as outlined in Goal 8; Goal 9 is also important as it is focused on jobs and industrialization, while Goal 1 is focused on poverty reduction. Job creation in South Asia has been stagnant or declining, averaged around 1.8% annually in India and 2.6% annually in the rest of South Asia between 1992 and 2012. While GDP growth has been three times faster than employment growth in India (6.8% annually) and 1.8 times faster than employment growth in the rest of South Asia, the result has been that prosperity has not been widely shared (Kumar et al, 2016).

Infrastructure Development South Asian countries are characterized by huge infrastructure gaps. Even India, when compared with Asian tigers, finds itself at a poor level in the recent global ranking of countries’ infrastructure development (with inadequate availability of transport infrastructure, electricity and information and communications technology services). South Asia lags in terms of transport infrastructure (SDG 9) and basic needs infrastructure, such as, access to sanitation (SDG 6) and access to electricity (SDG 7). Access to basic infrastructure services influences other SDG targets. For instance, improved sanitation can lead to better health outcomes in terms of a reduced under-five mortality rate. Access to roads can affect health outcomes and drive down the high maternal mortality ratio. Likewise, access to electricity can promote educational goals and overall human development. Closing infrastructure gaps in South Asia will require large-scale resources, approximately $2.5 trillion (about $7,700 per person in the US) by 2020, and $4 trillion (about $12,000 per person in the US) to $5 trillion (about $15,000 per person in the US) by 2030, according to recent UNDP (United Nations Development Programme) estimates. India alone is investing $1 trillion (about $3,100 per person in the US) in infrastructure, which is undertaken by the Twelfth Five Year Plan (2012-2017); South Asian countries are also part of the initiatives led by the Asian Development Bank and BRICS Bank (Andres et al., 2013).

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Renewable Energy South Asia must take the lead on renewable sources of energy (Goal 13). Countries like India can not only address the energy scarcities; they must actively save valuable foreign exchange from imports of hydrocarbons and develop sustainable green solutions. Nepal suffers from power scarcities, cutting power for 14 hours a day in the city of Kathmandu. The country situated in the Himalayan foothills is endowed with hydroelectric generation potential, but green technology is scarce. Bhutan, on the other hand, has harnessed hydropower potential, embraced sustainable growth, and higher levels of happiness. Vast solar and wind energy sources must be streamlined in South Asia; these countries can also switch over to cleaner fuels, natural gas and clean coal technologies. Advancing a unified energy market, linked by energy grids and pipelines will help the sub-region leapfrog towards enhancing energy conservation into the 21st century (Goal 11) (Kumar et al, 2016).

CONCLUSION This summer, the United Nations issued a report classifying global climate change as a present, and now seemingly irreversible, threat. Such scientific consensus has led entities in the financial sector (i.e., influential companies and individuals) to consider ESG (Environmental, Social, and Governance) factors in the investment process. But what exactly does ESG mean? More importantly, how has it allowed companies and other financial conglomerates to contribute to the larger fight against climate change in a substantive way? Firstly, the Chartered Financial Analyst (CFA) Institute describes ESG as “nonfinancial factors regarding sustainability which investors and companies apply as a part of their analysis process to identify material risks and growth opportunities.” Now, many institutions have been formed to create guidelines “and define materiality to facilitate incorporation of [ESG] factors into the investment process” (CFA Institute, 2021). Furthermore, as new research has uncovered links between rising global temperatures and the spread of Covid-19, some of the biggest financial players, like JPMorgan, have been motivated to get into the ESG game as of late. The world’s largest underwriter of green bonds, JPMorgan hopes to link sustainability to each form and level of finance (Bloomberg, 2021) Financial Technology, or FinTech, also ‘grew greener’ this summer when Aspiration Partners, an LAbased digital bank became the first publicly traded fintech company primarily centered around socially responsible and sustainable spending, saving, and investing. Also, “Aspiration offers its own managed IRAs and taxable accounts investing in 100% fossil fuel-free companies,” (Forbes, 2021) earning the moniker, fintech for environmentalists. Engine No. 1, a small hedge fund with just 0.02% stake in Exxon was able to successfully nudge the company’s board of directors, pushing them to diversify beyond oil (Bloomberg, 2021). Literalizing the political struggle between an underdog and a powerful big business – a dynamic which many activists know all too well – Engine No. 1’s feat shows that ESG issues are mainstream and of concern to many. Moreover, a recent report from Bank of America recorded that ESG assets grew to $329 billion (about $1,000 per person in the US) this past July. While progress on curbing climate change may have been stifled in the past by a minority of ‘deniers’ enthralled in political tribalism, recent climate developments have compelled the private sector -- whose gatekeepers arguably have contributed to global climate

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change more than any other powerful aggregate – to claim a stake in the fight for an environmentally friendly future. We would like to conclude with our experience at the United Nations, reflecting on the inefficiency in implementing sustainable policies, and on the role of the UN. Through a greater emphasis on the UN’s role as a facilitator and mediator, instead of an enforcer, we believe the SDGs can be even more successful in the US education, South Asian region, and the entire world. The United Nations has a profound and terribly difficult mission to sustain peace and secure a better future for all. Our main critique of the system would be the inability to act and steps towards implementation. It has been more than established what needs to be achieved, so it is time to act. The conversations should now shift from the problems to ingenious, tangible solutions. Linking STEAM, AI with sustainability is a way forward. As mentioned earlier, those in power, the representatives of member states, civil service organizations, NGOs, etc., are the ones having many necessary conversations. Part of the problem may be producing concrete solutions; those in a position of privilege and power do not know what the problems are at the local, community level. Advances in STEAM education and AI are needed in many of the poorer member states. This is where the UN’s role is key in partnership with the NGOs. The UN can start by giving a voice to those who do not have it, and to those who require help the most. It is those most behind that we must now think about first. The UN, as the international organization for upholding the law and peace, should be facilitating and supporting conversations at a local level. By building resources in many of the innovative areas of science and technology, the UN can help advance digital literacy and universal goals of education. It is the local citizen’s voice that needs to be amplified, and the UN can provide the means to make this possible. A problem with the inability for countries to fully adopt SDGs is the element of enforcement or imposition attached to them. With local ownership of these goals, it is likely they will be more successful. The UN should be encouraged to give a larger voice to those at the ground level and to the sociocultural realities of the local worlds. It is the people on the ground who these global goals are designed to help. Thus, STEAM and sustainability can be best implemented by local schools and educators.

REFERENCES Andrés, L., Biller, D., & Dappe, M. H. (2013). Reducing Poverty by Closing South Asia’s Infrastructure Gap. World Bank. Bers, U. M. (2017, Sep 29). Why kids should code. Accessed online on Nov 15, 2021 from: https://now. tufts.edu/articles/manifesto-kids-code Bloomberg. (2021). JP Morgan plots a derivative path into ESG finance. Accessed online on Nov 15, 2021 from: https://www.bloomberg.com/news/articles/2021-08-16/jpmorgan-plots-derivatives-pathinto-new-era-of-esg-finance Bloomberg. (2021). Engine-1’s Exxon win signals turning point for ESG investors. Accessed online on Nov 15, 2021from:https://www.bloomberg.com/news/articles/2021-05-27/engine-no-1-s-exxon-winsignals-turning-point-for-esg-investors

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Bureau of Labor Statistics. (2015). STEAM crisis or STEM surplus. Accessed online on Nov 15, 2021 from: https://www.bls.gov/opub/mlr/2015/article/stem-crisis-or-stem-surplus-yes-and-yes.htm CFA Institute. (2021). What is ESG investing? Accessed online on Nov 15, 2021 from: https://www. cfainstitute.org/en/research/esg-investing FIRST. (2021). FIRST Core Values. Accessed online on Nov 15, 2021 from: https://www.firstinspires. org/robotics/fll/core-values Forbes. (2021). Fintech grows greener. Accessed online on Nov 15, 2021 from: https://www.forbes.com/ sites/jonathanponciano/2021/08/18/fintech-grows-greener-sustainability-focused-aspiration-lands-23billion-deal-to-go-public-via-spac/?sh=1de26d13ad30 Kumar, N., Hammill, M., Raihan, S., & Panda, S. (2016). Strategies for Achieving the Sustainable Development Goals (SDGs) in South Asia. South and South-West Asia Development Papers 1601. LEGO Education. (2021). LEGO WeDo-2.0. https://education.lego.com/en-us/products/lego-educationwedo-2-0-core-set/45300#wedo-20 Milanovic, B. (2016, May 13). Why the global 1% and the Asian middle class have gained the most from globalization. Harvard Business Review. Accessed online on Nov 15, 2021 from: https://hbr.org/2016/05/ why-the-global-1-and-the-asian-middle-class-have-gained-the-most-from-globalization Murphy, J. (2021). Schooling in the post-industrial age. Accessed online on Nov 15, 2021 from: https:// peabody.vanderbilt.edu/docs/pdf/lpo/schooling_post_industrial_murphy.pdf NJSBA. (2011). New Jersey Sustainable Schools. Accessed online on Nov 15, 2021 from: https://www. njsba.org/services/sustainability/njssp-guidebook/executive-summary/ Pinker, S. (2018). Enlightenment now. Viking. Project Zero. (2015). Maker-centered learning and the development of the self. Accessed online on Nov 15, 2021 from: http://www.pz.harvard.edu/sites/default/files/Maker-Centered-Learning-and-theDevelopment-of-Self_AbD_Jan-2015.pdf Sachs, J. (2015). The age of sustainable development. Columbia University Press. doi:10.7312ach17314 Schwab, K. (2017). The Fourth Industrial Revolution. Crown Publishing Group. Scratch. (2021). Scratch coding. Accessed online on Nov 15, 2021 from: https://education.lego.com/ en-us/products/lego-education-wedo-2-0-core-set/45300#wedo-20 UNDP. (2017). Human Development in South Asia. Accessed online on Nov 15, 2021 from: https://hdr. undp.org/sites/default/files/en_2019_hdr_press_release_-_asia-pacific_-_final.pdf UNESCO. (2016). Sustainable Development Goals. Accessed online on Nov 15, 2021 from: http://data. uis.unesco.org/ World Bank. (2016). South Asia Remains World’s Fastest Growing Region, but Should Be Vigilant to Fading Tailwinds. Accessed online on Nov 15, 2021 from: https://www.worldbank.org/en/news/pressrelease/2016/04/09/south-asia-fastest-growing-region-world-vigilant-fading-tailwinds

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World Economic Forum. (2015). The Global Gender Gap Index. Accessed on Sep 7, 2017. http://reports. weforum.org/global-gender-gap-report-2015/the-global-gender-gap-index-2015/ World Hunger. (2015). Asia Hunger facts. Accessed online on Nov 15, 2021 from: https://www.worldhunger.org/asia-hunger-facts/

ADDITIONAL READING Campbell, C., & Speldewinde, C. (2022). Early Childhood STEM Education for Sustainable Development. Sustainability, 14(6), 3524. doi:10.3390u14063524 Gamage, K. A., Ekanayake, S. Y., & Dehideniya, S. C. (2022). Embedding Sustainability in Learning and Teaching: Lessons Learned and Moving Forward—Approaches in STEM Higher Education Programmes. Education Sciences, 12(3), 225. doi:10.3390/educsci12030225 Nguyen, T. P. L., Nguyen, T. H., & Tran, T. K. (2020). STEM education in secondary schools: Teachers’ perspective towards sustainable development. Sustainability, 12(21), 8865. doi:10.3390u12218865 Rogers, M., Pfaff, T., Hamilton, J., & Erkan, A. (2015). Using sustainability themes and multidisciplinary approaches to enhance STEM education. International Journal of Sustainability in Higher Education, 16(4), 523–536. doi:10.1108/IJSHE-02-2013-0018 Schelly, C., & Pearce, J. (2019). Bridging the social and environmental dimensions of global sustainability in STEM education with additive manufacturing. In Integrating 3D Printing into Teaching and Learning (pp. 155–172). Brill. Smith, C., & Watson, J. (2018). STEM: Silver bullet for a viable future or just more flatland. Journal of Futures Studies, 22(4), 25–44. Smith, C., & Watson, J. (2019). Does the rise of STEM education mean the demise of sustainability education? Australian Journal of Environmental Education, 35(1), 1–11. doi:10.1017/aee.2018.51

KEY TERMS AND DEFINITIONS Maker Education/Movement: Maker education and the maker movement is based on project-based and problem-based learning affordances. To demonstrate learning, the maker’s movement relies on hands-on, collaborative experiences where projects focus on solving real-world problems. Non-Government Organisation (NGO): Nonprofit organisations that are not affiliated with governments or similar bodies, usually formed to address issues of sociopolitical nature. Problem-Based Learning: According to this teaching methodology, in order to promote critical thinking and facilitate the development of meta-cognitive abilities, the students engage in -shorter than project-based learning- real world projects. Project-Based Learning: In project-based learning students learn by actively engaging in real world problems. Students work on a project that engages them in fixing a real-world problem or answering

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a challenging question over a long period of time – from a week to a semester. They demonstrate their knowledge and abilities by producing a public product or giving presentations. Project-based learning instills a contagious sense of creativity in both students and teachers. STEM/STEAM: A note about terminology is increasingly relevant. STEM education may be appropriately termed STEAM for the added emphasis on the Arts and Humanities. Most liberal Western democracies enjoy the arts education in the public schools to varying degrees, an emphasis that is somewhat variable or lacking in most developing societies; as the arts, humanities and broadly social sciences are seen as softer disciplines they invariably attract much less public and private investments. In hopes to reclaim the pinnacle in science and technology leadership, which the US and EU have enjoyed for decades if not for the past two-three centuries, the application of STEAM curriculum in some adaptive form has become a mainstay in American and European schools. As Asian countries in the Pacific have begun to liberalize their economies and dominate in the fields of science, technology and computing in the past two-three decades, there has been a parallel decline in science and math scores in the US and EU and an increase in high school drop-out rates in public schools. There are many reasons for this decline: breakdown of the family, urban blight, relative lack of investment in education, shifts in jobs and industries, the rise of information technology, and many others. The emphasis on arts and humanities may serve as the bridge to the discussions on sustainability within the STEAM fields. As a common complaint heard from many educators, STEAM does not fully incorporate the arts and humanities at the heart of the liberal arts educational program. Since STEAM education is focused on literate societies that are already economically developed and advanced, the calls for arts and humanities are of different kinds from many educators around the world. Mostly, in the EU and US where the educational standards have been somewhat challenged, the arts and humanities educators don’t want to jettison the liberal spirit of their local cultures. Among other factors this is in reaction to the rise of Asia, where the Asian tigers have been ramping up the training in sciences and technology, and fighting to gain and protect intellectual property (IP) values. Conversely, in most of the underdeveloped world, where we still struggle to fight for literacy – reading, writing and numeracy – STEAM needs to incorporate the STREAM curriculum with the added emphasis on the “R” for reading and writing. Sustainable Development Goals (SDGs): The United Nations approved the Sustainable Development Goals (SDGs), also known as the Global Goals, in 2015 as a universal call to action to end poverty, safeguard the environment, and ensure that by 2030, everyone lives in peace and prosperity. United Nations (UN): The United Nations is a global organization that was established in 1945. The United Nations, which now has 193 member states, is driven by the values and objectives outlined in its founding Charter. The United Nations has changed over time to keep up with a continuously changing planet.

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About the Contributors

Stefanos Xefteris got his B.Sc in Mathematics from Aristotle University of Thessaloniki and his Ph.D in biometrics with computer vision from the School of Electrical and Computer Engineering of the National Technical University of Athens, Greece. Dr. Xefteris has worked as a researcher for the Distributed Knowledge and Media Systems Lab of NTUA, and the Medical Physics Lab of AUTH. Since 2017 he has been an adjunct lecturer for the Elementary Education department of the University of Western Macedonia, teaching Educational Robotics, development of digital teaching scenarios as well as various post-graduate courses based on the integration of ICT in education. *** Veli Acar is currently primary school teacher in Ozel Ege Lisesi, Turkey. He earned his Bachelor’s Degree in Primary Education from Suleyman Demirel University, and Master of Education in Learning and Instruction from Mehmet Akif Ersoy University. He holds PhDc in Learning and Instruction from Ege University in 2012. Ioannis Arvanitakis holds a master’s degree in Technologies and Education, from the University of Western Macedonia and a bachelor’s degree in Information Technology from University of Macedonia in Thessaloniki, Greece and is currently a Ph.D candidate in the Elementary Education Department of the University of Western Macedonia, in Florina, Greece. He is an elementary education teacher with significant experience in organising Educational Robotics teams and a successful trainer with many awards in Robotics contests. His research focuses in design thinking process and embodied learning applications with ICT Virginia Arvaniti, MSc, MBA, is a STEM instructor and coordinator at Anatolia College STEM Center. She teaches Kindergarten and Elementary grade STEM courses and is responsible for coordinating after school STEM activities and developing STEM educational scenarios for Anatolia Elementary and High school. Moreover, she is responsible for developing activities for Anatolia College Erasmus projects related to STEM. Virginia holds a Physics degree from the Aristotle University of Thessaloniki with a focus on Atmospheric Physics, a “Master in Business Administration” (MBA) from the American College of Thessaloniki, an MSc in Sustainable Energy Systems from the Open University of Cyprus (OUC) and is a PhD candidate at the University of Western Macedonia. Furthermore, she is a certified Lego Education trainer for WeDo 2.0, EV3 and Spike (2019), and is certified as a STEM instructor from the Aegean University of Greece (2018). She has published 6 scientific papers in the field of STEM and participated in national and international STEM conferences and training.

 

About the Contributors

Tharrenos Bratitsis is a Full Professor at the Early Childhood Education Department, University of Western Macedonia, Greece and a director of the Creativity, Innovation and Technology in Education (CrInTE) Laboratory. He has participated in over 250 international conferences’ scientific committees; is a member of the reviewers’ board of 47 scientific journals (3 as an associate editor) and publishes regularly, having over 210 scientific papers with over 1000 citations on his work. He has participated in over 45 research funded projects, 21 as a coordinator (global or for UOWM). His research interests include Technology Enhanced Learning, Game-based Learning, Digital Storytelling, STEAM Education, Educational Robotics, Computer Supported Collaborative Learning and Learning Analytics. Ioannis Brouzos holds a Doctoral Degree in Natural Sciences and has worked as a researcher and educator for several years in Greece and in Germany. He is co-founder of Challedu- inclusion | games |education, an NGO that focuses on research and development of game-based methods and tools for education and inclusion. Ioannis has managed several national and European projects, facilitated more than 600 workshops and created more than 25 games tools and activities for educational and/or inclusion purposes. Today he is working as an educator in high school. Asimina Brouzou has studied Architecture in NTUA (Athens) and holds a MSc in Advanced Sustainable Design (Edinburgh). She has been working as an educator since 2011 and as game-designer since 2014. In 2016 she co-founded Challedu- inclusion | games | education, which focuses in research and development of game-based methods and tools for education and inclusion. The last 7 years Asimina has conducted research in various topics especially in the field of education, she has created over 50 game-methods and tools, she has facilitated over 500 workshops with educators and target groups and she has managed various national and European projects. Mert Büyükdede is PhD student of Physics Education at the Faculty of Education Buca, Dokuz Eylül University, also Physics Teacher in the Ozel Ege Lisesi, Turkey. He received his master’s degree in physics education in 2018 from Dokuz Eylül University. His research interests are physics education, quantum physics education, use of smartphones in physics experiments and STEM education. Vanessa Camilleri is an academic at the Department of Artificial Intelligence, Faculty of ICT, University of Malta. Her expertise is in the area of Human Computer Interactions, with a specialisation in Virtual Worlds and Serious Games. Her areas of interest include Virtual Reality applications for developing emotional intelligence values. Her previous experience in the area of education and pedagogy, as well as educational technologies and use of games for learning have contributed to her overall academic profile. Her main publications are in the areas of online learning and the use of innovative and emerging technologies for learning. She also has worked on a number of EU funded projects in the areas of game-based learning. More recently she has started working on developing virtual reality experiences for teaching and learning purposes related to various aspects of emotional intelligence. Andri Christoforou holds a Ph.D. in Women’s Studies from the University of York. Her work is interdisciplinary in nature and draws on theoretical concepts from feminist scholarship, sociology, and psychology. Her current research interests include gender-based violence as well as sexism and other forms of discrimination in education. Andri is currently teaching psychology and sociology courses at the European University Cyprus, where she has been employed as a Research Officer for the past 14 453

About the Contributors

years. Through her administrative position, she is representing the university in local and international networks aiming at gender equality, diversity and inclusion in STEAM research. Bob Eng is a wealth management advisor engaged in sustainability and ESG (environmental, social, governance) work. He holds a doctorate in Human Development and Psychology from Harvard University and an MBA from Columbia University. Tomas Hartley has a significant experience as a scientific consultant in Biomedical Sciences, ISO 15189 Quality systems and Statistics via his personal site, www.medlabstats.com. His recent work revolves around deploying Internet of Things applications with electronics boards under a STEAM framework targetted at Highschool students. Euripides Hatzikraniotis is a full Professor in the Department of Physics, Aristotle University of Thessaloniki - Greece. His research interests are on Materials Science (Thermoelectric Materials and Applications) and Science Education (Educational Technology, Lab & STEM education, DesignDevelopment & Evaluation of Teaching Learning Sequences). He has more than 350 publications in peer-reviewed journals, local and international conferences with more that 1650 citations (h-index: 20). Ilias Sitsanlis holds a bachelor’s degree in Physics from Aristotle University of Thessaloniki, a master’s degree in teaching natural sciences and currently is a Ph.D candidate in the deparment of Physics of Aristotle University of Thessaloniki. The working title of his thesis is “Design, creation and study of network simulations for teaching modern physics”. Mr. Sitsanlis has been teaching Science for 21 years and is an advisor for Greece’s Institute of Educational Policy regarding 21st century curriculum. Georgios Kalemis received his MS in Educational Science from the Hellenic Open University in 2019. Kostas Karpouzis is an Assistant Professor at the Department of Communication, Media and Culture. In his research, he’s looking for ways to make computer systems more aware of and responsive to the way people interact with each other. He is also investigating how gamification and digital games can be used in classroom and informal settings to assist conventional teaching and help teach social issues and STEAM subjects to children and adults. Since 1998, he has participated in more than twenty research projects funded by Greek and European bodies; most notably the Humaine Network of Excellence, leading research efforts in emotion modelling and recognition, the FP6 IP CALLAS project, where he served as Area Leader of Affective applications, the FP7 TeL Siren project (Technical Manager), which was voted Best Learning Game in Europe for 2013 by the Games and Learning Alliance Network of Excellence, the H2020 iRead project, which produced Navigo, the winner of the GALA Serious Games competition for 2018 and the H2020 ECoWeB project which builds engaging and personalized mobile applications to promote emotional wellbeing and prevent mental health problems in adolescents and young adults. He is a member of the BoD for the gi-Cluster of Corallia, which consists of industrial and academic members of the game and creative ecosystem in Greece, a member of the Hellenic Bioethics and Technoethics committee and Chairman of the Board of the Hellenic Association of Computer Engineers. He co-edited a book on “Emotion in Games: Theory and Practice” published by Springer in late 2016. His Google Scholar profile is available at https://scholar.google.gr/citations?user=12olpHgAAAAJ. Besides this, he is involved in a number of science communication activities, most notably Famelab Greece and 454

About the Contributors

openscience.gr. He’s also an advocate for technology and CS in primary schools, participating in the Girls Go Coding initiative and serving as an Ambassador of EU Code Week in Greece (until 2018). He has participated as a speaker in 3 TEDx events, including TEDxAthens in 2019, while in 2016, he authored a lesson on the TED-ed platform titled “Can machines read your emotions?”; the lesson surpassed 300.000 views in its first week. Iro Koliakou is the STEM Coordinator of Anatolia College. She teaches Physics and Biology in Anatolia College Thessaloniki, Greece and also teaches in the Masters Program Regenerative Medicine of the Medical School of Aristotle University of Thessaloniki. She is a member of the instructional staff of the John Hopkins Center for Talented Youth Greece and has developed the online course Biomedical Engineering and the future of Medicine. She is an ambassador for Scientix, the community for science education in Europe and a member of Science on Stage Deutschland, developing STEM activities related to the 17 Sustainable Development Goals. Furthermore she is a mentor for the Greek women in STEM association and a mentor for the Global talent mentoring program, led by the World giftedness Center. She holds a Physics degree from Aristotle University of Thessaloniki, a Master of Science from the Biomedical Engineering Department of Imperial College London and a PhD from the Biology Department of Aristotle University Thessaloniki. From 2009 she has worked in the private biotechnology sector in laboratory quality management and research and development responsible for implementation and internal audits of European R&D projects. She has published 15 scientific papers in international journals and has 190 references in international literature. She has received teacher training from ESA Robotics and Automation Lab (2018), European Molecular Biology Learning Lab (2017 & 2020), CERN (2019) and European Schoolnet Future Learning Classroom (2019). Anastasia Korompili is an active school teacher in Primary Education. She has also years of experience in teaching and creating educational material related to Physical Sciences, using STEM methodology; Educational Robotics and New Technologies in education. She graduated from the Department of Primary Education of University of Patras and she took part in Erasmus Program to study for a semester at the Faculty of Social studies of Masaryk University in Czech Republic. She received a master’s degree in «e-learning» after graduating from the Department of Digital Systems of University of Piraeus. She has successfully completed the attendance of a seven-month seminar entitled “School Psychology” of the University of Macedonia. She has also participated in seminars on educational technology tools, as well as in conferences related to the integration of technology in education as a speaker, such as the conference “Education Evolution” of the organization Socialinnov and the Panhellenic and International Conference “Teachers and Education STE (A) M”, with a presentation on the performance of girls in STEM fields, something that is the subject of her dissertation. Finally, she actively participates in educational robotics competitions as a team coach but also as a judge. Apostolos Kostas (B.Eng., M.Sc., Ph.D.) is Member of Laboratory and Teaching Staff at the University of the Aegean, where he teach undergraduate and postgraduates courses. He has participated in various national and EU-funded programs. Outcomes of his research on e-learning and Initial Teacher Ecucation have been presented in national and international conferences and published in journals and book chapters. He is also Director of the Lifelong Learning Centre of the University of the Aegean.

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About the Contributors

Spyros Kourias is an Educational Technologist (PhD) and his main research interests include the effectiveness of Maker Movement, Robotics, Coding, IoT methodologies in the context of non-formal education and technologically enhanced Instructional Design. He serves as Adjunct Lecturer in Constructionist Technologies at the Departments of Early Childhood Education and Primary Education of the University of Thessaly and since 2006 he has successfully implemented several R&D projects regarding technology-enhanced learning. Dr Kourias is also one of the founding members of TALOS Lab (talos.uth.gr) for which he is in charge as a project lead and educational technologist mentor since 2016. Manolis Kousloglou is a science teacher in 3rd Junior High School of Kavala and PhD student in the Department of Physics of Aristotle University of Thessaloniki, Greece (AUTH). His research interests include Mobile Learning, Inquiry-based learning and development of students’ 21st century skills - HOTS. Ilona-Elefteryja Lasica holds a BSc. in “Digital Systems” (2010) and an M.Sc. in “Technology Education and Digital Systems” (Track: e-Learning) (2012) from the Department of Digital Systems University of Piraeus, Greece. Her Ph.D. focused on Augmented Reality in Secondary Education in the Fields of STEM and was received from the European University Cyprus. Her research interests focus on Technology Enhanced Learning and Training, Innovation in STEM Education, Vocational Training and Lifelong Learning. During the past ten years, Dr. Lasica has been involved in more than fifteen EU funded research projects. Her research accomplishments include a number of articles and papers in international conferences and academic journals. She is a Research Associate at the EduTech Digital Innovation Hub of the University of the Aegean being involved in a number of projects concerning digital education and training. Dionysios M. Manesis, PhD, belongs to the teaching personnel of the department of Early Childhood Education of the National and Kapodistrian University of Athens, Greece. He has more than 17 years teaching experience in ICT in early childhood education and applied statistics. His research interests include the use of serious games in early childhood and primary education, the contribution of ICT and serious games in particular, in the learning and teaching process, augmented reality, and statistical applications in education and psychology. Maria Meletiou-Mavrotheris is a Professor at the European University Cyprus (EUC) and Director of ICT Enhanced Education Laboratory at EUC. She has a Ph.D. in Mathematics Education (University of Texas at Austin), an M.Sc. in Statistics (UT Austin), an M.Sc. in Engineering (UT Austin), an M.A. in Open and Distance Learning (UK Open University). She has engaged extensively in research and has directed and participated in several multinational, EU-funded projects focusing on the use of serious games and other ICT tools in teaching and learning at the school and higher education level, and in vocational training. Her research has been presented in numerous publications in scholarly international journals and books. Anastasios Molohidis’s main research work includes the design, development, implementation and evaluation of innovative Teaching Learning Sequences using ICT, within the framework of inquiry based learning and the study of professional development for both pre-service and in-service science teachers.

456

About the Contributors

Efthalia Mpalafouti is a kindergarten teacher who graduated from the department of Early Childhood Education of the National and Kapodistrian University of Athens, Greece. She is now a MSc candidate. Her research interests include the use of digital games in preschool education, and mobile devices technologies in primary and secondary education. Stavros Pitsikalis holds a Master of Science (M.Sc.) in “Technology Education and Digital Systems” (Track: e-Learning) from the Department of Digital Systems University of Piraeus, Greece and a BSc. in “Technology Electronic Engineering Educators” from the “School of Pedagogical and Technological Education”. He is currently a Ph.D. Candidate at the University of the Aegean, in the field of emerging technologies, specifically Augmented Reality, in Vocational Education and Training. As far as his professional experience is concerned, he is currently working extensively in the field of Educational and Vocational Management, as a Scientific Counselor at the Institute of Educational Policy (IEP) and the Head of the VET Unit, as well as the Teachers’ Training Unit. Moreover, he is a Research Associate at the University of the Aegean, being involved in a number of projects concerning digital education and training. In parallel, he is an Adult Educator, Vocational Trainer and Educator in Secondary Technical Education (Electronic Engineering field). His research interests focus on a number of topics, including Technology Enhanced Learning, Distance Learning and Training, Knowledge Management, Augmented Reality in Distance Education, STEM, Development of Vocational Education and Training (VET), Digital Media in Education, Open Education, ICT in Education, Instructional Design of Adult Learning Programs and Public Education Management. He has published several papers in National & International Conferences and Journals in the field of Education and especially, ICT in Education. Hariton Polatoglou is a Professor of Theoretical Solid State Physics and Didactics of Physics at the School of Physics of Aristotle University of Thessaloniki (AUTH) and is head of the graduate program on “Didactics of Physics & Educational Technology”. Also is head of the 1st Experimental Lyceum of Thessaloniki Greece. Recently his research focuses on Distance Learning, Nano-Science, STE(A) M Education, Education on Sustainable Development and Accessibility Technologies for students with disabilities. Sarantos Psycharis has published many papers in prestigious journals and has established various European-wide improved academic practices for Undergraduates, Postgraduates, and Fellow Professors alike. He was also the Coordinator, representing the Greek Government - for the European Network of Teacher Education Policies (ENTEP), and for two years President of the Network and Evaluator for European Commission. He also served as a Rector –and Chancellor of HE Institute- ASPETE. Currently he is Full Professor at the Higher Education Institute –School of Pedagogical and Technological Education –ASPETE- in the cognitive area «Education Applications of Computational Sciences”. Studies: Bsc in Physics (National University of Athens), PhD in Computational Physics (Glasgow University, UK) and Msc in Information Technology(National University of Athens). Lord Kelvin award for PhD students,1987, University of Glasgow, United Kingdom.He has published more than 120 papers in peer reviewed journals and international conferences. From 2015-2018 he was Scientific director of the Msc program “STEM in Education” a validated Msc program at ASPETE. Director of the research lab, “Educational Applications of Computational Sciences and Educational Technology Laboratory” He is President of the Hellenic Education Society of STEM, (Ε3 STEM)-www.e3stem.edu.gr and co-editor of the Hellenic Journal of STEM Education https://www.hellenicstem.com/index.php/journal His research 457

About the Contributors

interests include STEAM applications in Education, STEAM and Inclusive Education, Use of computing in Education. Professor Psycharis has been involved in many European and National projects for STEM and ICT in Education For a full CV you can visit http://education.aspete.gr/index.php/en/personnel/acc/ research-commitee/206-psycharis-sarantos.html and http://sarantospsycharis.weebly.com/. Doris Kristina Raave is currently a PhD student and junior research fellow at the Institute of Education at the University of Tartu. Her research focuses on the use of digital technology with and for personalization. Her background is in teaching foreign languages. She received her MA in Foreign Language Teaching from the University of Tartu in 2021. Eric Roldán Roa is a PhD candidate and junior researcher fellow in the Centre for Educational Technology, at the Institute of Education of the University of Tartu. His research topic is on pedagogical agent systems and how those systems could be meaningfully used to empower teacher practice with artificial intelligence pedagogy. He holds a Master degree in Educational Technology (University of Tartu, Estonia) and Bachelor degree in Music Production (Academia de Música FERMATTA, Mexico). Erika Roldan-Roa is currently a Marie Skłodowska-Curie Fellow in the EuroTechPostdoc Programme at the Technische Universität München (TUM) and EPFL Lausanne. At TUM, she is working with the Applied & Computation Topology group leaded by Ulrich Bauer. At EPFL, she is working with the Laboratory for Topology and Neuroscience lead by Kathryn Hess-Bellwald. Project: Topological and Geometrical Data Analysis of Random Growth Models. Until January 2020, she was Visiting Assistant Professor and Director Outreach at The Ohio State University (OSU) in the Department of Mathematics working with the Topology, Geometry, and Data Analysis (TDGA) research group. She got her PhD in May 2018 at the Center for Research in Mathematics (CIMAT). Her advisors were Matthew Kahle (OSU) and Víctor Pérez-Abreu (CIMAT). Her research interests include biomathematics, stochastic topology, topological and geometric data analysis, extremal topological combinatorics, discrete configuration spaces, recreational mathematics, learning analytics, and educational technology. Evgenia Roussou is a kindergarten teacher with extensive experience in public schools of Piraeus, Greece. She holds a Bachelor’s degree in Early Childhood Education and a Master’s degree in ICTE from the National Kapodistrian Univesity of Athens. She has also worked as an EFL teacher and holds an RSA Diploma from the Universtiy of Cambridge. She has successfully completed creative projects in the fields of Animation, Digital Storytelling and Documentary. She often blogs about innovative teaching ideas and lesson design and publishes articles in journals and conferences. She was given the Award for Excellent Educational Scenario by the Ministry of Education for her lessons on emotional intelligence. Her research interests involve Thinking, IC Technology and Robotics in authentic educational settings. She is currently involved in a study focusing on robotics and cognitive development of young children. Atajan Rovshenov is Computer Science Teacher in the Ozel Ege Lisesi, Turkey. He holds a Master of Computer Education and Instructional Technology (CEIT) from Ege University in 2020. His research areas include computer science education, instructional technologies, and assistive technologies. https:// orcid.org/0000-0001-9189-3438.

458

About the Contributors

Maria Teresa Sarmento Lopes is a Senior Researcher at CEiiA Centre of Engineering and Product Development. She has a Ph.D. from the Faculty of Engineering, University of Porto FEUP since 2013, where she developed her thesis on Service Design and Mobile Service Experiences. She is a Designer graduated from the College of Art and Design ESAD and Post-graduated from the Glasgow School of Art and the Portuguese Design Center. She also has an MSc in Industrial Design from ESAD / FEUP. She has been a lecturer since 1999 as a professor and guest professor in several contexts from Design, Creativity, Human Factors, or Marketing. After she did Post-Doctoral research at the Faculty of Economics of Porto University, her research work focused on new methods for multidisciplinary thinking in product and service experiences, considering the critical role of Design. She feels comfortably challenged in involving people from different backgrounds. She is currently coordinating an area of Future Design at CEiiA where maps trends and approaches for tomorrow. Recently, she published in the Journal of Place Management and Development and Handbook of Research on Solving Modern Healthcare Challenges. Amartya Sharma is a student in the Politics & Values Program at George Washington University, Washington, DC. Dinesh Sharma is the Director and Chief Research Officer at Steam Works Studio, an edu-tech company in Princeton, NJ. Elias Stouraitis holds a PhD in Historical Culture and Digital Games at Ionian University in Greece. He also holds a BA in History and Archaeology and a Master’s Degree in Modern Greek History from the University of Athens/Greece. He has worked as a researcher in several European and national projects concerning history, education and games. His main research interests are History Education, Historiography, Historical Culture, Design of Educational Software/Games for History and teaching/learning history with Digital Technology. He has been awarded a grant from the Japanese Nippon Foundation SYLFF (Sasakawa Young Leaders Fellowship Fund) and an award by Common Ground Community ‘The Learner’. Elena Stylianou is Associate Professor in Art and Art History at the European University Cyprus (EUC), and President of the International Association of Photography and Theory (IAPT). She holds an EdD in Art and Art Theory from Columbia University, TeachersCollege in NY and has worked as a postdoctoral fellow at the Institute of Education, UCL investigating the relationship between technology and museums. Her research evolves around the study of contemporary art and photography, as well as museums and curatorial practices. Her academic work has been published widely in book chapters and academic journals. In addition, she has curated a number of international exhibitions of contemporary art in Cyprus and has participated in many funded projects. Ioannis Theocharopoulos is a physicist currently working as a Secondary Education Physics teacher, Physics coordinator, STEAM instructor and STEAM coordinator at The European School Brussels III. He holds an MBA from the Athens University of Economics and Business and PhD in Informatics from the University of Piraeus.

459

About the Contributors

Timoleon Theofanellis has worked in the field of education for 27 years as a secondary and adult school teacher, teacher educator, curriculum designer and currently he works as Fellow Assistant of ASPETE School of Pedagogical and Technological Education. Currently he is the Director of secondary education on Lesvos and Limnos islands (2020-now). He has studied Physics and Computer Science from B.Sc. to Ph.D. and has 25 publications in journals and 60 presentations in conferences (Greek and international). Has participation in 17 books on educational issues, educational web use, and computer science education. His current interests are in the field of educational technology and social learning. Savvas Tsolakis received his bachelor degree in the Department of Electrical and Computer Engineering of the University of Thrace in 2000 and his MS in Automation In Irrigation, In Agricultural Constructions And In The Mechanization Of Agriculture of Department of Agriculture Crop Production and Rural Environment Of the University of Thessaly in 2016. He worked as an Electrical Engineer for two years. Since 2004 he is a secondary school teacher on informatics. One of his interests is in educational robotics, especially Arduino system and LEGO EV3. He is preparing school teams for robotic competitions. He is now studying Archaeology at the University of Thessaly in the Department of History, Archaeology and Social Anthropology. Ioanna Vekiri studied as a Fulbright scholar in the U.S., where she earned an MA in Educational Communications and Technology from New York University and a PhD in Education from the University of Michigan. She lives in Greece where she has worked as a researcher and educator in higher education for several years and has participated in the design and/or implementation of teacher professional development programs. Since 2017 she been affiliated with the European University Cyprus (EUC) Distance Learning Unit and with the Hellenic Open University in Greece. Her research focuses on the cognitive and motivational aspects of learning with ICTs and on teachers’ beliefs, knowledge, and classroom practices. She has presented her work at international conferences and journals. Chryssi Vitsilaki completed her Undergraduate Studies in Sociology at Trinity College, Hartford, Ct. and received an M.A. and a Ph.D. from the Department of Sociology, of the University of Chicago, Illinois, USA. She has been teaching at the Department of Preschool Education and Educational Design of the University of the Aegean since 1999. She has been responsible for designing, organizing and directing the Postgraduate program of the Department titled “Gender and New Educational and Work Environments in the Information Society”, which is the only postgraduate program in Greece that has implemented e-learning and blended learning techniques from 2004 until 2014 and which was awarded by the European Commission with the “2009 Award for Quality in eLearning”. From 2014 onwards, she has organized and directed the postgraduate program of the aforementioned Department titled “New Forms of Education and Learning”. Her academic work focuses on gender issues and new forms of education with the use of technology, on which she has published 10 books and more than 50 articles. In addition, she has designed and implemented as Scientific Coordinator a great number of European and co-funded research programs as well as intervention programs on these issues, and has been a member of national and international committees for the evaluation of relevant projects and programs. She has held the positions of Dean of the School of Humanities (2004-2006), Vice-Rector of Finance and Development, and President of the Research Committee of the University of the Aegean (2006-2010), Chair of the Department of Preschool Education and Educational Planning (2014-2018) and is presently the Rector of the University of the Aegean (2018-2022). 460

About the Contributors

Evagelia Voulgari received her bachelor’s degree in informatics from the University of Piraeus in 1997 and her MS in Department of Electrical and Computer Engineering of the University of Thessaly in 2008. She worked as a senior software engineer, developing in house software, for more than six years. She specialized in Document Management, Data Warehouse and Customer Relationship Management systems. Since 2003 she is a secondary school teacher on informatics. One of her interests is educational robotics and she is preparing teams for robotic competitions. She is now studying economics at the University of Thessaly in the Department of Economics. Iro Voulgari is a postdoctoral researcher at the Institute of Digital Games, University of Malta, and teaching staff at the Department of Early Childhood Education, National and Kapodistrian University of Athens, Greece. Her research and publications focus on game based learning, game studies, ICTs, and digital literacy. She is teaching undergraduate and postgraduate courses on digital games, virtual worlds, and learning technologies. She has organised several workshops and events relevant to game-based learning, game design, Information and Communication Technologies in Education, and Digital Storytelling. Georgios K. Zacharis is Adjunct Academic Staff at Aristotle University of Thessaloniki (AUTH) & Adjunct Academic Staff at Hellenic Open University (HOU). He holds a Diploma and a Master of Science in Physics from School of Science, Department of Physics, and a PhD from the Department of Primary Education, both from the University of Ioannina, Greece. He has participated in European and National projects since 2004. His main research interests are on ICT in Education, Learning Technologies, Science Eduacation and Educational Neuroscience. Anastasios Zoupidis is an Assistant Professor in physics education at the Department of Primary Level Education at the Democritus University of Thrace in Greece. His research interests include Design, Development, Implementation and Evaluation of Innovative Teaching Learning Sequences, for educating pupils and teachers, both in formal and informal education. These sequences are developed in a constructivist framework, aiming at learning through and about inquiry (e.g., Control of Variables Strategy, models, and modelling, etc.).

461

462

Index

21st century skills 2, 23, 26, 53, 84, 132-133, 135, 148, 154, 157, 161, 166, 169, 171-172, 177, 199, 230-231, 345, 349-350, 352-353, 357, 359, 361-362, 387 5E Learning Model 222-224, 229-230, 234

A activity center 100, 105 ADDIE 296, 302, 314-315, 319 affordances 59, 110, 115, 127, 132-135, 183, 340, 362, 406 AI education 1-6, 14-17 AI literacy 1, 3-4, 6, 8, 15, 20-21 Android Apps 361 Arduino 111, 113, 227, 231, 239-244, 247-251, 253257, 259-263, 349-350, 356, 362-365, 367-368, 379-380, 387 Artificial Intelligence 1-3, 7-8, 14, 19-21, 86, 110, 150, 155, 161, 175, 228, 397 Artificial Intelligence (AI) Literacy 21 Arvanitakis 132 Augmented Reality (AR) 57, 133, 135-136, 149, 153155, 161-164, 166, 169, 172, 175

B Blockly 364, 389 Bluetooth 206, 361-362, 366-368, 373-374, 377-379, 381, 383-386

C C++ 228, 239, 242, 244, 249-251, 253, 257, 259262, 287 Challedu 41 collaborative learning 151, 183, 195, 202, 214-216, 218, 231, 245, 322, 337, 339-340, 347, 358-359 Compromise Skills 105  

Computational Thinking (CT) 2, 18, 25, 37, 39, 84-86, 88, 101-102, 104-105, 110, 115, 128, 135-137, 148-149, 151, 239-242, 254-257, 267-268, 274, 293-294, 358, 389, 393-394 conceptual knowledge 324, 327, 331, 340, 345 constructionism 3, 76, 83, 104, 111-112, 225, 230, 347, 350, 358-359 Constructivism 23, 38, 129, 132, 241, 347, 357 control group 36, 40, 185-186, 192-193, 195, 344, 348-349, 351-354 Conversation Theory 265, 267-269, 293-294 course design 5, 7, 137, 224 Creative practices 320 Cybernetics 267-268, 293-294

D Digital Audio Workstation (DAW) 294 digital games 8, 35, 37, 42, 52, 55, 60 digital literacy 2-3, 11, 15, 18, 90, 392, 404 Digital to Analog Converter 294 disadvantaged groups 49, 65, 320, 338, 398

E early childhood 15, 20, 22-23, 39, 84, 87, 90, 101-104, 109, 128-130, 148, 220, 390, 394, 406 Education for Sustainable Development 61-62, 66, 70, 82-83, 406 educational games 43-44, 56-58, 60, 320, 336, 340 educational intervention 35-36, 40, 89-90, 104, 183, 321, 337, 349 educational robotics 22-26, 28, 35-40, 81, 85, 87-88, 101, 103, 109-110, 112, 116-117, 127-128, 130, 132-136, 148-151, 219, 221, 225-227, 229-232, 237, 240, 254, 256, 359, 362, 387 Educational Scenario/Lesson Plan 4, 6, 15-16, 21, 84-85, 88-91, 100, 142, 155, 163-164, 222, 224, 229, 235-236, 244-245, 256-257, 395

Index

educational workshop 321, 324, 336, 340 embodied learning 132-133, 135-136, 152 emerging technologies 153-156, 159, 161-162, 165170, 172, 174-175, 196, 218, 387, 393 EPAL 153-154, 166, 168, 170, 175 Erasmus+ 2, 17-18, 41, 62, 79, 170 ESA 344-345, 349, 355, 360 escape room 43, 49, 52-53, 57, 59-60 European University Cyprus 41 Evolutionary Algorithm 10, 21

inquiry continuum 304-305, 312, 314, 317, 319 inquiry learning 132, 136, 197, 199, 215, 304 inquiry-based learning 54, 137, 161-162, 168, 173, 176-177, 179-181, 184-186, 188, 194-199, 222, 297, 302, 304, 307, 313-315, 317 interdisciplinarity 153-154, 161, 173, 267, 306 interventions 23-24, 28, 36, 46, 89, 130, 132-138, 147-148, 169, 267, 344-345, 355, 357 IOT 155, 215, 361-363, 365, 367, 374-375, 384-387, 389

F

K

factor analysis 185, 191-192, 205, 209, 212, 218, 349-350 FemSTEAM Mysteries game 41-42, 44, 48-49, 51-53 floor robot 84 Fourier Analysis 276, 294 Fourth Industrial Revolution (4IR) 155, 170, 175 free play 94, 105, 127 Frequency of a Note 294

Kostas 1, 22, 153

G game-based learning 2, 39, 42-44, 53, 56, 58, 60, 90, 161, 217 Gamification 58, 323, 337-339 gender equality 26, 41-42, 49, 52, 55, 398, 402 gender gap 22-23, 26-27, 35-36, 38, 59, 402, 406 gender stereotypes 26-27, 37-38, 41-42, 45-46, 48, 55-56, 58, 60 General Systems Theory 293-294 Gordon Pask 265, 267, 293

H harmonics 268, 272, 274, 276, 294-295 high-level thinking 179, 199, 225 Hohmann transfer 296-298, 300-301, 310-311, 318-319 HP Inc 321, 337 human computer interaction 136, 306

I IBL 176-178, 180-182, 194-195 ICT 20, 27, 44, 58, 90, 101, 103, 132-136, 147-149, 152, 154, 171, 173, 176-177, 197, 216-217, 239, 245, 266, 271, 317, 337, 361, 389 IEK 153-154, 166, 168, 170, 175 IEP 173, 304, 319 in plenary 90, 94, 98, 106, 188

L Lasica 153-154, 162-163, 172-173 learning activities 17, 43, 72, 194, 201, 212-213, 245246, 321, 335, 340, 362 learning games 42-43, 53, 57, 60 learning theories 241, 257, 346 LEGO Education 225, 390, 405

M Machine Learning 1-2, 8, 14, 18-21, 294 Make-Ing 23, 40 Maker Education/Movement 406 Makerspace 37, 77-78, 83 Makey-Makey 132-133, 136-138, 140-141, 143-145, 148, 152 Marginalize Communities 340 mathematical approaches 320 mathematical thinking 90, 109-110, 114, 117, 119121, 127, 274 Max/MSP 265, 273-274, 284-285, 292, 294 mediators 109-110, 117 mIBL 176-177, 181-186, 194 MicroMite 361-362, 366-369, 371-374, 377-378, 389 mind-tools 109, 112-113, 117, 124, 127 MiniOpenLab 61, 69, 73, 78, 83 Mixed Reality (MR/XR) 132, 134-136, 138, 140, 147152, 155, 161, 172, 174-175, 255-256 MMBASIC 361, 366-367, 375, 378-380, 389 Mobile Inquiry-Based Learning 177, 181, 197-199 Mobile Learning/M-learning 24, 104, 176-178, 180184, 186, 195-199, 202-207, 213-218 mobile technologies 177, 180-181, 183, 198-199, 201, 213-214, 339 Modular Synthesis 284, 295 463

Index

motivation 26-27, 38, 43, 47, 52-53, 59, 75, 86, 97, 135, 142, 158-159, 169, 176-177, 181-185, 190-199, 203, 205-207, 215-216, 226, 229-231, 243, 248, 297, 317, 322-323, 325, 327, 333, 337, 339, 346 multidisciplinary 16-17, 64, 132-133, 135, 148, 294, 406 multimodal 37, 39, 110, 132-133, 135, 141, 148, 362 musical instrument 152, 272, 289, 294-295 Musical Instrument Digital Interface (MIDI) 294 MusicMath 321, 324, 329, 336-337, 341

N NASA 228, 297, 303, 316-317, 319, 396 Negotiation Skills 106 noise signal 280, 295 Non-Government Organisation (NGO) 406

O Ontology 267, 269, 272-273, 277-278, 280, 282, 289, 294-295 oscilloscope 273, 285, 295 Overtones 295

P Palaigeorgiou 132-135, 138, 140, 142, 148-151, 256 Perceived Ease of Use 205-206, 214, 218 perceived usefulness 181, 201, 205-207, 209, 211212, 214, 218 perceptions 4-5, 7, 13-14, 38, 44, 46, 55, 58, 71, 82, 96, 130, 149, 171-172, 175, 196, 201, 203-209, 211-214, 218, 233, 254, 297, 344, 360 PIC microcontroller 361-362, 366, 368 pitch 274, 282, 294-295 Pitsikalis 153-154, 160-161, 173-174 planetary and spacecraft orbits 296 pre-school 23-24, 84, 86, 345 preschool education 104, 109, 129 Preschooler/Kindergartner 106 primary education 1, 4, 11-12, 58, 66, 84-85, 103, 204, 214, 216, 401-402 primary school 23, 29, 31, 35, 37, 39, 61, 86, 103, 149, 228, 254, 256 Principal Component Analysis (PCA) 360 problem-based learning 156, 162, 222, 226, 346, 357, 360, 406 procedural knowledge 320-322, 330, 340 project-based learning 161, 222, 226, 231, 239, 254255, 257, 406-407 464

R Raspberry Pi 231, 361-362, 364, 366-367, 378-381, 388-389 Raspberry Pi PICO 361-362, 366-367, 378-381 Reinforcement Learning 2, 5-6, 8, 14-15, 21 robotics 11, 13, 22-26, 28, 35-40, 63, 66, 81, 84-89, 92, 100-105, 109-112, 116-117, 127-136, 141, 148-151, 155, 219, 221, 224-233, 237, 239-243, 249, 254, 256, 345, 351, 355, 357-360, 362-363, 387-388, 393-396, 405 Role Model Pedagogy 60 role models 27, 46, 52, 58, 60

S scaffolding 117, 162, 183, 195, 197, 199, 248, 256, 273, 338, 395 Schola Europaea 265 Scratch 24-25, 39, 111, 132-133, 136-138, 142-144, 148, 151-152, 162, 256, 364, 389, 394, 405 SDG Goals 390 SDGs 66-69, 83, 390, 398-401, 404-405, 407 secondary education 1-6, 8, 11-12, 14-16, 19-20, 23, 25, 38, 41, 63, 103, 154-155, 172, 201, 203, 212213, 222, 230, 256, 265, 349, 398 self-concept 55, 58, 201, 205 self-efficacy 26-27, 149, 183, 185, 192-194, 197, 201205, 207-209, 211-213, 215-218, 302, 323, 358 serious games 41-44, 52-54, 57-60 simulation 43, 137, 150, 231, 239-240, 243-244, 249251, 253, 255, 259, 263, 265, 296-298, 303-314, 318-319 skills acquisition 84, 86 smartphones 177, 180, 186-187, 189, 201, 211-212 SMQ II 176, 185 social interaction 40, 44-45, 89, 103, 111, 149, 207, 209, 211-212 Soft Skills 40 Software Development Kit (SDK) 295 software synthesizers 265, 276 sonification 269, 287, 295 spatial skills 109, 115 Spectrum Analysis 295 STEAM education 41-42, 47, 53-54, 57, 73, 148, 151-153, 155, 163-164, 166, 170, 239-241, 268, 292, 296, 312, 359, 362, 387-389, 391-392, 394, 397, 404, 407 STEAM Practices 340 STEM education 56-58, 60-64, 66, 70, 78-83, 105, 149, 151, 154, 162, 170, 173, 176-179, 181-183, 186,

Index

195, 197-199, 217, 219-226, 229-233, 235-237, 240, 242, 254-256, 267, 293, 298, 316, 347-348, 357-360, 363, 387-388, 406-407 STEM/STEAM 44-45, 47-49, 53, 87, 407 subtractive synthesis 265, 273, 276-277, 285, 295 Supervised Learning 2, 5-6, 8, 15, 21 Sustainable Development 2, 19, 61-62, 66-70, 72, 74, 78-79, 82-83, 175, 390-391, 398-400, 405-407 Sustainable Development Goals (SDGs) 69, 398, 405, 407 synthesizer 271-277, 279-286, 290, 295

timbre 274, 276, 281-282, 295 Tinkercad 239, 243-244, 247-251, 253-255, 257-259, 261, 263 TPD programs 153-155, 159-160, 163-168, 170

U

T

V

Tangible (or Haptic) Programming 39, 84, 111, 115, 118 teacher training 1-5, 7, 11-17, 57, 148, 172, 174, 198, 213, 233, 245 teaching intervention 114, 123, 132, 241, 344, 349350, 355-356 technology integration 159, 170-171, 205, 221, 224, 226, 229, 231, 234 Technology-Enhanced Learning 247, 339-340

Veroboard 365-368, 375, 377, 379-382, 389 Virtual Studio Technology (VST) 295 visual programming 23, 115, 265, 287, 290, 292, 364, 389 Vitsilaki 153-154, 161, 174

UARO 22-23, 28-29, 34-36 UN 61-62, 69, 78, 82-83, 390-391, 398, 401, 404, 407 United Nations (UN) 407 University of the Aegean 153

465