Pedagogy and Psychology in Digital Education 9819921066, 9789819921065

Citation preview

Stefanie Yen Leng Chye Bee Leng Chua   Editors

Pedagogy and Psychology in Digital Education

Pedagogy and Psychology in Digital Education

Stefanie Yen Leng Chye · Bee Leng Chua Editors

Pedagogy and Psychology in Digital Education

Editors Stefanie Yen Leng Chye National Institute of Education Nanyang Technological University Singapore, Singapore

Bee Leng Chua National Institute of Education Nanyang Technological University Singapore, Singapore

ISBN 978-981-99-2106-5 ISBN 978-981-99-2107-2 (eBook) https://doi.org/10.1007/978-981-99-2107-2 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023, corrected publication 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

Digital education can be defined as the innovative use of digital tools and technologies in teaching and learning (Mclaughlin, 2018). Technology has profoundly reshaped every aspect of education, from the way we deliver lessons to the pedagogies used in classrooms. There is increasing adoption of emerging technologies and tools in schools, ranging from adaptive learning systems, mobile learning, learning analytics, virtual and augmented reality, MOOCs, digital portfolios to virtual learning environments and communities. The COVID-19 pandemic forced many schools to shift to online remote learning, accelerating the adoption of digital learning worldwide. Even before the pandemic, there was already strong growth in the use of technology in education, with global education technology investments reaching $18.6 billion in 2019 and the market for online education projected to reach $350 billion in 2025 (World Economic Forum, 2020). A Gallup survey indicated that 65% of teachers used digital tools to teach every day, while 70% of students report using digital learning tools outside of school for schoolwork at least a few days a week (Gallup, 2019). With the transition to the endemic phase, digital education has become widely accepted and is considered an important approach that can overcome the limitations of in-person learning. The huge emphasis on digital education means that both students and educators have had to contend with disruptions and changes to school learning and classroom instruction as typically known. It is now the expectation and the norm to make necessary changes, adjustments and transitions to alternative modes of instruction delivered through asynchronous web-based instruction, real-time video conferencing or blended and hybrid instruction. In much of digital education especially in the last few COVID-19 years, the emphasis has been on the affordances of the tools and the digital environment in bringing out student learning. This is not surprising given the need for “rapid online learning” (Roman et al., 2021). Nevertheless, there is recognition that digital tools need to be accompanied by good pedagogy. There always remains a human element that cannot be automated, and so we need to place the “human” back in the core as we study digital education (Storme, et al., 2016).

v

vi

Preface

The use of technology-based learning, when appropriately designed, has the potential to deepen student-centered and active learning experiences, foster twentyfirst-century skills, such as creativity and critical thinking, increase learner engagement and motivation, allow greater access and equal opportunities in learning, and transform the way teachers and students communicate and collaborate. Digital learning environments can free learning from the constraints of time and space, allowing students to learn anytime-anywhere at their own pace. This enables nonlinear forms of education that encourage students to learn across a combination of formal and informal contexts (Foutsitzi & Caridakis, 2019). The chapters in this book endeavor to inform educational practice and research as learning and instruction are shifted to digital environments both in times of crisis and beyond. We consider the relationships and implications for digital education, pedagogy and the psychology of teachers and students. Through these chapters, with case studies and examples from international education institutions, readers will be able to gain a better understanding of the affordances of technology-based learning, how they impact the cognitive and affective processes of learners, facilitate new pedagogical approaches and transform learning environments. This book is divided into three thematic sections: Digital Education for Twentyfirst-Century Learning, Innovative Uses of Digital Technology in Education and Challenges in Digital Education.

Part I: Digital Education for 21st Century Learning Part I of the book consists of six chapters on the theme of digital education for twenty-first-century learning. In this section, we explore how digital environments can be designed to promote twenty-first-century approaches to education, such as self-regulated learning, problem-based learning, knowledge building and selfdetermination theory strategies, in order to facilitate the fostering of skills essential for the future. In Chapter “A Self-Determination Theory Perspective on Online Lessons,” Kah Loong Chue offers a self-determination theory (SDT) perspective on online lessons. A number of strategies are proposed to facilitate a sense of autonomy, competence and relatedness according to the tenets of SDT, to foster students’ intrinsic motivation in both synchronous and asynchronous online environments. Today, many higher education institutions are facing the challenge of teaching increasingly large cohorts of students. In Chapter “Student-Centered Learning with Large Student Groups: Rationale, Organization, and Experiences in Problem-, Project-, and Team-Based Learning,” Sofie Loyens, Elisa Ferrer, Ivette Van der Sluijs, Remy Rikers and Lisette Wijnia examine how problem-based learning, project-based learning and other student-centered learning approaches can be applied to large student groups through the support of appropriate technology.

Preface

vii

Boon Khing Song’s research study in Chapter “Online Synchronous Peer Feedback Practice During COVID-19: Learners’ Self-Regulated Learning Mediates Their Perceived Value of Feedback and Feedback Uptake” focuses on the pedagogical practice of peer feedback in online synchronous environments during COVID-19. The study investigates the relationship between the perceived value of feedback, self-regulated learning (SRL) and the uptake of feedback, and validates a model of feedback uptake mediated by SRL. In Chapter “Does Online Coaching Support Training Transfer? Coaches’ Perceptions of Early-Career Teachers’ Implementation of Self-Regulation Strategies in the Context of a Professional Development Programme,” Christine Buschor, Zippora Bührer, Andrea Frei, Simone Berweger and Christine Wolfgramm examine the practice of online coaching in the context of teacher education and professional development. Through interviews, content analysis is used to analyze the effectiveness of online coaching to support the transfer of self-regulation strategies for early-career teachers. The role of coaching and goal orientation in teacher education is discussed. Chapter “Digital Portfolios for Problem-Based Learning: Impact on Preservice Teachers’ Learning Strategies” explores the use of a digital portfolio platform to facilitate and enhance the problem-based learning process for preservice teachers. In this study, Bee Leng Chua, Oon-Seng Tan and Woon Chia Liu analyze the impact of problem-based learning within a digital portfolio environment and examine how it can help to facilitate the development of preservice teachers’ learning strategies. Chapter “Formative Assessment to Support Preservice Teachers’ Self-Regulated Learning in Digital Education” embarks on a study of formative assessment practices in digital education. Selda Aras identifies how the formative assessment process can help to foster self-regulated learning and reflection, and provides practical strategies on how assessment for learning practices can be integrated with distance education.

Part II: Innovative Uses of Digital Technology in Education Part II consists of six chapters demonstrating innovative uses of digital technology in contemporary education. Ranging from immersive virtual simulations, mobile applications, MOOCs, digital portfolios to danmaku video comments, the chapters provide case studies and insights into how these innovations can be effectively used to transform and deepen learning. In Chapter “Man–Machine Partnership to Support Remote Peer Tutoring—Psychological, Pedagogical, and Technological Considerations for the Development of a Mobile Application,” Seng Chee Tan, Chee Kit Looi, Yin Ling Cheung and Sheng Hung Chung propose a design for a mobile application that can support remote peer tutoring among university students. Relevant psychological concepts such as self-determination theory and self-system theory were considered to promote students’ motivation to learn. The application provides features, such as

viii

Preface

24/7 peer tutoring, tutor-tutee matching, canvas for shared resources, communication tools for collaboration that are aligned with various theories and pedagogical considerations. Chapter “Supporting Knowledge Building with Digital Technologies: From Computer-Supported Collaborative Learning to Analytics and Artificial Intelligence” explores how digital technologies and man-machine partnerships can be harnessed to support Knowledge Building (KB) classrooms. Chew Lee Teo analyzes the pedagogical design and integration of an online discussion forum and learning into a series of Literature lessons to give students the agency to create new learning possibilities for reflexive knowledge building. The coronavirus pandemic has led to a surge of interest in MOOCs as learning across the globe shifted online. To facilitate the design of good online courses, Chapter “Using Pedagogical Principles to Design a MOOC for Parents and Educators” by Chee Soon Tan, Stefanie Chye, Yvonne Seng and Caroline Koh proposes various educational psychology theories and pedagogical principles that can be applied to the development of MOOCs, illustrating them through a case study of a MOOC designed for parents and educators. In Chapter “Teaching Social-Emotional Learning with Immersive Virtual Technology: Exploratory Considerations,” Marcus Tan, Stefanie Chue and Shu Min Teng evaluate the effectiveness of Immersive Virtual Environments (IVEs) as a pedagogical approach to the teaching of social and emotional competencies. The findings show how IVEs can effectively facilitate perspective-taking and empathy, due to its ability to immerse the user in the fictional space of the narrative, thereby encouraging a deeper sense of presence and embodiment. Chapter “Supporting Health Professions Education with Virtual Simulations: The Role of Technical, Educational, and Affective Factors in Assessing Opportunities and Challenges” by Jason Harley, Elif Bilgic and Andrew Gorgy focuses on how virtual simulations can support health professions education, providing students the opportunity to practice healthcare procedures in a game-like environment. The chapter discusses technical, educational, motivational and emotional factors to be considered, as well as the valuable role virtual simulation technology can play as a distance learning tool. In Chapter “Can Social Presence Promote Meaningful Learning? Danmaku Video Learning to Enhance Social Presence and Meaningful Learning,” Tzu-Hsiang Peng and Tzu-Hua Wang analyze how Danmaku, a real-time comment system for online videos, can help to enhance social presence and promote meaningful learning. Using the cognitive–affective theory of learning with media (CATLM) model, the dimensions of emotional arousal, social presence and meaningful learning were measured and analyzed.

Preface

ix

Part III: Challenges in Digital Education With the rapid adoption of digital learning tools and platforms, we must be cognizant that technology is not a panacea for all the challenges of contemporary education. Part III consists of three chapters exploring various challenges and pitfalls that may arise from the use of technology in education, and what we can do to address them. In Chapter “The Other Side of the Promise: Some Precautions for Technology-Based Education,” Woei Hung emphasizes the need to critically examine possible hidden trade-offs behind the promises of technology-based education, to avoid being blindsided and to maximize positive effects on student learning. This chapter discusses seven possible trade-offs and cautions for employing technology-based learning from cognitive, social and pedagogical perspectives. A growing body of research suggests that digital learning resources can create in students a mismatched sense of familiarity and comprehension that does not align with how much they have actually learned. In Chapter “Misjudgements of Learning in Digital Environments,” Jason Lodge explores how students make judgments about their learning progress in these digital environments, why it is that these judgments go awry, and what might be done about it. In Chapter “Mediating Effect of Loneliness on Social Emotional Learning and Problematic Internet Use in Singapore Youth,” Martha Too, Stefanie Chye and Wee Kwang Tan address the rising prevalence of Problematic Internet Use (PIU) globally. The study investigates and analyzes the relationship between Social-Emotional Learning skills, loneliness and PIU, using data collected from Singapore schools. The implications on policy and practice, as well as directions for future research, are discussed. Digital education has the potential to bring about new possibilities and affordances, but learning transformation may not occur by simply adding on the latest technology tools in classrooms. The design of the virtual learning environment, the development of new learning models and the pedagogical understanding of teachers play crucial roles in improving student outcomes. We hope that this book can help to re-imagine new possibilities in education that will prepare students for a more complex and rapidly changing future. We wish to express our deepest gratitude to all authors, reviewers, consultants, editorial assistants and the Springer editorial team, for their invaluable contributions to this book. Singapore, Singapore

Stefanie Yen Leng Chye Bee Leng Chua

References Carraro, K., & Trinder, R. (2021). Technology in formal and informal learning environments: Student perspectives. Global Journal of Foreign Language Teaching, 11(1), 39–50.

x

Preface

Foutsitzi, S., & Caridakis, G. (2019, July). ICT in education: Benefits, challenges and new directions. In 2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA) (pp. 1–8). IEEE. Gallup. (2019). Education technology use in schools: Student and educator perspectives. Gallup Inc. & NewSchools Venture Fund. McLaughlin, C. (2018). What is digital education? Institute of Academic Development, University of Edinburgh. https://www.ed.ac.uk/institute-academic-development/learning-teaching/ staff/digital-ed/what-is-digital-education Roman, T. A., Edwards, B. P., Dias, M., & Brantley-Dias, L. (2021). STEM teachers’ designs for learning: Addressing the social and political climate during COVID-19. The Journal of Applied Instructional Design, 10(4). Storme, T., Vansieleghem, N., Devleminck, S., Masschelein, J., & Simons, M. (2016). The emerging pedagogy of MOOCs, the educational design of technology and practices of study. Journal of Computers in Education, 3(3), 309–328. World Economic Forum. (2020). The COVID-19 pandemic has changed education forever. https://www.weforum.org/agenda/2020/04/coronavirus-education-global-covid19-onl ine-digital-learning/

Contents

Digital Education for 21st Century Learning A Self-Determination Theory Perspective on Online Lessons . . . . . . . . . . . Chue Kah Loong Student-Centered Learning with Large Student Groups: Rationale, Organization, and Experiences in Problem-, Project-, and Team-Based Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sofie Loyens, Lisette Wijnia, Ivette van der Sluijs, Eliza Ferrer, and Remy Rikers Online Synchronous Peer Feedback Practice During COVID-19: Learners’ Self-Regulated Learning Mediates Their Perceived Value of Feedback and Feedback Uptake . . . . . . . . . . . . . . . . . . . . . . . . . . . . Boon Khing Song Does Online Coaching Support Training Transfer? Coaches’ Perceptions of Early-Career Teachers’ Implementation of Self-Regulation Strategies in the Context of a Professional Development Programme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Christine Bieri Buschor, Zippora Bührer, Andrea Keck Frei, Simone Berweger, and Christine Wolfgramm Digital Portfolios for Problem-Based Learning: Impact on Preservice Teachers’ Learning Strategies . . . . . . . . . . . . . . . . . . . . . . . . . Bee Leng Chua, Oon-Seng Tan, and Woon Chia Liu

3

17

49

73

91

Formative Assessment to Support Preservice Teachers’ Self-Regulated Learning in Digital Education . . . . . . . . . . . . . . . . . . . . . . . . 107 Selda Aras

xi

xii

Contents

Innovative Uses of Digital Technology in Education Man–Machine Partnership to Support Remote Peer Tutoring—Psychological, Pedagogical, and Technological Considerations for the Development of a Mobile Application . . . . . . . . . . 121 Seng Chee Tan, Yin Ling Cheung, Chee Kit Looi, Sheng Hung Chung, Starion Junhan Lim, and Wai Hoe Wong Supporting Knowledge Building with Digital Technologies: From Computer-Supported Collaborative Learning to Analytics and Artificial Intelligence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Chew Lee Teo and Seng Chee Tan Using Pedagogical Principles to Design a MOOC for Parents and Educators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Chee Soon Tan, Stefanie Yen Leng Chye, Yvonne Seng, and Caroline Koh Teaching Social-Emotional Learning with Immersive Virtual Technology: Exploratory Considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Marcus Cheng Chye Tan, Stefanie Yen Leng Chye, and Shu Min Teng Supporting Health Professions Education with Virtual Simulations: The Role of Technical, Educational, and Affective Factors in Assessing Opportunities and Challenges . . . . . . . . . . . . . . . . . . . 197 Jason M. Harley, Elif Bilgic, and Andrew Gorgy Can Social Presence Promote Meaningful Learning? Danmaku Video Learning to Enhance Social Presence and Meaningful Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Tzu-Hsiang Peng and Tzu-Hua Wang Challenges in Digital Education The Other Side of the Promise: Some Precautions for Technology-Based Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 Woei Hung Misjudgements of Learning in Digital Environments . . . . . . . . . . . . . . . . . . 239 Jason M. Lodge Mediating Effect of Loneliness on Social Emotional Learning and Problematic Internet Use in Singapore Youth . . . . . . . . . . . . . . . . . . . . 249 Martha Too, Stefanie Yen Leng Chye, and Wee Kwang Tan Correction to: Teaching Social-Emotional Learning with Immersive Virtual Technology: Exploratory Considerations . . . . . . Marcus Cheng Chye Tan, Stefanie Yen Leng Chye, and Shu Min Teng

C1

Digital Education for 21st Century Learning

A Self-Determination Theory Perspective on Online Lessons Chue Kah Loong

Abstract As technology progresses, online learning is becoming prevalent in schools as a tool for education. Teachers can now develop their teaching content that enhances learning in both synchronous and asynchronous online environments. Teachers who implemented these learning models have had to grapple with unfamiliar challenges, such as the lack of student motivation. Although there have been past recommendations for the development and conduct of effective online lessons, very few studies have viewed it from a motivational perspective. Thus, this chapter complements these suggestions by recommending strategies based on the motivational framework of self-determination theory. Self-determination theory posits that an individual’s motivation lies along a continuum ranging from amotivation to extrinsic motivation to intrinsic motivation. For a student to develop intrinsic motivation, the structural and interpersonal environment must be conducive to facilitate a sense of autonomy, competence and relatedness. Notably, there are sufficient differences between face-to-face and home-based learning such that additional strategies may need to be implemented. Three additional strategies that are aligned to the tenets of self-determination theory are suggested for home-based learning. As more schools embark on the practice of online learning, it is important for these strategies to be utilized and tested in the online environment. Keywords Online learning · Home-based learning · Self-determination theory · Motivation · Autonomy · Autonomous motivation

Introduction The use of online learning as a tool for education has accelerated tremendously. Whilst the online learning market has risen steadily over the past years, it was vastly propelled by the COVID-19 pandemic. Due to school closures, an astonishing 83% of all countries used an online platform to deliver education in 2020 (UNICEF, 2020). C. K. Loong (B) National Institute of Education, Nanyang Technological University, Singapore, Singapore e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Y. L. Chye and B. L. Chua (eds.), Pedagogy and Psychology in Digital Education, https://doi.org/10.1007/978-981-99-2107-2_1

3

4

C. K. Loong

In Singapore, students at all levels were abruptly required to attend lessons remotely during a period of lockdown. All classes were conducted fully on online platforms. Post-pandemic, the growth in online learning is unlikely to abate. In the latter part of the year, the Ministry of Education in Singapore has announced that the adoption of online lessons as a mainstay in schools will continue post-pandemic, albeit to a lesser degree. Schools are expected to schedule regular home-based learning days in which technology is leveraged on to deliver curriculum to students at home (Ministry of Education, 2020). Students who are involved in home-based learning are required to participate in online lessons according to a schedule that is similar to a normal timetable in school. These lessons can take place in either an asynchronous or synchronous environment. In the asynchronous environment, teachers would design learning content such that students are able to work at their own pace and time whereas in the synchronous environment, teachers would typically use a web conferencing application to conduct live face-to-face lessons. The decision on the choice of environment is usually entrusted to the individual schools, and over the passage of a day, students may experience a combination of these environments. For example, they may log on to a web conferencing application for synchronous lessons in English language and mathematics, but take part in asynchronous sessions for lessons in science and art. It is therefore no surprise that home-based learning can be quite demanding for students. Similarly, teachers who are involved in home-based learning would need to plan, design and deliver their lessons in a meaningful manner. Their main goals for any lesson are usually to achieve the relevant lesson outcomes through effective student engagement. In asynchronous lessons, this may entail creating highly structured content that facilitates reflective learning and critical thinking (DiPasquale & Hunter, 2017). At times, a progressive approach may be adopted by specifying predetermined ordered activities to scaffold students’ knowledge and skills acquisition (Bohol & Prudente, 2020). In synchronous lessons, teachers are required to provide real-time instruction to students at a scheduled time. Accordingly, they would have to consider suitable pedagogies that are comparable to face-to-face sessions (Wang & Huang, 2018). At the same time, they would need to ensure technical compatibility of all webcams and microphones, as well as perform additional duties such as monitoring questions/comments in the chat box and watching for digitally raised hands (Fadde & Vu, 2014). Unsurprisingly, teachers have had to grapple with unfamiliar challenges when faced with these new environments. In a series of interviews with primary school teachers across different schools and academic subjects, Wang et al. (2021) identified several concerns in home-based learning. A foremost concern was that many teachers were unprepared for online teaching. They struggled to find appropriate teaching platforms and resources, felt nervous in lesson preparation and delivery and had a sense of incompetence on the state of students’ learning. In addition, they were worried that students who were at risk of failing may not be able to muster enough self-discipline and motivation to complete their assignments (Wang et al., 2021). Similarly, a self-report questionnaire conducted by Almanthari et al. (2020) noted

A Self-Determination Theory Perspective on Online Lessons

5

that although secondary school teachers generally believed in the usefulness of online learning, their top teaching barrier was the lack of knowledge and skills. To address these issues, researchers and educators have proposed several suggestions for the development and conduct of effective online lessons. Wang and Huang (2018) recommended that teachers think in terms of pedagogical, social and technical designs. The pedagogical design aims to enable students to achieve the learning objectives through providing student engagement and sufficient teaching presence (i.e. instructional design and facilitation). The social design aims to provide students with a safe and comfortable environment that encourages multimodality interactions between peer-to-peers and peer-to-teacher. The technical design aims to have little or no technical difficulties in enacting the pedagogical and social designs through userfriendly technological tools and adequate training. Practical examples of these principles include redesigning activities to include regular interactions with students and teaching students on how to use the technological tool prior to the lessons (Wang & Huang, 2018). Likewise, Rhim and Han (2020) suggested that educators revisit the foundational concepts of distance learning, namely (a) transactional distance, (b) cognitive, social and teaching presences and (c) independent learners. Transactional distance refers to the social, psychological and relational distance between teachers and learners. It is dependent on the structure and extent of meaningful dialogues in the course. For example, a highly structured course without any flexibility for differentiation may result in an undesirably high transactional distance. Cognitive presence refers to the degree in which the learners make sense of their knowledge through cognitive activities, such as quizzes and discussions. Social presence refers to the socio-emotional support sensed by the learner and can be achieved through a projection of feelings and emotions into the community. Teaching presence refers to the design and facilitation of the educational experience. Finally, an effective online session requires teachers to view learners as active, capable and independent learners, rather than passive recipients of knowledge. When translated into practice, some explicit guidelines include promoting opportunities for practice and creating a community of learners within the course. Alternatively, some researchers focused on the concrete elements of online lessons in their recommendations. Huang et al. (2020) listed a set of criteria for selecting appropriate online resources such as licensing, ease of adaptability, interactivity and suitability of content. The researchers followed up by providing a comprehensive categorization of available tools with their pedagogical suitability and web links. In addition, a range of instructional methods that could be used in the online context was highlighted, together with suggestions on the type of learning resources and content, level of expertise for teachers and students, expected outcomes and potential risks. For example, synchronous real-time teaching would be suitable to teach key or difficult points in the subject. Learning materials should be provided before the start of the lesson, with the actual lesson focusing on face-to-face discussion. Teachers should have the capability to guide and facilitate online interaction. Potential risks include network bandwidth and poor student discussions (Huang et al., 2020).

6

C. K. Loong

Whilst the recommendations proposed above are beneficial in aiding teachers to plan for home-based lessons, there is a need to have a more specific focus on student motivation in the strategies. Students who are motivated may be more likely to engage and persist in the online activities. They may be more able to use complex learning strategies to make sense of the content. On the other hand, students who lack motivation may easily lose focus on the lesson objectives and have the tendency to sidetrack into other irrelevant tasks. Uninterested students may also assign insufficient time for their readings or assignment, thus resulting in poor quality work or late submissions for asynchronous sessions. Moreover, unmotivated students in synchronous sessions may be easily distracted by other online applications. The importance of motivation was clearly illustrated in a survey conducted with online learners across four different countries and culture whereby motivation was identified as the top critical element for effective online learning (Beaudoin et al., 2009). Other researchers have also demonstrated that higher motivation leads to better learning outcomes in the online context (e.g. Bailey et al., 2021; Stark, 2019). It is thus crucial that teachers incorporate strategies that foster and sustain motivation in home-based lessons. However, as the teacher and students are in separate physical locations, strategies that work in the face-to-face classroom may have to be modified to fit the online context. For example, teachers will find it a challenge to monitor students’ behaviours regardless of whether the lessons are synchronous (students’ screens are not available for viewing) or asynchronous (students work at their own time). Any motivational strategies may have to be incorporated into the structure of the lesson. Therefore, the remaining sections of this article will complement current home-based learning guidelines by suggesting strategies to increase the motivational level of students. Specifically, these strategies will be targeted at primary and secondary school teachers who have conducted online lessons or are thinking of implementing online learning as part of their curriculum.

Self-determination Theory The motivational framework arising from self-determination theory will be adopted for this purpose. Self-determination theory posits that individuals are naturally prone towards psychological growth (Ryan & Deci, 2020). The conditions to achieve this are rooted in three basic psychological needs, namely autonomy, competence and relatedness. Autonomy refers to the need to feel ownership of one’s behaviours. It is reinforced by experiences that are of interest and value to the individual and is undermined by experiences of being externally controlled. Competence refers to the need to feel mastery and a sense of growth. It can be supported by structured environments that offer growth opportunities and well-informed feedback. Relatedness refers to the need to feel a sense of belonging and connectedness with others. It can be supported by amiable relationships with other individuals that are infused with respect and caring. Failing to achieve any of these needs is seen as damaging to a person’s well-being and motivation (Ryan & Deci, 2020).

A Self-Determination Theory Perspective on Online Lessons

7

Within self-determination theory, an individual’s motivation is construed as lying along a continuum that ranges from intrinsic motivation to extrinsic motivation to amotivation. Intrinsic motivation indicates that the person is driven by inner forces. Activities are done purely out of enjoyment and inherent interest. On the contrasting end would be extrinsic motivation which indicates that the person is driven by outer forces. From the self-determination viewpoint, there are four subtypes of extrinsic motivation. External regulation concerns behaviours driven by externally imposed conditions such as rewards or punishments. Introjected regulation relates to behaviours that are driven by internal feelings of self-esteem, anxiety, shame or guilt. Identified regulation occurs when a person values or endorses the activity. Integrated regulation follows when the activity is not only valued by the person, it is also congruent with his or her core values. Lastly, amotivation indicates that the individual has a lack of intentionality in carrying out any form of activity. Although the various types of motivation are arranged in increasing levels of internal regulation, in reality, individuals can be motivated by more than one type of motivation simultaneously. For example, students may be motivated to study because they believe that good results will offer better opportunities later in life (identified regulation), but they may also be motivated because they do not want to disappoint their parents at the same time (introjected regulation). As such, many researchers in self-determination theory have measured motivation in terms of autonomous and controlled motives (Ryan & Deci, 2020). Autonomous motivation indicates the level in which behaviours are consistent with one’s sense of self and is usually associated with high levels of identified regulation, integrated regulation and intrinsic motivation. Controlled motivation indicates the level in which behaviours are determined by external factors and is usually associated with external regulation and introjected regulation. In a practical sense, this reclassification may have greater applicability in education research because very few students are motivated by solely one condition. There are two possible reasons as to why addressing autonomous motivation in home-based learning is appropriate. First, home-based learning requires teachers to view students as independent learners. For online lessons to be effective, it is necessary that students are internally regulated and self-motivated in their actions (Beaudoin et al., 2009). Self-determination theory offers an apt framework that can guide teachers in facilitating the development of their students’ autonomous motivation, specifically through increasing their internal regulation. Second, for a student to develop a greater level of autonomous motivation, a core hypothesis is that the structural and interpersonal environment must be conducive to facilitate a sense of autonomy, competence and relatedness (Ryan & Deci, 2020). This may be compatible with the foundational concepts of teaching, cognitive and social presence in distance learning. For example, the design and conduct of the lesson (teaching presence) could afford a sense of autonomy to the students, the manner in which learners make sense of the content (cognitive presence) could be accomplished through a sense of competence and the social support system of the learner (social presence) could be achieved through a sense of relatedness. Supporting the basic psychological needs of autonomy, competence and relatedness has been shown to predict autonomous motivation in many empirical studies

8

C. K. Loong

across different contexts. Particularly relevant to home-based learning, this relation has been illustrated for online lessons (e.g. Hsu et al., 2019), international students (e.g. Chue & Nie, 2012), students in secondary schools (e.g. Wang et al., 2019) and primary schools (e.g. Zhou et al., 2009). In turn, autonomous motivation has been shown to predict positive academic outcomes in many educational studies. A meta-analysis conducted by Taylor et al. (2014), involving studies across elementary school, high school and university, indicated that autonomous motivation was positively related to school achievement. Froiland and Worrell (2016) demonstrated that autonomous motivation predicted student engagement in an ethnically and racially diverse high school. The results are similar when transferred to the online context. Hsu et al. (2019) showed that self-determined motivation was directly related to learning gains, course grade and perceived knowledge transfer. In addition, Hong et al. (2017) showed that autonomous motivation predicted online learning self-efficacy and flow experience. Not surprisingly, many educators have aspired to inculcate autonomous motivation in students. As such, several teaching strategies have been identified that purport to support the basic psychological needs in the traditional classroom. These strategies are broadly categorized under two types, namely provisions of (a) autonomy support and (b) autonomy structure (Ryan & Deci, 2020). Autonomy support refers to approaches used by teachers to promote the needs for autonomy and relatedness. Several autonomy supportive teacher behaviours include (i) gaining an understanding of students’ perspectives and values, (ii) acknowledging students’ experiences and viewpoints, (iii) providing opportunities for students to take ownership, (iv) providing students with choices and (v) providing students with a meaningful rationale for tasks. Autonomy structure refers to the coherent organization of the lesson that will promote the need for competence. Some elements of autonomy structure include (i) formulating clear expectations, (ii) maintaining consistent rules and guidelines, (iii) providing instrumental help and support and (iv) providing efficacy supportive feedback. The above strategies involving autonomy support and structure have been adopted by educators with success in increasing the autonomous level of students (e.g. Domen et al., 2020; Jang et al., 2010; Taylor et al., 2008). Whilst the ideas behind the strategies pertain to the face-to-face classroom context, many of the strategies are still applicable in home-based learning, albeit in a different medium. For example, teachers may attempt to gain an understanding of students’ perspectives through online discussion forums, and teachers could also acknowledge students’ viewpoints when responding to the discussions. Similarly, clear rules and guidelines would need to make explicit in synchronous sessions. However, as there are differences in the characteristics between face-to-face and home-based learning, some additional strategies are suggested in the next section that would further support the basic needs of autonomy, competence and relatedness.

A Self-Determination Theory Perspective on Online Lessons

9

Increasing Autonomy, Competence and Relatedness in Home-based Learning The below-mentioned strategies are targeted specifically at teachers whose students are at the primary or secondary school level (ages 6 to 16). Naturally, it is up to the teacher to vary the intensity and duration of the strategies according to the level and characteristics of the students. Some suggested additional strategies are: • Provide ample opportunities to involve others – Incorporating collaborative activities – Utilizing the wider community • Provide structured opportunities for feedback – Having a good mix of asynchronous and synchronous lessons – Plan more online formative assessments in the lessons • Provide appropriate tools for personalized learning – Using a digital playlist – Using a digital badge model

Provide Ample Opportunities to Involve Others Developing a sense of relatedness implies organizing the environment and activities to foster a sense of belonging and connectedness with others. Students will need to perceive themselves in a group. Whilst supporting relatedness might arise naturally in a face-to-face classroom setting, it may require more substantial planning to involve the social community in home-based learning. This is because when lessons are conducted at home, there is always a likelihood that learners will experience feelings of isolation in the absence of physical interactions with peers and teachers. Findings amongst secondary school students have suggested that this is a real issue and may be one of the factors that cause mental exhaustion (Bhaumik & Priyadarshini, 2020). Furthermore, dialogues do not take place spontaneously. In a synchronous lesson, there can only be one conversation at a time. Students will tend to keep quiet unless spoken to as it requires additional effort to speak up. For instance, they have to toggle the mute button and ensure that they speak into the microphone to be audible. One possible strategy could be to provide sufficient opportunities within the lesson to involve other individuals. This may be achieved through two ways: (1) incorporating collaborative activities and (2) utilizing the wider community.

10

C. K. Loong

Incorporating Collaborative Activities Incorporating collaborative activities within the lesson has been shown to inculcate a sense of belonging when students feel that they have genuinely worked together to achieve a common goal and that other team members accept and value them (Peacock et al., 2020). In asynchronous lessons, this could denote a group assessment, such as the development of an artefact or a seminar presentation on a particular topic. However, care must be taken in the design of the collaborative activity. The activity should truly require group interaction and engagement, preferably through short discussions. If it requires a complex output such as a lengthy document, the group may likely divide up the work and end up working in silos. In synchronous lessons, this could mean scheduling regular short activities in-between content dissemination. These activities could be in the form of problem-solving, sharing on personal thoughts or brainstorming for ideas. Notwithstanding the form, the activities should preferably be held in smaller breakout groups, where students are given more opportunities to talk.

Utilizing the Wider Community Similarly, the learning community plays an important function in developing a sense of belonging and connectedness (Peacock et al., 2020). The contribution of peer support and teacher support to this aspect is well researched (Allen et al., 2018). However, in the home-based learning context, these supports can be severely impeded as the technological mechanisms do not allow for prompt interactions when support is needed. To offset this, teachers could broaden the learning community by involving more groups of individuals. Bronfenbrenner’s theory of ecological systems (Bronfenbrenner, 1986) offers some possibilities of the involvement of the various groups. In the theory, a student’s environment can be divided into five different systems, namely the microsystem, mesosystem, exosystem, macrosystem and the chronosystem. Of relevance to the current context are the relations within the first two systems. The microsystem encompasses all objects that are in direct contact with the student whereas the mesosystem comprises of the interactions between objects in the microsystem. For instance, parents, peers and teachers fall within the microsystem; the interactions between parents and teachers fall within the mesosystem. Accordingly, increasing the level of relatedness may be achieved through involving groups within the microsystem and tightening the relations within the mesosystem. This may entail setting tasks that require students to collaborate with their parents or other members within the school. For example, one possible primary level language assignment could be on discovering the likes and dislikes of family members. In addition, a pairing could be made between lower-level classes and upper-level classes. Students in the upper-level classes could share on their experiences in synchronous lessons and act as other points of support for students in the

A Self-Determination Theory Perspective on Online Lessons

11

lower-level classes. Alternatively, beyond online lessons, teachers could strengthen relations between parents and the various subject teachers by setting up a chat group or a similar communication channel for academic matters. However, in this case, care must be taken that individuals do not hijack the channel for other purposes.

Provide Structured Opportunities for Feedback Effective feedback is a key influence in developing a sense of competence in students. To determine whether feedback in home-based learning is effective, the types of feedback and some key attributes would need to be examined. Hattie and Timperley (2007) differentiated feedback into four levels, namely task (how well the task is performed/understood), process (the main process needed to perform/understand the task), self-regulation (self-monitoring and directing) and self (personal evaluations and affect about the student), that are pertinent regardless of feedback medium. Process level and self-regulation feedback are the most powerful forms of feedback (Hattie & Timperley, 2007). In addition, Yuan and Kim (2015) identified five attributes for effective online feedback, namely (i) content, (ii) timing, (iii) dialogue, (iv) sources and (v) student follow-up. (i) Content refers to information that is relevant and useful to the learner. It should fulfil the criteria of specific goals to be attained, current progress and additional steps to attain those goals. (ii) Timing refers to the length of the interval between completion of the task and the provision of feedback. Many students prefer immediate feedback although delayed feedback may be more useful for challenging tasks as it allows more time for information processing. In addition, some tasks may require feedback on certain sections before the student can proceed. (iii) Dialogue between the student and teacher enables students to clarify the feedback. As written feedback may be ambiguous to the student, conversations would help the student to better understand the content of the feedback. (iv) Sources refer to the trustworthiness of the feedback provider. In the school setting, this usually refers to the teacher, but may also refer to peer and self-assessment. (v) Finally, effective feedback requires students to follow up, that is, students need to pay attention to the feedback and make use of the feedback in subsequent tasks (Yuan & Kim, 2015). Many of the feedback attributes in the above paragraph are transferred from the traditional face-to-face classroom. However, opportunities for feedback do not come naturally in home-based learning and the onus is on the teacher to integrate these opportunities skilfully. This integration may occur in two ways: (1) Having a good mix of asynchronous and synchronous lessons, and (2) plan more online formative assessments in the lessons. Home-based learning should not comprise solely of asynchronous or synchronous lessons. Rather, there should be a good blend of both elements for each subject. Asynchronous lessons provide time for students to process feedback information, reflect on it and perform appropriate follow-up actions. When students are given process-level or self-regulation-level feedback, the home-based context allows them sufficient time to conduct additional explorations on the feedback, either online or

12

C. K. Loong

otherwise. For example, they may do an online search for mathematical principles after receiving feedback that their method of problem-solving is incorrect. On the other hand, synchronous lessons provide the chance for feedback dialogue so that students can seek understanding and teachers can clear up any ambiguities. This implies that teachers should set aside some time in synchronous lessons to answer queries on preceding lessons. Alternatively, teachers can also reserve time slots especially for feedback. For instance, within the span of one week, teachers can allocate time on one specific day solely to meet up students in small groups to check their understanding. In order for more feedback opportunities to materialize, it is logical to include more online formative assessments in the lessons. Online formative assessments help students to identify their weaknesses and increase time efficiency in receiving feedback (Cherem, 2011). In some cases, the use of appropriate technological tools could allow students to demonstrate their application of feedback. For example, in asynchronous math lessons, certain applications could provide immediate task-level feedback for straightforward computations. Some of these applications could also provide additional questions through an item bank, in which students would have the opportunity to apply their feedback on variations of the question. Process and selfregulation feedback on word problems could be provided in asynchronous lessons by supplying students with a link to a website or video that explains the process. The teacher would simply need to check that the students have completed their assignments satisfactorily. Additionally, in synchronous lessons, formative activities such as online quizzes, whiteboarding, reaction buttons and backchannel chats may contribute to the quality of interactions and enhance the focus of students. In general, it may be better to reduce content coverage so as to slot in more formative assessments in home-based learning.

Provide Appropriate Tools for Personalized Learning Personalized learning can be defined as a manner in which the pace of learning and instructional approach are optimized according to the learner’s needs (Alamri et al., 2021). It is a critical vehicle to deliver autonomy supportive teacher behaviours in home-based learning. Personalization in the learning process demonstrates to students that teachers recognize their individual differences and that tasks are meaningful, thus paving the way for students to take ownership of their learning. In the class, learning is no longer uniform; rather, the aim is to engage all students regardless of pace, place or time. In practice, it may be difficult to achieve personalization at the primary or secondary level because it requires the teacher to expend a huge amount of time and effort. However, two personalization tools may be useful for teachers to consider, namely (1) a digital playlist and (2) a digital badge model. First, teachers may want to consider the use of a digital playlist. A digital playlist is essentially a series of activities that the student has to complete to achieve the learning objectives (Bohol & Prudente, 2020). These activities, which may be in

A Self-Determination Theory Perspective on Online Lessons

13

Fig. 1 Partial example of a playlist

the form of online articles, quizzes, video streams, game-based activities, formative assessments, reflections and so on, are usually charted in a sequential manner that allows students to work at their own pace. Creating a playlist is relatively simple. Teachers break down the learning objectives into a series of micro-tasks. Completion of each micro-task leads students to advance nearer to the objectives. Students are then given access to the playlist through technological means. They may have the flexibility to choose the completion path or the type of task. Monitoring of performance is done through automated means, either through a learning system or an online application. It can be argued that a digital playlist is highly suitable for homebased learning—asynchronous times are used to complete the tasks and synchronous times are used to check-in with the students. Figure 1 shows a partial example of a playlist. Second, teachers may want to consider the use of a digital badge model. A digital badge is a graphic representation of a skill or competency that is earned through fixed criteria (Alamri et al., 2021). The main aim of digital badges is to identify learning progress in different content categories. They are similar to achievement artefacts in digital games and provide learners with products that represent the completion and accreditation of their work (Gibson et al., 2015). It can be used as a platform to support personalization where teachers use the digital badges as a learning pathway for students to visualize their learning and progress towards learning goals (Ahn et al., 2014). The use of digital badges is prevalent in higher education settings (Alamri et al., 2021), and their use may be modified to the primary and secondary school environment. For example, general science teachers usually have a variety of topics to teach, such as matter, light and forces. Mastery of these topics and their corresponding sub-topics would entail completing a set of requirements, which could

14

C. K. Loong

comprise of playlist activities and summative assessments. Students would then earn a badge for each topic they have mastered. Moreover, this information can be shared through a social platform with other teachers and students.

Conclusion The global education trend appears to be shifting towards home-based learning, where students access lessons and resources online, and teachers facilitate sessions rather than uploading content. This has posed a number of challenges for primary and secondary school teachers as many of them are unused to the new mode of delivery. A primary concern is one of student motivation. Educators need to address this issue. Investigations into possible interventions that can raise the level of motivation need to be conducted. This chapter puts forth a number of suggestions, aligned to selfdetermination theory, that are designed to do so. Hopefully, this would have given teachers some fresh ideas on how to approach home-based learning. However, future empirical research that utilizes these strategies in the primary and secondary school context is still necessary for validation purposes.

References Ahn, J., Pellicone, A., & Butler, B. S. (2014). Open badges for education: What are the implications at the intersection of open systems and badging? Research in Learning Technology, 22. Alamri, H. A., Watson, S., & Watson, W. (2021). Learning technology models that support personalization within blended learning environments in higher education. TechTrends, 65(1), 62–78. Allen, K., Kern, M. L., Vella-Brodrick, D., Hattie, J., & Waters, L. (2018). What schools need to know about fostering school belonging: A meta-analysis. Educational Psychology Review, 30(1), 1–34. Almanthari, A., Maulina, S., & Bruce, S. (2020). Secondary school mathematics teachers’ views on e-learning implementation barriers during the COVID-19 pandemic: The case of Indonesia. Eurasia Journal of Mathematics, Science and Technology Education, 16(7), em1860. Bailey, D., Almusharraf, N., & Hatcher, R. (2021). Finding satisfaction: Intrinsic motivation for synchronous and asynchronous communication in the online language learning context. Education and Information Technologies, 26(3), 2563–2583. Beaudoin, M., Kurtz, G., & Eden, S. (2009). Experiences and opinions of e-learners: What works, what are the challenges, and what competencies ensure successful online learning. Interdisciplinary Journal of E-Learning and Learning Objects, 5(1), 275–289. Bhaumik, R., & Priyadarshini, A. (2020). E-readiness of senior secondary school learners to online learning transition amid COVID-19 lockdown. Asian Journal of Distance Education, 15(1), 244–256. Bohol, D. O., & Prudente, M. S. (2020, January). Using lesson playlist through schoology-based Flipping the Classroom (FTC) approach in enhancing STEM students’ performance in general biology 1. Proceedings of the 2020 11th International Conference on E-Education, E-Business, E-Management, and E-Learning (pp. 284–289).

A Self-Determination Theory Perspective on Online Lessons

15

Bronfenbrenner, U. (1986). Ecology of the family as a context for human development: Research perspectives. Developmental Psychology, 22(6), 723. Cherem, B. F. (2011). Using online formative assessments for improved learning. Currents in Teaching and Learning, 3(2), 42–48. Chue, K. L., & Nie, Y. (2012). International students’ motivation and learning approach: A comparison with local students. Journal of International Students 2016, 6(3), 678–699. DiPasquale, J., & Hunter, W. (2017). Critical thinking in asynchronous online discussions: A systematic review. Canadian Journal of Learning and Technology/La Revue Canadienne de L’apprentissage et de la Technologie, 43(2). Domen, J., Hornstra, L., Weijers, D., van der Veen, I., & Peetsma, T. (2020). Differentiated need support by teachers: Student-specific provision of autonomy and structure and relations with student motivation. British Journal of Educational Psychology, 90(2), 403–423. Fadde, P. J., & Vu, P. (2014). Blended online learning: Benefits, challenges, and misconceptions. Online Learning: Common Misconceptions, Benefits and Challenges, 33–48. Froiland, J. M., & Worrell, F. C. (2016). Intrinsic motivation, learning goals, engagement, and achievement in a diverse high school. Psychology in the Schools, 53(3), 321–336. Gibson, D., Ostashewski, N., Flintoff, K., Grant, S., & Knight, E. (2015). Digital badges in education. Education and Information Technologies, 20(2), 403–410. Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. Hong, J. C., Hwang, M. Y., Tai, K. H., & Lin, P. H. (2017). Intrinsic motivation of Chinese learning in predicting online learning self-efficacy and flow experience relevant to students’ learning progress. Computer Assisted Language Learning, 30(6), 552–574. Hsu, H. C. K., Wang, C. V., & Levesque-Bristol, C. (2019). Reexamining the impact of selfdetermination theory on learning outcomes in the online learning environment. Education and Information Technologies, 24(3), 2159–2174. Huang, R. H., Liu, D. J., Tlili, A., Yang, J. F., & Wang, H. H. (2020). Handbook on facilitating flexible learning during educational disruption: The Chinese experience in maintaining undisrupted learning in COVID-19 Outbreak. Smart Learning Institute of Beijing Normal University. Jang, H., Reeve, J., & Deci, E. L. (2010). Engaging students in learning activities: It is not autonomy support or structure but autonomy support and structure. Journal of Educational Psychology, 102(3), 588. Ministry of Education, Singapore. (2020, December 29). Blended learning to enhance schooling experience and further develop students into self-directed learners [Press release]. https://www.moe.gov.sg/news/press-releases/20201229-blended-learning-to-enhanceschooling-experience-and-further-develop-students-into-self-directed-learners Peacock, S., Cowan, J., Irvine, L., & Williams, J. (2020). An exploration into the importance of a sense of belonging for online learners. International Review of Research in Open and Distributed Learning, 21(2), 18–35. Rhim, H. C., & Han, H. (2020). Teaching online: Foundational concepts of online learning and practical guidelines. Korean Journal of Medical Education, 32(3), 175. Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, 101860. Stark, E. (2019). Examining the role of motivation and learning strategies in student success in online versus face-to-face courses. Online Learning, 23(3), 234–251. Taylor, G., Jungert, T., Mageau, G. A., Schattke, K., Dedic, H., Rosenfield, S., & Koestner, R. (2014). A self-determination theory approach to predicting school achievement over time: The unique role of intrinsic motivation. Contemporary Educational Psychology, 39(4), 342–358. Taylor, I. M., Ntoumanis, N., & Standage, M. (2008). A self-determination theory approach to understanding the antecedents of teachers’ motivational strategies in physical education. Journal of Sport and Exercise Psychology, 30(1), 75–94.

16

C. K. Loong

United Nations Children’s Fund. (2020). Covid-19: Are children able to continue learning during school closures? A global analysis of the potential reach of remote learning policies using data from 100 countries. UNICEF. Wang, C. J., Liu, W. C., Kee, Y. H., & Chian, L. K. (2019). Competence, autonomy, and relatedness in the classroom: Understanding students’ motivational processes using the self-determination theory. Heliyon, 5(7), e01983. Wang, Q., & Huang, C. (2018). Pedagogical, social and technical designs of a blended synchronous learning environment. British Journal of Educational Technology, 49(3), 451–462. Wang, Z., Pang, H., Zhou, J., Ma, Y., & Wang, Z. (2021). “What if… it never ends?”: Examining challenges in primary teachers’ experience during the wholly online teaching. The Journal of Educational Research, 114(1), 89–103. Yuan, J., & Kim, C. (2015). Effective feedback design using free technologies. Journal of Educational Computing Research, 52(3), 408–434. Zhou, M., Ma, W. J., & Deci, E. L. (2009). The importance of autonomy for rural Chinese children’s motivation for learning. Learning and Individual Differences, 19(4), 492–498.

Student-Centered Learning with Large Student Groups: Rationale, Organization, and Experiences in Problem-, Project-, and Team-Based Learning Sofie Loyens , Lisette Wijnia , Ivette van der Sluijs, Eliza Ferrer, and Remy Rikers Abstract Student-centered educational approaches are increasingly being implemented in undergraduate institutions. With the rising number of students and lack of resources, institutions need to gather students in large classes. This study investigated the implementation and adjustment of Problem-Based Learning (PBL) with large student groups. Professionals having experience with PBL with large student groups were interviewed to answer the following questions: (1) What was the rationale behind the implementation of PBL with large groups? (2) How was it organized? and (3) What were the experiences? Results showed that an increasing interest in studentcentered methods combined with a lack of sufficient resources was put forward as the rationale for implementing PBL for large student groups. In terms of organization, all interviewees mentioned small group discussions within the large classrooms. Moreover, the integration of technology within and in addition to the class aimed to facilitate the management of large student groups and to enhance students’ collaborative learning. Students’ and tutors’ experiences with large group PBL were mainly positive. These findings suggest that PBL can be applied to large student groups as a small-scale, student-centered educational approach. Small group discussions can still be kept as a critical aspect and technology can help class management and collaborative learning. Keywords Problem-based learning · Student-centered learning · Large student groups · Technology S. Loyens (B) · I. van der Sluijs · E. Ferrer · R. Rikers Utrecht University, Utrecht, The Netherlands e-mail: [email protected] I. van der Sluijs e-mail: [email protected] R. Rikers e-mail: [email protected] L. Wijnia Open Universiteit, Heerlen, The Netherlands e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Y. L. Chye and B. L. Chua (eds.), Pedagogy and Psychology in Digital Education, https://doi.org/10.1007/978-981-99-2107-2_2

17

18

S. Loyens et al.

Introduction The number of students entering higher education is increasing (National Center for Education Statistics, 2022), and consequently, universities and higher education institutes face the challenge of teaching large student groups. The increasing group sizes pose a particular challenge to educational institutes that have adopted smallscale, student-centered education (i.e., teaching students in small groups). In addition to increasing student numbers in higher education, the COVID-19 pandemic also required a shift in the design and setup of instruction. Programs had to switch to online education, in which technology plays a much more prominent role. This study investigates the implementation of Problem-Based Learning (PBL) as a student-centered method with large student groups. Although initially designed to be implemented with small groups of students, PBL is increasingly applied in large groups of students, as is evidenced by the growing number of publications on large-scale PBL (Khan & Fareed, 2001; Klegeris & Hurren, 2011; Pastirik, 2006). However, much is still to be discovered regarding the rationale behind the specific procedures and experiences regarding PBL with large student groups. This study is a first attempt to fill this gap.

What Is PBL? PBL is a student-centered educational method that uses an ill-structured problem as the starting point of students’ learning process. Weiss (2003) defines the PBL illstructured problem as “messy like the problems that are faced in everyday life and in professional practice” (p. 27). They are realistic and authentic (Hmelo-Silver, 2004; Hung et al., 2008) and aim to make students aware of their knowledge gaps, referred to as “knowledge deprivation” (Schmidt et al., 2011, p. 799). After discovering and exploring the “problem space” (Chin & Chia, 2004, p. 709), students become aware of their knowledge gaps (i.e., what they do not know and what they need to know) and formulate learning issues. Learning issues are topics, or subtopics, identified after a prior questioning and discussion. They are essential because they determine students’ self-study. After a first session for the problem presentation and a first group discussion, students have time for self-study. During this time, students look for relevant information, material, and explanation to help them understand the problem. After this self-study time, students gather again and discuss what they have found. The ill-structured problems used in PBL intend to develop students’ generic problem-solving skills (PSS), defined as “an individual’s capacity to engage in cognitive processing to understand and resolve problem situations where a method of solution is not immediately obvious” (Organisation for Economic Co-Operation & Development, 2013, p. 122). The problems are created based on the student’s prior

Student-Centered Learning with Large Student Groups …

19

knowledge, which is aimed to be activated and elaborated upon. The activation of prior knowledge occurs during a brainstorming session and allows the identification of knowledge gaps (Loyens et al., 2012).

How Does PBL Work? Usually twice a week, students are gathered into small groups, between six and twelve, under the supervision of a “facilitator” or “tutor” (Loyens et al., 2012). A problem is presented during the first tutoring session, followed by small group discussion aiming for students to identify knowledge gaps and learning issues through collaborative learning. The following tutoring session is based on what students have been learning during their self-study time. Throughout this session, students solve, step by step, the initial problem.

Role of the Tutor Students are supervised by a tutor during the tutorial sessions. The tutor makes sure that students are going in the right direction in their process of problem-solving or understanding. Given this different role for the teacher, the label tutor or facilitator is used. In direct instruction, like lectures, teachers mainly provide knowledge. However, in PBL, students are the constructors of their own knowledge (Kirschner et al., 2006). A clear understanding of the tutor’s role is necessary when implementing PBL in an institution. The tutor ensures that the different steps in the PBL process are followed well and guides students in their learning process. Azer (2005) identifies his role as being a facilitator (i.e., facilitating the group discussion) and stimulator (i.e., stimulating students’ learning process). With open-ended questions and suggestions, a tutor directs students in their learning process without providing them with answers or lectures. Chan (2008) explains that besides being a facilitator, a tutor is also a mentor, an expert, and a team builder. Moreover, as Schmidt et al. (2010) mentioned, a tutor should be able to guide students in identifying what they should focus on, motivate learning, and enable students to understand complex concepts more easily. Shifting from a traditional teaching method to a student-centered approach needs to be explained, and guidelines need to be given to tutors. Asking open-ended questions, giving suggestions, and avoiding giving direct answers are the advices given to teachers becoming tutors in a PBL process.

20

S. Loyens et al.

PBL and Small Scale Because of its focus on group sessions with a relatively small number of students supervised by a tutor, PBL is characterized as a small-scale instructional format. Small group sessions intend to develop students’ intrinsic motivation and collaboration skills, both being crucial goals of PBL (Dolmans & Schmidt, 2006; Schmidt & Moust, 1998). According to Willis et al. (2002), small group sessions indeed have a strong motivational and educational role. Stimulation emerging from the group interactions and the “collective team spirit” (p. 500) create a sense of responsibility toward the group and enhance students’ engagement in the group discussion. Group work and interaction have been shown to bring several benefits to students, including improving communication and teamwork skills (Pluta et al., 2013; Wun et al., 2007). With “small group learning [being] the heart of PBL” (Mennin, 2007, p. 305), other benefits emerging from this characteristic have been found. Jones (2007) identified the promotion of deep learning leading to an in-depth understanding and longer-term retention of knowledge, the opportunity for students to acquire self-directed learning (SDL) skills, greater control over their studies, and the aforementioned increased self-motivation. Moreover, small group sessions allow students to participate in their learning, acknowledging the importance of learning as an active rather than a passive process. Rehman et al. (2012) mentioned that several benefits of group work in PBL include a better understanding of complex topics and increased student engagement. Also, students themselves awarded group sessions in PBL a motivational role and perceived them as facilitating learning (Shankar et al., 2014).

Integration of Technology in PBL The use of technology has increased within educational settings (Selwyn, 2020) and has brought promising opportunities for future education. As a result of the growing integration of technology within classrooms and the shift to online learning, especially during the COVID-19 pandemic, this chapter also looks into a potential integration of technology in PBL, both on-campus and online. This section gives a description of the use of technology in education and the consequences of online learning. Educational technologies are implemented for various purposes. First, local area networks such as virtual libraries and discussion forums are used to enhance communication and collaboration. Second, audiovisual aids are used to help in the understanding of difficult concepts and allow for creativity in teaching. Lastly, information and communications technologies (ICTs) broaden access to online degrees (Stefan, ¸ 2019).

Student-Centered Learning with Large Student Groups …

21

Technology Within the Classroom Technology has been integrated within the classroom as a way to facilitate students’ learning. In a study conducted by So and Kim (2009), ICT tools such as modeling programs, videos, or animations were reported as being useful by students. Moreover, Loyens et al. (2012) mentioned the use of video cases and virtual patients in PBL as another way to integrate technology in the classroom. In addition, Neo and Neo (2001) supported the belief that learning was more effective when using multimedia. They reported that students retained more when the information was given through various modalities, such as clips and virtual cases. Pearson (2006) indicated that ICT could support learning by providing diverse teaching materials. Raja and Nagasubramani (2018) explained that, for example, PowerPoint presentations and visuals enhanced the efficiency of learning and increased students’ curiosity. With the opportunity to provide information through various platforms, ICT gives opportunities to teachers to adapt their teaching to individual needs (Ratheeswari, 2018). Furthermore, Henriksen et al. (2018) brought up the potential benefits of technology in the development of creative thinking. As an ill-structured skill defined by the capacity to produce useful solutions or new ideas, creativity is considered a beneficial skill in our constantly changing society. Technology could enhance creativity by providing multiple platforms for gathering, collecting, and presenting new information. However, the implementation of technology in educational settings also raises various concerns. Raja and Nagasubramani (2018) mentioned several disadvantages in implementing technology in a classroom, including the lack of time, lack of access, and lack of resources. Institutions are not always willing to change, and technology requires a “new moral vision” (Cloete, 2017, p. 2), as institutions need to acknowledge technology’s crucial role in modern societies. Tondeur et al. (2017) explained that technology tended to be more adopted by teachers believing in constructivist learning theories. Constructivism emphasizes learning in relevant contexts and aims to prepare students for their future profession. In an era where technology is becoming increasingly important, the inclusion of technology in educational settings would allow students to learn ICT skills useful for future professions in the twenty-first century. Therefore, aligning teachers’ pedagogical beliefs on the importance of technology influences the implementation and use of technology within their classrooms (Tondeur et al., 2017).

Online Learning Moreover, the COVID-19 pandemic has had drastic consequences on education. As courses were entirely online, teachers and faculty had to change their educational methods in an attempt to provide students with efficient educational and qualitative alternatives. Online platforms have been used, and small group sessions have been revisited. Goh and Sandars (2020) mention the “interactive Webinars using web conferencing platforms” (p. 2) as a replacement for small group sessions. They

22

S. Loyens et al.

explain that large group in-person lectures were streamed, but platforms allowing for more interactions were used to replace small group sessions. Positive and negative consequences of online learning during the pandemic have been observed. Haslam et al. (2021) mentioned several disadvantages, including the difficulty for students to concentrate and a lack of variety of learning activities. However, the increased use of e-learning during the pandemic has also shown benefits noticed by Elzainy et al. (2020). They noted that live-streaming lectures were effectively replacing the on-campus lectures. Moreover, e-learning allows students to be in different places, which could be very beneficial for international students. Lastly, they explained that e-learning could overcome the difficulty of gathering large student groups on campus, overcoming the necessity of sufficient infrastructure. In addition, online learning provides the possibility for professors to teach from a different country and the possibility for students to get online degrees from foreign universities. Online learning could be very beneficial for a teaching organization “independent of time, place, and synchronous constraints of participation” (Hiltz & Turoff, 2005, p. 2). PBL online learning has also been developed in computer-supported learning environments, designed to promote online learning by structuring the students’ learning process (Hakkarainen & Sintonen, 2002). For example, Computer-Supported Collaborative Learning (CSCL) has been developed to provide students with relevant assignments, encourage them to become actors in their learning process, enhance their collaboration, and provide them with learning tasks (Chen & Chen, 2012). CSCL is used to enhance collaboration among students, one of the critical aspects of PBL. While integrating PBL online, maintaining the group’s collaborative learning experience is crucial, and the development of CSCL is a way of enhancing collaboration online. The benefits of computer-supported learning environments have been mentioned in several studies. Strømsø et al. (2004) concluded that computer-supported learning environments could allow students to work together while being in different places and time zones by taking place asynchronously or synchronously. Moreover, students gained knowledge in using web-based resources and confidence in their computer skills. However, cooperation seemed more difficult in the online environment, and more structure and support were needed. A study conducted by Ak (2011) demonstrated that computer-supported PBL benefited students’ approaches to learning. Students seemed to adopt deeper approaches to learning, implying a true intention to understand the content, as opposed to a surface approach when external task demands drive the students’ learning objectives. In sum, technology seems to have multiple benefits in education. Firstly, it could help students develop flexible and diverse learning methods within the classroom. Moreover, the development of online learning before and during the pandemic has shown possibilities for future education. Consequently, this study will also look at the potential use of technology in education, more precisely in PBL.

Student-Centered Learning with Large Student Groups …

23

PBL with Large Student Groups Small-scale learning is not always possible. Universities and high schools often have large classrooms, where the number of students might not allow for PBL to be implemented. Organizational and technical issues, including teachers’ availabilities and suitable accommodation, are often not conducive to the shift from traditional learning to PBL. Khan and Fareed (2001, p. 2) explained: “curriculum-wide changes specially in a class size of more than 100 students are costly in terms of finances, faculty time, strength of staff, and number of rooms required.” Nevertheless, an increasing number of studies on PBL with large student groups have been published. Experiments have been conducted to look at the positive and negative effects of PBL with large numbers of students. In one study, Pastirik (2006) examined the use of PBL within a nursing school. Students were divided into small groups, gathered in a large classroom. The “floating facilitator” (p. 262) was circulating among these groups. Large group discussions alternated discussions in small groups. The recorder of every group, a student responsible for gathering the group information and sharing it, displayed their ideas to the whole class. In this study, students reported being satisfied with the small and large group sessions. These small groups within a large classroom have been mentioned as “study teams” by Moust et al. (2005, p. 64). In their study, four teams of three students were given different learning issues to focus on. Each team presented what they had discovered while studying during the following class. Khan and Fareed (2001) used the same idea of study teams, but larger. Eight groups of fifteen to twenty students were created. Division of workload and presentations were crucial elements of this revised PBL method, which resulted in high student satisfaction. Klegeris and Hurren (2011) had a similar approach. Their study conducted at the University of British Columbia Okanagan demonstrated that a tutorless group approach (i.e., single tutor for a large classroom) had positive effects. Discussions in small groups, followed by a class brainstorming, were positively perceived by students. No additional costs were required, and no additional facilitators were needed. However, according to them, “in classrooms with over 100 students, the process may break down because the time needed for group reports would create too much idle time for the majority of students” (p. 414).

The Present Study A growing number of studies on PBL with large student groups have been conducted due to the increasing number of students in undergraduate studies (National Center for Education Statistics, 2022) and a growing interest in student-centered educational approaches (Krahenbuhl, 2016). Institutions are increasingly faced with the necessity of teaching larger student groups. However, PBL, as a student-centered educational method, emphasizes the active participation of and collaboration among students.

24

S. Loyens et al.

Through small group sessions under the supervision of a tutor, PBL intends to reach its goal of preparing students for their future professions. Therefore, institutions face a complex challenge: implementing a small-scale, student-centered educational approach (i.e., PBL) for large student groups. This study will look into the possibility of implementing PBL at a large scale and aims to answer the following question: How can PBL be implemented with large student groups? To that end, educational professionals at programs who have implemented PBL at a large scale (i.e., with large student groups) were interviewed to shed light on (a) the rationale for implementing PBL at a large scale (i.e., the why), (b) the way in which PBL is implemented at a large scale (i.e., the how), and (c) experiences with the implementation of PBL at a large scale. The outcomes of this study allow institutions to understand the possibilities for implementing PBL for large student groups.

Methods Participants Purposive sampling was used for this research. Participants who have been working with PBL with large groups of students and educational researchers were asked to participate in our study. A first list of potential interviewees was made based on research found during the literature review as well as contacts of the first author, who were known for having experience with large student PBL groups. They were contacted via email explaining the study and a request for an online interview. Seven professionals who have had direct experience with PBL with large student groups agreed to participate in the research. Details about the participants can be found in Appendix A.

Materials As a basis for all interviews, an interview guide was developed to center the interview around our topic of interest while still being flexible by giving the possibility to the interviewees to express their opinions. The interview guide was divided into five subsections: (1) background information, (2) rationale, (3) organization, (4) experiences, and (5) technology. Details of each sub-section are given in Table 1. Moreover, the interview guide was adjusted for each interviewee based on their experiences and research publications. Therefore, some interviews were more theoretically-driven, while others were more based on direct experiences.

Student-Centered Learning with Large Student Groups …

25

Table 1 Generic interview guide Background

• Educational background of the interviewee • Past and present experiences with PBL

Rationale

• Reasons behind the implementation of PBL with large students groups • Resources • Institution’s pressure

Organization

• • • • •

Experiences

• Interviewees’ own experience • Tutors’ experiences with large student groups • Students’ experiences

Technology

• Online management system • Technology within the classroom • Online learning during the COVID-19 pandemic

Organization within the classroom Number of students and tutors Interaction between students as well as students and tutors Physical learning environment Assessment methods

Procedure Interviews were conducted for this study, with chosen participants based on their professional experience with PBL with large student groups. Interviews were chosen as a way to get an in-depth understanding of the three main questions: (1) the rationale behind the use of PBL with large student groups, (2) the organization of PBL with large groups, and (3) the experiences associated with large groups of students. Moreover, questions about the participant’s background and questions about technology were asked, as mentioned in Table 1. Two interviewers were present, with one of them taking the lead in the interview and the other asking for clarifications or additional questions whenever deemed appropriate or necessary. The interviews were semi-structured to allow flexibility in responses and get a broad and diverse understanding of PBL with large groups of students. The interviews were audio-recorded, and both interviewers independently took notes. Authorization to audio record was asked at the beginning of each interview, and all participants agreed. The decision to audio record was made to reduce potential mistakes in interpretation or oversights and provide an opportunity to study the content more thoroughly (Aksu, 2009). The interviews were conducted online via the Zoom platform. All were run in English and lasted approximately 1h to 1h30.

26

S. Loyens et al.

Analyses The note-taking and audio recordings allowed a transcription of all interviews. The transcripts enabled a thematic analysis of the content of the interviews (Fox, 2006). Moreover, the analyses were conducted in accordance with Roulston (2014): (1) data reduction as a selection of the relevant information included in the interviews, (2) data reorganization to reorganize, classify, and categorize the answers, and (3) data representation as a last phase for the interpretation and writing up of the findings. The data was reorganized by assigning a category to each question and gathering the same categories across the different interviews. After categorizing and coding every interview, a comparison of each interview was possible, and similar patterns, as well as differences, were identified.

Results Rationale The first sub-question of our study aimed to identify the rationale behind the implementation of PBL with large student groups. The interviewers brought up two main reasons behind using PBL with large groups: a switch from lecture-based instruction to PBL with large groups and a lack of resources.

Large Classroom as a Starting Point Several interviewees explained their desire to switch from a lecture-based to a more student-centered instructional method. They decided to apply PBL to their students and had to find ways to organize it within their own classrooms. Furthermore, three schools were mentioned as having to implement PBL, project-based learning (PjBL), or team-based learning (TBL) at a large scale from the beginning, as they wanted to change their whole curriculum to PBL (for a detailed definition of TBL and PjBL and their differences with PBL, see Appendix A). Therefore, the organization for implementing PBL had to take place on a large scale from the start. One of the interviewees explained that their school (i.e., CESI, as a nationally organized school) wanted to switch from lecture-based to PBL and PjBL on all 25 campuses across France. They wanted all students to have the same learning materials, assessments, and learning outcomes. Therefore, they had to organize PBL and PjBL at a large scale from the beginning. Moreover, one interviewee brought up the idea of quality control over students’ learning. The institute of this interviewee, LKCMedicine, believed that large classes would allow more control over students’ learning quality, as it would be easier to control their learning in a large classroom under the supervision of a single or a

Student-Centered Learning with Large Student Groups …

27

few facilitators supervising the learning process. Therefore, when transforming an educational curriculum into PBL, it is often required to consider the vast number of students, as another interviewee mentioned.

Resources Besides the desire to switch from lecture-based to PBL with large student groups as a starting point, a lack of resources was identified as a challenge. Four out of seven interviewees mentioned the limitation of resources as a reason for implementing PBL at a larger scale. The resource limitations included limitations of finances, difficulties finding a sufficient number of tutors, and insufficient infrastructure. Financial Resources. Financial wise, one interviewee mentioned a decreasing budget per student, creating financial pressure. Moreover, applying the original smallscale format of PBL would require hiring multiple tutors to have a tutor for each small group. However, institutions can often not offer this possibility, as their financial means are limited. Insufficient Tutors. The lack of resources also referred to the difficulty of finding sufficient tutors for PBL or content experts for TBL. An interviewee mentioned the pressure from other professors who wanted to keep a lecture-based format rather than switch to PBL. Another interviewee mentioned the difficulty of finding sufficient tutors available for what he described as a time-consuming educational approach. Related to TBL, an interviewee indicated difficulty finding sufficient content experts available for TBL sessions. Lack of Infrastructure. Infrastructure-wise, two interviewees mentioned the lack of sufficient infrastructure in terms of available rooms. If the original model of PBL were to be applied, numerous small rooms would be required, which institutions often cannot offer.

Organization All interviewees mentioned the importance of keeping small group discussions in the implementation of PBL with large student groups. The following section gives a detailed description of their organization. A summary is given in Table 2, with the design and characteristics of the physical learning environment and the details about assessment described separately thereafter.

Small Group Students’ Division and Group Composition All interviewees mentioned splitting students up into small groups within large classrooms. Group sizes differed but did not usually exceed seven students. The small

28 Table 2 Summary of the organization of PBL with large student groups

S. Loyens et al. Students’ division

• Division of students in small groups (3 to 7 students) • Classroom: from 5 to 30 groups (tables)

Group composition

• • • •

Random group every session The same group per PBL case The same group over a semester Assigned scribe, chair, team representative

Tutors

• • • • • •

Tutors Tutor assistant Graduate students Part-time and senior tutors Circulation of tutor around the class TBL: 1 facilitator and 1 content expert

Group interactions

• Plenary and group discussion • Presentation from each group

Changes for large scale • No supervision of group discussions by the tutor • Modification of reporting phase

group sizes aimed to facilitate students’ engagement within the groups. One interviewee mentioned a group size of three students, with the idea that making the groups as small as possible would force all students in each group to participate. All interviewees explained that students were divided into small groups within a single large classroom, and group discussion was a crucial part of their organization. Some interviewees, but not all, mentioned that scribes and chairs were assigned within each group. The number of groups within a classroom differed from five to 30 small groups within a single classroom. The composition of these small groups was varied. Some interviewees mentioned the re-shuffle of group members every session with the aim for students to experience different group interactions. On the contrary, some tutors preferred to keep the same groups sometimes for a whole semester. Two main reasons behind the same group composition were identified. First, it allowed students to get used to their learning environment and stabilize their group dynamics. Second, one interviewee mentioned a group composition based on students’ educational backgrounds, mixing students with different preuniversity backgrounds. A re-shuffle of the group composition would require more effort, organization- and timewise. Keeping the same group composition based on students’ backgrounds for the complete semester was easier in terms of organization.

Role of the Tutor With the creation of small student groups within a large classroom, many interviewees explained that tutors were walking around the classroom, going from one group to

Student-Centered Learning with Large Student Groups …

29

another to ensure that each group effectively discussed the problem. The tutors did not constantly supervise each group discussion. Tutors were available for questions if needed, and they went from one group to another to ensure that students were making progress. Most of the interviewees mentioned gathering students for plenary discussions. All students were gathered during plenary discussions either for the problem presentation before the group discussions or after to collect input from every group and discuss potential questions or difficulties. Plenary discussions with all groups together alternated with small group discussions. Concerning the number of tutors, some interviewees reported having tutor assistants in the classroom, either part-time tutors or master students. They explained that the tutor and tutors’ assistants were going from one group to another. The tutors’ assistants helped supervise multiple small groups within a large classroom since the tutors could walk around independently and supervise small groups at the same time. Moreover, an interviewee mentioned having a teaching assistant make notes on a whiteboard during the plenary discussions. The teaching assistant was also responsible for uploading these notes into the digital learning environment to enable students to access the notes later on.

Changes from Small Scale to Large Scale The interviews enabled the identification of similarities and differences between small-scale and large-scale PBL. All interviewees kept the small group discussions, but the tutors’ roles differed since they did not have the same supervision over their students’ learning processes. Furthermore, one interviewee reported a modification of the reporting phase due to large student groups. He explained that keeping students engaged in large groups could be challenging, and the reporting phase was found to be frustrating and not entirely adequate for well-prepared students. Therefore, he modified the reporting phase in order to use the time for what he called “calibration.” Some of the time was used to quickly summarize what students had learned and answer questions if necessary. The rest of the time was used for in-depth complex discussion questions prepared by the course coordinator (i.e., the instructor who developed the course and defined the learning objectives. This person also guides the different tutors in a course).

Physical Learning Environment Three interviewees explained the organization of their physical learning environment used for large student groups. A description of the three types of learning environments is given in this section. LKCMedicine. To facilitate the management of large student groups, LKCMedicine provided every student with an iPad as a learning tool. The iPads have various integrated applications for assessment, peer evaluations, access to learning

30

S. Loyens et al.

resources, and communication. An example of the benefits brought to communication and interaction is related to the so-called burning questions. In TBL, students have the opportunity to ask burning questions to the content expert. However, it becomes difficult for the teams to ask their questions in large classrooms without creating a hubbub. Therefore, iPads are used as a way of sending burning questions directly to the TBL facilitator. The facilitator can then group similar questions, see which teams sent the questions, and order them to make the content expert’s answer more structured. LKCMedicine is an example of a learning environment heavily relying on technology for its TBL organization. LKCMedicine uses projectors all over the classroom and has computers available to each student. Furthermore, LKCMedicine uses projection screens, accessible for every student, and microphones on each table, improving communication between teams and staff members. The use of technology will be explained in more detail later in this chapter. CESI. The CESI engineering school in France has conducted some research on the effectiveness of various physical learning environments. Their studies were mainly based on PjBL, but since PjBL shares characteristics with PBL in terms of small group discussion and interaction, their studies could create opportunities for PBL as well. CESI implemented various table shapes and sizes and assessed their influence on students’ behaviors during discussion. Their idea was to find a table that would enhance group discussion and prevent students from dominating the discussion by, for example, sitting at the table head at a rectangular table (Blandin, 2018). They first implemented tables inspired by the Scale-Up Project (Beichner et al., 2007). These tables aimed to enhance collaboration and interactivity among students with individual desks creating one bigger table for six students. A screen and whiteboard were available at each table to enhance collaborative learning. However, the setting did not allow enough flexibility within and between groups. From these results, CESI developed individual tables with wheels that could be easily moved around the classroom. However, a non-controlled experiment with over a hundred students showed that these chairs decreased students’ productivity, and students did not feel part of a group due to their constant ability to move around (B. Blandin, personal communication, April 7, 2021). The last table created was table A2P2, illustrated in Fig. 1. CESI uses these tables for PjBL, but Prof. Dr. Blandin mentioned the possibility of using these tables for PBL as well since both use small group discussions. Each student has a designated place compartmentalized in stainless steel, as shown in Fig. 1. Every student has a laptop connected to the middle of the table, giving them the possibility to share their screen on the TV placed at the end of the table. CESI has placed about thirty tables in the same classroom. Quadrants Used at Indiana University Bloomington. One of the participants, Dr. Craig at Indiana University Bloomington, implemented a different learning environment, with the creation of quadrants to break down students’ thought processes and a way for tutors to look at the groups’ progress without interrupting their discussions (Bae et al., 2018). With multiple small groups within a single classroom, the tutor does not have the possibility of thoroughly supervising the group discussions. However, it is essential for the tutor to quickly get an idea of the groups’ progress

Student-Centered Learning with Large Student Groups …

31

Fig. 1 A2P2 Table developed by © CESI

when walking around the classroom. Dr. Craig explained that the use of quadrants on whiteboards, PowerPoints, or iPads was helpful as they provided a rapid overview of the students’ discussion. Moreover, quadrants scaffolded students’ learning by structuring their research and discussion. As shown in Fig. 2, the four categories are clearly defined and provide structure to their learning process. The four categories are (1) potential hypothesis, (2) what we know, (3) what we don’t know, and (4) research agenda. The quadrants allowed students to see the relationship between categories that a columnar structure would not allow. This representational tool allowed students to see how their learning process was evolving and gave structure to students that a “floating” facilitator could not directly provide. It is important to note that Dr. Craig did not organize plenary discussions. Other interviewees used plenary discussions to align students in their learning process and scaffold the groups’ discussions. However, without plenary discussions, the quadrants were mentioned as beneficial for both students and tutors by providing structure to students and allowing tutors to quickly get an overview of the groups’ discussion status.

Assessment Interviewees mentioned different ways of assessing students based on individual and group work. A summary of individual and group assessments used by the interviewees is given in Table 3. As shown in Table 3, students’ assessments were divided into individual and group assessments. Many interviewees mentioned peer evaluation to assess students’ preparation, participation, and engagement in group discussions. Group presentations served as the result of students’ learning processes, and some interviewees mentioned

32

S. Loyens et al.

Fig. 2 Example of quadrant used in a history class of Dr. Craig

Table 3 Summary of individual and group assessment in large PBL groups

Individual assessment

Group assessment

• • • •

• Peer Evaluation • Presentation grade • Evaluation of group functioning

Exam Presentation grade Portfolio Grade on professional behavior • Participation grade • Reflection on readings • Individual reflection

that tutors could use presentations to assess a group’s engagement and learning outcomes. Concerning individual assessment, techniques varied across interviewees. Some of them used exams to assess students’ learning outcomes. One interviewee implemented the preparation of a portfolio, which was sent every week to the tutor for individual feedback. Although requiring intensive work for both students and tutors, the portfolio forced students to prepare for the discussion and stay engaged in their learning process. The reflection on readings used by one interviewee had the same aim of keeping students engaged. Several interviewees mentioned the assessment of professional behavior. Their tutors evaluated students’ engagement in the group discussion and participation in the whole PBL process. A non-controlled study conducted by one interviewee showed that the professional behavior grade (i.e., how well students prepared for and engaged in the group discussion) seemed to have good reliability and appeared to be a good predictor of students’ performance on the

Student-Centered Learning with Large Student Groups …

33

exam (G. Smeets, personal communication, March 30, 2021). However, one interviewee had a different opinion on assessing students based on their behavior. He explained that natural differences among students exist, and while some students can be very comfortable in group discussions, others might look less engaged, although being very engaged cognitively. Moreover, grading students on presentations was also mentioned by one interviewee as a potential problem, privileging some students over others.

Experiences Students’ Experiences Students’ experiences were assessed through course evaluations and surveys used by most interviewees throughout the term. The interviewees reported the overall experience of students as positive. They mentioned that some students reported PBL to be demanding and challenging. The interviewees using a portfolio and reading reflection in PBL with their large groups explained that it was, at first, very demanding for their students. However, these students usually expressed positive experiences after getting used to the process. Most interviewees mentioned that their students expressed the benefits brought by PBL to their understanding of the material and acquired knowledge. Furthermore, interviewees explained that their students were satisfied with the different roles of tutors. Some interviewees mentioned that less supervision by the tutors gave students the possibility to participate, while they might feel uncomfortable doing so with the tutor being constantly present. However, some interviewees noted that some students were unsatisfied with PBL with large student groups. Some students reported the challenging character of the process (i.e., due to the greater emphasis put on one’s own responsibility in the learning process) to their tutors, and others reported the struggle related to the decreased tutor’s supervision. However, gaining experience with PBL usually overcame the demands required by the approach. The interviewees explained that most students managed to develop their group-work skills, and the interviewees observed that their students started becoming more independent and autonomous without constant tutor supervision. Although students’ experiences explained by the interviewees were diverse, they generally reflected an overall satisfaction with PBL with large student groups. Moreover, two interviewees working in institutions having all of their curricula based on PBL, PjBL, or TBL explained that students joined these programs/institutes because they were generally interested in the approaches. Therefore, the interviewees explained that these students were usually satisfied with the student-centered learning approaches.

34

S. Loyens et al.

Tutors’ Experiences Tutors’ experiences were diverse but generally positive, according to the interviewees. Interviewees explained the challenging aspect of PBL with large student groups for novice tutors. However, they usually explained that tutors were more comfortable with supervising multiple small groups simultaneously as they gained confidence with time, practice, and experience. For example, one interviewee noted the difference between her first PBL session as a tutor and her recent experiences a few years later. She explained the difficulty of identifying the right moment to intervene in her students’ discussion without interrupting them in their learning process. However, she mentioned that it became easier for her to identify when her students needed help with her experience. Many interviewees mentioned the use of tutor assistants in the management of large groups. The tutor assistants’ profiles varied, but essential characteristics were brought up in several interviews. Firstly, it was considered necessary for tutors and tutor assistants to have sufficient background knowledge on the topic being discussed as tutors needed to recognize students’ difficulties and give relevant information and feedback. One interviewee also mentioned the importance for tutors to have sufficient tutoring skills in addition to sufficient background knowledge. Several interviewees mentioned that novice tutors needed an explanation of their facilitating instead of a transmissive role in the classroom. Besides the management of multiple small student groups simultaneously, one interviewee mentioned the management of large groups by multiple tutors. Large student groups had to be coordinated to make sure that students were learning the same things. Few interviewees mentioned the organization of conferences or meetings with tutors to explain the problems or projects given to the students and the expectations for tutors and students. Moreover, one interviewee mentioned a regular organization of these meetings to allow the discussion of potential difficulties and improvements.

Technology Digital Learning Environment Almost all interviewees mentioned digital learning environments. Tutors used online platforms to share the problem information, notes taken during discussions, and useful material for students. The digital learning environment ensured the capacity for students to access what was discussed in groups by uploading all the materials on a platform accessible to everyone. Moreover, some interviewees mentioned ensuring that all students had similar notes, learning objectives, and materials by sharing all the information needed on the same platform. Digital learning environments enable tutors to provide the same content to every student.

Student-Centered Learning with Large Student Groups …

35

Technology Within the Classroom In addition to the digital learning environment, several interviewees mentioned using technology within their classrooms. The example of the LKCMedicine learning environment in the section on organization shows the benefits of technology in enhancing communication and interaction among students. The use of projection screens in the classrooms enabled all students in a large group to see what was being written down. Moreover, microphones on tables allowed students to hear each other. CESI placed a TV screen on every A2P2 table to allow students to share their screens to facilitate the discussion. Indeed, when a student wanted to show something on his computer, he could project it on the TV, visible to every student in the group.

Online Learning During COVID-19 Pandemic Due to the circumstances engendered by the COVID-19 pandemic, tutors and students have been forced to adapt PBL to online learning. All interviewees had to find effective ways to continue PBL online, and they adapted their methods in various ways. The interviewees mostly kept the same organization as before the pandemic. Small groups were created online for group discussions in between plenary discussions. Tutors were going from one breakout room to another as they were going from one group to another in class before the pandemic. Interviewees mentioned that the use of digital learning environments already before the pandemic enabled a gentle switch to online learning, as the learning material was already accessible online. However, one interviewee mentioned the required adjustments due to online learning. He explained that more breaks and shorter class times were needed because online learning required more intense attention from students. Furthermore, he noted that his tutor’s role differed in an online setting, as he had to help students define their learning goals. Students needed more help and structure in defining the learning goals and drawing conclusions from their group discussions. He could then share the information on the chat function and the digital learning environment. On the other hand, some interviewees decided to adopt an asynchronous model, without live sessions, due to external circumstances, including international students living in different time zones. In addition, some institutions modified their attendance requirements due to the pandemic, which made the organization of a structured PBL model difficult, as students could miss classes more often. One interviewee explained that it was difficult to organize effective PBL sessions when students were not required to be present at each session. Unlike the previously mentioned organization of live PBL sessions, the asynchronous organization did not gather students together, nor did the tutors have live time with their students. Students were expected to work together with autonomy, without the direct supervision of a tutor. A few interviewees mentioned the benefits and drawbacks of online learning. TBL seemed to benefit from online learning for two reasons. Firstly, it was easier to find content experts available for TBL sessions, as the online setting did not have the same requirements timewise. Moreover, one interviewee observed more

36

S. Loyens et al.

activity and participation from students, which could be explained with the safer character of the online environment for shy students. The chat option also seemed to enhance students’ participation. However, other interviewees had different opinions. According to some, online learning made the discussions less spontaneous and therefore less productive. Furthermore, the asynchronous organization seemed to decrease students’ engagement. The online learning experiences created new opportunities for future education, as mentioned by several interviewees. Some brought up the possibility of blended education, combining online and on-campus sessions. Some interviewees mentioned the benefits of online learning, including fewer financial requirements and less struggle to find content experts available for TBL. Moreover, online learning enabled international students to be where they wanted to be. However, several interviewees also mentioned the importance of meeting on campus for students, as it allows students to meet each other and enhance social integration. Moreover, it has been reported to be easier for students to have online sessions when they already know each other from on-campus classes compared to when they are online from the beginning of the course. With the advantages of online and oncampus teaching, a few interviewees mentioned a potential future-blended education. Possibilities included starting the course on campus and switching to online learning later on or teaching some topics online with larger groups and some topics related to skill trainings on campus.

Discussion By interviewing professionals with experience regarding PBL with large student groups, this study aimed to answer the following question: How can PBL be implemented with large student groups? This research question was divided into three sub-questions: (a) why is PBL implemented at a large scale, (b) how is PBL implemented at a large scale, and (c) what are the experiences with the implementation of PBL at a large scale, with a special focus on the role of technology?

Increased Interest in PBL and Lack of Resources The interviews have shown that the implementation of PBL with large student groups results, first of all, from an increased interest in student-centered educational approaches and the desire to change lecture-based education. Student-centered educational approaches are becoming increasingly popular in educational institutions (Krahenbuhl, 2016), as they are thought to better prepare students for their future professions (Carlson & Bracke, 2015). The shift from a teacher to a tutor role facilitating the learning process and an increased emphasis on students (Lindholm & Astin, 2008) results in significant curriculum modifications. Studies displaying numerous

Student-Centered Learning with Large Student Groups …

37

benefits of PBL, including a better application of knowledge (Hung et al., 2008) and improved communication skills (Koh et al., 2008), encourage institutions to adopt PBL and other instructional models, including TBL and PjBL. Consequently, a rising number of tutors and institutions look into the possibility of leaving a complete lecture-based education behind and moving toward a more student-centered approach (Wright, 2011). Furthermore, the implementation of PBL with large student groups is a consequence of a lack of resources in terms of finances, infrastructure, and available tutors, confirming the difficulties faced by Khan and Fareed (2001). Education has suffered from budget cuts (Johnson et al., 2011) and the growth of for-profit universities (Delavande & Zafar, 2019). These financial pressures leading to a decreased budget per student have forced educational institutions to change their organization, often including increased class size and reduced additional aid for students with difficulties (Villanueva, 2013). This study confirmed that the increased class size as a consequence of budget cuts is one of the main reasons for the shift to PBL with large student groups, as institutions face the impossibility of providing small group tutoring sessions under the supervision of a tutor.

Keeping Small Group Discussions in Large-Scale PBL After identifying the rationale behind the implementation of PBL with large student groups, our research aimed to understand how the (re-)organization was made. A significant characteristic found in the large-scale PBL is the upkeep of small group discussions. The interviewees identified the small group discussions as a crucial component of PBL and made sure to keep them in their large-scale implementation. Group sizes differed but did not exceed seven students, smaller than what can be found in the original PBL tutoring sessions gathering between six and twelve students (Loyens et al., 2012). Small group discussions intend to enhance collaborative learning and students’ engagement. Studies have shown that they increase intrinsic motivation (Jones, 2007; Schmidt & Moust, 1998), develop SDL (Loyens et al., 2008; Moust et al., 2005), improve communication and group-work skills (Pluta et al., 2013; Wun et al., 2007), and facilitate learning of students (Shankar et al., 2014). The aim for students to become effective collaborators, foster their intrinsic motivation, and develop their SDL skills is the goal of PBL mentioned by Loyens et al. (2012). Therefore, the upkeep of small group discussions is essential when adapting PBL for large student groups. Thus, tutors divide their students into small groups within their large classrooms and supervise multiple groups simultaneously. By making the group sizes small, they expect students to be engaged in the group discussion. The fewer students are in a group, the more opportunity they have to participate in the discussion. It is also worth noting that tutors cannot supervise all group discussions in a large classroom. They mainly go from one group to another to be aware of the group’s status and sometimes gather all students for a plenary discussion. The role

38

S. Loyens et al.

of the tutor in large-scale PBL remains the same as in small scale, that is, a facilitator, stimulator (Azer, 2005), mentor, expert, and team builder (Chan, 2008), guiding and motivating students in their learning process (Schmidt et al., 2010). However, when indirectly supervising the group discussions, tutors need to find ways to assess the groups’ learning status and provide relevant feedback.

Physical Learning Environments for Large Student Groups This study identified the potential benefits of effective physical learning environments in the management of multiple groups simultaneously. Physical learning environments refer to the physical properties of a place where learning occurs (Choi et al., 2014). They are designed to facilitate students’ learning process, the supervision of the tutors, and communication between and within groups. Lackney (1994) notes that a physical learning environment could indirectly affect students’ achievement by affecting students’ and teachers’ attitudes by, for example, creating enthusiasm. The design of physical learning environments can enhance collaboration among students (Blandin, 2018), and studies are conducted on the development of, for example, precise table shapes and sizes that could have implications on groups’ discussion and students’ engagement. Engaging students in large groups can be challenging when the tutor does not have constant supervision over their learning process. Thus, designing a learning environment that enhances students’ discussion and engagement could be very beneficial in managing large student groups.

Technology in Large Classrooms This study noted that the integration of technology in the physical learning environment was increasing to facilitate the management of large student groups. Projectors, TVs, computers, iPads, and microphones facilitate collaboration and communication among students, within and between small groups. ICT provides different platforms for students to share and present information and enhances communication between students, confirming the opportunities of educational technologies mentioned by Stefan ¸ (2019). ICT is implemented in the classrooms to support learning (Kervin & Mantei, 2010), integrating digital projectors, interactive whiteboards, and computers, as mentioned by Tondeur et al. (2015). Microphones are used in large classrooms to facilitate communication between groups and staff members. TVs and digital projectors are used to display relevant material and information to students, reachable by all the students gathered in the same classroom.

Student-Centered Learning with Large Student Groups …

39

Online Learning Environment for Large Student Groups Besides the physical learning environment, an increasing number of institutions nowadays use a digital learning environment to provide students with various online platforms. The online learning environment provides students with the learning material and relevant content (Klegeris & Hurren, 2011). In addition, it has become a way of communication with the use of forums and chats. A digital learning environment is a way to provide the same learning material to students, more accessible for large student groups. Moreover, online learning seems to have benefits. Arkorful and Abaidoo (2015) mention the flexibility of time and space in teaching delivery, discussion forums enabling discussion, and increased cost-effectiveness due to the ability to gather more students without the need for a large physical classroom and travel time. The benefits of online learning concerning class sizes were also noted by Hockly (2018). Therefore, there could be an opportunity for future education with large student groups when institutions do not have enough building space and furniture. Online learning could also help overcome the financial burden of large classes, as classroom spaces are not needed, and furniture such as microphones or TVs neither. Furthermore, online learning is beneficial for international students, as it allows learners to attend class remotely (Singh, 2021). It does not require students to be at the same place or necessitate tutors or content experts to be on campus. However, students’ and tutors’ experiences in online learning need further research, as the students’ engagement, motivation, discussion, and learning outcomes are still unclear. The importance of students’ social integration provided by oncampus teaching is essential for students. Careful consideration of online learning needs to be applied, acknowledging the importance of social relationships in the students’ learning processes. Moreover, as Haslam et al. (2021) mention, online learning requires students’ motivation and time management skills, and explanations and interpretations can sometimes be more complicated than in-person. Lastly, skill-related courses are difficult to implement online, as they require students’ practice.

Students’ and Tutors’ Experiences with Large Student Groups Our study aimed to identify the overall students’ and tutors’ experiences with PBL with large student groups as a last sub-question. Students’ experiences were, in the majority, positive, as well as tutors’ experiences. However, the management of large student groups creates difficulties for tutors, as they face decreasing supervision of their students’ learning. Tutors’ organizations need to be carefully developed, and it is often a strenuous exercise for novice tutors. Schmidt and Moust (1995) explained that good tutors should possess three characteristics: subject-matter expertise, social

40

S. Loyens et al.

congruence, and cognitive congruence. Novice tutors need to have sufficient background knowledge on the topic being discussed (i.e., subject-matter expertise), good tutoring skills to facilitate the sessions and being able to explain issues at the level of the student (i.e., cognitive congruence), and the ability to establish an informal relationship with their students (i.e., social congruence). Managing large student groups challenges social congruence, as tutors face decreased supervision of their students’ learning. It is also essential to consider the social relevance in education when implementing online learning. It often has consequences on creating informal relationships between tutors and students and among students. Furthermore, the struggle to find available tutors can threaten the level of tutoring skills, a key characteristic for PBL tutors. Hiring tutors’ assistants from master’s degree programs or part-time tutors can help overcome this obstacle. However, novice tutors need to get aligned on the tutoring methods, especially with large student groups, as it requires particular management skills, such as the ability to assess multiple groups’ learning status simultaneously and ensure that all students are on the same track. Moreover, senior tutors who have had experience with PBL on a small scale need to adapt their methods to large student groups and adjust their organization. A way to tackle these challenges is the implementation of conferences or regular meetings with all tutors. These meetings serve to explain the tutors’ role and what is expected from them and the students. Moreover, regular meetings during the term allow for discussing potential difficulties and improvements for the future. Tutors understanding their role in a large classroom and having the knowledge and skills concerning the management of large PBL student groups are crucial elements in the success of the implementation of PBL on a large scale and needs close attention. Students also need to understand the aim of PBL and the benefits brought to their learning. Conferences and meetings with students providing information and surveys throughout the term to assess their experience of the process are equally important as conferences for tutors.

Limitations and Recommendations A first limitation is the small number of participants due to a lack of literature found on the topic, as interviewees were selected based on published articles on this issue besides the personal networks of the authors. As such, further research is needed to get a broader picture of the possibilities. The participants in our study came from North America, Europe, and Singapore and did not include institutions from the Middle East, Africa, or South America. Research on implementations in these regions would allow for a deeper knowledge of the various possibilities. Moreover, most of our interviewees had implemented PBL in medical or psychology curricula. Further research on the implementation of PBL with large groups in humanities, as did only one of our participants, could support the implementation of PBL in a wider variety of curricula.

Student-Centered Learning with Large Student Groups …

41

Furthermore, the lack of research does not enable a clear comparison between small-scale and large-scale PBL. Recommendations for future research would be to assess the differences between small-scale and large-scale PBL in the students’ engagement, learning outcomes, group discussions, and interaction among them and tutors. Such studies would allow a deeper understanding of the consequences of large student groups on learning, as less supervision and more autonomy of students can influence learning. Moreover, our study only interviewed one member of each institution. Further research should include a direct assessment of students’ and novice and senior tutors’ experiences to get a broader picture of the specificities of large PBL groups. A second limitation relates to the different models of PBL used. Definitions of PBL and the structure of the process differ, leading to difficulties in comparing the different implementations. Steps taken in the process differ, as do the beliefs on what the tutor’s role should be. While some tutors give more autonomy to students, others provide more structure in their process and discussions. In addition, the development of other approaches, such as TBL or PjBL, sometimes gives rise to mixed and intertwined models, difficult to define.

Conclusion PBL, PjBL, and TBL are increasingly implemented in higher education institutes as interest in student-centered educational approaches grows. However, the small-scale educational format is faced with a growing number of students in undergraduate studies and a lack of financial and infrastructure resources. Therefore, higher institutions are struck with a challenge: implementing PBL, an originally small-scale method, with large student groups. This study identified the rationale, organization, and experiences associated with the implementation of PBL with large student groups and showed that PBL could be implemented in large classrooms while keeping its small group discussion characteristic.

Appendix A: Definition of Team-Based Learning (TBL) and Project-Based Learning (PjBL) and Their Differences with Problem-Based Learning (PBL) TBL is characterized by students divided into small teams within a large classroom. It acknowledges the central role of learners, the importance of problem-solving, and the emphasis on collaboration among students (Hrynchak & Batty, 2012). The TBL process is divided into three phases: (1) pre-class study during which learners study assigned material, (2) readiness assurance during class with individual and group readiness assurance tests, as well as immediate feedback given by the instructor, and

42

S. Loyens et al.

(3) application of acquired knowledge in teams using problem-solving exercises. Furthermore, Michaelsen and Sweet (2008) give four elements of successful TBL: an effective formation of teams enhancing group cohesiveness, accountability of students for their own learning, immediate feedback from the instructor, and assignments promoting learning and team work. TBL is organized according to knowledge acquisition before class followed by knowledge application in class. PjBL is also based on collaborative learning as students are divided into small groups. Students have the freedom to design their own project and work in groups in order to develop their project and create a final product (Gary, 2015). The projects are conducted over a varying period of time from a few days to a few weeks and are often interdisciplinary (Coffey, 2008). De Graaff and Kolmos (2007) give five principles of PjBL: problem orientation, project-organization, interdisciplinary considerations, participant control, and exemplary function (i.e., students have to link the theories to practice). A significant difference between PBL and PjBL is the creation of an end product in PjBL, compared to PBL which is considered more focused on the learning process and the resulting knowledge acquisition (Kokotsaki et al., 2016).

Appendix B: Background of Participants The following seven participants were interviewed: • Prof. Dr. Henk Schmidt Prof. Dr. Henk Schmidt was the first interviewee, as the founding father of PBL in the Netherlands. He initiated PBL in the Psychology program at Erasmus University Rotterdam in the Netherlands. He started his PBL career as a student tutor assistant at Maastricht University and started his research in the area of (medical) education there. He has had experiences with various PBL implementations, including the One Day One Problem approach at Republic Polytechnic in Singapore, the implementation of PBL with large numbers of students at Erasmus University in Rotterdam, and Team-Based Learning at Lee Kong Chian School of Medicine (LKCMedicine) in Singapore. He still holds a consultancy position at LKCMedicine. • Prof. Dr. Guus Smeets Prof. Dr. Guus Smeets is a professor of Educational Psychology at Erasmus University Rotterdam. He worked together with Prof. Dr. Schmidt in developing the PBL Psychology curriculum at Erasmus University Rotterdam. He is a clinical psychologist by training but got involved in managing educational programs at Maastricht University and later at Erasmus University Rotterdam. He was very much involved in setting up the Psychology curriculum and implemented PBL at the School of Law of Erasmus University Rotterdam. Recently, as a Psychology Professor, he has started to implement PBL with large groups of students.

Student-Centered Learning with Large Student Groups …

43

• Prof. Dr. Andis Klegeris Prof. Dr. Andis Klegeris is a full professor in the Biochemistry Department at the University of British Columbia - Okanagan (UBC) in Canada, originally coming from Latvia. His research areas focus on Neurobiology and Pharmacology. He got involved with PBL first as a tutor in England and always tries to apply a student-centered educational approach in his Biochemistry classes, gathering between approximately 60 to 90 students. He published several journal articles on implementing PBL with large student groups. • Dr. Kalani Craig Dr. Kalani Craig is an associate professor of Medieval History at Indiana University Bloomington in the United States. She decided to switch from a lecture-based approach to PBL in her already large classroom, with between 75 and 100 students. • Prof. Dr. Bernard Blandin Prof. Dr. Bernard Blandin is a research director in CESI, an engineering school in France. CESI is a national private engineering school with 25 campuses across France, which requires a nationally-based organization. His educational background is Engineering and Sociology. He got involved in educational sciences and focuses on developing learning environments, including studies on suitable furniture that could be used in student-centered educational methods with large student groups. He published several journal articles on his experiences with PBL with large student groups. • Prof. Dr. Diana Dolmans Prof. Dr. Diana Dolmans is a full professor in the field of innovative learning environments at the School of Health Professions Education (SHE) at Maastricht University in the Netherlands. She has been involved in the management of several curricula and has been involved with PBL and other educational methods including study teams and TBL. She has published numerous articles on PBL and, more recently, on TBL and PBL. • Dr. Jerome Rotgans Dr. Jerome Rotgans is an assistant professor and medical education researcher at the Lee Kong Chian School of Medicine (LKCMedicine) in Singapore. He started his career in the navy, where he became responsible for officers’ training and developed an interest in learning and education. After quitting the navy, he started developing master’s programs and moved to Singapore, where he worked first at the Republic Polytechnic, and then at the National Institute of Education (NIE), and currently at the LKCMedicine. His research domain was first focused on the psychology of learning to then shift to psychometrics and assessment. He has had experience with PBL at the Republic Polytechnic with the One Day One Problem approach and Team-Based Learning at LKCMedicine.

44

S. Loyens et al.

References Ak, S. (2011). The effect of computer supported problem based learning on students’ approaches to learning. Current Issues in Education, 14(1). http://cie.asu.edu/ojs/index.php/cieatasu/article/ view/712 Aksu, H. H. (2009). Questionnaires and interviews in educational researches. Journal of Graduate School of Social Sciences, 13(1), 201–216. Arkorful, V., & Abaidoo, N. (2015). The role of e-learning, advantages and disadvantages of its adoption in higher education. International Journal of Instructional Technology and Distance Learning, 12(1), 29–42. Azer, S. A. (2005). Challenges facing PBL tutors: 12 tips for successful group facilitation. Medical Teacher, 27(8), 676–681. https://doi.org/10.1080/01421590500313001 Bae, H., Xia, F., Chen, Y., Craig, K., & Hmelo-Silver, C. E. (2018). Developing historical thinking in PBL class supported with synergistic scaffolding. In J. Kay & R. Luckin (Eds.), Rethinking learning in the digital age: Making the learning sciences count. 13th International Conference of the Learning Sciences (ICLS) 2018, Volume 3. International Society of the Learning Sciences. https://doi.org/10.22318/cscl2018.1483 Beichner, R. J., Saul, J. M., Abbott, D. S., Morse, J. J., Deardorff, D., Allain, R. J., Bonham, S. W., Dancy, M. H., & Risley, J. S. (2007). The student-centered activities for large enrollment undergraduate programs (SCALE-UP) project. Research-based Reform of University Physics, 1(1), 2–39. https://www.compadre.org/Repository/document/ServeFile.cfm?ID=4517&DocID=183 Blandin, B. (2018). Pourquoi les pédagogies actives au CESI: Le point de vue d’un non spécialiste [Why active pedagogies at CESI: The point of view of a non specialist]. In B. Blandin (Ed.), Actes du Colloque Penser la formation aujourd’hui: Un nouveau paradigme (pp. 43–46). CESI. Carlson, J., & Bracke, M. S. (2015). Planting the seeds for data literacy: Lessons learned from a student-centered education program. International Journal of Digital Curation, 10(1), 95–110. https://doi.org/10.2218/ijdc.v10i1.348 Chan, L. C. (2008). The role of a PBL tutor: A personal perspective. The Kaohsiung Journal of Medical Sciences, 24(35), S34–S38. https://doi.org/10.1016/S1607-551X(08)70092-5 Chen, C. H., & Chen, C. Y. (2012). Instructional approaches on science performance, attitude and inquiry ability in a computer-supported collaborative learning environment. Turkish Online Journal of Educational Technology, 11(1), 113–122. http://www.tojet.net/articles/v11i1/11110. pdf Chin, C., & Chia, L. G. (2004). Problem-based learning: Using students’ questions to drive knowledge construction. Science Education, 88(5), 707–727. https://doi.org/10.1002/sce.10144 Choi, H. H., Van Merriënboer, J. J. G., & Paas, F. (2014). Effects of the physical environment on cognitive load and learning: Towards a new model of cognitive load. Educational Psychology Review, 26(2), 225–244. https://doi.org/10.1007/s10648-014-9262-6 Cloete, A. L. (2017). Technology and education: Challenges and opportunities. HTS Theological Studies, 73(4), Article 4589. https://doi.org/ https://doi.org/10.4102/hts.v73i4.4589 Coffey, H. (2008). Project-based learning. Learn NC, 1–3. De Graaff, E., & Kolmos, A. (2007). History of problem-based and project-based learning. In E. De Graaff & A. Kolmos (Eds.), Management of Change (pp. 1–8). Brill Sense. https://doi.org/ 10.1163/9789087900922_002 Delavande, A., & Zafar, B. (2019). University choice: The role of expected earnings, nonpecuniary outcomes, and financial constraints. Journal of Political Economy, 127(5), 2343–2393. https:// doi.org/10.1086/701808 Dolmans, D. H. J. M., & Schmidt, H. G. (2006). What do we know about cognitive and motivational effects of small group tutorials in problem-based learning? Advances in Health Sciences Education, 11(4), 321–336. https://doi.org/10.1007/s10459-006-9012-8 Elzainy, A., El Sadik, A., & Al Abdulmonem, W. (2020). Experience of e-learning and online assessment during the COVID-19 pandemic at the College of Medicine, Qassim University.

Student-Centered Learning with Large Student Groups …

45

Journal of Taibah University Medical Sciences, 15(6), 456–462. https://doi.org/10.1016/j.jtu med.2020.09.005 Fox, N. (2006). Using interviews in a research project. Trent Research & Development Support Unit. Gary, K. (2015). Project-based learning. Computer, 48(9), 98–100. https://doi.org/10.1109/MC.201 5.268 Goh, P. S., & Sandars, J. (2020). A vision of the use of technology in medical education after the COVID-19 pandemic. MedEdPublish, 9(49). https://doi.org/10.15694/mep.2020.000049.1 Hakkarainen, K., & Sintonen, M. (2002). The interrogative model of inquiry and computersupported collaborative learning. Science & Education, 11(1), 25–43. https://doi.org/10.1023/ A:1013076706416 Haslam, C. R., Madsen, S., & Nielsen, J. A. (2021). Problem-based learning during the COVID-19 pandemic. Can project groups save the day? Communications of the Association for Information Systems, 48, 161–168. https://doi.org/10.17705/1CAIS.04821 ˇ Henriksen, D., Henderson, M., Creely, E., Ceretkova, S., Cernochová, M., Sendova, E., Sointu, E. T., & Tienken, C. H. (2018). Creativity and technology in education: An international perspective. Technology, Knowledge and Learning, 23(3), 409–424. https://doi.org/10.1007/s10758018-9380-1 Hiltz, S. R., & Turoff, M. (2005). Education goes digital: The evolution of online learning and the revolution in higher education. Communications of the ACM, 48(10), 59–64. https://doi.org/10. 1145/1089107.1089139 Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235–266. https://doi.org/10.1023/B:EDPR.0000034022.16470.f3 Hockly, N. (2018). Blended learning. ELT Journal, 72(1), 97–101. https://doi.org/10.1093/elt/ ccx058 Hrynchak, P., & Batty, H. (2012). The educational theory basis of team-based learning. Medical Teacher, 34(10), 796–801. https://doi.org/10.3109/0142159X.2012.687120 Hung, W., Jonassen, D. H., & Liu, R. (2008). Problem-based learning. In J. M. Spector, M. D. Merrill, J. Van Merriënboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (pp. 485–506). https://doi.org/10.4324/9780203880869.ch38 Johnson, N., Oliff, P., & Williams, E. (2011). An update on state budget cuts. Center on Budget & Policy Priorities. https://www.cbpp.org/sites/default/files/atoms/files/3-13-08sfp.pdf Jones, R. W. (2007). Learning and teaching in small groups: Characteristics, benefits, problems and approaches. Anaesthesia and Intensive Care, 35(4), 587–592. https://doi.org/10.1177/031005 7X0703500420 Kervin, L., & Mantei, J. (2010). Incorporating technology within classroom literacy experiences. Journal of Literacy and Technology, 11(3), 77–100. https://ro.uow.edu.au/edupapers/313/ Khan, I., & Fareed, A. (2001). Problem-based learning variant: transition phase for a large institution. Journal of Pakistan Medical Association, 51(8), 271–274. https://ecommons.aku.edu/pakistan_ fhs_mc_bbs/615 Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86. https://doi.org/10.1207/ s15326985ep4102_1 Klegeris, A., & Hurren, H. (2011). Impact of problem-based learning in a large classroom setting: Student perception and problem-solving skills. Advances in Physiology Education, 35(4), 408– 415. https://doi.org/10.1152/advan.00046.2011 Koh, G. C. H., Khoo, H. E., Wong, M. L., & Koh, D. (2008). The effects of problem-based learning during medical school on physician competency: A systematic review. Canadian Medical Association Journal, 178(1), 34–41. https://doi.org/10.1503/cmaj.070565 Kokotsaki, D., Menzies, V., & Wiggins, A. (2016). Project-based learning: A review of the literature. Improving Schools, 19(3), 267–277. https://doi.org/10.1177/1365480216659733

46

S. Loyens et al.

Krahenbuhl, K. S. (2016). Student-centered education and constructivism: Challenges, concerns, and clarity for teachers. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 89(3), 97–105. https://doi.org/10.1080/00098655.2016.1191311 Lackney, J. A. (1994). Educational facilities: The impact and role of the physical environment of the school on teaching, learning and educational outcomes. Center for Architecture and Urban Planning Research. https://dc.uwm.edu/caupr_mono/10 Lindholm, J. A., & Astin, H. S. (2008). Spirituality and pedagogy: Faculty’s spirituality and use of student-centered approaches to undergraduate teaching. The Review of Higher Education, 31(2), 185–207. https://doi.org/10.1353/rhe.2007.0077 Loyens, S. M. M., Kirschner, P. A., & Paas, F. (2012). Problem-based learning. In K. R. Harris, S. Graham, T. Urdan, A. G. Bus, S. Major, & H. L. Swanson (Eds.), APA educational psychology handbook, Vol. 3. Application to learning and teaching (pp. 403–425). American Psychological Association. https://doi.org/10.1037/13275-016 Loyens, S. M. M., Magda, J., & Rikers, R. M. J. P. (2008). Self-directed learning in problem-based learning and its relationships with self-regulated learning. Educational Psychology Review, 20, 411–427. https://doi.org/10.1007/s10648-008-9082-7 Mennin, S. (2007). Small-group problem-based learning as a complex adaptive system. Teaching and Teacher Education, 23(3), 303–313. https://doi.org/10.1016/j.tate.2006.12.016 Michaelsen, L. K., & Sweet, M. (2008). The essential elements of team-based learning. New Directions for Teaching and Learning, 116, 7–27. https://doi.org/10.1002/tl.330 Moust, J., Roebertsen, H., Savelberg, H., & De Rijk, A. (2005). Revitalising PBL groups: Evaluating PBL with study teams. Education for Health, 18(1), 62–73. https://doi.org/10.1080/135762805 00042705 Neo, M., & Neo, K. T. (2001). Innovative teaching: Using multimedia in a problem-based learning environment. Journal of Educational Technology & Society, 4(4), 19–31. https://www.jstor.org/ stable/jeductechsoci.4.4.19 Organisation for Economic Co-Operation and Development. (2013). PISA 2012 assessment and analytical framework: Mathematics, reading, science, problem solving and financial literacy. OECD Publishing. https://doi.org/10.1787/9789264190511-en Pastirik, P. J. (2006). Using problem-based learning in a large classroom. Nurse Education in Practice, 6(5), 261–267. https://doi.org/10.1016/j.nepr.2006.02.003 Pearson, J. (2006). Investigating ICT using problem-based learning in face-to-face and online learning environments. Computers & Education, 47(1), 56–73. https://doi.org/10.1016/j.com pedu.2004.09.001 Pluta, W. J., Richards, B. F., & Mutnick, A. (2013). PBL and beyond: Trends in collaborative learning. Teaching and Learning in Medicine, 25(Suppl. 1), S9–S16. https://doi.org/10.1080/ 10401334.2013.842917 Raja, R., & Nagasubramani, P. C. (2018). Impact of modern technology in education. Journal of Applied and Advanced Research, 3(Suppl. 1), S33–S35. https://doi.org/10.21839/jaar.2018.v3S 1.165 Ratheeswari, K. (2018). Information communication technology in education. Journal of Applied and Advanced Research, 3(Suppl. 1), S45–S47. https://doi.org/10.21839/jaar.2018.v3S1.169 Rehman, R., Khan, A. N., & Kamran, A. (2012). Role of small group interactive sessions in two different curriculums based medical colleges. Journal of the Pakistan Medical Association, 62(9), 920–923. Roulston, K. (2014). Analysing interviews. In U. Flick (Ed.), The SAGE handbook of qualitative data analysis (pp. 297–312). Sage. https://doi.org/10.4135/9781446282243.n20 Schmidt, H. G., & Moust, J. H. (1995). What makes a tutor effective? A structuralequations modelling approach to learning in problem-based curricula. Academic Medicine, 70(8), 708–714. https://doi.org/10.1097/00001888-199508000-00015

Student-Centered Learning with Large Student Groups …

47

Schmidt, H. G., & Moust, J. H. (1998, April 13–17). Processes that shape small-group tutorial learning: A review of research [Paper presentation]. Annual Meeting of the American Educational Research Association, San Diego, CA, USA. https://files.eric.ed.gov/fulltext/ED419792. pdf Schmidt, H. G., Cohen-Schotanus, J., Van Der Molen, H. T., Splinter, T. A. W., Bulte, J., Holdrinet, R., & Van Rossum, H. J. M. (2010). Learning more by being taught less: A “time-for-self-study” theory explaining curricular effects on graduation rate and study duration. Higher Education, 60(3), 287–300. https://doi.org/10.1007/s10734-009-9300-3 Schmidt, H. G., Rotgans, J. I., & Yew, E. H. J. (2011). The process of problem-based learning: What works and why. Medical Education, 45(8), 792–806. https://doi.org/10.1111/j.1365-2923.2011. 04035.x Selwyn, N. (2020). Telling tales on technology: Qualitative studies of technology and education. Routledge. Shankar, P. R., Nandy, A., Balasubramanium, R., & Chakravarty, S. (2014). Small group effectiveness in a Caribbean medical school’s problem-based learning sessions. Journal of Educational Evaluation for Health Professions, 11(5). https://doi.org/10.3352/jeehp.2014.11.5 Singh, H. (2021). Building effective blended learning programs. In B. H. Khan, S. Affouneh, S. Hussein Salha, & Z. N. Khlaif (Eds.), Challenges and opportunities for the global implementation of e-learning frameworks (pp. 15–23). IGI Global. https://doi.org/10.4018/978-1-79987607-6 So, H. J., & Kim, B. (2009). Learning about problem based learning: Student teachers integrating technology, pedagogy and content knowledge. Australian Journal of Educational Technology, 25(1). https://doi.org/10.14742/ajet.1183 Stefan, ¸ T. ¸ (2019). Implications of modern digital technologies in higher education. In Proceedings of the international scientific and practical conference on digital economy (pp. 271–274). Atlantis Press. https://doi.org/10.2991/iscde-19.2019.107 Strømsø, H. I., Grøttum, P., & Hofgaard Lycke, K. (2004). Changes in student approaches to learning with the introduction of computer-supported problem-based learning. Medical Education, 38(4), 390–398. https://doi.org/10.1046/j.1365-2923.2004.01786.x Tondeur, J., De Bruyne, E., Van Den Driessche, M., McKenney, S., & Zandvliet, D. (2015). The physical placement of classroom technology and its influences on educational practices. Cambridge Journal of Education, 45(4), 537–556. https://doi.org/10.1080/0305764X.2014.998624 Tondeur, J., Van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understandingthe relationship between teachers’ pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational Technology Research and Development, 65(3), 555–575. https://doi.org/10.1007/s11423-016-9481-2 National Center for Education Statistics. (2022, May). Undergraduate enrollment. https://nces.ed. gov/programs/coe/indicator_cha.asp#:~:text=Between%202000%20and%202018%2C%20t otal,increase%20to%2017.0%20million%20students Villanueva, C. K. (2013). School finance and the budget. Center for Public Policy Priorities. https:// forabettertexas.org/images/ED_2013_04_SchoolFinance.pdf Weiss, R. E. (2003). Designing problems to promote higher-order thinking. New Directions for Teaching and Learning, 95, 25–31. https://doi.org/10.1002/tl.109 Willis, S. C., Jones, A., Bundy, C., Burdett, K., Whitehouse, C. R., & O’Neill, P. A. (2002). Smallgroup work and assessment in a PBL curriculum: A qualitative and quantitative evaluation of student perceptions of the process of working in small groups and its assessment. Medical Teacher, 24(5), 495–501. https://doi.org/10.1080/0142159021000012531 Wright, G. B. (2011). Student-centered learning in higher education. International Journal of Teaching and Learning in Higher Education, 23(1), 92–97. https://files.eric.ed.gov/fulltext/EJ9 38583.pdf Wun, Y. T., Tse, E. Y. Y., Lam, T. P., & Lam, C. L. K. (2007). PBL curriculum improves medical students’ participation in small-group tutorials. Medical Teacher, 29(6), e198–e203. https://doi. org/10.1080/01421590701294349

Online Synchronous Peer Feedback Practice During COVID-19: Learners’ Self-Regulated Learning Mediates Their Perceived Value of Feedback and Feedback Uptake Boon Khing Song Abstract Feedback is a powerful attribute of effective teaching and learning. In particular, peer feedback practice is touted as the enabling activity of feedback effectiveness. While there is a plethora of studies that focuses on self-regulated learning (SRL) and feedback, feedback has mostly played the role of academic conduit for SRL. Little is known whether SRL provides a catalytic support for feedback effectiveness. Therefore, this study aims to address this research gap by foregrounding the role of feedback to investigate the relationship between the following variables: (1) perceived value of feedback (PV), (2) self-regulated learning (SRL), and (3) uptake of feedback (UF) in an online synchronous peer feedback environment. Validity and reliability analyses revealed good psychometric quality of the survey research instrument, which comprised 14 items. This study drew on survey data from 957 learners from a Year 1 compulsory module in an institute of higher learning in Singapore. Overall, it was found that learners endorsed strongly their SRL experiences during their online peer feedback activities. More importantly, SRL served as a full mediator between PV and UF variables. The theoretical and practical implications as well as further research direction are discussed in the paper. Keywords Online synchronous peer feedback · Perceived value of feedback · Self-regulated learning · Feedback uptake · Exploratory factor analysis · Confirmatory factor analysis · Mediation analysis · Structural equation modelling

Introduction Feedback is a complex concept. It has been conceptualised as the information used to address the gap between current performance level and the desired referenced level (Boud & Molloy, 2013; Ramaprasad, 1983). While it is recognised as “one of the most powerful influences on learning and achievement”, there are, invariably, disparate findings relating to the ineffectiveness or debilitating effects of feedback on B. K. Song (B) Republic Polytechnic, Singapore, Singapore e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Y. L. Chye and B. L. Chua (eds.), Pedagogy and Psychology in Digital Education, https://doi.org/10.1007/978-981-99-2107-2_3

49

50

B. K. Song

learning (Hattie & Timperley, 2007, p. 81). For instance, factors such as timeliness of feedback (Lipnevich et al., 2016; Shute, 2008); tone of feedback (Baron, 1993) and complexity of feedback (Brookhart, 2017) offer differing results on feedback effectiveness. Particularly, the results for the national student surveys in Australia (Quality Indicators for Learning and Teaching 2019) and the UK (Office for Students 2019) highlight students’ dissatisfaction with the effectiveness, timeliness and understanding of feedback. In this regard, there exist dissonances in the viewpoints of teachers and students towards feedback efficacy. Clearly, feedback information on its own may not be sufficient for students to act action and improve (Crisp, 2007; Evans, 2013). There appears to be a need for a more fundamental rethinking of feedback concept to improve feedback practices. In the recent years, there has been a transformational shift in the notion of feedback. Feedback processes are deemed to be successful only if the feedback information is used (Boud & Molloy, 2013; Sadler, 2010). In the Feedback Mark 2 model proposed by Boud and Molloy (2013, p. 7), students are positioned as committed “effective practitioners in the domain of their study” and “… active learner who seek to do whatever they need to understand what is required of them, what constitutes good work within the context of their study and whether their efforts at producing good work meet the appropriate standards and criteria within the knowledge domain”. From this perspective, learners are no longer understood as passive recipients of feedback but rather individuals who can actively seek, understand and use feedback (Boud & Molloy, 2013; Carless, 2019). In this new feedback paradigm, feedback is regarded as “all dialogues to support learning in both formal and informal situations” (Askew & Lodge, 2000, p. 1). It is worthwhile to note that the conception of dialogue is about all kinds of interactions between the various actors (teachers, peers, textbooks, learning artefacts and learning systems) and not merely face-to-face or one-to-one dialogue conversations (Boud & Molloy, 2013). More importantly, learner agency and the learning milieu play essential roles in enhancing feedback quality and processes (Boud & Molloy, 2013; Hoo et al., 2020). Underpinning this new understanding of feedback is the explicit orientation towards “… the purpose of feedback as self-regulating, and to view it as a means to increase capability in making judgments and acting upon them” (Boud & Molloy, 2013, p. 9). In this learner-centric feedback space, there are many studies investigating learners’ attributes towards feedback, such as self-regulation ((Butler & Winne, 1995; Nicol, 2006); motivation (Pitt & Norton, 2017); feedback engagement (Winstone, 2017a, 2017b); and feedback uptake (Crisp, 2007; Henderson et al., 2019). From these studies, it elucidates the need for teachers to decentralise feedback control and to allow students more opportunities to engage in feedback practices to acquire evaluation skills and foster feedback uptake (Winstone, 2017b).

Online Synchronous Peer Feedback Practice During COVID-19 …

51

Peer Feedback Practice Peer feedback collaborative practices have been touted pedagogically as enabling activities to promote learners’ self-regulation and their feedback uptake (Ibarra-Sáiz et al., 2020; Mercader et al., 2020; van der Pol, 2008). The practice of peer feedback involves students providing feedback on their peers’ work and in turn receiving feedback on their own work. Dialogic peer feedback, referred to, as a process in which learners engage in dialogue with their peers to make sense of feedback collaboratively (Filius, 2018; Nicol, 2010) aims to develop agentic learners who can collectively decide on their learning actions to enhance their performance (Yang, 2013). Palloff (2007) further suggests that interactive and collaborative learning allow learners to have the opportunity to extend and deepen their learning experiences through sharing, experimenting new ideas and receiving critical and constructive feedback. There is a variety of terminologies used to describe the different natures of peer feedback practices. This includes peer marking, peer feedback, peer grading, peer appraisal, peer evaluation, peer assessment, peer review and peer correction (Fernández-Toro & Duensing, 2020; Liu & Carless, 2006; Topping, 1998; Van Gennip, 2012). Amongst all these terms, peer feedback is defined as “a communication process through which learners enter into dialogues related to performance and standards” while peer assessment is related to “students grading the work or performance of their peers using relevant criteria” (Liu & Carless, 2006, p. 280). In other words, peer feedback is formative in nature and involves the provision of feedback comments without the awarding of grades. In contrast, peer assessment encapsulates grading and does not necessitate the provision of comments. From the described definitions, peer feedback is clearly situated within the social constructivist paradigm whereby learners and peers discuss, interpret and co-construct the meaning of feedback during dialogic collaborative sessions which in turn develop their capability in making judgement and reflective skills (Nicol, 2010; Nicol et al., 2014; Price et al., 2011; Roscoe, 2008). In this present study, peer feedback is investigated as it has greater potential for formative learning than peer assessment (Liu & Carless, 2006; Nicol, 2006).

Online Peer Feedback Practice In the current COVID-19 situation, many educational institutions have converted to online learning and virtual education in place of traditional face-to-face lessons to minimise social contact and the spread of the virus (Daniel, 2020). Studies have revealed the effectiveness of using online peer feedback tool for students’ learning (ONeill et al., 2020; Roman et al., 2020; van der Pol, 2008). In the research on how technology and pedagogy influenced New Zealand senior high school students’ learning experiences during COVID-19 pandemic, Yates et al. (2021) found supporting evidences that the effective use of technology and pedagogy enhanced

52

B. K. Song

learning experiences. The use of technology in learning may not be new—even before the pandemic, learners were already using e-tools such as Google doc, Dropbox, Microsoft OneDrive, Google Drive and Google classroom to work collaboratively on online documents (Conole, 2008)—but the use of a new online learning approach with technology may be novel and sudden to learners (Yates et al., 2021). Taking all these together, it may be insufficient to merely focus on the investigation of the usefulness of technology such as digital recording, collaborative writing tool, learning management system (LMS) and automated feedback in facilitating feedback sessions (Carless & Boud, 2018; Dawson et al., 2018). In fact, it is equally crucial to gain deeper insights to learners’ cognitive processes during online peer feedback activities (Nicol et al., 2014).

Self-Regulated Learning and Feedback Pintrich and Zusho (2002, p. 64) postulate that self-regulated learning (SRL) is “an active constructive process whereby learners set goals for their learning and monitor, regulate and control their cognition, motivation and behaviour, guided and constrained by their goals and the contextual features of the environment”. This definition highlights the social elements present in peer feedback practices as well as the constraints experienced by learners as they negotiate their cognitive, motivational and behavioural levels of SRL. Essentially, self-regulated learning (SRL) and feedback are closely associated (Butler & Winne, 1995; Nicol, 2006). Firstly, SRL involves learners’ cognitive, motivational and behavioural aspects of learning (Bandura, 2001; Pintrich & Zusho, 2002; Zimmerman, 2000). Secondly, feedback, whether internal or external, influences learners to adopt active approaches in controlling and regulating their own learning (Butler & Winne, 1995; Nicol, 2006). Thirdly, as theorised by Butler and Winne (1995) in their self-regulated learning (SRL) and feedback model (as depicted in Fig. 1), feedback activates self-regulated learning. Based on prior knowledge and motivational beliefs, learners set and plan their learning goals; employ tactics and strategies to tackle the given task; generate internal feedback and regulate their beliefs, strategise in the midst of monitoring their progresses towards the goals. The administration of external feedback from teachers and peers informs learners’ quality of work and in turn trigger subsequent revisions to their performance (i.e. external outcome and actual performance).

Conceptual Framework As seen in the SRL and feedback model, feedback exists in the background as it provides catalytic support for the emergence of SRL. However, in the current study, the focus is on peer feedback and specifically taking action on feedback via learners’

Online Synchronous Peer Feedback Practice During COVID-19 …

53

Task

Domain knowledge Strategy knowledge

Goals (desired performance)

Motivational beliefs

Tactics and strategies

Products (internal outcome, perceived performance)

Monitoring

Cognitive system

External feedback

Performance (external outcome, actual performance)

Fig. 1 Self-regulated learning (SRL) and feedback model by Butler and Winne (1995)

self-regulatory processes. As such, there is a wider need to target on the motivational, cognitive and behavioural aspects of learning, namely learners’ perceived feedback beliefs, monitoring of learning and behavioural action towards feedback in peer feedback which will be discussed in detail next.

Perceived Value of Feedback (PV) The notion of motivational belief in SRL may be elucidated by the expectancy-value theory that conceptualises motivation (Wigfield & Eccles, 2000). The theory postulates that expectancies (beliefs about how well one will perform on an activity) and values (the extent to which one values the activity) explain individuals’ choice, persistence and performance (Atkinson, 1957; Eccles & Wigfield, 2002). Emphasising on the value component of this theory, Eccles and Wigfield (2002) categorise it in the following aspects: attainment value, intrinsic value, utility value and cost. Attainment value refers to the importance of performing well on a task due to one’s self beliefs and personal values. Intrinsic value relates to the inherent enjoyment experienced in engaging with an activity. In addition, utility value is concerned with an individual’s belief in the usefulness of the task for immediate or long-term benefits. Finally, cost describes the trade-off between the benefits and the sacrifices associated with engaging in a particular activity. Particularly, utility value captures learners’ beliefs of the other valued outcomes that feedback can lead to (Linderbaum & Levy,

54

B. K. Song

2010). It is defined as “an individual’s tendency to believe that feedback is useful in achieving goals or obtaining desired outcomes” (Linderbaum & Levy, 2010, p. 1376). In fact, studies have revealed the importance of perceived usefulness of feedback in influencing learners’ motivation to accept and use feedback (Brett & Atwater, 2001; Harks, 2014). Therefore, learners’ perception of the value of feedback forms a crucial part of motivational beliefs and serves as an important variable in the conceptual framework employed in this study.

Self-Regulated Learning (SRL) In addition, self-regulated learning (SRL) contributes significantly to the effectiveness of learning processes (Panadero et al., 2017). While SRL involves cognitive goal-orientation aspects of learning in which learners plan, monitor and evaluate their cognitive, metacognitive and motivational levels of feedback engagement (Pintrich, 2004; Zimmerman, 2000), the present study scopes the SRL variable to the main monitoring and regulating components of the SRL and feedback model depicted in Fig. 1. The reason is that learners’ perception of the value of feedback serves to represent the motivational belief aspect of SRL while learners’ feedback uptake provides proxy to actual performance in SRL. Importantly, it is worthwhile to note that studies unfold the importance of SRL in mediating individual and contextual characteristics and the extent of achievement and performance (Jansen et al., 2019; Järvelä et al., 2016). On the other hand, the interactive nature of peer feedback activities enables peers to assist one another to transcend their zones of proximal development to perform the task and to learn about the regulation of their own actions (McCaslin & Hickey, 2001). To a large extent, learners and their peers co-regulate as learners progress to appropriation of self-regulation strategies through interaction with the more capable peers. In the current study, with references from Pintrich and Zusho (2002) and Zimmerman and Schunk (2013), SRL is presented as an active constructive cognitive process that learners engaged in, to strategise, monitor and regulate their learning processes.

Uptake of Feedback (UF) Finally, feedback effectiveness entails the ability of learners to apply their feedback to their subsequent works for improvement (Sadler, 1989). The nub of the notion of engagement lies in feedback uptake. Despite acknowledging feedback at every stage of the feedback process, learners might not perform the action of acting on feedback (Price et al., 2011). Researchers have identified the importance of learners’ engagement with learning goals, tasks and processes in influencing the effectiveness of feedback uptake (Price et al., 2011; Reeve & Tseng, 2011; Winstone et al., 2019;

Online Synchronous Peer Feedback Practice During COVID-19 …

Perceived value of feedback (PV)

Self-regulated learning (SRL)

55

Uptake of feedback (UF)

Fig. 2 Conceptual framework of feedback uptake used in this study

Winstone, 2017a). A conducive learning environment in which students see the value of using feedback and, more importantly, the need to put in time and effort and to implement the advice is crucial in the success of feedback practice (Winstone et al., 2019). Fundamentally, feedback uptake is an essential theoretical underpinning of feedback. There is a need for a more thorough examination of this variable, in lieu of the traditional focus of feedback research on academic achievement. In this study, feedback uptake refers to the behavioural characteristic of a learner taking further concrete action on feedback received on their assessed work. In sum, the conceptual framework of feedback uptake used in this study is illustrated in Fig. 2.

Research Problem Most peer feedback studies tend to focus on students’ perceptions of the usage of online peer feedback system (Donia et al., 2021); feedback dialogues (Ajjawi & Boud, 2017; Nicol, 2010; Reddy et al., 2021); peer assessment accuracies and issues (Liu & Carless, 2006); and design of peer feedback in online environments (Gikandi & Morrow, 2016). To date, few studies have focused on their attention of the mediating role of SRL in influencing feedback uptake. In particular, the empirical relationship between perceived value of feedback, self-regulated learning and feedback uptake manifested within peer feedback has not been fully established, especially for online sessions that have been converted abrupted from face-to-face ones due to the COVID-19 pandemic.

Significance of Study Therefore, there is a litany of potential in explicating these motivational, cognitive and behavioural processes whilst learners engaged in online peer feedback activities. Above all, in the recent shift to emergency remote teaching, this study contributes to literature by strengthening the theory–practice nexus of understanding the selfregulatory processes experienced by learners, in terms of their perceived value of

56

B. K. Song

feedback, self-regulated learning and feedback uptake, during online synchronous peer feedback activities. The results garnered from the study will likely allow educators and practitioners to gain useful insights into the mechanisms of learners’ self-regulatory processes within online peer feedback practices.

Aims of the Study This present research investigates learners’ perception of the value of feedback (motivational belief), SRL (cognitive engagement) and feedback uptake (behavioural engagement) in online synchronous peer feedback environment. More specifically, the following research questions (RQs) frame this present study: RQ1: What are the perceptions of learners, i.e. value of feedback (PV), selfregulating learning (SRL) and uptake of feedback (UF) within online peer feedback context? RQ2: To what extent does learners’ self-regulated learning (SRL) mediate their perceived value of feedback (PV) and uptake of feedback (UF) within online peer feedback context? To ensure that there is a common understanding of the constructs used in this study, Table 1 summarises their definitions. Table 1 Definition of the constructs Construct

Definition

Source

Peer feedback

A communication process through which learners enter dialogues related to performance and standards

Liu and Carless (2006)

Perceived value of feedback (PV)

An individual’s perception of the usefulness of feedback to assist in goal achievements and valued outcomes

Linderbaum and Levy (2010)

Self-regulated learning (SRL) An active constructive process whereby learners control, monitor and regulate their cognition, guided and constrained by their goals and the contextual features of the environment Uptake of feedback (UF)

Pintrich and Zusho (2002)

The behavioural characteristic Winstone et al. (2019) of an individual taking further concrete action on feedback received on their assessed work

Online Synchronous Peer Feedback Practice During COVID-19 …

57

Methods Research Context Polytechnics are educational institutes of higher learning that prepare learners for the relevant skills, knowledge and aptitudes for the workplace. In a local polytechnic in Singapore, social constructivism is the underpinning approach of teaching and learning adopted by the institution. There are various instructional strategies, such as problem-based learning (PBL) and cognitive apprenticeship, utilised in the classrooms to facilitate learning. The common characteristics of these pedagogical practices involve helping the learners to activate their prior knowledge to engage in meaningful collaborative efforts to co-construct knowledge amongst team members. Lecturers perform the role of facilitators or coaches to provide scaffolds to assist learners in their learning. For the under-studied module (conducted via 13 weeks semester) using PBL approach for mainly Year One students in the institution, learners learnt critical thinking skills concepts, such as claims and arguments, types of argument, various cognitive biases and logical fallacies as well as critical thinking dispositions, for instance, open-mindedness, scepticism and empathy. Due to the COVID-19 pandemic, all lessons in academic year 2020 semester 1 were converted to online delivery mode using Microsoft Teams software. Lessons 10–12 were a cluster of three full day lessons (spanned across three weeks) situated in a large problem context that reflected a real-world complexity of the food insecure individuals or households in Singapore. Learners played the role of service-learning club (a voluntary group aimed at helping the needy) leaders in the institution. After learning about the systems thinking framework to understand the underlying issues with food insecurity in Singapore, they proceeded to draft proposals to convince relevant stakeholders in the community to help the food insecure beneficiaries. As these learners have not experienced proposal writing previously, they were guided with a template structure of a simple proposal. A peer formative feedback activity was designed as part of the curriculum in this cluster of lessons. It was initially planned to be a face-to-face activity with the following schema. 1. To prepare the learners for this activity, the four levels of feedback (i.e. self, task, process and self-regulation) from Hattie and Timperley’s feedback model will be introduced (Hattie & Timperley, 2007). 2. Learners are to provide written feedback to one other, using the three-step process of Praise-Question-Polish (PQP). This will involve (1) praising the part in the proposal that was done well; (2) raising a question to seek clarification; and (3) suggesting a recommendation to enhance the work. 3. Thereafter, learners will discuss in pairs in their classrooms to explain their written feedback messages and seek clarification if needed.

58

B. K. Song

However, due to lessons being converted to online synchronous ones, there was a need to adjust the peer feedback activity. Point 1 and 2 in the initial schema continued to be implemented for the online lessons. As dialogic feedback exchanges are important for effective learning, learners were instructed to set up live synchronous online peer conference sessions to conduct the schema in Point 3. Additionally, it was conveyed clearly to the learners that the peer feedback administered to their peers would be formative in nature and this activity was meant to help them enhance the quality of their draft proposal in preparation for the final submission at the end of Lesson 12.

Participants A total of 957 learners, between the ages of 17 and 20, from the described module took part in this study. It constituted a response rate of approximately 40%. About 56% of the participants were females (N = 537). The ethics composition of the study participants was 539 (56.3%) Chinese, 257 (26.9%) Malay, 103 (10.8%) Indian and 58 (6.1%) Others. In addition, 278 (29%) of them were from the Engineering discipline, 217 (22.7%) were from the Infocommunications discipline, 203 (21.2%) were from the Management and Communication discipline, 172 (18%) were from the Service and Hospitality discipline and 87 (9.1%) were from the Health and Leisure discipline.

Procedures and Data Collection Prior to the undertaking of the study, ethics approval was obtained from the institution. Two weeks before the commencement of data collection, the module chairs and lecturers of the described module were briefed about the details of this research. An online survey, using the Microsoft form platform, was administered to learners taking the described module in Week 12 of the semester. Convenience sampling was used to collect the data. Before the start of the whole study, lecturers briefed the learners about the purpose of the research as well as informed them that their participation was voluntary and that they could withdraw from the study at any time. Most importantly, an online consent was sought from all participants before survey administration, and it was also emphasised to them that the results obtained from the survey would not contribute to their assessment grade for the module taken.

Online Synchronous Peer Feedback Practice During COVID-19 …

59

Instrument A survey was employed as the research instrument for this study. It comprised 14 relevant items adapted from existing literature with three subscales, namely perceived value of feedback (PV), self-regulated learning (SR) and uptake of feedback (UF) as described earlier. The scale adopted a five-point Likert scale with the following representations: 1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree and 5 = strongly agree. To enhance the content and face validity of the survey items, the described module chair and co-chair as well as the author were involved in improving the items. The backgrounds of the item reviewers are subject matter experts in the areas of the curriculum, assessment, scale development as well as quantitative and qualitative research. Items in the perceived value of feedback (PV) subscale were adapted from the students’ perception of the usefulness of the formative assessment scale by (Rakoczy, 2019). Some of the items were modified to reflect the context of peer feedback. For example, for a particular item, instead of using “which type of task I should practice”, it was tweaked to “what actions I can take to improve in my learning”. In addition, the items from the self-regulated learning (SRL) subscale were adopted from the student perception of peer assessment in practice questionnaire developed by Ibarra-Sáiz et al. (2020). Only the item stems were changed slightly by replacing “peer assessment” with “peer feedback” to accurately portray the peer formative feedback setting. Finally, items in the uptake of feedback (UF) subscale were modified from Winstone et al.’s (2019) Acting subscale in their feedback literacy survey. Attempts were made to simplify the items to improve clarity for the learners. For example, the original item “I want to take on board my feedback and learn from it” was amended to “I use the peer feedback to improve my learning”.

Data Analysis Plan The research instrument was evaluated for psychometric quality. For assessing internal consistency of the items in the survey, Cronbach’s alpha, inter-item correlation and item-total correlation were investigated. Apart from achieving face and content validity of the items in the various subscales, it is also important for the survey to demonstrate construct validity. This was achieved using exploratory and confirmatory factor analysis with the intention to establish model fit to the measurement model. Finally, since one of the focuses in this study is to conduct mediation analysis, the measurement and structural relationships between the described relevant variables were assessed using structural equation modelling (SEM) which is useful in deriving comprehensive relationships between the different constructs in a complex setting (Byrne, 2012).

60

B. K. Song

Result Analysis Descriptive Statistics of the Items Before the commencement of data analysis, the data was checked for extreme multivariate collinearity, outliers, normality and missing data. Using SPSS Version 26.0 statistical software via box plot and stem and leaf diagram, no outlier was detected. In addition, there was no missing data. Skewness and kurtosis values of the items ranged from −1.29 to −0.89, and 1.26 to 2.73, respectively. These values were within the recommended guidelines of absolute skewness value less than 2 and absolute kurtosis value less than 7 for univariate normality (West et al., 1995). In addition, histogram plots analyses of the variables revealed that the data displayed characteristics of normality. The descriptive statistics (i.e. mean, standard deviation [SD]) of the items in the PV, SRL and UF constructs are illustrated in Table 2. On the other hand, there was no evidence of extreme collinearity between the items as shown by their Pearson correlation coefficients in Table 3. In general, the means for all the items were above the average mean rating (3). Specifically, the means for items 7, 9 and 10 were the highest amongst the items (M = 4.26, 4.23 and 4.24, respectively). These were items from the SRL construct. Only one item, i.e. item 14, garnered a mean rating of below 4.0.

Reliability Analysis Overall, the survey scale demonstrated good internal consistency with alpha value of 0.96, exceeding the accepted threshold of 0.70 (Hair et al., 1998). Moreover, good reliabilities were also observed in the constructs, namely PV, SRL and UF with Cronbach’s alpha values of 0.94, 0.94, and 0.87, respectively. Furthermore, the inter-item correlations ranged from 0.51 to 0.82 whereas the item-total correlations spanned across the values of 0.67 to 0.82, thereby exhibiting reasonable reliability between the items since these values were above the minimum cut-off value of 0.30 as suggested by (Cristobal et al., 2007).

Correlation Analysis Correlation analysis indicated that there were significant positive correlations between the constructs as shown in Table 3. The results showed that more information could be obtained by further examining the relations of the variables with SEM. All the correlations between the constructs were considered moderate to strong as r > 0.60 in psychological studies (Dancey & Reidy, 2017).

Online Synchronous Peer Feedback Practice During COVID-19 …

61

Table 2 Descriptive statistics of the survey items Item No. Survey No. Content

Mean Standard deviation Construct

The peer feedback activity: 1

1(i)

Makes me put in effort in learning

4.09

0.773

2

1(ii)

Helps me reach my learning goal

4.02

0.797

3

1(iii)

Helps me recognise my learning gaps

4.14

0.810

4

1(v)

Indicates what actions I can take to improve in my learning

4.18

0.789

5

1(vi)

Reaffirms the areas 4.16 that I have done well

0.763

6

1(vii)

Is sufficient in assisting my learning

4.02

0.827

4.26

0.7541

Perceived value of feedback (PV)

The peer feedback activity helped me to: 7

2(i)

Analyse my own work and that of others

8

2(ii)

Learn to appreciate 4.18 the effort and dedication needed to complete a task

0.800

9

2(iii)

Identify my weaknesses and mistakes

4.23

0.776

10

2(iv)

Learn from my mistakes

4.24

0.790

11

2(v)

Learn to help others to improve

4.22

0.790

12

3(i)

I use the peer 4.17 feedback to improve my learning

0.804

13

3(ii)

I do spend time to 4.13 think about the peer feedback to improve my learning

0.816

14

3(iii)

I use the peer 3.97 feedback because I have chosen to, not because I am told to do so

0.906

Self-regulated learning (SRL)

Uptake of feedback (UF)

62

B. K. Song

Table 3 Pearson bivariate correlation coefficients between the constructs Construct

Mean

Standard deviation

PV

PV

4.10

0.70

–

SRL

SRL

4.23

0.70

0.73**

–

UF

4.10

0.75

0.72**

0.76**

UF

–

Note **p < 0.01 (2-tailed); N = 957

Validity Analysis Exploratory Factor Analysis (EFA) The principal component analysis with promax rotation was conducted using EFA to explore the factor structure of the under-studied construct. The Kaiser–Meyer– Olkin (KMO) test—measurement of sampling adequacy—revealed a value of 0.96, indicating that the sample size was adequate to perform factor analysis. The statistical significance (p < 0.001) of Bartlett’s Test of Sphericity suggested that the data was likely to be factorisable. The results yielded a 3-factor solution that accounted for 79% of the total variance as indicated in Table 4. The EFA factor loadings were all within the range of 0.64 to 1.00. All communalities were above 0.45 as recommended by Hair et al. (1998). As shown, there were six items loaded onto Factor 1, five items loaded onto Factor 2, and three items loaded onto Factor 3.

Confirmatory Factor Analysis (CFA) To ensure sufficient power for structural equation modelling (SEM) analysis, a-prior sample size calculator for SEM was used to generate the minimum sample size (Sopher, 2020). The results indicated that to obtain 0.80 power to detect medium effect size (0.30) at the 0.05 significance level, a minimum sample size of 150 was required. Hence, the sample size of 957 for this study garnered sufficient power for the analysis. Mplus version 8.4 (Muthén & Muthén, 1998–2017) was used to perform CFA to evaluate the measurement model. Since the data displays normality, the default maximum likelihood (ML) parameter estimates with standard errors and a chi-square test statistic that is robust to normality was employed as the estimator approach (Muthén & Muthén, 1998–2017). The goodness-of-fit of the model was evaluated using the following absolute and relative indices: (1) the χ2 goodness-of-fit statistics; (2) the Comparative Fit Index (CFI); (3) the Tucker-Lewis Index (TLI); (4) Standardised Root Mean Square Residual (SRMR) and (5) Root Mean Square Error of Approximation (RMSEA). For both the TLI and CFI, values above 0.95 are used to indicate adequate fit (Hu & Bentler, 1999). For SRMR, a reasonably good fit is supported for values below 0.08 (Hu & Bentler, 1999). For RMSEA, values below 0.06 are indicating of good model fit (Hancock & Mueller, 2013). Reasonably good model fit was obtained for the measurement model, i.e. χ2 = 428.87, df =

Online Synchronous Peer Feedback Practice During COVID-19 …

63

Table 4 Pattern matrix of the items loaded onto the three factors Item No.

Item

1

2

3

Communality

The peer feedback activity: 1

Makes me put in effort in learning

0.84

0.80

2

Helps me reach my learning goal

0.91

0.82

3

Helps me recognise my learning gaps

0.82

0.77

4

Indicates what actions I can take to improve in my learning

0.81

0.77

5

Reaffirms the areas that I have done well

0.85

0.73

6

Is sufficient in assisting my learning

0.91

0.76

The peer feedback activity helped me to: 7

Analyse my own work and that of others

0.87

0.75

8

Learn to appreciate the effort and dedication needed to complete a task

0.80

0.73

9

Identify my weaknesses and mistakes

0.90

0.79

10

Learn from my mistakes

0.90

0.82

11

Learn to help others to improve

0.90

0.75

12

I use the peer feedback to improve my learning

0.64

0.70

13

I do spend time to think about the peer feedback to improve my learning

0.72

0.69

14

I use the peer feedback because I have chosen to, not because I am told to do so

1.00

0.51

Eigenvalue Explained total variance (%)

9.17

1.20

0.71

–

65.50

74.10

79.17

–

Note 1—Factor 1; 2—Factor 2; 3—Factor 3

74, p < 0.001, CFI = 0.972, TLI = 0.965, SRMR = 0.023, RMSEA = 0.071, 90% CI [0.064, 0.077]. In addition, all items loaded significantly with their associated constructs. Their high standardised regression weights of varying magnitude from 0.820 to 0.920 were indicative of strong relationships (at least 0.5 recommended by Hair et al. [1998]) of the manifest variables with their related latent variables.

Structural Model The structural equation model is illustrated in Fig. 3. It also showcases the significant standardised regression path coefficients and error coefficients. In particular, the following fit indices: χ2 = 531.79, df = 75, p < 0.001, CFI = 0.963, TLI = 0.956, SRMR = 0.042, RMSEA = 0.080, 90% CI [0.073, 0.086] were obtained for this model. Hence, reasonably good model fit was obtained for the structural model.

64

B. K. Song

Fig. 3 Structural equation model with standardised factor loadings, significant standardised regression path coefficients and error coefficients

The coefficients of determination, R2 , of the endogenous latent variable, namely SR and UF, were 0.622 and 0.726, respectively, which implies that the model explained 62.2% and 72.6% of these latent variables. More precisely, PV accounted for 78.9% of the variance in SR. Henceforth, the model is able to provide great amount of information relating to these constructs.

Mediation Analysis In the model, self-regulated learning (SRL) served as a mediating variable between perceived value of feedback (PV) and uptake of feedback (UF). Drawing upon 5000 bootstrapping samples, the following mediation analysis result was obtained: only the specific indirect effect (0.672) with 95% CI [0.609, 0.735] of the relationship from PV to UF was significant. In other words, there was no significant direct effect from PV to UF. Hence, it is evident that a complementary full mediation of perceived value of feedback and uptake of feedback has occurred. This suggests that self-regulated learning is the main academic catalyst in propelling learners to uptake their feedback after they perceived the feedback as valuable for their learning.

Discussion RQ1: What are the perceptions of learners, i.e. value of feedback (PV), selfregulating learning (SRL) and uptake of feedback (UF) within online peer feedback context?

Online Synchronous Peer Feedback Practice During COVID-19 …

65

The analysis of the descriptive statistics revealed that learners had good endorsements relating to their perceived value of peer feedback, their experiences with selfregulated learning processes as well as their subsequent action on feedback. In particular, the online peer feedback activity assisted learners greatly in (1) analysing their own work as well as the work of their peers; (2) identifying their strengths and weaknesses; (3) reflecting on their mistakes committed and (4) helping their peers to improve on their work. Interestingly, for the learners, the decision to act on their peers’ feedback appeared to have been derived from the instruction of the learners’ lecturers rather than on their own accord. This was inferred from the below 4.0 rating for item 14, i.e. I use the peer feedback because I have chosen to, not because I am told to do so. Since lecturers also assessed learners’ collaborative learning efforts during the lessons, it might not surprising that learners were inclined to act on the feedback to enhance their collaborative learning scores. In its entirety, learners perceived feedback provided by their peers in a positive light and greatly valued the provided comments in enhancing their work. In addition, despite learning in online peer feedback environments, learners were perceived to be practising monitoring, regulating and adapting in their learning processes to a large extent. More importantly, the relatively high endorsement of learners’ application of peer feedback to improve work (i.e. feedback uptake) indicates learners’ engagement to take action to minimise the rift between current learning status and the desired outcomes. RQ2: To what extent does learners’ self-regulated learning (SRL) mediate their perceived value of feedback (PV) and uptake of feedback (UF) within online peer feedback context? What is notable in the mediation analysis is that SRL functions as a crucial academic catalyst in propelling learners to act on their feedback. The full mediation indirect effect of SRL suggests that it explains fully the relationship between learners’ perceived value of feedback and their feedback uptake. Consequently, this implies that without the monitoring and regulating aspect of learning, learners may not be inclined to act on feedback despite acknowledging the value of feedback. Moreover, the significant standardised regression path coefficient (0.852) between SRL and UF is indicative of the influential status of self-regulated learning on feedback uptake. In this regard, it has shown in this study that it is important to activate the self-regulatory learning ability of learners to enhance their propensity to apply the ultimate step of feedback uptake. This will likely result in learners being able to evaluate their own malleable strengths and weakness which in turn minimise their reliance on teachers’ advice (Winstone, 2017b). A major contemporary goal of education is to equip learners with the knowledge and skills for lifelong or sustainable learning (Lüftenegger et al., 2012). Motivation and self-regulation have been touted as central determinants of lifelong learning (Huie, 2014; Pintrich & de Groot, 1990; Pintrich & Zusho, 2002; Schunk, 2005; Zimmerman, 2008). Essentially, self-regulated learners are capable of learning actively and are equipped with the ability to monitor and adapt their own progresses in an autonomous fashion. From this viewpoint, self-regulation is a highly desirable skillset that can better prepare learners for their lifetime as they navigate the future world of complexity (Puustinen & Pulkkinen, 2001).

66

B. K. Song

Implications A SRL-mediated feedback uptake model—that integrates learners’ perceived value of feedback, SRL and feedback uptake within an online synchronous peer feedback context—has been established, with empirical support. Therefore, the theoretical implication of this study is the potential application and extension of this model in other pedagogical contexts (e.g. self-assessment and technology-enhanced assessment) and subject domains. For the practical implication, the survey instrument offers a convenient tool for educators to analyse and understand the perceptions of learners towards the value of feedback, self-regulated learning (SRL) and feedback uptake within an online/physical peer feedback setting. Moreover, the emergence of SRL as a powerful mediator informs curriculum developers of the need to design possible interventions to enhance learners’ SRL to improve feedback uptake. Finally, the results garnered from this study have the impact of creating awareness for both educators and learners about the interplay between perceived value of feedback, SRL and feedback uptake during peer feedback activities.

Limitations and Future Directions There are some limitations present in the current study. Firstly, this study employed cross-sectional design without explicit control of intervening variables. Hence, the causal influences of the investigated variables cannot be inferred. As a result, the inferences made from the mediation analysis will also be limited. For the results to be made more generalisable, further studies could explore the use of repeated measure experimental design in longitudinal studies. Future investigations should assess the function of the various investigated variables across at least three time points to validate the relationships established. Secondly, measures of the variables could be further enhanced by not merely focusing on collecting self-reported perception of learners. Researchers contend that self-reported data may not be reliable and have limitations as measures of SRL (Perry & Winne, 2006; Schraw, 2010). Alternative measurements from other sources, such as lecturers’ observation or evaluation of learners’ self-regulated learning processes, could be incorporated to enhance reliability. Thirdly, more research is required on the pedagogical aspect of peer feedback. For future studies, this research could be replicated in the usual face-to-face lesson setting to assess for potential differences in the findings. Also, the study could be performed on modules of different discipline contexts and academic years. Lastly, for a more comprehensive understanding of the reasons exhibited by the responses of learners in the survey, an explanatory sequential mixed design method may be utilised in which the qualitative findings would be used to explain the trends and relationships demonstrated from the analysed quantitative results.

Online Synchronous Peer Feedback Practice During COVID-19 …

67

Conclusion In this study, the result findings revealed that SRL fully mediates learners’ feedback uptake to improve current work from their perception of the value of feedback. This suggests that albeit a positive endorsement of the value of feedback, learners are not likely to act on feedback received unless SRL has been triggered. In particular, this chapter has contributed to the body of research on online peer feedback practices by validating a model of feedback uptake mediated by SRL. Curriculum could also be better designed to target the characteristics of SRL in peer feedback contexts that need beefing up or require further developments.

References Ajjawi, R., & Boud, D. (2017). Researching feedback dialogue: An interactional analysis approach. Assessment & Evaluation in Higher Education, 42(2), 252–265. https://doi.org/10.1080/026 02938.2015.1102863 Askew, S., & Lodge, C. (2000). Gifts, ping-pong and loops—Linking feedback and learning. In S. Askew (Ed.), Feedback for learning (pp. 1–17). Routledge. Atkinson, J. W. (1957). Motivational determinants of risk-taking behavior. Psychological Review, 64(6), 359. https://doi.org/10.1037/h0043445 Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52(1), 1–26. https://doi.org/10.1146/annurev.psych.52.1.1 Baron, R. A. (1993). Criticism (informal negative feedback) as a source of perceived unfairness in organizations: Effects, mechanisms, and countermeasures. In Justice in the workplace: Approaching fairness in human resource management (pp. 155–170). Lawrence Erlbaum. Boud, D., & Molloy, E. (2013). Rethinking models of feedback for learning: The challenge of design. Assessment & Evaluation in Higher Education, 38(6), 698–712. https://doi.org/10.1080/ 02602938.2012.691462 Brett, J. F., & Atwater, L. E. (2001). 360° feedback: Accuracy, reactions, and perceptions of usefulness. Journal of Applied Psychology, 86(5), 930–942. https://doi.org/10.1037/0021-9010.86. 5.930 Brookhart, S. M. (2017). How to give effective feedback to your students (2nd ed.). Association for Supervision and Curriculum Development. Butler, D. L., & Winne, P. H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65(3), 245–281. https://doi.org/10.3102/00346543065003245 Byrne, B. M. (2012). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Routledge. Carless, D. (2019). Feedback loops and the longer-term: Towards feedback spirals. Assessment & Evaluation in Higher Education, 44(5), 705–714. https://doi.org/10.1080/02602938.2018.153 1108 Carless, D., & Boud, D. (2018). The development of student feedback literacy: Enabling uptake of feedback. Assessment & Evaluation in Higher Education, 43(8), 1315–1325. https://doi.org/10. 1080/02602938.2018.1463354 Conole, G. (2008). ‘Disruptive technologies’, ‘pedagogical innovation’: What’s new? Findings from an in-depth study of students’ use and perception of technology. Computers & Education, 50(2), 511–524. https://doi.org/10.1016/j.compedu.2007.09.009

68

B. K. Song

Crisp, B. R. (2007). Is it worth the effort? How feedback influences students’ subsequent submission of assessable work. Assessment & Evaluation in Higher Education, 32(5), 571–581. https://doi. org/10.1080/02602930601116912 Cristobal, E., Flavián, C., & Guinalíu, M. (2007). Perceived e-service quality (PeSQ): Measurement validation and effects on consumer satisfaction and web site loyalty. Managing Service Quality: An International Journal, 17(3), 317–340. https://doi.org/10.1108/09604520710744326 Dancey, C. P., & Reidy, J. (2017). Statistics without maths for psychology (6th ed.). Pearson. Daniel, S. J. (2020). Education and the COVID-19 pandemic. Prospects, 49(1–2), 91–96. https:// doi.org/10.1007/s11125-020-09464-3 Dawson, P., Henderson, M., Ryan, T., Mahoney, P., Boud, D., Phillips, M., & Molloy, E. (2018). Technology and feedback design. In M. J. Spector, B. B. Lockee, & M. D. Childress (Eds.), Learning, design, and technology: An international compendium of theory, research, practice, and policy (pp. 1–45). Springer. https://doi.org/10.1007/978-3-319-17727-4_124-1 Donia, M. B. L., Mach, M., O’Neill, T. A., & Brutus, S. (2021). Student satisfaction with use of an online peer feedback system. Assessment & Evaluation in Higher Education, 47, 269–283. https://doi.org/10.1080/02602938.2021.1912286 Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53(1), 109. https://doi.org/10.1146/annurev.psych.53.100901.135153 Evans, C. (2013). Making sense of assessment feedback in higher education. Review of Educational Research, 83(1), 70–120. https://doi.org/10.3102/0034654312474350 Fernández-Toro, M., & Duensing, A. (2020). Repositioning peer marking for feedback literacy in higher education. Assessment & Evaluation in Higher Education, 46, 1202–1220. https://doi. org/10.1080/02602938.2020.1863911 Filius, R. M. (2018). Strengthening dialogic peer feedback aiming for deep learning in SPOCs. Computers & Education, 125, 86–100. https://doi.org/10.1016/j.compedu.2018.06.004 Gikandi, J. W., & Morrow, D. (2016). Designing and implementing peer formative feedback within online learning environments. Technology, Pedagogy & Education, 25(2), 153–170. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (Vol. 5). Prentice Hall. Hancock, G. R., & Mueller, R. O. (2013). Structural equation modeling: A second course (2nd ed.). Information Age Publishing, Incorporated. Harks, B. (2014). The effects of feedback on achievement, interest and self-evaluation: The role of feedback’s perceived usefulness. Educational Psychology, 34(3), 269–290. https://doi.org/10. 1080/01443410.2013.785384 Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487 Henderson, M., Ryan, T., & Phillips, M. (2019). The challenges of feedback in higher education. Assessment & Evaluation in Higher Education, 44(8), 1237–1252. https://doi.org/10.1080/026 02938.2019.1599815 Hoo, H.-T., Tan, K., & Deneen, C. (2020). Negotiating self- and peer-feedback with the use of reflective journals: An analysis of undergraduates’ engagement with feedback. Assessment & Evaluation in Higher Education, 45(3), 431–446. https://doi.org/10.1080/02602938.2019.166 5166 Huie, F. C. (2014). Employment and first-year college achievement: The role of self-regulation and motivation. Journal of Education & Work, 27(1), 110–135. https://doi.org/10.1080/13639080. 2012.718746 Hu, L.-t, & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118 Ibarra-Sáiz, M. S., Rodríguez-Gómez, G., & Boud, D. (2020). Developing student competence through peer assessment: The role of feedback, self-regulation and evaluative judgement. Higher Education, 80(1), 137–156. https://doi.org/10.1007/s10734-019-00469-2

Online Synchronous Peer Feedback Practice During COVID-19 …

69

Jansen, R. S., van Leeuwen, A., Janssen, J., Jak, S., & Kester, L. (2019). Self-regulated learning partially mediates the effect of self-regulated learning interventions on achievement in higher education: A meta-analysis. Educational Research Review, 28, 100292. https://doi.org/10.1016/ j.edurev.2019.100292 Järvelä, S., Järvenoja, H., Malmberg, J., Isohätälä, J., & Sobocinski, M. (2016). How do types of interaction and phases of self-regulated learning set a stage for collaborative engagement? Learning & Instruction, 43, 39–51. https://doi.org/10.1016/j.learninstruc.2016.01.005 Linderbaum, B. A., & Levy, P. E. (2010). The development and validation of the Feedback Orientation Scale (FOS). Journal of Management, 36(6), 1372. https://doi.org/10.1177/014920631037 3145 Lipnevich, A. A., Berg, D. A., & Smith, J. K. (2016). Toward a model of student response to feedback. In Handbook of human & social conditions in assessment (pp. 169–185). Routledge. Liu, N.-F., & Carless, D. (2006). Peer feedback: The learning element of peer assessment. Teaching in Higher Education, 11(3), 279–290. https://doi.org/10.1080/13562510600680582 Lüftenegger, M., Schober, B., van de Schoot, R., Wagner, P., Finsterwald, M., & Spiel, C. (2012). Lifelong learning as a goal—Do autonomy and self-regulation in school result in well prepared pupils? Learning & Instruction, 22(1), 27–36. https://doi.org/10.1016/j.learninstruc. 2011.06.001 McCaslin, M., & Hickey, D. T. (2001). Educational psychology, social constructivism, and educational practice: A case of emergent identity. Educational Psychologist, 36(2), 133–140. https:// doi.org/10.1207/S15326985EP3602_8 Mercader, C., Ion, G., & Díaz-Vicario, A. (2020). Factors influencing students’ peer feedback uptake: Instructional design matters. Assessment & Evaluation in Higher Education, 45(8), 1169–1180. https://doi.org/10.1080/02602938.2020.1726283 Muthén, L. K., & Muthén, B. O. (1998–2017). Mplus user’s guide (8th ed.). Muthén & Muthén. Nicol, D. J. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199–218. https://doi.org/10.1080/ 03075070600572090 Nicol, D. J. (2010). From monologue to dialogue: Improving written feedback processes in mass higher education. Assessment & Evaluation in Higher Education, 35(5), 501. https://doi.org/10. 1080/02602931003786559 Nicol, D., Thomson, A., & Breslin, C. (2014). Rethinking feedback practices in higher education: A peer review perspective, Assessment & Evaluation in Higher Education, 39(1), 102–122, https:// doi.org/10.1080/02602938.2013.795518 ONeill, T. A., Boyce, M., & McLarnon, M. J. W. (2020). Team health and project quality are improved when peer evaluation scores affect grades on team projects. Frontiers in Education, 5, 49. https://doi.org/10.3389/feduc.2020.00049 Palloff, R. M. (2007). Building online learning communities: Effective strategies for the virtual classroom (2nd ed.). Jossey-Bass. Panadero, E., Jonsson, A., & Botella, J. (2017). Effects of self-assessment on self-regulated learning and self-efficacy: Four meta-analyses. Educational Research Review, 22, 74–98. https://doi.org/ 10.1016/j.edurev.2017.08.004 Perry, N. E., & Winne, P. (2006). Learning from learning kits: gStudy traces of students’ selfregulated engagements with computerized content. Educational Psychology Review, 18(3), 211– 228. https://doi.org/10.1007/s10648-006-9014-3 Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16(4), 385. https://doi.org/10.1007/s10 648-004-0006-x Pintrich, P. R., & de Groot, E. V. (1990). Motivational and self-regulated learning components of classroom academic performance. Journal of Educational Psychology, 82(1), 33–40. https:// doi.org/10.1037/0022-0663.82.1.33

70

B. K. Song

Pintrich, P. R., & Zusho, A. (2002). Student motivation and self-regulated learning in the college classroom. In J. C. Smart & W. G. Tierney (Eds.), Higher education: Handbook of theory and research (pp. 55–128). Springer. https://doi.org/10.1007/978-94-010-0245-5_2 Pitt, E., & Norton, L. (2017). ‘Now that’s the feedback I want!’ Students’ reactions to feedback on graded work and what they do with it. Assessment & Evaluation in Higher Education, 42(4), 499–516. https://doi.org/10.1080/02602938.2016.1142500 Price, M., Handley, K., & Millar, J. (2011). Feedback: Focusing attention on engagement. Studies in Higher Education, 36(8), 879–896. https://doi.org/10.1080/03075079.2010.483513 Puustinen, M., & Pulkkinen, L. (2001). Models of self-regulated learning: A review. Scandinavian Journal of Educational Research, 45(3), 269–286. https://doi.org/10.1080/00313830120074206 Rakoczy, K. (2019). Formative assessment in mathematics: Mediated by feedback’s perceived usefulness and students’ self-efficacy. Learning & Instruction, 60, 154–165. https://doi.org/10. 1016/j.learninstruc.2018.01.004 Ramaprasad, A. (1983). On the definition of feedback. Behavioral Science, 28(1), 4–13. https://doi. org/10.1002/bs.3830280103 Reddy, K., Harland, T., Wass, R., & Wald, N. (2021). Student peer review as a process of knowledge creation through dialogue. Higher Education Research & Development, 40(4), 825–837. https:// doi.org/10.1080/07294360.2020.1781797 Reeve, J., & Tseng, C.-M. (2011). Agency as a fourth aspect of students’ engagement during learning activities. Contemporary Educational Psychology, 36(4), 257–267. https://doi.org/10. 1016/j.cedpsych.2011.05.002 Roman, T. A., Callison, M., Myers, R. D., & Berry, A. H. (2020). Facilitating authentic learning experiences in distance education: Embedding research-based practices into an online peer feedback tool. TechTrends, 64(4), 591–605. https://doi.org/10.1007/s11528-020-00496-2 Roscoe, R. D. (2008). Tutor learning: The role of explaining and responding to questions. Instructional Science, 36(4), 321–350. https://doi.org/10.1007/s11251-007-9034-5 Sadler, D. R. (1989). Formative assessment and the design of instructional systems. Instructional Science, 18(2), 119–144. Sadler, D. R. (2010). Beyond feedback: Developing student capability in complex appraisal. Assessment & Evaluation in Higher Education, 35(5), 535–550. https://doi.org/10.1080/026029309 03541015 Schraw, G. (2010). Measuring self-regulation in computer-based learning environments. Educational Psychologist, 45(4), 258–266. https://doi.org/10.1080/00461520.2010.515936 Schunk, D. H. (2005). Commentary on self-regulation in school contexts. Learning & Instruction, 15(2), 173–177. https://doi.org/10.1016/j.learninstruc.2005.04.013 Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153–189. https://doi.org/10.3102/0034654307313795 Sopher, D. S. (2020). A-priori sample size calculator for structural equation models (Software). https://www.danielsoper.com/statcalc Topping, K. (1998). Peer assessment between students in colleges and universities. Review of Educational Research, 68(3), 249–276. https://doi.org/10.3102/00346543068003249 van der Pol, J. (2008). The nature, reception, and use of online peer feedback in higher education. Computers & Education, 51(4), 1804–1817. https://doi.org/10.1016/j.compedu.2008.06.001 Van Gennip, A. (2012). Assessing together: Peer assessment from an interpersonal perspective (Doctoral Dissertation). Leiden University. West, S. G., Finch, J. F., & Curran, P. J. (1995). Structural equation models with nonnormal variables: Problems and remedies. In R. Hoyle (Ed.), Structural equation modeling: Issues, concepts, and applications (pp. 56–75). Sage. Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68. https://doi.org/10.1006/ceps.1999.1015 Winstone, N. E. (2017a). ‘It’d be useful, but I wouldn’t use it’: Barriers to university students’ feedback seeking and recipience. Studies in Higher Education, 42(11), 2026–2041. https://doi. org/10.1080/03075079.2015.1130032

Online Synchronous Peer Feedback Practice During COVID-19 …

71

Winstone, N. E. (2017b). Supporting learners’ agentic engagement with feedback: A systematic review and a taxonomy of recipience processes. Educational Psychologist, 52(1), 17–37. https:// doi.org/10.1080/00461520.2016.1207538 Winstone, N. E., Mathlin, G., & Nash, R. A. (2019). Building feedback literacy: Students’ perceptions of the developing engagement with feedback toolkit. Frontiers in Education, 4(39). https:// doi.org/10.3389/feduc.2019.00039 Yang, M. (2013). The feedback triangle and the enhancement of dialogic feedback processes. Teaching in Higher Education, 18(3), 285–297. https://doi.org/10.1080/13562517.2012.719154 Yates, A., Starkey, L., Egerton, B., & Flueggen, F. (2021). High school students’ experience of online learning during Covid-19: The influence of technology and pedagogy. Technology, Pedagogy & Education, 30(1), 59–73. https://doi.org/10.1080/1475939X.2020.1854337 Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13–39). Academic Press. https://doi.org/10.1016/B978-012109890-2/50031-7 Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166–183. https://doi.org/10.3102/0002831207312909 Zimmerman, B. J., & Schunk, D. H. (2013). Reflections on theories of self-regulated learning and academic achievement. In B. Zimmerman & D. Schunk (Eds.), Self-regulated learning and academic achievement: Theoretical perspectives (pp. 282–301). Routledge.

Does Online Coaching Support Training Transfer? Coaches’ Perceptions of Early-Career Teachers’ Implementation of Self-Regulation Strategies in the Context of a Professional Development Programme Christine Bieri Buschor , Zippora Bührer , Andrea Keck Frei , Simone Berweger , and Christine Wolfgramm Abstract The aim of this study is to analyse 15 coaches’ perceptions of an online coaching (OC) process designed to support early-career teachers’ transfer of selfregulation strategies in the context of a professional development (PD) programme. The coaches supported 49 primary school teachers working with professional OC software during a 5-month period. We used content analysis to analyse the interviews with the coaches after completion of the OC. Based on the coachees’ development level, coaches rated the OC as effective with reference to goal commitment, pursuit, attainment, coping with challenges, and reflection. Physical distance correlated with a disinhibiting effect, a collaborative and playful approach to using various tools, including the handover of responsibility for the process, increasing objectivation, and a focus on goals rather than emotion. In addition, a lack of nonverbal cues was observed that contrasted with the high level of language awareness. Reflecting on their new role, coaches showed different attitudes towards OC. The role of coaching and goal orientation in teacher education are discussed. Keywords Online coaching · Effectiveness · Early-career teachers’ self-regulation · Training transfer · Professional development

C. Bieri Buschor (B) · Z. Bührer · A. Keck Frei · S. Berweger · C. Wolfgramm Zurich University of Teacher Education, Zurich, Switzerland e-mail: [email protected] Z. Bührer e-mail: [email protected] A. Keck Frei e-mail: [email protected] S. Berweger e-mail: [email protected] C. Wolfgramm e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Y. L. Chye and B. L. Chua (eds.), Pedagogy and Psychology in Digital Education, https://doi.org/10.1007/978-981-99-2107-2_4

73

74

C. Bieri Buschor et al.

Introduction Professional development (PD) is a crucial aspect of early-career teachers’ further learning and retention (Darling-Hammond et al., 2017). Online formats in particular have a high potential to reach teachers around the world (Dede et al., 2009) and experience with online technologies is even more effective when it is personalized and job-embedded (Powell & Bodur, 2019). Recently, web-based virtual teacher coaching has been discussed as a way to address the need for high-quality coaching and individual feedback (Kraft et al., 2018). Online coaching (OC) can be defined as a PD intervention based on a reflective, goal-oriented relationship using technology (Berninger-Schaefer, 2018; Grant, 2014). In contrast to top-down programmes, this approach addresses teachers’ individual needs and strengthens their ownership. In this view of PD, effectiveness refers to teachers’ own perceptions of their needs, self-regulated learning, goals, reflection, interaction, and beneficial transfer to the teaching practice (Darling-Hammond et al., 2017; Powell & Bodur, 2019; Ross, 2011). The effect of coaches’ interventions on the coaching outcome can be evaluated either through the coachees’ perspective (Osatuke et al., 2017; Smither, 2011) or through coaches’ assessment of the entire coaching process (Vandaveer et al., 2016). However, assessment of (online) coaching processes is still scarce (Kraft et al., 2018; Vandaveer et al., 2016). The aim of the present study is to contribute to filling this gap. It focuses on coaches’ perception of online coaching to support early-career teachers’ transfer of self-regulation strategies in the context of a research-based PD programme.

Professional Development to Enhance Teachers’ Self-Regulation Professional development is related to learning processes. These comprise thoughts, feelings, ideas, inspirations, and goals which lead to changes in practitioners’ practices and reflection (Kelchtermans, 2004; Korthagen, 2017). Current approaches place great importance on the sustainability and effectiveness of PD programmes. It is understandable that the effect of such programmes fades over time when teachers return to their daily routine. Therefore, the question arises of how long the effect lasts and how it can be improved (Liu & Phelps, 2019; Sancar et al., 2021). Studies from the field of induction and retention programmes for early-career teachers emphasize the high significance of sustainable PD programmes to strengthen teachers’ selfregulation and goal orientation through social support and professional coaching (Darling-Hammond et al., 2017; Keller-Schneider & Hericks, 2014). The concept of self-regulation has been adapted to teachers’ own learning activities and strategies (Vermunt & Endedijk, 2011). It refers to the ability to control one’s own cognition, motivation, emotion, and behaviour in the pursuit of short- or long-term goals. The process includes (1) goal orientation, goal setting, and assessing self-efficacy related

Does Online Coaching Support Training Transfer? …

75

to planning and goal pursuit before a task, (2) monitoring goal pursuit and attainment by controlling learning strategies and results while performing the task, and (3) reflection, evaluation of the learning experience, and drawing consequences for further learning (Pintrich, 2000; Zimmerman, 2000, 2006). Goal pursuit is one of the most important self-regulation strategies of teachers’ learning (Vermunt & Endedijk, 2011). It leads to a positive attitude towards professional development as it is related to self-efficacy, interest in teaching activities, reflection, and beneficial perception of help in seeking to solve problems at the workplace (Nitsche et al., 2013). In the context of motivational and cognitive goal theories, goal pursuit incorporates (1) goal setting and commitment, (2) goal striving, and (3) monitoring of goal attainment. Self-regulation techniques referring to mental contrasting and implementation intentions have been shown to foster effective goal pursuit and behaviour change in many domains. Mental contrasting activates a process in which individuals realize that action is necessary to overcome possible obstacles to reaching their goal (Oettingen & Gollwitzer, 2001; Oettingen et al., 2015). Professional coaching further strengthens goal implementation and reflection on the process (Brandstätter et al., 2001, 2013).

Online Professional Development and Coaching Online courses, workshops, and modules delivered in an online format have been increasingly used to provide flexible, wide-scale, and personalized learning opportunities. However, there is a lack of a research-based framework related to their efficiency and efficacy, despite various guidelines for quality teaching (Powell & Bodur, 2019). Over the past decade, video resources for teacher PD in all subjects have increased, supporting reflection on teaching and instructional best practices (Christ et al., 2017; Gaudin & Chaliès, 2015). Features such as relevancy, authenticity, and usefulness related to personal needs and reflection are linked to teachers’ positive perceptions of job-embedded online PD (Powell & Bodur, 2019). Parsons et al. (2019) illustrate that one of the most beneficial aspects of participating in wide-scale online PD is teachers’ ability to work at their own pace. However, their willingness to receive feedback seems to be low, due to the anonymity of the process. Recently, teacher coaching and mentoring have become more prominent in teacher education (Führer & Cramer, 2020; Kraft et al., 2018; Orland-Barak, 2016). Whereas mentoring relationships are long-term, providing guidance on career development from an experienced mentor to an inexperienced mentee (Eby et al., 2013), the coaching relationship is characterized by specific objectives comprising 3 core elements: (1) formation and maintenance of a helping relationship, (2) a defined contract setting personal development goals, and (3) pursuing goals and achieving objectives through a development process by providing tools, skills, opportunities, and reflection (Smither, 2011). Even though mentoring and coaching are different concepts, there is a high amount of overlap (e.g. goal orientation, methods). In a meta-analysis, Jones et al. (2016) found that online coaching was as effective as face-to-face coaching, and that the number of sessions or longevity had no impact

76

C. Bieri Buschor et al.

on the outcome. (Online) coaching has a positive effect on workplace learning and self-regulation. Grant (2014) showed that a goal-focused relationship was a predictor of coaching success, whereas satisfaction with the relationship was not significant. Noh and Kim (2019) illustrated that OC improved the acquisition of self-directed learning competences and implementation of associated practices among nursing students. In the clinical context, the beneficial aspects of OC and a combination of face-to-face coaching with OC have been discussed. Even though coaches tend to be more sceptical about OC than clients, they emphasize the advantage of the low threshold to access, which enables them to intervene in critical situations (e.g. Anthony, 2015; Barak et al., 2008; Wong et al., 2018). Similarly, OC in the format of weblogs has been found beneficial to support student teachers’ reflection (Petko et al., 2015; Wopereis et al., 2010). Teachers value OC due to the location-independent, temporally flexible, and low-threshold approach (Keck Frei et al., 2020).

Assessing (Online) Coaching Outcomes Coaching and mentoring contribute to the increase in teachers’ professional knowledge, reflective skills, and the associated reflective activities on a meta-level (Führer & Cramer, 2020). As theoretical concepts and assessment of coaching outcomes in teacher education are still scarce, we consider studies from the clinical and executive coaching context which present different frameworks for assessing the effectiveness of coaching. Jones et al. (2016), for instance, suggest that a systematic framework of cognitive, affective, and competence-based outcome criteria should be used. In contrast, Theeboom et al. (2013) propose a model based on participants’ perceptions (bottom-up criteria), such as goal-directed self-regulation, competences, well-being, coping, and work attitude. Osatuke et al. (2017) present an assimilation model based on psychotherapy and counselling research to evaluate coaching effectiveness. This model focuses on tracking clients’ developmental level and coping success as they experience and describe their needs and solve the problems they bring to coaching sessions. It aims at assessing coaching effectiveness with reference to clients’ needs, self-perception of goal attainment, reflection, and self-awareness. The model further balances the dynamic nature of coaching with the demands of objective programme evaluation using an empirically grounded taxonomy for describing clients’ stances towards their concerns. Vandaveer et al. (2016) introduced an empirically founded and competence-based model, rooted in organizational psychology, to define critical success and coaching failure factors along different steps in the process. From this perspective, coaching effectiveness is assessed by experienced coaches using the following success factors: (1) coaching quality in terms of personal effectiveness, (2) quality of the coaching relationship, and (3) coachee readiness related to motivation, willingness to learn, and openness to feedback. Failure factors refer to the lack of coachees’ motivation and commitment, and overinvestment in what the coach wants. Richards and Vigano (2013) emphasize the new role of coaches in OC. They suggest that coaches assess the outcomes related to empirically based coaching

Does Online Coaching Support Training Transfer? …

77

criteria, such as self-disclosure (disinhibition), convenience, time-delay, loss of cues, positive effect of writing (self-awareness), attitudes, and experiences. However, even though the role of the coaches is still unclear, it can be assumed that they differ in their effectiveness (Blazar & Kraft, 2015; Bozer & Jones, 2018; Kraft et al., 2018).

The Present Study The study is part of a larger research project at the Zurich University of Teacher Education in Switzerland, funded by the Swiss National Science Foundation (Keck Frei et al., 2020). The research design is an intervention study consisting of training at the university and subsequent OC. The context is an annual 3-week PD programme comprising content-focused pedagogical courses, workshops, action research projects, etc. for early-career teachers. For our study, we developed a research-based self-management training course (3 × 4 h over 3 weeks within the PD programme, see Bieri Buschor et al., 2022) based on other programmes (e.g. Schaarschmidt & Fischer, 2013) and the concept of mental contrasting and implementation with the intention of fostering goal pursuit (Oettingen & Gollwitzer, 2001). The aim was to enhance teachers’ self-regulation, supporting them in transferring the acquired strategies to the workplace in a subsequent 5-month OC programme. At the end of the training, teachers set personal goals (e.g. self-regulation related to time-management, classroom management, and coping with difficult situations, etc.) in terms of an action plan (steps with reference to goal striving, anticipated goal attainment, and support). The focus of this article is on coaches’ perspectives on OC during the training transfer. The research questions were as follows: 1. What are coaches’ perceptions of and reflections on their experience with OC? 2. How do these perceptions and reflections refer to aspects of OC effectiveness?

Method Evaluation of transfer is challenging due to its processual nature (Baldwin et al., 2017). In addition, coaching as such is fluid and aims to empower coachees to take charge of their own development. These features make quantitative evaluation design impractical (Osatuke et al., 2017). We, therefore, chose a qualitative approach.

Participants In the context of our intervention study, which commenced in January 2018, 49 earlycareer teachers were supported by 15 coaches (11 female, 4 male) in a subsequent

78

C. Bieri Buschor et al.

5-month OC transfer phase. The coaches also served as trainers during the selfmanagement training to enable them to establish a relationship with the teachers. The majority (N = 13) worked as lecturers and counsellors in the department of continuing education (8) and/or the departments of primary or secondary education (5) at our university; 2 female coaches worked at other Swiss universities of teacher education. All coaches (aged 46–63) had a background in teaching, further studies in educational sciences, a Master’s degree in coaching/counselling, and between 9 and 20 years of experience in counselling and coaching teachers. None had previous experience in OC. The sample of teachers was as follows: 72 out of 150 early-career teachers participated in the self-management training and were randomly assigned to the OC group. The original sample comprised 145 women (97%) and 5 men working as primary school teachers. The majority (83%) had 3 or more years of experience and worked 80–100%. Their average age was 28 years (SD = 5.54; range = 23–52). Overall, 49 early-career teachers participated in the OC. These participants attended 3–4 online coaching sessions (N = 36), 2 sessions (7), or just one session (6). 23 of the 72 did not participate in the OC. The majority were not willing to participate because they already had coaching at the workplace or perceived it as a burden; others had left their position or were on maternity leave.

Training the Coaches The aim was to “train the trainers” in the field of OC, basing the work on the theoretical context. We emphasized teachers’ self-regulation (strategies), methods from the field of (peer-) coaching, and the process of goal pursuit (Oettingen & Gollwitzer, 2001). The teachers’ action plan was an important part of the contract. Coaches attended a one-day training course, provided by two e-coaching professionals, to learn to use the OC software cai-world (www.cai-world.com) efficiently. The software provides professional coaching methods, such as system drawings and pictures, reflection tools, chat, protocol, logging of the process, as well as an online diary. During the past decade, it has been efficiently used in various domains in German-speaking countries (Berninger-Schaefer, 2018). Coaches were instructed by the researchers firstly to refer to the teachers’ action plan in the coaching sessions. The sessions also provided space for teachers’ current teaching-related concerns. Coaching interventions are dynamic in nature, which enables coachees to collaboratively choose areas of development with the coach (Osatuke et al., 2017). The core idea was to move from a rather structured coaching framework, based on the transfer of self-regulation strategies, to a more learner-centred approach, focusing on teachers’ needs.

Does Online Coaching Support Training Transfer? …

79

Data Collection We conducted semi-structured interviews with the coaches in 3 groups one month after completion of the OC phase in July 2018. The first part of the interview comprised an open-ended question related to their experience. The second part was more structured, incorporating questions related to the entire coaching process, transfer, the comparison between online and face-to-face coaching, and the coaching software.

Data Analysis The interviews were transcribed and evaluated using a content-analytical method (Mayring, 2015) by 3 researchers working as an interpretational group to enhance validity. We used the software MAXQDA (Version 20) to code the data and included inductive as well as deductive strategies. The open question at the beginning of the interview allowed us to use an inductive approach. For the structured part of the interviews, we used a deductive strategy with reference to the interview questions.

Results The results related to the open question at the beginning of the interview show that the coaches’ experience mainly relates to topics covered and discussed during the OC and the evaluation of the process (Table 1, categories 1–3). Their answers to the more narrowly focused questions refer to the handling of the coaching software, physical distance relationship, and general differences between face-to-face coaching and OC (Table 1, categories 4–6).

Topics Covered and Discussed During the Online Coaching Process The topics covered and discussed during the OC are related to teachers’ goal implementation and current issues. Teachers’ precise formulation of the goals in the action plan and their goal commitment were important conditions for working in the online sessions. One coach said: “It went wonderfully well to refer to their self-set goals”. Some of the coaches mentioned that the coachees “even transferred self-regulation strategies to their team to enhance collaborative learning”. Furthermore, the sessions

80

C. Bieri Buschor et al.

provided space for teachers’ current issues from daily working life, such as dynamics in the classroom, dealing with pupils in difficult interactions, the school team, stress, and setting priorities. Table 1 Categories, description, and examples of coaches’ perception of the online coaching process with early-career teachers over a 5-month period Nr Codes/categories

Description

Examples

1

Topics covered and discussed The topics covered in the OC during OC sessions mainly focused on the implementation of self-regulation strategies, goals, and current issues from everyday working life

“It actually went wonderfully well to refer to their self-set goals. In addition, I always looked quickly at what the current issues were. […] Private and other professional topics were also addressed”

2

Evaluation of the entire process

The OC process was assessed as effective in maintaining teachers’ goal commitment, pursuit, and professional development

“It was mentioned by all five of my coachees that it was truly sustainable. They would have forgotten their goals and strategies if they had not had these online coaching sessions again and again. […] It helped them to recall and activate their goals, to look closely into the process and where exactly they stood”

3

Randomized allocation as a challenge

Coaches identified a link between the randomized allocation to the OC and the outcome. The challenges incorporate lack of commitment, lack of real concern, differences related to goal orientation, quality of goals and goal pursuit, and reflection

“Actually, all the coachees wanted to participate. However, I had to contact one person four times, and that person always said “yes, I will get back to you with dates for an appointment”. The other three were committed. […] Two of them achieved the goals they had set themselves in the context of the self-management training. There was no real need for action anymore, which did not make it easy for me to continue working with them” (continued)

Does Online Coaching Support Training Transfer? …

81

Table 1 (continued) Nr Codes/categories

Description

Examples

4

Handling of the OC software/tools

Coaches and coachees used the platform based on their affinity to technology. They appreciated the wide range of tools, including standard formats (e.g. video) and specific coaching tools (e.g. visualization)

“For me, this tool is a container for many things, for single puzzle pieces, inside which I can move around. And I can concentrate well when I am in this cai-world. I do not have to put everything together myself. I can just use different tools. […] I also notice that my attitude has changed. I am much more relaxed about it […]”

5

Physical distance relationship

Physical distance correlated with a disinhibiting effect, handover of responsibility, and a high objectivity, but also with a lack of nonverbal aspects and low commitment in some cases

“Somehow, there is a bit of a distance. As a coach, I can more easily address a topic because the other person is not too close. I found this very interesting and fascinating”

6

Differences between face-to-face/OC

Coaches developed a linguistic accuracy and the awareness that a shared understanding was important for goal pursuit. The process led to a form of objectivation related to time, emotion, and language

“I am much more precise concerning the language I use, and I am generally paying more attention to it. Together with the coachee, I took a closer look at whether we were really accurate. […] And I had the experience of slowing down. It is interesting that slowing down, e.g., writing, looking for some button [on the cai-world platform] is advantageous”

Evaluation of the OC Process The coaches agreed that feedback was one of the most important “drivers of the process”, and “goal commitment was beneficial for ensuring action during the transfer phase”, preventing “teachers’ neglect of goal pursuit”. Coaching effectiveness was linked to coachees’ high engagement and coaches’ support. One coach said: “They would have forgotten their goals and topics if they had not had these coaching sessions again and again”. The sessions helped them to “activate their goals” and to “reflect on where they stood in the process”. Another coach was surprised how her coachees adapted some of the self-regulation strategies and said: “They just adapted them to the school context […] the sequences from the self-management training have stuck

82

C. Bieri Buschor et al.

somehow”. The coaches illustrated how their coachees set more and more actionoriented goals and took on more responsibility throughout the process. One coach, for instance, talked about a coachee who stopped complaining about the principal, whom she perceived as passive, instead focusing on her goals, and increasingly reflecting them in action. At the same time, coaches reflected on their own coaching activities. One had this to say: I really observed my coachees’ development over time […] But I also became aware of my own development and my concerns related to my new role […] She was so goal-oriented that I had a guilty conscience because I could or, shall I say, should have supported her more. But she appreciated the meetings and was absolutely satisfied with the entire OC process.

Some coaches described the process in terms of an “intensive weaving” of different formats of support. One coach described how she had a coaching session before school started and a successful subsequent online communication: “It was amazing to observe how she reacted when students entered the classroom […], and suddenly I realized what her problem was. […]I immediately gave her feedback, and we continued in the chat”.

Randomized Allocation as a Challenge Coaches established a close link between the randomized allocation to the OC group due to the design of the study, and challenges and failure of the OC. One teacher left her position and cancelled the OC session. Other teachers said that they already had support at the workplace and therefore dropped out. Some of the coachees were critical because the coaching was not based on “voluntariness” and “real concerns or serious problems”. However, the majority of the coachees were perceived as open-minded, and deeply involved from the beginning. Some teachers, who initially showed resistance, became increasingly committed to their goal, and set further goals during the process. “At first, I thought that it was impossible to support this teacher”, said one coach. However, he felt a sense of self-efficacy when his coachee made considerable progress in goal striving and attainment. Some teachers had set their goals in a rather superficial way, achieved them quickly, and seemed to avoid feedback. As one coach illustrated: “They achieved the goals […]; there was no real need for action anymore, which did not make it easy for me”.

Handling of the OC Software and Tools Coaches emphasized the important role of their own and coachees’ openness to online tools and methods for the OC process. The coaches appreciated the easy handling of the coaching software cai-world, as well as the broad range of tools. Video, whiteboard, and chat were perceived as “standard tools”. Additional visualization

Does Online Coaching Support Training Transfer? …

83

tools, such as sociograms, system representation (drawing relationships, networks, etc.), image/photo galleries (boxes of photos, images to express emotions, thoughts, etc. related to goal pursuit, current issues, etc.), were highly appreciated and led to a “collaborative, playful approach to problem-solving”. Some teachers, however, showed little affinity for technology. In this case, coaches narrowed their support down to only a few methods and Skype sessions. Furthermore, some coaches were more sceptical than others: “I am not the type who absolutely needs more toys”, commented one coach. Overall, coaches differed in their way of using the tools. Whereas some were inspired, others reached their limits and wished to go back to face-to-face coaching when technical problems occurred.

Physical Distance Relationship One of the coaches brought up the question of whether coaching should increasingly be offered online, which triggered a heated debate among the coaches. Some perceived the disinhibiting effect as one of the most important advantages of OC. The majority agreed that coachees were more open to addressing topics and issues than in face-to-face sessions. “It was fascinating how a rather introverted teacher suddenly talked about her concern”, mentioned one coach. Another coach stated that she herself also felt more comfortable about addressing certain topics due to the distance. The coaches agreed that this insight was “fascinating” and “irritating” at the same time because they had assumed that a “good coach-coachee relationship was based on being present in the same room”. Objectivity regarding emotional aspects and the stronger focus on relevant issues and content were discussed. One coach got straight to the point: OC helps to objectify, particularly when big emotional dramas emerge […], distance has an impact on objectification. I can keep my distance as a coach, and to be honest, in some cases, I prefer having some distance. For instance, one coachee could not stop talking about biographical aspects. It was easier for me to interrupt her and go back to the question than in a face-to-face meeting. […] I think that OC supports my professional stance.

In contrast to this, some coaches missed the cues provided by nonverbal aspects. One coach talked about his own uncertainty: “I was completely unsettled because I am usually aware of the whole body”. Some of the coaches expressed their interest in coaching based on text to focus on the content and “avoid distraction in the room”. Another aspect, already mentioned above, was the change regarding responsibility, which was contrasted with the low commitment of some teachers because it was “easy to become submerged”. One coach said: “I used to be the one writing on a flip-chart, but they absolutely wanted to take over, steering their process”.

84

C. Bieri Buschor et al.

Differences Between Online and Face-To-Face Coaching In the latest sequence of the group interview, differences between OC and face-toface coaching were discussed more systematically than before. The coaches were of the opinion that distance had a positive impact on their linguistic accuracy. Generally, they became aware that they placed more importance on their language and more accurate formulations than in face-to-face sessions. One coach mentioned that she “took a closer look at whether they were really accurate” in cooperation with the coachee. Another coach referred to the chat function as a summary in terms of “a written form of active listening” supporting the OC process. Furthermore, they attached more importance to “shared understanding” related to goal pursuit. Concurrently, they perceived a “positive deceleration” due to the focus on the language and the tools they used. Some of the coaches found it easier to activate coachees and hand over responsibility in the OC process than in face-to-face settings. One coach referred to her own sense of control: “I managed to stand back and give them more space in the virtual than in the real room, which is beneficial”. One of the coaches appreciated the online diary, which enabled her “to react very flexibly to the coachees’ needs”. However, some of the coaches stated that OC did not change their practices. One of them commented: “Actually, I do not work differently than in other coaching sessions”. Even though some coaches were more open-minded towards a goal-oriented, multiple-tool approach than others, they agreed that the OC process led not only to a form of objectivation related to time, emotional aspects, and language, but also to close collaboration and shared responsibility. Finally, the shorter duration and lower costs compared to face-to-face meetings were briefly mentioned.

Discussion Our study shows that coaches’ perceptions of their experiences with online coaching (research question 1) are related to effectiveness in general and to early-career teachers’ transfer of self-regulation strategies to their teaching practice. In addition, the coaches’ experiences were linked to their own professional role and identity. They referred to dimensions of effectiveness in different ways (research question 2) emphasizing various challenges of OC in contrast to face-to-face coaching. The coaches showed different attitudes towards technology-based learning environments, ranging from scepticism to inspiration and deep reflection. These individual differences have also been mentioned in other studies (Kraft et al., 2018; Richards & Vigano, 2013). The analysis of the interviews with the coaches revealed the following 6 core categories: (1) topics covered/discussed during the OC sessions, (2) process evaluation, (3) randomized allocation, (4) OC software/tools, (5) physical distance, and (6) comparison of face-to-face/online coaching. As studies on teacher coaching are

Does Online Coaching Support Training Transfer? …

85

still scarce, we discuss the results further in the context of approaches from different domains (Kraft et al., 2018; Vandaveer et al., 2016). Topic/process evaluation: the coaches perceived the OC to support teachers’ transfer as a process with different levels of effectiveness. In their view, early-career teachers’ implementation of self-regulation strategies and goals was successful. They attributed the coaching outcome to teachers’ engagement, but also to their own feedback, various forms of support and interventions, and the activation of goal pursuit that they provided during the process. Overall, coaches perceived a relatively high OC effectiveness based on their observations of coachees’ development level. The coachees’ development was assessed in relation to factors such as increasing goal orientation (e.g. setting increasingly clear goals), coping with issues at the workplace, self-reflection, and awareness. This is comparable with the approach proposed by Osatuke et al. (2017). This model evaluates coaching effectiveness in terms of coaches’ description of clients’ developmental level and how they cope with challenges. Interestingly, coaches referred to coachees’ development while reflecting on their own development in the online learning environment. They concluded that the coaching outcome was not dependent on the number and duration of the sessions, which is consistent with the findings of Jones et al. (2016), who found that OC was as effective as face-to-face coaching, and the number of sessions or longevity had no impact on the outcome. Some of the coaches even held the opinion that short OC sessions had a higher quality than long face-to-face meetings due to factors such as flexibility, accurate language, and strong focus on the content. These factors have also been mentioned in studies comparing face-to-face and online coaching (e.g. Richards & Vigano, 2013). One of the most important findings is the crucial role of coaches’ feedback, which, according to other studies, has a strong impact on the effectiveness and sustainability of PD programmes (Liu & Phelps, 2019; Sancar et al., 2021). In our study, coaches’ feedback is not only linked to long-lasting effects, but also to motivational and volitional aspects with reference to self-regulation. It can be assumed that teachers’ self-regulation, including goal orientation (planning), monitoring, and reflection on the process was enhanced by coaches’ interventions, such as questions, comparing actual and target values, and reflection on overcoming obstacles and decision-making. In addition, it supported them in goal pursuit while enabling them to disregard other conflicting goals (Keck Frei et al., 2020; Zimmerman, 2000). The action plan not only served as a ‘contract’ for collaboration and commitment, but also as a valuable starting point for the coaching process. The important role of coachees’ goal commitment for the process of goal striving and monitoring for goal attainment, mentioned by the coaches in our study, was found in numerous other studies (Oettingen & Gollwitzer, 2001; Oettingen et al., 2015). The randomized allocation of the teachers to the OC, due to the design of the study, was perceived as a challenge or even failure factor. From the perspective of counselling effectiveness, clients’ readiness, motivation to learn, and openness for feedback are among the most important critical success factors (Vandaveer et al., 2016). Coaches’ narratives show that some teachers became more and more committed to goal pursuit, which was probably due to the increasingly job-embedded, tailor-made coaching. However, some coaches struggled with the coaching framework, because

86

C. Bieri Buschor et al.

it conflicted with their concept of coaching based on “real concerns or problems”. We assume that this aspect led to a form of identity threat. In contrast, most of the coaches appreciated the opportunity to learn and the strong goal orientation. One of the controversial aspects was the physical distance relationship, which correlated with coaches’ perceptions of a disinhibiting effect, lack of nonverbal clues, handover of responsibility, high objectivity/objectivation, and professional distance when emotional “dramas” occurred. Supporters of the OC emphasized the positive impact of the distance on their professional role. Those who were more critical contended that it did not affect them. From the coaches’ view, differences between online and face-to-face coaching are mainly in the following areas: linguistic accuracy, awareness that a shared understanding was important for goal pursuit, and an increasing objectivation related to time, emotion, and language. The characteristics of OC shown in Table 2 were discussed. They are comparable in part with other studies (Jones et al., 2016; Petko et al., 2015; Richards & Vigano, 2013; Wong et al., 2018; Wopereis et al., 2010). These characteristics do not primarily reflect differences between face-to-face coaching and OC, as some of them can also be found in face-to-face coaching formats. They describe the coaches’ perception in this study. One of the most important results of our study is that the characteristics of OC correlate with a new role for coaches (Richards & Vigano, 2013), who are often more critical towards online coaching than clients (Anthony, 2015). In agreement with Kraft et al. (2018), we believe that coaches’ characteristics, attitudes, and online experience have an impact on coaching outcomes. Therefore, further research is needed on OC and coaching/mentoring in teacher education and PD. For the purposes Table 2 Characteristics of teacher online coaching based on the coaches’ perceptions Characteristics of online coaching 1

Disinhibiting effect, self-disclosure (e.g. introverted teachers)

2

Lack of nonverbal clues/signals

3

Low hurdle to drop-out

4

Handover of responsibility to coachee regarding the use of different OC tools/methods

4

High objectivity/objectification (focus on content, goal orientation, problem-solving)

5

Playful multi-media approach, wide range of tools/methods (e.g. chat, system drawing/visualization)

6

Positive effect of writing, linguistic accuracy, and language awareness

7

Self-reflection and self-awareness

8

Flexibility, low-threshold access, fast interventions, time, and space-independence

9

Access to teachers’ workplace (school, classroom, etc.)

Notes The OC was based on work with the software cai-world, which provides professional coaching tools. Some of the characteristics are not only related to OC

Does Online Coaching Support Training Transfer? …

87

of our study, it would be interesting to follow coaches’ own development after the Covid-19 pandemic because this experience might have further shaped their attitude towards online learning environments.

Limitations Our study has several limitations. Firstly, we conducted a qualitative study due to the fluid coaching process. However, we discussed our findings against a background of coaching effectiveness that is generally researched using quantitative approaches. Secondly, it would be beneficial to include coaches’ and coachees’ perspectives in the form of coach-coachee dyads over time to analyse the coaching outcome. We will evaluate this aspect using the quantitative data collected. Thirdly, it is important to note that the coaches were involved not only in the role of coaches, but also as trainers in the self-management training, which had an impact on their perception of the OC in general as well as its effectiveness.

Implications Overall, goal-oriented support and coaching, which have found to be effective in many other domains (Brandstätter et al., 2013; Grant, 2014), could also be established in teacher education. In this context, our study shows that OC can enhance the effectiveness of transfer of self-regulation training to teaching practice, due to coaches’ flexible interventions and support of coachees’ individual development. In addition, OC can lead to a more collaborative approach to coaching than in face-toface settings. In sum, the time-flexible, low-threshold, goal-oriented online coaching (and mentoring) approach is beneficial in supporting pre- and in-service teachers in different phases of their career.

References Anthony, K. (2015). Training therapists to work effectively online and offline within digital culture. British Journal of Guidance and Counselling, 43, 36–42. https://doi.org/10.1080/03069885. 2014.924617 Baldwin, T. T., Ford, J. K., & Blume, B. D. (2017). The state of transfer of training research: Moving toward more consumer-centric inquiry. Human Resource Development Quarterly, 28(1), 17–28. https://doi.org/10.1002/hrdq.21278 Barak, A., Hen, L., Boniel-Nissim, M., & Shapira, N. (2008). A comprehensive review and a meta-analysis of the effectiveness of internet-based psychotherapeutic interventions. Journal of Technology in Human Services, 26, 109–160. https://doi.org/10.1080/15228830802094429 Berninger-Schaefer, E. (2018). Online-coaching. Springer.

88

C. Bieri Buschor et al.

Bieri Buschor, C., Berweger, S., & Keck Frei, A. (2022). Training manual (English version): Professional development program for the induction phase—A self-management training course for early career teachers. University of Teacher Education. https://zenodo.org/record/7189323#. Y2Of_nbMK5c Blazar, D., & Kraft, M. A. (2015). Exploring mechanisms of effective teacher coaching: A tale of two cohorts from a randomized experiment. Educational Evaluation and Policy Analysis, 37(4), 542–566. https://doi.org/10.3102/0162373715579487 Bozer, G., & Jones, R. J. (2018) Understanding the factors that determine workplace coaching effectiveness: A systematic literature review. European Journal of Work and Organizational Psychology, 27(3), 342–361. ISSN 14640643. https://doi.org/10.1080/1359432X.2018.144 6946 Brandstätter, V., Herrmann, M., & Schüler, J. (2013). The struggle of giving up personal goals: Affective, physiological, and cognitive consequences of an action crisis. Personality and Social Psychology Bulletin, 39(12), 1668–1682. https://doi.org/10.1177/0146167213500151 Brandstätter, V., Lengfelder, A., & Gollwitzer, P. M. (2001). Implementation intentions and efficient action initiation. Journal of Personality and Social Psychology, 81(5), 946–960. https://doi.org/ 10.1037/0022-3514.81.5.946 Christ, T., Poonam, A., & Chiu, M. M. (2017). Video use in teacher education: An international survey of practices. Teaching and Teacher Education, 63, 22–35. https://doi.org/10.1016/j.tate. 2016.12.005 Darling-Hammond, L., Hyler, M. E., & Gardner, M. (2017). Effective teacher professional development. Learning Policy Institute. Dede, C., Ketelhut, D. J., Whitehouse, P., Breit, L., & McCloskey, E. M. (2009). A research agenda for online teacher professional development. Journal of Teacher Education, 60(1), 8–9. https:// doi.org/10.1177/0022487108327554 Eby, L. T., Allen, T. D., Hoffman, B. J., Baranik, L. E., Sauer, J. B., Baldwin, S., & Evans, S. C. (2013). An interdisciplinary meta-analysis of the potential antecedents, correlates, and consequences of protege perceptions of mentoring. Psychological Bulletin, 139, 441–476. https://doi. org/10.1037/a0029279 Führer, F.-M., & Cramer, C. (2020). Mentoring und coaching in der Lehrerinnen- und Lehrerbildung. In C. Cramer, J. König, M. Rothland, & S. Blömeke (Eds.), Handbuch Lehrerinnen- und Lehrerbildung (pp. 748–755). Klinkhardt. https://doi.org/10.35468/hblb2020-091 Gaudin, C., & Chaliès, S. (2015). Video viewing in teacher education and professional development: A literature review. Educational Research Review, 16, 41–67. https://doi.org/10.1016/j.edurev. 2015.06.001 Grant, A. M. (2014). Autonomy support, relationship satisfaction and goal focus in the coach– coachee relationship: Which best predicts coaching success? Coaching: An International Journal of Theory, Research and Practice, 7(1), 18–38. https://doi.org/10.1080/17521882.2013. 850106 Jones, R. J., Woods, S. A., & Guillaume, Y. R. F. (2016). The effectiveness of workplace coaching: A metaanalysis of learning and performance outcomes from coaching. Journal of Occupational and Organizational Psychology, 89(2), 249–277. https://doi.org/10.1111/joop.12119 Keck Frei, A., Berweger, S., Bührer, Z., Wolfgramm, C., & Bieri Buschor, C. (2020). Als Lehrperson zielgerichtet mit Belastungen umgehen: Ein Selbstmanagement-Training. Journal für lehrerInnenbildung, 20(4), 48–57. Kelchtermans, G. (2004). Continuous professional development for professional renewal: Moving beyond knowledge for practice. In C. Day & J. Sachs (Eds.), International handbook on the continuing professional development of teachers (pp. 217–237). Open University Press. Keller-Schneider, M., & Hericks, U. (2014). Forschungen zum Berufseinstieg. Übergang von der Ausbildung in den Beruf. In E. Terhart, H. Bennewitz, & M. Rothland (Eds.), Handbuch der Forschung zum Lehrerberuf (pp. 386–407). Waxmann. Korthagen, F. (2017). Inconvenient truths about teacher learning: Towards professional development 3.0. Teachers and Teaching, 23(4), 387–405. https://doi.org/10.1080/13540602.2016.1211523

Does Online Coaching Support Training Transfer? …

89

Kraft, M. A., Blazar, D., & Hogan, D. (2018). The effect of teacher coaching on instruction and achievement: A meta-analysis of the causal evidence. Review of Educational Research, 88(4), 547–588. https://doi.org/10.3102/0034654318759268 Liu, S., & Phelps, G. C. (2019). Does teacher learning last? Understanding how much teachers retain their knowledge after professional development. Journal of Teacher Education, 71(6). https://doi.org/10.1177/0022487119886290 Mayring, P. (2015). Qualitative Inhaltsanalyse. Beltz. Nitsche, S., Dickhäuser, O., Fasching, M. S., & Dresel, M. (2013). Teachers’ professional goal orientations: Importance for further training and sick leave. Learning and Individual Differences, 23, 272–278. https://doi.org/10.1016/j.lindif.2012.07.017 Noh, G.-O., & Kim, D. H. (2019). Effectiveness of a self-directed learning program using blended coaching among nursing students in clinical practice: A quasi-experimental research design. BMC Medical Education, 19, 225. https://doi.org/10.1186/s12909-019-1672-1 Oettingen, G., & Gollwitzer, P. M. (2001). Goal setting and goal striving. In A. Tesser & N. Schwarz (Eds.), Blackwell handbook of social psychology: Intraindividual processes (pp. 329–347). Blackwell. Oettingen, G., Kappes, H. B., Guttenberg, K. B., & Gollwitzer, P. M. (2015). Self-regulation of time management: Mental contrasting with implementation intentions. European Journal of Social Psychology, 45, 218–229. Orland-Barak, L. (2016). Mentoring. In J. Loughran & M. L. Hamilton (Eds.), International handbook of teacher education (pp. 105–141). Springer. Osatuke, K., Yanovsky, B., & Ramsel, D. (2017). Executive coaching: New framework for evaluation. Consulting Psychology Journal: Practice and Research, 69(3), 172–186. https://doi.org/ 10.1037/cpb0000073 Parsons, S. A., Hutchison, A. C., Hall, L. A., Parsons, A. W., Ives, S. T., & Leggett, A. B. (2019). U.S. teachers’ perceptions of online professional development. Teaching and Teacher Education, 82(1), 33–82. https://doi.org/10.1016/j.tate.2019.03.006 Petko, D., Egger, N., Schmitz, F. M., Totter, A., Hermann, T., & Guttormsen, S. (2015). Coping through blogging: A review of studies on the potential benefits of weblogs for stress reduction. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 9(2), 5. https://doi.org/10. 5817/CP2015-2-5 Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 451–502). Academic Press. Powell, C. G., & Bodur, Y. (2019). Teachers’ perceptions of an online professional development experience: Implications for a design and implementation framework. Teaching and Teacher Education, 77, 19–30. https://doi.org/10.1016/j.tate.2018.09.004 Richards, D., & Vigano, N. (2013). Online counseling: A narrative and critical review of the literature. Journal of Clinical Psychology, 69(9), 994–1011. https://doi.org/10.1002/jclp.21974C Ross, J. D. (2011). Online professional development. Design, deliver, succeed! Corwin. Sancar, R., Atal, D., & Deryakulu, D. (2021). A new framework for teachers’ professional development. Teacher and Teacher Education, 101(2), 103305. https://doi.org/10.1016/j.tate.2021. 103305 Schaarschmidt, U., & Fischer, A. W. (2013). Lehrergesundheit fördern – Schulen stärken. Beltz. Smither, J. W. (2011). Can psychotherapy research serve as a guide for research about executive coaching? An agenda for the next decade. Journal of Business Psychology, 26, 135–145. https:// doi.org/10.1007/s10869-011-9216-7 Theeboom, T., Beersma, B., & van Vianen, A. E. M. (2013). Does coaching work? A meta-analysis on the effects of coaching on individual level outcomes in an organizational context. The Journal of Positive Psychology, 9(1), 1–18. https://doi.org/10.1080/17439760.2013.837499 Vandaveer, V. V., Lowman, R. L., Pearlman, K., & Brannick, J. P. (2016). A practice analysis of coaching psychology: Toward a foundational competency model. Consulting Psychology Journal: Practice and Research, 68(2), 118–142. https://doi.org/10.1037/cpb0000057

90

C. Bieri Buschor et al.

Vermunt, J. D., & Endedijk, M. D. (2011). Patterns in teacher learning in different phases of the professional career. Learning and Individual Difference, 21, 294–302. https://doi.org/10.1016/ j.lindif.2010.11.019 Wong K. P., Bonn G., Tam C. L., & Wong, C. P. (2018). Preferences for online and/or face-to-face counseling among university students in Malaysia. Frontiers in Psychology, 9(64). https://doi. org/10.3389/fpsyg.2018.00064 Wopereis, I. G. J. H., Sloep, P. B., & Poortmann, S. H. (2010). Weblogs as instruments for reflection on action in teacher education. Interactive Learning Environments, 18(3), 245–261. Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13–39). Academic Press. Zimmerman, B. J. (2006). Development and adaptation of expertise: The role of self-regulatory processes and beliefs. In K. Ericson, N. Charnes, P. J. Feltovich, & R. R. Hoffman (Eds.), The Cambridge handbook of expertise and expert performance (pp. 705–742). Cambridge University Press.

Digital Portfolios for Problem-Based Learning: Impact on Preservice Teachers’ Learning Strategies Bee Leng Chua, Oon-Seng Tan, and Woon Chia Liu

Abstract The digital portfolio is often used to assess both student learning process and outcomes. It provides a space where students assume agency over their learning and assessment. However, beyond assessment, the digital portfolio in initial teacher preparation programme can be a student-centric scaffold to facilitate preservice teachers’ acquisition of learning strategies. This is increasingly relevant in a postcovid teaching and learning environment where technology is used to minimise disruption to learning. In this chapter, ePBL is a pedagogical approach whereby the digital portfolio is used as a mediating space for preservice teachers to learn within a Problem-based Learning (PBL) environment. The digital portfolio allows preservice teachers to make their thinking visible to themselves, peers and tutors, reflect on their thoughts and acquire learning strategies for self-directed ad collaborative learning. The focus of this study is to examine the effects of ePBL on preservice teachers’ learning strategies. The understanding of the changes in preservice teachers’ learning strategies after PBL (face-to-face PBL and ePBL) will inform teacher educators on how to improve on its implementation to develop preservice teachers’ learning strategies. Specifically, it informs the design and use of the digital portfolio within a PBL environment to facilitate the development of preservice teachers’ learning strategies. In addition, limitations of the study and future research will also be discussed in the chapter. Keywords eProblem-based learning (ePBL) · Digital portfolio · Learning strategies

B. L. Chua (B) · O.-S. Tan · W. C. Liu National Institute of Education, Nanyang Technological University, Singapore, Singapore e-mail: [email protected] O.-S. Tan e-mail: [email protected] W. C. Liu e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Y. L. Chye and B. L. Chua (eds.), Pedagogy and Psychology in Digital Education, https://doi.org/10.1007/978-981-99-2107-2_5

91

92

B. L. Chua et al.

Introduction The COVID-19 pandemic has reinforced to educators the importance of preparing future-ready learners to learn for life rather than to focus solely on content acquisition. Future-ready learners need to acquire the necessary skillsets and dispositions to be effective problem-solvers in today’s VUCA (Volatile, Uncertain, Complex and Ambiguous) world. Problem-based learning is a pedagogical innovation where an authentic real-world task triggers students’ self-directed learning and collaborative learning to solve the problem presented. Through this problem-solving process, students acquire subject disciplinary knowledge for interdisciplinary knowledge application and development of competencies such as learning strategies for independent learning and peer learning. In addition, this global crisis has accelerated the use of technology to augment students’ learning. Technology is changing the way we learn and live and its exponential growth is a compelling driving force in political, social, economic and educational reforms. The use of technology that provides greater connectivity and easier access to information enables learning to take place anytime and anywhere, beyond the confines of the classroom. As such, the synergy of PBL and e-learning must be explored to support new ways of learning. As Tan (2007) argued “by considering the possibilities and impact of e-learning, PBL can take on new perspectives” (p. 12) and “hopefully the forces of technology will make PBL learning effective and enjoyable” (p. 13).

Literature Review for the Present Study Problem-Based Learning (PBL) According to Barrows and Tamblyn (1980), problem-based learning is the learning that results from the processes of working towards the understanding or resolution of a problem. Learners acquire knowledge, problem-solving and reasoning skills to resolve the problem presented to them. The key characteristics of PBL include the following: 1. Use of an Authentic Problem Trigger. The use of a real-life task stimulates learners’ intrinsic interest for learning (Ross, 1991). During the problem-solving process, students become active problem-solvers, acquiring the knowledge bases, cognitive and metacognitive skills transferable to another learning situation. 2. Self-directed Learning. During the PBL process, students are empowered to selfdirect their learning by identifying their learning gaps, creating learning objectives, actively acquiring new knowledge and strategies, and assessing how well learning has progressed to solve the problem presented (Charlin et al., 1998).

Digital Portfolios for Problem-Based Learning: Impact on Preservice …

93

3. Collaborative Learning. Throughout the PBL process, learners learn collaboratively in knowledge-building communities where they articulate their perspectives, negotiate and reflect on each other’s ideas (Sulaiman et al., 2004). 4. Scaffolding of Learning. PBL situates learners’ learning in authentic, unstructured and complex problems. Such a complex problem-solving process requires scaffolding to assist students in articulating their thinking, managing their investigations and evaluating and reflecting on their learning (McLoughlin & Luca, 2002; Quintana et al., 2004). Within a PBL environment, scaffolding is provided by a teacher or more knowledgeable other that allows the students to complete tasks that would otherwise be difficult (Wood et al., 1976). 5. Reflective Practice. Learners reflecting on their problem-solving process and learning is an essential feature of PBL (Hmelo-Silver, 2004). Through constant reflection, learners are able to address the gaps in their thinking, question assumptions and ideas, evaluate the validity and reliability of information obtained and build new knowledge based on prior understanding. This reflective process also allows students to transfer knowledge, cognitive skills and metacognitive skills across different learning contexts and situations.

PBL and Constructivism Having reviewed the major characteristics of PBL, it is apparent that the theoretical underpinnings for PBL is constructivism. Constructivist principles of learning argue that understanding comes from the interactions with the environment, and cognitive dissonance is the stimulus for learning that determines the structure of knowledge constructed. Students construct knowledge actively, engaging in a process of meaning-making through connection with prior knowledge and the real world (Phillips, 2000; von Glasersfeld, 1991). They do this as individual learners, and through social interactions and negotiation with others (Savery & Duffy, 2001; Savin-Baden & Major, 2004). According to Vygotsky (1978)’s social constructivism, learners learn not as solitary actors in the world, but by using ways of acting and thinking specific to their culture (Kozulin & Presseisen, 1995). Therefore, social interaction is fundamental to Vygotsky’s theory of learner development. As a learner interacts with more knowledgeable others, he/she develops higher mental functions such as language, cognitive skills, problem-solving skills, moral reasoning and memory schemas. It is posited for learners to develop cognitive structures to handle complex and difficult tasks beyond their current abilities, scaffolding is essential to make these tasks manageable and within students’ Zone of Proximal Development. Thus, elements of the PBL environment which stems from the constructivist and Vygotskian perspectives are characterised by: 1. The Use of Authentic Goal-directed Activities. Vygotsky (1978) believed that the critical role of education is to facilitate construction of knowledge through experiential, contextual and social interactions in real-world environments. The learning

94

B. L. Chua et al.

environment should consist of authentic tasks, which serve as cognitive triggers to stimulate learners’ learning and determine what to be learned and how learning will take place. These authentic activities allow a social context whereby learners collaborate, apply and co-construct knowledge with more knowledgeable others. 2. The Need for Social Interaction. Students are active learners who learn through the opportunities given to interact with each other, through sharing perspectives and clarifying ideas, seeking assistance, negotiating problems and brainstorming on solutions. As learners work collaboratively to solve authentic problems and through the interaction with more knowledgeable others, they transit from the lower to the upper limits of their Zone of Proximal development. 3. The Need for Self-directed Learning. Leaners need to feel empowered for their own as well as group learning. They should formulate their own learning objectives and be given the autonomy to acquire competencies and knowledge bases necessary in their learning process. In this way, learning becomes meaningful, which is an important motivating factor. 4. The Need for Scaffolds. To enable a learner to reach his or her learning potential, scaffolds are needed. There are three major forms of scaffolds, namely (i) the human mediator, (ii) knowledge representational tools and (iii) psychological tools. In the context of the classroom, a human mediator refers to the teacher who is the facilitator of the student’s learning process. Knowledge representational tools can also be used to facilitate the learning process. Hung and Nichani (2002) stated that such knowledge representational tools can include visualisation and simulation functions, concept mapping, information-gathering templates, forms of self-evaluation and web-based discussion platforms. The third category of scaffolding mechanisms involves “psychological tools” that affect human psychological processes. Kozulin (1998) explained that psychological tools are those symbolic artefacts (e.g. signs, symbols, formulae and graphic-symbolic devices) that help individuals master their own “natural” psychological functions, such as perception, memory and attention.

PBL and Learning Strategies Learning strategies refer to the learner’s use of different cognitive and metacognitive strategies (Pintrich et al., 1993). According to Bassok and Holyoak (1993), in PBL learners need to (i) tap on their prior knowledge and have metacognitive awareness of what they know and do not know; (ii) employ cognitive and metacognitive learning strategies such as elaboration skills, critical thinking skills and metacognitive selfregulation to analyse the problem, identify learning issues and set learning goals; (iii) pace their learning and use appropriate learning strategies to make judgements on ideas and facts proposed, acquire new knowledge to solve the problem presented; and (iv) monitor and evaluate their learning, and determine whether their learning goals have been met. Thus, situating learning in real-world problems in PBL allows learners to make visible their cognitive and metacognitive processes to their peers

Digital Portfolios for Problem-Based Learning: Impact on Preservice …

95

and tutors. This visibility will allow monitoring and evaluation of learning by the learners, their peers and tutors, which is pivotal for effective transfer of knowledge and learning strategies in new situations. A review of studies that examined PBL’s impact on learners’ cognitive and metacognitive outcomes showed that learners who went through PBL had higher cognitive, metacognitive and self-directed learning skills (Dwi-Hastuti et al., 2022; Kuvac & Koc, 2019; Siagan et al., 2019). Specifically, according to Oja (2011), there was a positive relationship between PBL and nursing students’ critical thinking. In addition, in a study by Suhirman et al (2020), PBL has a positive impact on Indonesia secondary school students’ higher order thinking skills, such as critical thinking, creative thinking and problem-solving skills. However, findings from two other studies indicated that there were no significant differences in students’ cognitive and metacognitive skills after PBL (Strømsø et al., 2004; Wong & Lam, 2007). A possible explanation for these contrary findings may be the diversity of contexts and applications pertaining to PBL. As such, it is of value to examine the impact of PBL on preservice teachers’ learning strategies within the context of an initial teacher preparation programme in Singapore.

PBL in the Current Study In this study, the PBL component was designed to last seven weeks out of the thirteen weeks of the Educational Psychology course for preservice teachers at the National Institute of Education (NIE), Nanyang Technological University (NTU), Singapore. Preservice teachers went through the PBL cycle (for both face-to-face and ePBL,). The stages for PBL include (i) Meeting the problem, (ii) Problem Analysis and Learning Issues, (iii) Discovery and Reporting, (iv) Solution Presentation and (v) Overview, Integration and Evaluation. There were structured weekly sessions of two hours each for the first three stages of the PBL cycle to facilitate group discussions and tutor facilitation. During the first session of PBL, preservice teachers were given an overview of PBL, its philosophy, objectives and evaluation process. The preservice teachers were divided into groups of three to five and presented with the problem scenario, and the PBL portfolio. At the Meeting the Problem stage, preservice teachers’ learning was triggered by an authentic problem on classroom management or students’ motivation. The preservice teachers discussed and brainstormed on facts presented by the problem scenario and assumptions they made which set the stage for the next PBL phase. At Problem Analysis and Learning Issues stage, preservice teachers analysed the problem scenario, deliberated on the assumptions and hypotheses made which gave raise to a list of questions or learning issues which they had to answer through self-directed and collaborative learning. Preservice teachers presented their learning and findings to their group members at the Discovery and Reporting stage. If preservice teachers’ list of questions and findings lead to proposed solutions to the real-work scenario presented to them, they will proceed to the Solution Presentation stage whereby they will present the proposed

96

B. L. Chua et al.

solutions to the class. However, if the learning issues, hypotheses and learning do not lead to the successful proposal of solutions to the problem scenario, preservice teachers will go back to the Problem Analysis and Learning Issues stage and the iterative learning continues. For the face-to-face PBL, the portfolio preservice teachers used for their problemsolving process was in the form of a deck of “static” PowerPoint slides which comprised a set of question prompts for each stage of the PBL cycle to initiate and sustain the preservice teachers’ inquiry process. For the ePBL model, the essential stages and characteristics of the PBL cycle were similar to those of the face-to-face PBL model. However, in lieu of a “static” set of PowerPoint slides that contained questions for each stage of the PBL process to facilitate preservice teachers’ faceto-face PBL experience, a dynamic e-learning platform was used to provide the scaffolding. PBworks was selected as the e-learning platform for the digital portfolio for the ePBL which integrated learning objects, e-tools and e-platforms to promote online collaborations between team members. The design considerations for the web-based digital portfolio for ePBL include (i) e-scaffolds to facilitate preservice teachers’ problem-solving process, (ii) opportunities for preservice teachers to conduct self-directed and collaborative learning and (iii) platforms for preservice teachers to make their thinking and thoughts throughout the PBL experience visible to themselves, their peers and tutors. The e-scaffolds include embedded learning objects which allowed preservice teachers’ access to essential information about the group project such as the overview of PBL, course and project information. These were resources preservice teachers would need as they solved the authentic problem scenario presented to them. For example, an overview of PBL and its PBL stages prepare preservice teachers’ mindset and readiness to embark on a problemsolving learning process which is student-centric and calls for students’ agency in their learning. In addition, the explicit articulation of the PBL cycle and pedagogical stages will scaffold preservice teachers’ learning processes (Chua et al., 2015). For ePBL, the affordances of technology allowed for the use of video technology for the problem scenarios presented to the preservice teachers at the Meeting the Problem stage. The presentation of the scenarios in video format rather than in narrative format for the face-to-face PBL allowed a richer perceptual experience for preservice teachers and permitted them to analyse the problem scenario taking into accounts the behavioural and expression cues by the various parties involved in the video scenarios. There was the use of e-question prompts at every stage of the ePBL cycle sequentially structured and facilitated preservice teachers’ problem-solving process in ePBL. In addition, e-tools and e-templates such as mind maps and KND (What do we Know, What do we Need to know and How Do we find out?) charts provided the anchor for online collaboration and were useful physical representations that guided preservice teachers in their discussion. Also, e-platforms embedded within the digital portfolio such as asynchronous discussion threads and synchronous online collaborations brought forth meaningful negotiation between peers and active seeking of opinions. Preservice teachers’ active use of the e-tools, e-templates, asynchronous and synchronous online platforms provided them with the ease of documentation of

Digital Portfolios for Problem-Based Learning: Impact on Preservice …

97

their thoughts and learning points which enhance the engagement and visibility of their learning. In addition, all these e-resources, e-scaffolds and e-platforms for selfdirected and collaborative learning were made available to the preservice teachers at any place at any time. The last two tutorial sessions on Solution Presentation and Overview, Integration and Evaluation were conducted face-to-face. Each lasted two hours and was dedicated to the presentations of the PBL groups, followed by preservice teachers’ reflections on their PBL learning process. Technology is changing the way we live and its rapid advancement is a compelling driving force in education reforms. With the advancement of technology, especially with Web 2.0 tools, there is great potential for using technology to support PBL. Thus, the focus of this study is to examine the effects of PBL on preservice teachers’ learning strategies such as cognitive and metacognitive strategies, such as rehearsal skills, elaboration skills, organisation skills, critical thinking skills and metacognitive selfregulation. The research question for this study is “What are the effects of PBL (faceto-face PBL and ePBL) on preservice teachers’ learning strategies?” Specifically, the research questions are: 1. Are there any significant differences in preservice teachers’ learning strategies over two time points (Pre-PBL, Post-PBL)? 2. Are there any significant differences in preservice teachers’ learning strategies in face-to-face PBL and ePBL learning environments? 3. Are there any significant interaction effects of time (Pre-PBL and Post-PBL) and learning environment (face-to-face PBL and ePBL) on preservice teachers’ learning strategies?

Research Method Research Sample The first sample comprised 1041 preservice teachers doing a core Educational Psychology course with the face-to-face PBL approach. The second sample comprised of 1029 preservice teachers doing the same core Educational Psychology course with the ePBL approach.

Measures The measures used for this study were taken from the Motivated Strategies for Learning Questionnaire (MSLQ) by Pintrich et al. (1993). The MSLQ is a selfreport questionnaire designed to assess learners’ learning strategies and motivational orientations. The learning strategies section contains 29 items and assesses five key

98

B. L. Chua et al.

dimensions of learning strategy, including learners’ rehearsal, elaboration, organisation, critical thinking and metacognitive self-regulation. Preservice teachers rated each item on a 5-point Likert scale, from 1 (strongly disagree) to 5 (strongly agree).

Data Analyses A 2 × 2 repeated-measures analysis of variance (ANOVA) was conducted to examine potential differences in learning strategies among preservice teachers in the face-toface PBL and ePBL environments before and after their PBL experience. That is, the MSLQ (learning strategies) was administered to preservice teachers in face-to-face PBL and ePBL environments at two points in time during the Educational Psychology course, in Week 5 before their PBL experience (for both face-to-face and ePBL) and Week 12 after their PBL experience with an interval of seven weeks. The descriptive statistics, distributional properties and internal consistency of the subscales at preface-to-face PBL and post-face-to-face PBL as well as pre-ePBL and post-ePBL experience are reported in Tables 1 and 2, respectively. Table 1 Descriptive Statistics and Cronbach’s Alphas for Subscales of Pre-face-to-face PBL and Post-face-to-face PBL Learning Strategies Mean

Standard deviation

Skewness

Kurtosis

Cronbach’s α

−0.04

0.66

Pre-f2fPBL learning strategies (5 subscales) Rehearsal

3.15

0.66

−0.03

Elaboration

3.63

0.58

−0.19

0.10

0.80

Organisation

3.47

0.67

−0.15

−0.07

0.72

Critical thinking

3.43

0.60

−0.04

0.03

0.79

Metacognitive self-regulation

3.35

0.54

−0.15

0.11

0.83

Post-f2fPBL learning strategies (5 subscales) Rehearsal

3.29

0.67

−0.30

0.06

0.74

Elaboration

3.70

0.54

−0.03

−0.17

0.82

Organisation

3.60

0.62

−0.23

0.15

0.74

Critical thinking

3.56

0.58

−0.07

−0.10

0.82

Metacognitive self-regulation

3.49

0.53

−0.11

−0.03

0.87

Digital Portfolios for Problem-Based Learning: Impact on Preservice …

99

Table 2 Descriptive Statistics and Cronbach’s Alphas for Subscales of Pre-ePBL and Post-ePBL Learning Strategies Mean

Standard deviation

Skewness

Kurtosis

Cronbach’s α

Pre-ePBL learning strategies (5 subscales) Rehearsal

2.89

0.71

0.09

0.28

0.69

Elaboration

3.56

Organisation

3.33

0.63

0.02

−0.01

0.83

0.72

−0.09

0.02

0.74

Critical thinking Metacognitive self-regulation

3.38

0.63

0.09

0.18

0.78

3.29

0.57

0.15

0.58

0.85

Post-ePBL motivation orientations (5 subscales) Rehearsal

3.07

0.69

−0.11

0.13

0.77

Elaboration

3.57

0.58

0.10

0.10

0.87

Organisation

3.40

0.65

−0.13

0.15

0.78

Critical thinking

3.44

0.57

0.14

0.12

0.81

Metacognitive self-regulation

3.40

0.56

0.13

0.47

0.90

Results Main Effects of Time (Pre-PBL, Post-PBL) For learning strategies (see Table 4), there were significant main effects of time on rehearsal, Wilks’s Ʌ = 0.944, F(1, 2068) = 121.57, p < 0.001, η2 = 0.056; elaboration, Wilks’s Ʌ = 0.995, F(1, 2068) = 10.44, p = 0.001, η2 = 0.005; organisation, Wilks’s Ʌ = 0.976, F(1, 2068) = 50.04, p < 0.001, η2 = 0.024; critical thinking, Wilks’s Ʌ = 0.972, F(1, 2068) = 60.14, p < 0.001, η2 = 0.028, and metacognitive self-regulation, Wilks’s Ʌ = 0.937, F(1, 2068) = 69.39, p < 0.001, η2 = 0.063. For each of the learning strategy dimensions, preservice teachers’ post-PBL scores were significantly higher than their pre-PBL scores (see Table 3), suggesting that they perceived themselves as using more rehearsal, elaboration, organisation, critical thinking and metacognitive self-regulation strategies after going through PBL.

Main Effects of Environment (Face-to-Face PBL, ePBL) There were significant main effects of PBL environment on rehearsal, F(1, 2068) = 83.42, p < 0.001, η2 = 0.039; organisation F(1, 2068) = 41.30, p < 0.001, η2 = 0.020; critical thinking, F(1, 2068) = 13.63, p < 0.001, η2 = 0.007; and metacognitive selfregulation, F(1, 2068) = 10.13, p = 0.001, η2 = 0.005. As shown in Table 3, the

100

B. L. Chua et al.

Table 3 Means and Standard Deviations of Learning Strategies across Two Periods (Pre-PBL, Post-PBL) and Environment (face-to-face PBL, ePBL) Environment

Time Pre-PBL M

Post-PBL SD

M

SD

Learning strategies (5 subscales) f2fPBL

3.15

0.66

3.29

0.67

ePBL

2.89

0.71

3.07

0.69

Elaboration

f2fPBL

3.63

0.58

3.70

0.54

ePBL

3.56

0.63

3.57

0.58

Organisation

f2fPBL

3.47

0.67

3.59

0.62

ePBL

3.33

0.72

3.40

0.65

Rehearsal

Critical thinking Metacognitive self-regulation

f2fPBL

3.43

0.60

3.56

0.58

ePBL

3.38

0.63

3.44

0.57

f2fPBL

3.35

0.54

3.49

0.53

ePBL

3.29

0.57

3.40

0.56

rehearsal, organisation, critical thinking and metacognitive self-regulation scores of the preservice teachers in the face-to-face PBL environment were significantly higher than the corresponding scores of the preservice teachers in the ePBL environment.

Interaction Effects of Time and Environment on Learning Strategies There was significant interaction effect between time (pre-PBL, post-PBL) and types of environment (face-to-face PBL, ePBL) on preservice teachers’ critical thinking (see Table 4). There were however no significant interaction effects for the other learning strategies, namely rehearsal skills, elaboration skills, organisation skills and metacognitive self-regulation. Follow-up tests to assess simple effects were conducted when the interaction between time and environment was significant. Simple effect tests were used for interaction comparisons. Specifically, the following sets of comparisons were carried out. 1. Compare between ePBL and face-to-face PBL at pre-PBL and post-PBL. 2. Compare between pre-PBL and post-PBL for ePBL and face-to-face PBL. In terms of preservice teachers’ critical thinking, there was no significant difference in their critical thinking in the ePBL and face-to-face PBL environment at pre-PBL, t(2068) = 1.90, p = 0.058. At post-PBL, however, preservice teachers’ critical thinking in the face-to-face PBL environment was significantly higher than

Digital Portfolios for Problem-Based Learning: Impact on Preservice …

101

Table 4 Results of 2 × 2 ANOVA for Learning Strategies on Time (Pre-PBL, Post-PBL) and on Environment (face-to-face PBL, ePBL) Time Ʌ

Environment P

η

2

F(1, 2068)

p

Interaction η

2

Ʌ

p

η

2

Learning strategies (5 subscales) Rehearsal

0.944**