Video Games: A Medium That Demands Our Attention 9781351235266, 9780815376897, 9781138593183, 1351235265

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VIDEO GAMES

This entry in the BEA Electronic Media Research Series, born out of the April 2017 BEA Research Symposium, takes a look at video games, outlining the characteristics of them as cognitive, emotional, physical, and social demanding technologies, and introduces readers to current research on video games. The diverse array of contributors in this volume offer bleeding-edge perspectives on both current and emerging scholarship. The chapters here contain radical approaches that add to the literature on electronic media studies generally and video game studies specifically. By taking such a forward-looking approach, this volume aims to collect foundational writings for the future of gaming studies. Nicholas David Bowman (Ph.D., Michigan State University) is an Associate Professor in the Department of Communication Studies at West Virginia University, where he founded and directs the Interaction Lab (#ixlab). His work considers the intersection of communication technology and human interaction, and the manner in which mediated communication places a variety of different demands on users. He has authored or co-authored over 120 peer-reviewed manuscripts and book chapters related to these issues, and his work has been recognized by regional, national, and international associations. He is the current editor of Communication Research Reports and is an associate editor of Journal of Media Psychology, and he serves on a number of editorial boards, external review panels, and grant committees.

E L E C T RONIC ME D IA R E S EARCH SERI ES Sponsored by the Broadcast Education Association Robert K. Avery and Donald G. Godfrey, Series Editors

MEDIA MANAGEMENT AND ECONOMICS RESEARCH IN A TRANSMEDIA ENVIRONMENT Edited by Alan B. Albarran MEDIA AND THE MORAL MIND Edited by Ron Tamborini MEDIA AND SOCIAL LIFE Edited by Mary Beth Oliver, Arthur A. Raney DIGITAL TECHNOLOGY AND THE FUTURE OF BROADCASTING Edited by John V. Pavlik RACE AND GENDER IN ELEC TRONIC MEDIA: CONTENT, CONTEXT, CULTURE Edited by Rebecca Ann Lind RISK AND HEALTH COMMUNICATION IN AN EVOLVING MEDIA ENVIRONMENT Edited by H. Dan O’Hair

VIDEO GAMES A Medium That Demands Our Attention

Edited by Nicholas David Bowman

First published 2018 by Routledge 711 Third Avenue, New York, NY 10017 and by Routledge 2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN Routledge is an imprint of the Taylor & Francis Group, an informa business © 2018 Taylor & Francis The right of Nicholas David Bowman to be identified as the author of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Library of Congress Cataloging in Publication Data Names: Bowman, Nicholas David, editor. Title: Video games : a medium that demands our attention / [edited by] Nicholas Bowman. Description: New York, NY : Routledge, 2018. | Series: Electronic media research series | Includes bibliographical references. Identifiers: LCCN 2018003848 (print) | LCCN 2018021133 (ebook) | ISBN 9781351235266 (ebook) | ISBN 9780815376897 (hardback : alk. paper) | ISBN 9781138593183 (pbk. : alk. paper) | ISBN 9781351235266 (ebk.) Subjects: LCSH: Video games. | Video games–Psychological aspects. | Video games–Social aspects. Classification: LCC GV1469.3 (ebook) | LCC GV1469.3 .V5266 2018 (print) | DDC 794.8–dc23 LC record available at https://lccn.loc.gov/2018003848 ISBN: 978-0-8153-7689-7 (hbk) ISBN: 978-1-138-59318-3 (pbk) ISBN: 978-1-351-23526-6 (ebk) Typeset in Sabon LT Std by Sunrise Setting Ltd, Brixham, UK

CONTENTS

List of Contributorsvii Series Editor’s Foreword  xv Acknowledgmentsxvii Introductionxix   1 The Demanding Nature of Video Game Play nicholas david bowman   2 Video Games and Cognitive Skills c. shawn green

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  3 The Role of Engagement in Facilitating Games-Based Persuasion44 brett sherrick   4 Research on the Emotions Caused by Video Games Demands Integration matthew grizzard and c. joseph francemone

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  5 Gaming Is Awesome! A Theoretical Model on Cognitive Demands and the Elicitation of Awe during Video Game Play daniel possler, christoph klimmt, and arthur a. raney

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  6 Behavioral Demands as Behavioral Affordances in Video Games allison eden, david r. ewoldsen, joomi lee, and david beyea

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  7 Applying Psychological Theory to In-Game Moral Behaviors Through the Development of a Purpose-Made Game sarah e. hodge, john mcalaney, christos gatzidis, eike falk anderson, davide melacca, and jacqui taylor   8 A Communication Model of Social Demands in Video Games jorge peña   9 Tandem Play: Theorizing Sociality in SinglePlayer Gameplay mia consalvo, jason begy, sarah christina ganzon, and rainforest scully-blaker 10 Social Demand in Video Games and the Synchronization Theory of Flow kevin kryston, eric novotny, ralf schmälzle, and ron tamborini 11 Explicating the Electricity of eSports: Motivations for Play and Consumption kenon a. brown, andrew c. billings, melvin lewis, and kimberly bissell 12 Live Streams and Revenue Streams: Twitch as a Hybrid Gaming Culture john a. velez, melissa r. gotlieb, geoffrey graybeal, alan abitbol, and jonathan a. villarreal

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13 Development of the Video Game Demand Scale nicholas david bowman, joseph wasserman, and jaime banks

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Appendix A Appendix B Index

234 243 245

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CONTRIBUTORS

Alan Abitbol (Ph.D., Texas Tech University) is an Assistant Professor of Public Relations in the Department of Communication at the University of Dayton. His research focuses on public relations, corporate social responsibility (CSR) communication, and social capital in a corporate setting. Eike Falk Anderson is Principal Academic (Principal Lecturer) in Game Development and program leader for the BSc (Hons) Software Development for Animation, Games and Effects undergraduate degree program at the National Centre for Computer Animation (NCCA), Bournemouth University (U.K.). He holds a Ph.D. in Computer Animation and his work focuses on virtual environment infrastructure and related application areas (e.g. serious games and cultural heritage visualization). This includes the development of methods and techniques for the creation of interactive virtual environments as well as methods for the creation of (virtual world) visuals through procedural synthesis. He has authored and contributed to numerous publications in these interrelated domains. Jaime Banks (Ph.D., Colorado State University) is an Assistant Professor in the Department of Communication at West Virginia University. Her research is animated by questions about the relationships between humans and technologies, principally in the domains of interactive media and social robots. Jaime was the founding chair of the National Communication Association’s Game Studies Division and she has edited a number of volumes on videogames and their characters, including Avatar, Assembled: The Social and Technical Anatomy of Digital Bodies. Jason Begy is a games researcher, consultant, educator, and book indexer. In addition to tandem play, he has published on games and cultural memory and games and metaphor, and in 2015 co-authored Players and Their Pets (University of Minnesota Press) with Mia Consalvo. He consults on game design and gamification for corporate and government clients in North America and Europe. Begy also specializes in indexing scholarly texts in media and game studies, communication, and linguistics. vii

LIST OF CONTRIBUTORS

In between all of these, he finds time to teach at Concordia University, Montreal, and Champlain College. David Beyea (M.A. University of Central Florida) is a doctoral student in the Department of Communication at Michigan State University. His research interests focus on computer-mediated communication and interactive media such as video games. His research typically focuses on how aspects of CMC and video games affect interpersonal communication. Andrew C. Billings (Ph.D., Indiana University, 1999) is the Ronald Reagan Chair of Broadcasting in the Department of Journalism and Creative Media and the Executive Director of the Alabama Program in Sports Communication at the University of Alabama. He is the author/editor of 18 books and over 150 journal articles and book chapters, the majority of which pertain to the role of mediated sport in society. Kimberly Bissell is the Southern Progress Endowed Professor in Magazine Journalism and the director for the Institute for Communication and Information Research in the College of Communication and Information Sciences at The University of Alabama. Her research interests lie in the intersection of media, health, sport and children, and her recent publications have been related to the role of media in the development of children’s nutritional knowledge and attitudes. Nicholas David Bowman (Ph.D., Michigan State University) is an Associate Professor in the Department of Communication Studies at West Virginia University, where he founded and directs the Interaction Lab (#ixlab). His work considers the intersection of communication technology and human interaction, and the manner in which mediated communication places a variety of different demands on users. He has authored or co-authored over 120 peer-reviewed manuscripts and book chapters related to these issues, and his work has been recognized by regional, national, and international associations. He is the current Editor of Communication Research Reports and is an Associate Editor of Journal of Media Psychology, and he serves on a number of editorial boards, external review panels, and grant committees. Kenon A. Brown is an Assistant Professor and Graduate Coordinator in the Department of Advertising and Public Relations at The University of Alabama. He is also the Programming Director for the Alabama Program in Sports Communication. His research focuses on audience effects of sports media, with an emphasis on athlete image management and Olympic media’s impact on national identity.

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LIST OF CONTRIBUTORS

Mia Consalvo is Professor and Canada Research Chair in Game Studies and Design at Concordia University in Montreal. She is the co-author of Players and their Pets, co-editor of Sports Videogames and author of Cheating: Gaining Advantage in Videogames. She has most recently published the book Atari to Zelda: Japan’s Videogames in Global Contexts, about Japan’s influence on the videogame industry and game culture. Mia runs the mLab, a space dedicated to developing innovative methods for studying games and game players. She’s a member of the Centre for Technoculture, Art and Games (TAG), and she has presented her work at professional as well as academic conferences including regular presentations at the Game Developers Conference. She is the former President of the Digital Games Research Association, and has held positions at MIT, Ohio University, Chubu University in Japan, and the University of Wisconsin-Milwaukee. Allison Eden (Ph.D., Michigan State University) is an Assistant Professor in the Department of Communication at Michigan State University, specializing in media entertainment research. Her work is interdisciplinary, drawing from communication and media psychology, social psychology, and neuroscience in the areas of media psychology, media entertainment, and media processing. Allison is a founding organizer and current secretary of the Communication Science and Biology interest group at ICA, an affiliated scholar with the Media Neuroscience Lab at the University of California, Santa Barbara as well as with the Neuroscience of Messaging Lab and the iVerse Virtual Reality Lab at Michigan State University. David R. Ewoldsen joined the Department of Media and Information at Michigan State University in 2016. Dr. Ewoldsen received a joint Ph.D. in psychology and speech communication at Indiana University in 1990. After completing his Ph.D., he was a postdoctoral fellow in the cognitive sciences program at Vanderbilt University (1990 to 1991). He was recently named a Fellow of the International Communication Association. Dr. Ewoldsen is founding co-editor of the journal Media Psychology (1998 to 2007) founding editor of the journal Communication Methods and Measures (2007 to 2010), and is currently editing the Annals of the International Communication Association. David’s research focuses primarily on media psychology with specific emphasis on racism, video games, entertainment, and health communication. He has also edited three books: Communication and Emotion (with Jennings Bryant and Joanne Cantor), Communication and Social Cognition: Theories and Methods (with Jennifer Monahan), and The Handbook of Communication Science (with Chuck Berger and Michael Roloff), and recently co-authored Communication Science Theory and Research: An Advanced Introduction (with Marina Krcmar and Ascan Koerner).

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LIST OF CONTRIBUTORS

C. Joseph Francemone (B.A., University at Buffalo) is a Master’s student in the Department of Communication at the University at Buffalo, The State University of New York. His research focuses on media psychology, mass communication, and moral judgments within narrative. He is currently interested in pursuing his Ph.D. and becoming either a professor of mass communication and media effects or a quantitative data analyst within the private sector. Sarah Christina Ganzon is a Ph.D. candidate in Communication Studies at Concordia University. Her research revolves mostly around the areas of game studies and global fandoms. Currently, she is writing her thesis on Japanese maiden games (otome games) in English and their players. She holds an M.A. in English Literature from Cardiff University and a B.A. in English Studies from the University of the Philippines, Diliman. Prior to starting her doctorate, she taught courses in literature and the humanities at the University of the Philippines, University of Santo Tomas, and Far Eastern University. Christos Gatzidis is the Head of the Creative Technology Department at Bournemouth University in the U.K. (in the Faculty of Science and Technology), which delivers a number of taught undergraduate games development programs, such as the BSc in Games Design and the BSc in Games Software Engineering. He has contributed to several refereed conference, book, and journal publications. Christos has also served as a member on a number of international program committees for various conferences plus has reviewed for numerous journals in the past. He has been the general chair/co-chair of the VS Games 2013 and Edutainment 2017 conferences as well as guest edited special issues of journals such as Elsevier’s Entertainment Computing. Melissa R. Gotlieb (Ph.D., University of Wisconsin) is an Assistant Professor of advertising in the College of Media and Communication at Texas Tech University. Her research explores the intersections of media, politics, and consumer behavior. She is particularly interested in how individual orientations and communication processes relate to youth engagement. Geoffrey Graybeal (Ph.D., University of Georgia) is an Assistant Professor in the College of Media and Communication at Texas Tech University. He is a media management scholar and entrepreneur who uses economic and management theory to explore issues of media sustainability. He is particularly interested in entrepreneurship and new media business models such as micropayments.

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LIST OF CONTRIBUTORS

C. Shawn Green is an Associate Professor of Psychology at the University of Wisconsin-Madison. He received his B.A., M.A., and Ph.D. in Brain and Cognitive Sciences from the University of Rochester in the lab of Daphne Bavelier. He then completed a Postdoctoral Fellowship in Machine Learning and Computer Vision under the supervision of Daniel Kersten and Paul Schrater at the University of Minnesota before joining the faculty at Wisconsin. Dr. Green’s research focuses on learning in the perceptual and cognitive domains broadly construed. He is particularly interested in exploring the factors that influence the rate at which skills are acquired, the asymptotic level of performance that is reached, and the extent to which learning to perform one task produces generalizable enhancements in performance on new tasks. In this, he uses a mix of standard lab-based tasks as well as video game training environments—both custom designed and off-the-shelf commercial video games—as training platforms. Matthew Grizzard (Ph.D., Michigan State University) is an Assistant Professor in the Department of Communication at University at Buffalo, The State University of New York, where he teaches courses in mass communication, media effects, and quantitative research methods. His research examines moral emotions and moral judgment processes related to the consumption of narrative and interactive media entertainment. His research has been published in journals such as Journal of Communication, Communication Monographs, Communication Research, Media Psychology, and Mass Communication and Society. He is a member of the editorial boards of Journal of Media Psychology and Communication Research Reports. Sarah E. Hodge is a Ph.D. candidate and lecturer in psychology at Bournemouth University, U.K. Her background is in psychology with her Ph.D. focusing on the role of morality in video games. Her research interests span psychology and technology, with a particular interest in video games, cyber, social, educational, moral, and developmental psychology. Christoph Klimmt received his Ph.D. in Communication from Hanover University of Music, Drama, and Media (Germany) in 2004. He worked as an Assistant Professor of Online Communication at the Johannes Gutenberg University of Mainz (2007 to 2010) and returned to Hanover University of Music, Drama, and Media to serve as Associate Professor. In 2013, he was promoted to Full Professor. Klimmt served as department head from 2011 to 2017. Since 2011, he is one of the associate editors of the Journal of Media Psychology. His primary research interests are uses and effects of new media, entertainment research, and public communication of science and technology.

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LIST OF CONTRIBUTORS

Kevin Kryston (M.A., University of Dayton) is a doctoral student in the Department of Communication at Michigan State University. His research is on the selection, experience, and outcomes of media exposure. He is interested in why people perceive certain media experiences as more influential to their own perceptions and behaviors than others, and how those perceptions translate into behavioral outcomes. He is also interested in using neuroscience and other real-time measures to determine shared biological phenomena underlying perceptions experienced during media exposure. Joomi Lee (M.A., Indiana University) is a doctoral student in the Department of Communication at Michigan State University. Her research focuses on motivational responses and perception of affordances from human media interaction from an embodied, embedded, and dynamic systems perspective. Melvin Lewis is an Assistant Professor in the Sports Business Management Graduate Program and Fellow of the Alabama Program in Sports Communication at the University of Alabama. His current research focuses on sport-consumer behavior and technology in sports. John McAlaney is a Chartered Psychologist and Senior Lecturer at Bournemouth University in the U.K. His research focuses on social psychological determinants of risky behaviors. He is particularly interested in how group dynamics and social identity may influence decision making and behavior within socio-technical systems. Davide Melacca is a graduate in Game Technology at Bournemouth University, with a background in media studies such as cinema and photography, as well as a camera operator and light director. He has worked as an assistant for various researchers, to support the development of games and simulator connected to the different area of study. Those roles varied from modelling and compositing different environment, animation, and scripting. His interests are in level design and modelling and shading to create a wide range of materials from photorealistic to stylized representations. Eric Novotny (M.A., University at Buffalo) is a doctoral student in the Department of Communication at Michigan State University. His research focuses on interpersonal motor synchrony and its ability to elicit positive social outcomes. He is interested in virtual reality and motion capture technology as means of measuring synchrony and its outcomes in a controlled environment.

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LIST OF CONTRIBUTORS

Jorge Peña (Ph.D., Cornell University) is an Associate Professor in the Department of Communication at University of California, Davis. His research focuses on cognitive, affective, and behavioral processes involved in online collaboration and play. He is also a founding member and executive officer of the National Communication Association Game Studies Division. Daniel Possler (M.A. in Media Management) is a research associate and doctoral candidate at Hanover University of Music, Drama and Media (Germany) at the Department of Journalism and Communication Research (IJK). His research focuses on uses and effects of interactive digital media, particularly video games and interactive forms of journalism (data journalism), as well as on the use of computational methods in communication science. Arthur A. Raney (Ph.D., University of Alabama) is the James E. Kirk Professor of Communication in the School of Communication at Florida State University. His research primarily examines how and why we enjoy media entertainment, with specific attention to the role morality plays in those processes. Ralf Schmälzle (Ph.D., University of Konstanz, Germany) is an Assistant Professor in the Department of Communication at Michigan State University. He examines brain responses to dynamic media content to better understand the micro-level mechanisms of media effects and motivations for media use. Rainforest Scully-Blaker is currently doing a Ph.D. in Informatics at UC Irvine’s Donald Bren School of Information and Computer Sciences. His research examines user subversion and repurposing of software with a current focus on emergent gameplay practices such as speedrunning and contemporary content creation platforms like Twitch. He received his M.A. in Media Studies from Concordia University in Montreal in 2016. Brett Sherrick (Ph.D., The Pennsylvania State University) is an Assistant Professor in the Department of Journalism and Creative Media at the University of Alabama. His research interests include video games, persuasion, digital media, sports media, and media effects, and he primarily examines these topics from a social scientific perspective. He is particularly interested in how games and other digital media can be used to improve the lives of media consumers. Ron Tamborini (Ph.D., Indiana University) is a Professor in the Department of Communication at Michigan State University where he teaches

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LIST OF CONTRIBUTORS

courses in media process and methods of communication inquiry. His research examines both traditional and new media, with a focus on how characteristics of technology alter the psychological experience and influence of media. Jacqui Taylor is an Associate Professor in the Department of Psychology at Bournemouth University. Jacqui is a Chartered Psychologist and has a Ph.D. in Applied Psychology, awarded by the University of Portsmouth for one of the first research projects investigating the social psychological impacts of online communication. Jacqui has taught on both psychology and computing degrees on the topic of cyberpsychology and her research investigates a wide variety of impacts of the internet on human interaction. She has published in both computing and psychology journals and books. John A. Velez (Ph.D., Ohio State University) is an Assistant Professor of Electronic Media in the College of Media and Communication at Texas Tech University. His research explores the psychological processes underlying new media selection and effects. His primary research program examines how cooperative social interactions can attenuate the deleterious effects of violent video games on players’ subsequent cooperative and aggressive behaviors. Jonathan A. Villarreal is a doctoral student in the College of Media and Communication at Texas Tech University, U.S.A. He received his Bachelor and Master of Arts degrees from Texas A&M University—Corpus Christi. His research focus is on new media processes and effects, with a specific interest in video game-related topics, including frustration, genre appeal, and social components. Joseph Wasserman (M.A., West Virginia University) is a doctoral student in the Department of Communication Studies at West Virginia University, where he is the Lab Manager of the Interaction Lab (#ixlab). His research is on learning via gameplay, with an emphasis on systems thinking outcomes and the role of game modality in playing and learning processes.

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SERIES EDITOR’S FOREWORD

When the Broadcast Education Association was formed seventy years ago, the organization’s mission was to promote and to nurture scholarly research, a commitment that became more formal with the publication of the Journal of Broadcasting in 1957, now the Journal of Broadcasting and Electronic Media. Throughout the Association’s rich intellectual history, BEA’s annual meetings have afforded both academics and professionals a wide range of opportunities for the presentation of important scholarship focusing on broadcasting and the electronic media. Ten years ago, BEA launched the BEA Research Symposium, a series of programs designed to advance original research under the direction of BEA’s Research Committee. Over the last decade the Symposium has advanced the research agendas of our discipline by providing a forum for leading scholars to present the latest ground-breaking research in our field. Professor Jennings Bryant oversaw the first Symposium in 2008 which centered on Media Effects, followed the next year by a Symposium chaired by Professor Linda Kaid which focused on TechnoPolitics. The success of these two symposia led to this series. In 2010, BEA and the Taylor and Francis Group of Routledge formed a partnership to enable publication of an annual volume resulting from the yearly BEA Research Symposium. The new work becomes a part of the BEA Electronic Media Research Series, and each new publication offers cutting edge, seminal work on a specific research topic. This book, Video Games: A Medium That Demands Our Attention, is the latest addition to the series, and it resulted from the 2017 Research Symposium chaired by Professor Nicholas Bowman of West Virginia University. It focuses on the cognitive, emotional, physical, and social demands of the ever-changing video gaming world. The 13 chapters present the latest in gaming studies and provide readers with a pivotal foundation for future inquiry into the field of gaming. This volume joins seven others in the Electronic Media Research Series that cover topics in sports, digital technology, risk and health communication, race and gender studies, media and social life, media and morals, and media management and economics. Each edition

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has offered unique, original research and has been a catalyst for future inquiry. This book will do the same for the area of video games, and the Broadcast Education Association and Routledge are proud to make it available. Louise Benjamin Kansas State University

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ACKNOWLEDGMENTS

Scholarship is an exercise in knowing when to talk and when to listen, and when to fall back on the shoulders on the giants before you. This is especially true in a collaborative effort such as an edited volume in which the content is inherently co-created. As such, I am indebted to those colleagues who offered to contribute to this volume, and who shared a similar vision for how to better understand our increasingly complex relationship with video games. Along with the authors here, there were many others who submitted and presented work at the April 2017 Broadcast Education Association’s Research Symposium in Las Vegas (from which the title of this volume was borne). Appendix A includes a complete list of all presenters as well as their presentation abstracts. Appendix B captures some of the Twitter conversation around the #beagames hashtag during our event. Special thanks are in order for our four keynote speakers at the event, which included Dr. Allison Eden of Michigan State University, Dr. C. Shawn Green of the University of Wisconsin-Madison, Dr. Matthew Grizzard of the University of Buffalo-State University of New York, and Dr. Jorge Peña of the University of California-Davis. Allison and Matt have been colleagues of mine for several years (spanning back to our days as graduate students in East Lansing), and they’ve been a constant source of inspiration (and occasionally, indigestion) for more than a decade. It was a delight working so closely with Jorge for this project as well—a colleague who I’d always known by name but never had the pleasure of collaborating with. Likewise for Shawn, given that my earliest work (including my dissertation) was directly informed by his work—even if he’s a Cubs fan, I can look the other direction from May to September. The list of inspirations for this work would take nearly an entire volume in itself, but at minimum I should acknowledge my long-time mentor Dr. Ron Tamborini (who edited a previous volume in the Routledge Electronic Media Research Series, “Media and the Moral Mind”) as well as Dr. Mary Beth Oliver and Dr. Arthur A. Raney (who also edited a previous volume in the series, “Media and Social Life”). Both have been common and often sources of inspiration for my career. xvii

AC K N OW L E D G M E N T S

Some of the earliest thoughts for this volume can be traced back to conversations with Dr. Andrew Weaver of Indiana University as well as his students, including (now Drs.) Nic Matthews and Teresa Lynch, during a 2014 on-campus colloquium in Bloomington—while some of those early concepts have since been relegated to the cutting-room floor, it was during that presentation that I first began to string together the concepts presented here. In fact, from that one talk at IU, I was able to engage in similar conversations (in somewhat of a chronological order) with colleagues at: the University of Utah (Dr. Jakob Jensen and Dr. Roger Altizer); National Chiao Tung University and National ChengChi University in Taiwan (Dr. Jih-Hsuan “Tammy” Lin and Dr. Chen-Chao Tao, along with Dr. Shu-Fang Lin and Yen-Shen “Sammy” Chen); the Technology University of Chemnitz (Germany) with Dr. Benny Liebold, Dr. Daniel Pietschmann, and Kevin Koban; Cleveland State University with Dr. Cheryl Campanella-Bracken; the students of WVU’s 2016 Global Game Jam; University of Connecticut with Dr. Saras Bellur and Dr. Rory McGloin; and the Catholic University of Leuven (Belgium) with Dr. Kathleen Buellens. To each of these colleagues and the audiences for those presentations and workshops, I am incredibly grateful for the equal parts inspiration and perspiration that you created for me—for all of you, a reminder that knowledge truly is a mix of international and collegial forces. I should also thank those BEA members who reached out to me about pursuing this project, including Dr. Louisa K. Benjamin of Kansas State University and Dr. Robert “Bob” Avery of the University of Utah—they put their trust in me to helm the eighth installment of the BEA Research Symposium to fruition (including the event, as well as this volume) and I am indebted to their trust. My most sincere thanks to BEA Executive Director Heather Birks as well as our Routledge Editor Ross Wagenhofer—both were instrumental in helping administer this project, and showed extreme patience with my persistent questions (especially Ross, who was willing to extend for us a slight extension of our publication deadline in recognizing that collaborating the efforts of over three dozen academics requires a bit of “wiggle room”—in the publishing industry, I’m sure this is referred to as “late authors”) with respect to the Gregorian calendar. Finally, no support network would be complete without mentioning those family and friends who keep us so balanced and grounded—Jaime, Izzy, and Stella kept me fat and happy during this process, and Mary, David, and Nathan gave me an ear to complain to. I’m sure I demanded far more of their time and attention than I’ve given them in the last months, and a better family, I could hardly imagine.

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INTRODUCTION

Dear Reader, This collection of manuscripts represents the first offering in Routledge’s Electronic Media Research Series wholly dedicated to the study of video games. On first glance, such a focus might seem myopic, especially given the more topic or theory-focused previous entries. However, our focus on video games represents the evolution of the medium itself, a medium that has grown at a rate far quicker than our collective understanding of its uses and effects. A technology first viewed as an interesting computational curiosity (testing the limits of early computer hardware and software) and then considered more a child’s pastime (keeping younger generations distracted) has since become so commonplace that one can hardly find an individual who has not engaged in some form of video gaming. Such ubiquity has led some, such as noted game designer and scholar Ian Bogost (in his book How to Do Things with Video Games, University of Minnesota Press, 2011), to wonder if video games are mundane among 21st century media offerings. At least one explanation for the growth of gaming into a commonplace facet of the modern media ecology is the medium’s ability to constantly and continually engage users on numerous dimensions. More so than engaging users, video games demand users to take up their systems—to play a video game, as explained by education scholar James Gee, is to engage an inherently and intrinsically learning experience, as the player is required to make sense of the on-screen environment in order to play. Designer and professor of entertainment technology, Jesse Schell, likewise explains that the emergence of video gaming represents a shift in our relationships with media. In a presentation at the 2013 Game Developers Conference in San Francisco, Schell explained that just as films because a respected and serious medium when they “learned how to talk,” games are on the verge of a similar evolution as they “learn to listen” to the players. In a sense, video games represent an exemplary form of human-machine interaction today, just as they did on their inception in the Kluge Room of the Massachusetts Institute of Technology in the early 1960s, when novice xix

B OW M A N

programmers wanted to test the limits of the new computing equipment in their lab (discussed further in Chapter 1). In a sense, to play a video game is a demanding experience that requires a type of multidimensional involvement by users that is phenomenologically unique among other forms of electronic media. The “lean forward” nature of video games described by scholars such as Frank Biocca, Jeroen Jansz, Peter Vorderer, and many others, are at least one of the features of games that makes them superior to other media—gamers can, and do, directly interact with the digital world in variably novel and intimate ways. This involvement is either explicitly or implicitly assumed to be a net gain for the overall experience, but at times lost in these discussions is the increased amount of effort required by such involvement—effort that can likely cost as well as benefit the overall gaming experience. In Chapter 1, I argue for an understanding of video games as demanding technologies on at least four such dimensions—cognitive (engaging player’s attention and processing faculties), emotional (engendering lower- and higher-order affective responses in players), physical (requiring tactile interaction between the player and the system), and social (fostering a sense of social interaction between players and other social actors, both digital and corporeal). This chapter sets a conceptual foundation for the chapters to follow and serves as a point of departure for the many discussions and deliberations presented afterwards. In Chapter 2, cognitive psychologist C. Shawn Green breaks down the specific associations between action video games—those that require exceptional speed, perceptual and cognitive load, and motor load—and the increased cognitive skills in players. In his chapter, Green offers a summary of the leading findings and challenges for this research, including ways in which video games might be superior to other forms of cognitive tests that suffer from the “curse of specificity” as the skills learned and honed by video games have applicability far beyond the digital world. Chapter 3 is offered by communication scholar Brett Sherrick and outlines theoretical connections between increased cognitive demand and persuasion in purpose-made video games. This central thesis is that as gaming requires some level of cognition on behalf of the player, persuasive games made for advertising, marketing, or social causes should be careful to balance out the attention required to play with the attention required to process the persuasive messages. Notably, Sherrick argues that moderate levels of cognitive demand stemming from the immersive nature of games are critical to reducing counter-argument among players, adding a useful design note to the growing number of developers making persuasive games. As the reader shifts to Chapter 4, so too does the focus shift away from the cognitive elements of gaming and toward the emotional demands. Here, media psychologist Matthew Grizzard and C. Joseph Francemone provide a challenge to game scholars to take the broad range of emotions xx

INTRODUCTION

elicited by gameplay more seriously. Most critically, Grizzard and Francemone offer three calls to action for gaming research, namely that: (a) emotions should be core concerns in gaming research; (b) emotional responses to gaming content mediate the play experience; and (c) game studies scholars should take care to specify the antecedents, and effects, of gaming emotions a priori. The critiques are borne from observations that while emotions are frequently assessed in gaming research, their conceptualization and operationalization often appear more incidental than integrated into the research program. In Chapter 5, media psychologist Daniel Possler and his international group of scholars from Germany and the United States propose a model of awe reactions in video games. As video game production becomes increasingly complex from both a narrative perspective, as well as a graphical one (with many games approaching photo-realism), the notion of awe experiences—an emotional response to perceptually vast stimuli that does not fit into established mental structures —is a compelling and novel approach to explaining yet another emotional dimension by which video games entertain players. In this chapter, Possler and his colleagues also discuss an emergent paradox of awe in gaming in the relationship between the increased cognitive engagement required to engage the task of gameplay and the perceptual resources required for one to be awe-inspired by the game’s environment. This latter discussion shows the intrinsic interplay between cognitive and emotional demands and, by extension, highlights the necessity of considering the chapters of this volume in tandem with each other. Chapter 6 offers a challenging extension on the notion of behavioral demand, as media scholar Allison Eden and her colleagues propose a refinement of the concept to focus less on the player’s physical engagement with the gaming system and more on the decisions that the gaming system offers to the player. Borrowing from James Gibson’s affordances theory, Eden and colleagues suggest that while the focus on player-side controller inputs is useful in understanding the decisions made, such a position is myopic with respect to a broader set of affordances within a video game that players both perceive and exploit. By recasting behavioral demands as determined by the affordances of a gaming system—both those that are encouraged by the system, as well as those that are hidden from the player—Eden gets to the very core of both Meier and Gee’s approaches to gaming. As with Possler and his writing on awe (which blended cognitive and emotional demand), Eden ends the chapter with a discussion on how social factors, such as playing with others, can inform a player’s understanding of a system’s affordances (blending behavioral and social demand). In a shift to purposeful game design, Chapter 7 is presented by a team of psychologists and game developers headed up by Sarah Hodge at Bournemouth University (UK), who delved deep into theory and research xxi

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of moral psychology to outline their approach to bespoke game design, with the end goal to challenge biases from players and game design. In their chapter, Hodge and her team provide comprehensive-yet-concise coverage of leading theories of morality broadly and as applied to video gaming, before outlining the role of psychological science in their game development process. Their approach offers insights for researchers engaged in the creation of games as morality simulators looking to strike a balance between internal validity (by way of conceptually and operationally valid moral scenarios) and external validity (by way of providing gaming experiences that closely resemble cutting-edge and commercially available content). Notably here, Hodge and her team place specific focus on the creation of morally relevant in-game decisions, somewhat invoking Eden and her team’s recasting of the behavioral demand construct. For Chapter 8, communication technology scholar Jorge Peña greatly expands on the concept of social demand by situating the concept within a larger communication framework. The approach, heavily inspired by foundational communication models first penned by Claude Shannon, Norbert Weiner, and Harold Lasswell, which diagrammed the human communication process as parallel to that of early communication technologies, shows that messages are crafted by a sender who selects a medium, within a context, directed toward a receiver, with accompanying noise, who, in turn, provides feedback to the sender. In the chapter, Peña elaborates on how these features operate in video games in ways both familiar and novel to communication scholars and suggests numerous areas of research elaboration—just as in previous mediated communication systems, any impact on one feature can have a drastic impact on both the quantity and quality of the social demands of a video game. Chapter 9 extends the focus on the social demands of gaming with an inspired chapter from games scholars Mia Consalvo and her team that explores an often-overlooked (and seeming oxymoronic) type of social play during so-called single-player games. Consalvo and her team propose the concept of tandem play to explain the surprising common gaming scenario by which, in their words, “two or more players engage with a single-player game together, moving through the game with a variety of potential motives.” Their chapter outlines some of the unexpected sociality that occurs in gaming environments that are seemingly made for solo consumption. Among their observations, culled from two separate data collection periods, is that in tandem scenarios, the social bonds between the tandem players often take precedence over the gameplay itself. For Chapter 10, a group of media psychologists from Michigan State University (USA) offer a more intrapersonal and neurological approach to social demands. In their chapter, Kevin Kryston and his colleagues explain that the intrinsically rewarding nature of video game play can be tied to their ability to engage the neural systems of the player. Moreover, while xxii

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extant literature here tends to focus on more game-specific stimuli such as play elements that demand a player’s visual and motor attention—their previously established (neural) synchronization theory of flow—gaming experiences can also involve sources of demand from social elements, such as interactions with other players as well as social relationships that players might form with or through on-screen avatars. In a sense, Kryston and co-authors suggest that the social dynamics of games can provide the same types of psychophysiological rewards to players as more traditional cognitive dynamics, and they call for more research into social-task and visuo-motor task demands, in isolation and in tandem. In Chapter 11, Kenon Brown and the group of scholars from the Program in Sports Communication at the University of Alabama (USA) take on the growing phenomenon of eSports—the public professional performance of video gaming that very much resembles modern sports spectatorship. For Brown and his colleagues, eSports represent a curious blending of performer and spectator, as unlike professional sports in which the on-field actions can hardly be engaged in an easily accessible fashion, the competitive artifacts of eSports can be replicated in their functional entirely by almost anyone with access to a computer or gaming console. Engaging a sample of just over 1300 eSports players, they found that eSports are engaged for many of the same reasons as traditional sports, such as arousal, camaraderie among players, competition, escape, passing time, self-esteem, social support, gaming fanship, and a sense of Schwabism, or superior knowledge of video games. In particular, an emergent finding from their project suggested eSports to be a rather social and more communal activity, similar to work on fantasy sports. That eSports and fantasy sports are similar in their social demands is notable, given that both activities are borne of communication technologies that tend to explicitly or implicitly encourage social interaction. Chapter 12, authored by John Velez and colleagues from a variety of disciplinary backgrounds, which include psychology, public relations, advertising, and media management, provides a compelling argument for understanding the game streaming platform Twitch as a hybrid gaming culture, exemplary of four zones of participatory social networks—social community, social publishing, social entertainment, and social commerce. Their chapter offers extensive theoretical and observational evidence to support Twitch’s ability to each of these types of participation, casting the platform as a one that could go far beyond gaming and rather a space with exciting social and civic potential. On the flip-side, the same chapter discusses potential disadvantages of commodifying participation and the implications this commodification may have for the civic benefits originally proposed for participatory cultures. Finally, Chapter 13 (authored by myself and colleagues Joe Wasserman and Jaime Banks, both with the WVU Interaction Lab), takes many of the xxiii

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arguments from throughout the volume—in particular, Chapter 1—and integrates them into a proposed measure called the Video Game Demand Scale. Based on data from more than 600 gamers, we present a 26-item survey instrument with five factors that can be used by researchers who want to assess the components of demand felt by video game players: cognitive, emotional, physical device, physical exertion, and social demands. Our data also demonstrates predictive, concurrent, and convergent validity with several variables related to gaming, such as entertainment, game ratings, and need satisfaction. As a whole, the diverse array of contributors and contributions in this volume as outlined above offer bleeding-edge perspectives on both current and emerging scholarship. The chapters here contain radical approaches that add to the literature on electronic media studies generally and video game studies specifically. By taking such a forward-looking approach, this volume aims to collect foundational writings for the future of gaming studies—the critical goal here is not to review or look back on game scholarship, but rather, more forward with novel lines of research inspired by the chapters offered here. I hope you enjoy the collection and I can speak from each of our authors and say that future debate and discussion is welcome, expected, encouraged … we even demand it. Sincerely,

Nicholas David Bowman, PhD Morgantown, WV, USA December 2017

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1 T H E D E M A N D I N G N AT U R E O F V I D E O G A M E P L AY Nicholas David Bowman

Video games are an increasingly common—perhaps, even mundane—aspect of the modern media ecology (Bogost, 2011). Moving into the 21st century, the video game industry began regularly out-performing the film and music industries in annual revenues (Nath, 2016), and popular media outlets report that over 90 percent of children are actively playing video games (Reisinger, 2011). Dispelling myths that games are “just for kids,” industry data reports that the average gamer is 35 years old and the population of gamers of women over the age of 18 is a larger proportion of the overall gaming market than boys under age 18 (Entertainment Software Association, 2017). In short, games have been demanding our leisure time (or at least, our leisure budgets) for the better part of the Digital Age (Castells, 1999). Although there is some debate about the “first” video game (Grizzard and Francemone, Chapter 4, this volume, discusses the earliest patents filed in the US for gaming technologies), the development of the medium was focused less on creating an enjoyable leisure technology and more about demanding more of computing technology. Graetz (1981) describes the development of one of first video games in the Kluge Room of the Massachusetts Institute of Technology (MIT), and the common ethos that was embraced by its creators. For them, a “computer simulation” needed to satisfy at least three criteria: 1. It should demonstrate as many of the computer’s resources as possible, and tax those resources to the limit; 2. Within a consistent framework, it should be interesting, which means every run should be different; 3. It should involve the onlooker in a pleasurable and active way—in short, it should be a game. (para. 28, emphasis added)

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For their team, the installation of a computer called the programmed data processor, or PDP-1, represented several notable advances into the (pre) Digital Age. Chief among them was the machine’s use of a cathode ray tube display scope—a digital display screen that allowed programs to view and edit programs in real-time. Prior to the PDP-1, most human-computer interactions were of a more analog nature in which data was organized onto a medium (such as a set of paper punch cards), manually input into the system’s processing unit, and after some elapsed time to process (highspeed computers of the time could perform about 100,000 calculations per second, or about 0.000003 percent of the speed of a home computer in 2017), results were then transcribed to paper by the machine. Early on, the denizens of the Kluge Room were set on moving beyond this more passive engagement to explore a new paradigm of human-machine interaction in which a display screen was a real-time, mediated reflection of the will of the former and the capability of the latter. Pushing the limits of the PDP-1’s processor (it was only one year prior, in 1961, that the National Space and Aeronautics Agency was still using human computers to hand-calculate the trajectory of Friendship 7’s orbit around Earth), by 1962, the team had developed SpaceWar! (1962)—an intergalactic battle between the Needle and the Wedge ships with both locked in the gravity well of a central star, with limited fuel and ammunition to accomplish the end-goal of obliterating the other. This program, developed ostensibly to demonstrate the computational power of the PDP-1, as well as the creativity and prowess of its programmers, is lauded as one of the first video games. Indeed, the self-described hackers that programmed SpaceWar! because they felt compelled by the computer to do so—Graetz (1981, who was a member of the group) explains that much of the early programming was as much about writing “new stuff that couldn’t have been done before” (para. 33) as anything else. In a sense, these early programmers demanded more out of their computing equipment, and, in turn, created one of the first video games that, in turn, demanded more out of the user.

Interactivity as Demand Although perhaps not intended by its creators, the development of SpaceWar! represents a core element of video games—they require users to engage a novel system and, while engaging, to manipulate the form and content of the on-screen displays in real-time (notions that would serve as core to later definitions of interactivity; Steuer, 1992). In this way, the user’s relationship with the medium shifts from that of a more passive recipient of information to a more active and lean-forward engagement with it (Jansz, 2005). This interactivity—the dialogue between the player

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and the program—is also one that is demanding of the player, as it requires constant player-side input in order to earn the desired program-side output, as outlined for the balance of this chapter. Of course, distinguishing media along the dimension of passive and active engagement (and perhaps, even demand) is not a new concept—McLuhan (1964) suggested that media broadly can be understood as either hot or cool depending on the number, as well as the intensity, to which a user’s perceptual senses are engaged. Yet, video games somewhat complicate McLuhan’s classic distinctions in that they both engage (at least) one sense with great intensity (a marker of a hot medium) but also engage nearly the entire human perceptual system, and in a highly participatory nature (a marker of a cool medium). Adding further complication is that even the locus of a technology’s interactivity can be debated, some (e.g., Sundar, 2004) suggest that interactivity is a property of the medium itself and is tied to the system affordances, while others (e.g., Bucy, 2004) counter that interactivity is as much a psychological phenomenon as it is technical. To illustrate the pith of this debate, Sundar (2004) argues that: If we were to theorize about the psychological effects of interactivity using such a technologically independent conception of interactivity, then we would be building knowledge about people (i.e., theories of psychology) rather than about media. (p. 386) On this point, and recognizing Sundar’s contributions to the psychological influences of various interactive affordances (such as his Theory of Interactive Media, or TIME: Sundar, Jia, Waddell, & Huang, 2015), I somewhat align with Bucy’s (2004) argument, at least for the case of video games— or perhaps more accurately, it is productive to follow Stromer-Galley’s (2004) suggestion in focusing more in interactivity-as-process rather than interactivity-as-product. In fact, it is a focus on the process (rather than the product) of interactivity as the intersection of media and human experience (Rutledge, 2013)—an active relationship between the player and program that forms the basis of the model of interactivity-as-demand. Such a proposal requires us to consider (a) the interaction of the stimulus (the video game) and the organism (the player) and (b) that the various requirements that a game places on a user should be expected to mediate the relationships between the game and its effects on the player. Such a process focus is critical in gaming, because it represents the dialogic nature of interactivity (Haraway, 1991) by which the user is required to constantly co-create the experience with the system (Bowman & Banks, 2016)—as noted by

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designer Sid Meier (2012), video games at their core are a series of interesting decisions. This deliberative co-creation process was illustrated by Bowman (2016): At the most basic level, one can track the first board of Super Mario Bros. (1985, Nintendo) as an example of this co-production. As the player initiates the start menu, they encounter a blue-sky world with a solid, flat terrain—entering this world stage-left with little guidance as to what lies ahead. Tapping the controller’s directional pad to the right causes the player-avatar Mario to move in that direction, which happens unimpeded in until the sight of a similarly sized (and angry-looking, given its furled brow) entity blocking in the path—quickly closing in on Mario until a remarkably primal decision must be made: fight or flight? The decision tree is further complicated and/or expanded by the presence of shiny blocks, marked with question marks that seem to beg to be explored further: three contain coins (assumed to be of some value) while one contains a mushroom-shaped object that, when consumed (re: made contact with), causes the player-​ avatar Mario to double in size and stature, possibly encouraging the player to reconsider an encounter with the “Goomba” or perhaps providing them with the confidence to continue exploring the gameworld. Consequently, a player choosing to ignore the tantalizing shiny boxes and trudge on ahead (regardless of whether or not they fight or flee the Goomba) is forced to take on a brave new world, in which they are of equal stature to the other word denizens as they progress stage-right through the Mushroom Kingdom. (pp. 108–109) The above scenario represents several of the required player-program dialogues that make games at once incredibly engaging and incredibly demanding. At the cognitive level, players must make sense of the novel symbols in the environment and their relationships with one another; on an emotional level, players must manage their implicit reactions to existential threat posed by an advancing creature; at the physical level, players must engage an abstract controller in synchronization with their visual processing of the environment; at the social level, the relationship that players have with their on-screen Mario can determine the weight given to some decisions over others. The balance of this chapter will focus more specifically on the cognitive, emotional, physical, and social demands of video games, and suggest how players’ interactions with games on (at least) these four dimensions are core to how we understand the experience of playing games. 4

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That discussion will challenge assumptions that increased levels of interactivity are necessarily beneficial to the experience (Gonzales, Finley, & Duncan, 2009; also discussed in the Introduction of this volume), and instead, discuss the extent to which these four dimensions of demand mediate players’ experiences in games, for better and for worse. For example, Bucy (2004) notes that whereas the technological affordances of a given interactive system are constant and objective properties of that system (Sundar, 2004; Sundar et al., 2015), it is unlikely that users experience those affordances in the same way given natural variance in the users themselves (for example, their cognitive skills or past experiences with interactive system). Moreover, increasing the interactivity of the system on any one dimension probably has a curvilinear association with our positive experiences of the system (Bucy, 2004), as increased interactivity also brings with it an increased demand on the users to make sense of, and function within, the system, which can make for an increasingly negative experience (Hart, 2006). Specific to video games, this curvilinear relationship was demonstrated by Bowman and Tamborini (2012), who found that a high-demand video game (one requiring players to engage numerous functions of an aircraft; essentially an increase of physical and cognitive demand) was less effective than a moderate-demand game at facilitating mood repair, and replication by Bowman and Tamborini (2015) demonstrated that these effects resulted in diminished preference for the high-demand game. In this vein, the mixed-valence connotation of the term “demand” is intentional throughout the chapter, as optimal demand experiences are likely those that carefully balance and synchronize the program’s demands with the user’s desires.

Cognitive Demand Perhaps the most apparent source of demand in a video game is that of cognitive demand, defined herein as the extent to which the user is required to implicitly or explicitly rationalize or understand the game. This approach is represented in the aforementioned discussion of Meier (2012) and his focus on games as interesting decisions, as well as the work of Gee (2003), who argues that video games by their nature are learning experiences—players are required to constantly learn and adapt as they play, and this learning often happens implicitly as players progress through a game. The specific focus on “rationalizing” is hewn from Boyan and Banks (2017), who explain that a prerequisite to any player’s success in a digital world is that they must construct durable-yet-pliable mental models of the systems themselves. The relationships between video games and cognitive skills has been well-established in the research on cognitive psychology. While an exhaustive overview of these links is provided by Green (Chapter 2 of 5

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this volume), research from nearly 30 years ago had already begun to establish positive correlations between gaming and increased spatial ability (Dorval & Pepin, 1986; Gagnon, 1985), with Greenfield (1987) discussing gaming’s broad impact on cognitive development and Jones (1984) even suggesting video games as a tool in psychological testing in a variety of contexts. Green and Bavelier (2003) offered one of the most comprehensive tests of the causal relationships between gaming and visual selective attention (in particular, games that require high levels of perceptional, cognitive, and/or motor load; cf. Green, Chapter 2 of this volume), and follow-up research has also demonstrated effects of (action) gaming on other cognitive skills, such as task switching (Green, Sugarman, Medford, Klobusicky, & Bavelier, 2012) and working memory (Colzato, van Leeuwen, van den Wildenberg, & Hommel, 2010). Much of this research is rooted in a general understanding of neural plasticity— that is, that the human brain is more dynamic than static and, through experience, neural networks can be exercised and strengthened (Green & Bavelier, 2008). To some extent, it may be argued that the notion of “video game skill” is somewhat of a misnomer, given research showing the correlation of specific cognitive skills to in-game performance (such as the role of mental rotation in performance at first-person shooters; Bowman, Weber, Tamborini, & Sherry, 2013; Rogers, Bowman, & Oliver, 2015) and the stark differences in gamers and non-gamers with respect to attention, memory, and executive control assessments (Boot, Kramer, Simons, Fabiani, & Gratton, 2008). Put simply, video games place such a demand on various cognitive resources is the reason that makes them particularly useful as tools for helping train cognitive skills. Of course, the cognitive skills required to play a game (such as mental rotation ability) are not the whole of the decision making that game. Juul (2011) explains: A game is a rule-based system with a variable and quantifiable outcome, where different outcomes are assigned different values, the player exerts effort to influence the outcome, the player feels emotionally attached to the outcome, and the consequences of the activity are negotiable. (p. 36, emphasis added) Several dimensions of Juul’s definition are critical to how we understand games, but one that is most apparently aligned with cognitive demand is that of games as rule-based system(s). From a player-program dialogue perspective, these rules set the parameters of the interaction, with the player learning and negotiating the rules set in place by the program. Of course, the extent to which players have the capacity or motivation of understanding the entirety of these rules can be understood as an 6

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additional source of cognitive demand. Fiske and Taylor (1991) proposed in their cognitive miser approach to human cognition—a suggestion that people tend to be frugal with respect to expending mental energy in the absence of motivation. A. Lang (2000) expanded on this concept in the limited capacity model for motivated mediated message processing, or LC4MP, suggesting that when engaging any mediated message (such as a video game), users will only attend to those message elements are extrinsically or intrinsically motivating—in a video game, this might refer to approaching on-screen enemies that are extrinsically motivating as part of the goal-pursuit, and intrinsically motivating in terms of survival and threat mitigation. LC4MP holds specific relevance to video games insofar as they represent highly multimodal environments with an array of messages that must be encoded, stored, and retrieved for future usage— all processes critical to developing and refining a player’s mental models (Boyan & Banks, 2017). Returning to a player-program dialogic perspective of gaming, as the system provides an increasing number of messages to players, players are in turn left with fewer cognitive resources for which to process any one message—eventually, devoting resources to some and ignoring others. Such a perspective might explain the role of heuristics in gameplay observed broadly by Martinez-Garza and Clark (2017) and specifically by Joeckel, Bowman, and Dogruel (2012). In the latter study, gamers with decreased moral sensitivity toward a given scenario (such as an innocent being harmed or a child running away from home) were more likely to make random rather than moral decisions, which could be explained via LC4MP as an effect of diminished intrinsic motivation. Although not studied, it is plausible that players engaging in amoral rather than moral decision-making processes might have been conserving cognitive resources for more pressing in-game decisions down the way (a similar line of reasoning is offered by Possler and colleagues in Chapter 5 of this volume, with respect to the experience of awe in gaming as requiring attention allocation to the awe-inducing stimulus). Yet another aspect of the cognitive demand of gaming can come from the in-game environmental affordances presented to the player—a perspective informed by affordance theory (Gibson, 1979) and expanded on by Eden and colleagues in Chapter 6 of this volume. In summary, we can understand the cognitive demand of video games as a function of the cognitive skills required to play games as well as the cognitive resources that the game pulls from the player in order to arrest attention toward the myriad messages in a game’s environment. These demands are both a prerequisite for enjoyable gaming experiences, yet also a core source of the frustration that comes from gaming (Sherry, 2004), and understanding the mental intricacies of the player-program dialogue holds potential for improving our knowledge of the intended and unintended effects of gameplay. 7

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Emotional Demand The earliest games such as SpaceWar! and Pong (1972) were designed primarily as rules-based puzzles to tax the cognitive (and somewhat, physical) resources of the player. In a sense, this focus on gameplay mechanics can even be found in the nomenclature mechanics of video game genres, such as “first-person shooter” to describe games in which the player is charged with three-dimensional navigation and weapons combat and “platformer” to describe games in which the player is charged with the negotiation of a rapid-succession of two-dimensional jumps and puzzles. However, taking a broader understanding of emotional demand as the extent to which a video game causes the user to have an implicit or explicit affective response to the game, we can consider the emotions that take place within the player during the experience (as suggested by Grizzard and Francemone, Chapter 4 of this volume). Borrowing from Tan’s (2008) assertions that entertainment can be understood as an emotion, we can suggest that the target emotional experience of gaming is that of enjoyment—comporting with the historical view of games as pleasurable toys and past-time pursuits (Ivory, 2015). Broadly, McGonigal (2011) offers that during video game play, the player is “intensely engaged” and thus “precisely the right frame of mind and physical condition to generate all kinds of positive emotions” (p. 28) and similar claims are offered by Grodal (2000) with respect to the exhilaration and joy that comes with engaging video game systems. Such arguments suggest a broad impact of games in that playing them is generally appraised by gamers as a positive experience and thus, serves to encourage future play (Olson, 2010)—in fact, a requirement of play is that the activity be enjoyable (see Garvey, 1990). From a need satisfaction perspective, Tamborini and colleagues (2010) demonstrated that the enjoyment of video game play—the pleasures of control, as stated by Grodal (2000)—were in part due to the medium’s ability to satisfy basic psychological needs associated with autonomy, competence, and relatedness core to self-determination theory (Deci & Ryan, 2000); follow-up work from Tamborini et al. (2011) further demonstrated that these need satisfaction mechanics were distinct from arousal and other hedonic mechanisms. Peering closer into the human mind, Ravaja and colleagues (2006) used physiological indicators to demonstrate event-specific emotional reactions while gaming, with positively valenced arousal (i.e., enjoyment) associated with active player engagement. In sum, there is ample reason to believe that games engage players in ways that make them enjoyable—for some, perhaps at clinically addictive levels of gameplay (Li et al., 2017) given that games are particularly adept at encouraging highly enjoyable experiential flow states (Chen, 2007; Sherry, 2004). Critical in this discussion of emotions in gaming is an understanding of the increasingly complex emotional content in video games—that the

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emotional experiences from games can (and do) extend beyond pleasure. Benedetti (2010) observed that in lock-step with the technical advances of gaming technologies and the maturing video game player population, video games also began to “grow up” along with their audiences, games “peer(ing) into the dark reaches of the very real human heart to deliver stories that are thrilling, chilling and utterly absorbing” (para. 6). This evolution in gaming was also recognized by Schell (2013), who explained that “[just as] film wasn’t taken seriously as a medium until it learned to talk, games are waiting to learn to listen.” He continued to explain that video games are “really good at below-the-neck verbs” (such as shooting and running), which often do not engender the sort of deeper emotional experience of more developed storytelling media, but that game design seemed to be shifting toward more “above-the-neck” verbs (such as talking, asking, and pleading). While, historically, video games in the role-playing game (RPG) genre, such as Hironobu Sakaguchi’s Final Fantasy (1987), were remarkably keen at Schell’s above-the-neck verbs, Kowert (2017) explains that the game’s kishotenketsu approach to storytelling (as with many other Japanese-style RPGs of the time) was successful at engrossing players into the lives and struggles of the game’s characters. We highlight Final Fantasy in particular because despite widespread concerns that the game would fail (Sakaguchi saw it as his last attempt to tell a story with games; Fear, 2007), the game launched a franchise that has sold more than 130 million copies (Square Enix, 2017). These above-the-neck video games are more focused on triggering a richer tapestry of emotional responses. Lynch and Martins (2015) focused on players’ fear experiences in video games and found that recollections of fear were highest with highly interactive and realistic games. Games such as Dead Space (2008) and Resident Evil (1996), and other such survival games, are designed to elicit fear in part because as players involve themselves in the experience, the players might feel as helpless as their on-screen avatars; Grodal (2000) gives the example of encountering a tiger both “in the wild” and “in a video game” eliciting similar levels of fear. Moreover, emotions such as fear represent more basic and primal motivational states, triggered in players in advance of their evaluation of the experience (Buck, 1999; Panksepp, 1982). In fact, to extend this discussion a bit further, the fear reactions identified by Lynch and Martins (2015)—and emotion that is prima facie quite negative—could well be re-appraised by gamers later in the experience as rather enjoyable (Lazarus, 1991). Hemenover and Bowman (2017) give the example of the video game Mortal Kombat as another example of appraisal theory in video games, in which the objectively gruesome and graphic on-screen fatalities that earned the eponymous video game the ire of parents and policy makers of the time (Previte, 2003) were often appraised by gamers

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as indicators of superior game skill and conquest, likely leading to feelings of pride. A similar effect can be identified in the research on guilt reactions in gaming, which have received a good deal of empirical attention (Grizzard, Tamborini, Lewis, Wang, & Prabhu, 2014; Hartmann, Toz, & Brandon, 2010; Mahood & Hanus, 2017). Of these studies, Grizzard et al. (2014) stands out as it used the game Call of Duty: Modern Warfare 2 to demonstrate that players engaging the role of a terrorist assigned to attack a civilian airport (resulting in the deaths of hundreds of innocents) both (a) felt higher levels of guilt and (b) were more sensitive to moral issues (such as those associated with harm and fairness) following gameplay. That infamous “No Russian” mission was controversial—the developers eventually released a patch to allow players to skip the level—but according to the game’s designer Mohammad Alavi: It isn’t really relevant whether that makes you enjoy the entertainment experience even more because you’re being naughty (à la Grand Theft Auto) or it engrosses you further into the story and makes you resent your actions. What’s relevant is that the level managed to make the player feel anything at all. (As cited by Totilo, 2012, para. 3, emphasis added) Of course, fear (as a motivated emotion) and guilt (as an appraisal emotion) are but a few of the emotions that may be experienced during highly narrative video game play. Oliver et al. (2015) found that nearly threefourths of gamers in their non-probability sample could identify feelings of meaningfulness associated with being touched, moved, compassionate, and inspired—in line with the notions of eudaimonia-as-entertainment offered by Oliver and Raney (2011). In a similar vein, Possler and colleagues (Chapter 5, this volume) discuss the potential of video games to inspire feelings of awe, and Wulf, Breuer, Bowman, and Velez (2017) demonstrated the role of video game memories to spark a unique sense of nostalgia. Perhaps in borrowing from Schell’s (2013) pursuit of the “Shakespeare of video games,” we might suggest that “in a video game, if somebody is crying it’s likely because the player both caused it and can solve it” (Oliver et al., 2015, p. 403) and thus, the emotional demands of this player-game dialog can help better inform how players interact in these spaces. For example, from the perspective that emotions can be experienced as implicit (re: pre-cognitive) reactions (motivated approach and avoidance states; see P. Lang, Bradley, & Cuthbert, 1998), we can think of the player-program dialogue as having an intuitive emotional tinge to it—players will often feel rather than think through the interactions, especially when those interactions are particularly novel or tap primary reactions (such as fear) in the player. Likewise, the more explicit emotional response can be understood 10

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by focusing on the content of the dialogue itself, as the player might ponder and consider the ongoing interaction and its consequences, such as the case in feelings of guilt or awe, or even nostalgia. As suggested by the Thomas theorem (Thomas & Thomas, a 1928), if an action has consequences, then it matters—even if those actions are purely digital—and by extension, it is the fact that those in-game actions have consequences is what demands player’s emotional reactions to them. In a sense, and in borrowing from Elson and colleagues (2014), video games must be considered as more than just stories with buttons. Rather, they are narratively rich experiences that demand a rich tapestry of emotional responses in their players, who are often feeling rather than thinking through the various on-screen trials and tribulations (Raney, 2004).

Physical Demand Yet another source of demand that games place on their players is that of physical interaction, which can be conceptualized as the extent to which a system requires the user to exert discrete or holistic physical effort.1 The simplest version of this would be the physical controller apparatus, which literally mediates the player’s efficacy and experience in the system (Bowman, Liebold, & Pietschmann, 2017)—that is to say that without the player’s active physical engagement with these devices, there is no player-program dialogue. As players take up these controllers, they begin to form mental models of the relationships between the controller functions and the desired on-screen actions, and it is the strength of these mental models that reduces the physical demands of the system (most computer users who have learned to type with the QWERTY key layout have experienced this very phenomenon; Noyes, 1983). For example, with SpaceWar!, the developers quickly learned that the PDP-1’s console was ill-equipped to handle the game’s functions and developed a rudimentary controller module that mapped dedicated game controls to specific buttons. Parisi (2015) explained that the handheld gamepad was central to the immense market success of the Nintendo Entertainment System (NES)— most argue that the NES single-handedly saved the video game industry, as it provided a measure of consistency and quality control uncommon at the time (Cunningham, 2013). The simple five-button gamepad was sized and shaped to fit in the hands of most gamers, while abstract enough to be mapped to the more than 1,000 different NES video game releases. The console’s and controller’s success implicitly established a “golden hands” rule (persisting for nearly four decades) by which game designers tend to focus development on console and controller-based games (Parisi, 2015, para. 6). Notable here are efforts to reduce the physical demand of controller interfaces by creating naturally mapped systems, or systems that tap into 11

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the familiar human perceptual system (cf. Biocca, 1997). The assumption here is that by using a person’s existing mental model of the relationship between input and physically embodied action rather than requiring them to learn an abstract model through an artificial device, barriers to the experience should be removed as the overall task will be less demanding on the individual (Bowman et al., 2017; Skalski, Tamborini, Shelton, Buncher, & Lindmark, 2011). Although the concept of natural mapping is certainly not new, for example, early racing games and flight simulators used a traditional steering wheel or flight stick controls, perhaps most representative of the gaming industry’s movement toward natural mapping was the 2006 release of the Nintendo Wii system. By using a Wiimote, rather than a traditional “golden hands” controller, players interfaced with games on the Wii by waving their controller to mimic realworld behaviors, such as swinging a tennis racket or rolling a bowling ball (Tamborini & Bowman, 2010). These efforts have been met with mixed empirical results. Using controllers that very carefully replicate their analogous physical-world activities (such as a golf club controller or steering wheel) generally leads to superior feelings of spatial presence—a sense of non-mediation in the game’s environment (that is likely impeded when physical demands are high) as well as greater enjoyment (McGloin, Farrar, Krcmar, Park, & Fishlock, 2016; Skalski et al., 2011). However, using naturally mapped controllers that do not completely replicate real-world actions, such as using the Wiimote as a firearm (in which players point the remote toward the television and press the device’s trigger, both with one hand) are more cumbersome and hinder performance, while increasing frustration (Rogers, Bowman, & Oliver, 2015). Rogers and colleagues (2015) argued that at least one reason for the gamepad’s superior evaluation was that it more directly tapped the cognitive skills (such as mental rotation and targeting ability) essential for success at the game (Bowman et al., 2015)—indeed, in Rogers et al. (2015), as well as other studies using the Wiimote (Tamborini et al., 2010), performance was higher for players using traditional gamepads. Arguing further, Bowman et al. (2017) suggested that while it makes sense to assume that natural control systems should be lower in their physical demand than more abstract controller systems, one barrier might be that gamers have to first unlearn the heuristically familiar mental models that they have long associated with controllers—again here, we can point to the continued success of the QWERTY keyboard layout as an example of an inferior interface (intentionally designed to slow down typists to prevent jamming early analog typewriters) that enjoys widespread preference (Noyes, 1983). For most gamers who have spent decades learning how to adapt a handheld controller to myriad different game experiences, the expectation of engagement without physical buttons might present a bit of a paradox with respect to what is “natural” in a video game—and 12

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so present higher demand. Indeed here, the novel controller scheme might present both a physical demand with respect to learning a new set of eye-hand coordination combinations as well as a cognitive demand with respect to having to mentally map the same. As with most all human-machine interactions, the dialogue between player and program in video games requires a good deal of physical interaction on behalf of the former in order to respond to the latter’s requests, which bring with them a unique source of demand. One illustration of this can be found in the classic platformer game genre, the action video game sort defined by Green (Chapter 2, this volume), in which the temporal load on the player requires instant input—the player might well have solved the cognitive demand posed by the system (i.e., they know where the avatar needs to go) and acclimated themselves to the emotional demand of the same (i.e., they have mitigated their implicit and explicit aversion to the task), but if the player is not able to handle the controller system itself, then success is unlikely. Rather, the controller is probably going to end up on the floor instead of in the player’s hands (Banks, personal communication, 17 December 2017)—severing the player-program dialogue.

Social Demand A fourth source of demand identified by Bowman (2016) was that of social demand, defined as the extent to which a system triggers an implicit or explicit response in the user to the presence of other social actors. Again here, we can look back to SpaceWar! for inspiration, as the game’s Needle and Wedge avatars required human controllers, as the programmers had not yet though of developing an artificial intelligence system capable of controlling one of the ships (it is unlikely that the PDP-1’s processor would have been able to handle such advanced programming). Indeed, the earliest home gaming consoles—such as the Atari VCS (Video Computer System) in 1977 and the aforementioned NES of 1983— included two controllers and numerous games that encourage so-called couch co-op play by which players sit next to each other and engage the system together. The more obvious source of social demand might be the social interactions that take place between players, but social demands can also be more implicit in nature, such as the mere presence of others boosting arousal in individuals (see Bowman et al., 2013) or other physiological orientations that humans make toward each other (such as the synchronization of neural systems, cf. Kryston and colleagues, Chapter 10 of this volume). Moreover, the social demands of gaming come from both physically and digitally co-located human players, as well as from the avatars themselves (including both non-player characters as well as the player’s own avatar; cf. Banks & Carr, 2017). 13

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The social dimensions of video game play are evidenced by Egli and Meyers (1984) who explored the role of public video game arcades as spaces for bonding and performance, and Steinkuehler and Williams (2006) framed online gaming communities in largely the same terms. That these social play situations have spanned the history of the medium are largely represented in the research on gameplay motivations in which social interactions are a prominent gratification sought from gaming (Sherry, Lucas, Greenberg, & Lachlan, 2006; Yee, 2006). Even if players are not directly engaging each other, the presence of others exerts social pressure on the player, be it indirectly by way of a social facilitation effect in which the presence of others is a source of arousal that transfers to gaming performance (Bowman et al., 2013) or directly by way of the social interactions of tandem play (when several people engage a single-player game, together; Consalvo, 2017) that can compel players to make in-game decisions aimed at maintaining the social interaction rather than accomplishing in-game goals (see also Consalvo and colleagues, Chapter 9 of this volume). The growth of online gaming has brought with it a renewed interest in the social dimensions of games, given that these spaces provide social interactions with numerous and non-collocated individuals (Cole & Griffiths, 2007; Yee, Ducheneaut, & Nelson, 2012). If we consider the notion of extroverted personality types as those who are energized by the demands of social interaction (Jung, 1921), then the positive correlation between extroversion and online gaming found by Huh & Bowman (2008) comports with the suggestion that online games might, for some people, provide spaces for superior human interaction. Kowert and Oldmeadow (2013, 2014) likewise find that online games are particularly social for individuals who are apprehensive to communicate outside of games, given that games provide players the opportunity to control both their self-representation (via avatar selection) as well as the environment in which the communication occurs. Follow-up work by Kowert, Domahidi, and Quandt (2014) found that self-identified shy individuals found the interactions in video games to be far less demanding, and therefore, were more comfortable communicating with others. Such findings are largely supported through the hyperpersonal model of communication (Walther, 1996) by which individuals engaging in mediated interpersonal interactions can form deeply meaningful relationships when motivated to do so, and discussions of electronic propinquity (Walther & Bazarova, 2008) likewise suggest that the various social cues present in digital environments, along with the user’s perceived social relationships with the users signaling those cues, can foster a sense of closeness and social presence with others. Even when players are not directly engaging socially with others, their co-presence provides both an audience and ambient social backdrop to gameplay (Ducheneaut, Yee, Nickell, & Moore, 2006). In fact, such audience effects might be core to the appeal and demand of 14

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game streaming, in which gamers broadcast their gameplay to online audiences (Lin, Bowman, Lin, & Chen, 2017) in a merging of gaming and social networks (see Velez and colleagues, Chapter 12 of this volume). When talking about the presence of other social actors, we need not assume that those social actors are humans. For example, gamers users can have variably social relationships with their avatars that span the asocial, parasocial, and fully social (Banks & Bowman, 2016a), and these various social relationships can impact on how games are played. For example, Chen (2011) found that elite World of Warcraft (Blizzard Entertainment, 2004) players tended to burn out as they progressed through the game, as they found themselves often spending as much time coaching and training younger players as they did trying to play the game for themselves. Banks (2013) suggested that one reason for this shift in playstyle might be explained by a shift in how those players saw their avatar. Her data identified four rather stable player-avatar relationship types in the Avatar as Tool, Avatar as Me, Avatar as Symbiote, and Avatar as Other that progress, respectively, in the relative sociality that the player sees in the relationship. Whether or not those elite WoW players began with a Me orientation (in which they identified heavily with their on-screen character) or an Other orientation (in which they might have treated the on-screen character as a distinct social being), over time, their ­player-avatar relationship likely began to shift toward an asocial being for accomplishing in-game tasks, reducing social demand toward the avatar (and perhaps, boosting the social demands of the younger players in need of tutelage). Linguistic analysis of how players talk about their avatars (Banks & Bowman, 2016b) found avatar-as-other players to be significantly more likely to refer to their avatar in the third person, discussing it as a distinct social other with its own needs, which the player in turn feels compelled to respect in gameplay practice. To illustrate this, Banks (2018) tells a story of a player and his character Labris, and their first encounter with “The Art of Persuasion” mission in WoW (Wowhead.com, n.d.) in which the game asks the player to torture an in-game character: It is fortunate you’re here, [player]. You see, the Kirin Tor code of conduct frowns upon our taking certain “extreme” measures – even in desperate times such as these. You, however, as an outsider, are not bound by such restrictions and could take any steps necessary in the retrieval of information. Do what you must. We need to know where Lady Evanor is being held at once! I’ll just busy myself organizing these shelves here. Oh, and here, perhaps you’ll find this old thing useful. (Wowhead.com, n.d.) 15

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As recounted in Banks (2018), the player explained that as a gamer he wanted to see the mission play out, but that he could not bring himself to force Labris to engage in an action that, according to the player, “[Labris] would not do that for a whole host of reasons that I know are personal for him,” (p. 6). In a sense, the avatar Labris exerted the same social pressure on the player as flesh-and-blood social others can exert on each other. Although it might be easy to assume that the social demands of others, either human or digital, are really just manifestations of other demands— we might think differently when engaging others, or we might feel different social emotions when around friends and family, or we might coordinate our movements with others—it is plausible that social demands can represent their own unique source. As suggested by Banks and Carr (2017), such demands are likely at an intersection of variably implicit or explicit awareness of and response to the other. Moreover, and through the lens of the player-program dialogue, this other can be located either inside or outside of the game context and is not necessarily human—the program itself can exert and demand social attention.

Conclusion From the start of SpaceWar!, video games continue to demand our attention, and this demand has evolved to pull on the player’s cognitive, emotional, physical, and even social resources. Their motivational pull, as well as their effects, have fascinated psychologists, parents, policy-makers, and a plethora of other stakeholders for as long as the medium has prevailed. The scientific record is rife with critical and empirical discussions of the role that games play in society, yet the present chapter hopes to re-center some of these debates as less about games as a phenomenon and more about the dialogic interaction of the game and the player—that is, from a media psychology perspective (Rutledge, 2013). Although surely more complex than presented here, at least four discrete dimensions have been identified that serve to orient future research into the gaming experience and toward consideration. For example— and noting that a more complete accounting of the implications of these demand sources is threaded throughout the rest of this volume—we might examine the extent to which these demand sources compliment or counteract each other. Fielder and Garcia (1987) suggest in their cognitive resource theory that increased levels of stress among decision makers (the gamer, in the player-program dialogue) tends to reduce the ability to engage in rational thought; such a perspective might allow us to understand potential conflicts between intense emotions and intense on-screen actions examined by Oliver et al. (2015) in video games. We might also consider that increased arousal, such as from the physical demand of engaging a motion controller or the mere presence of social others, could 16

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be transferred via misattribution mechanisms (Bryant & Miron, 2003) and reappraised by the player as highly enjoyable (in a sense, showing how physical and social demand mechanisms could impact down-the-line emotional reactions to the game). Moreover, experienced gamers surely have some expectation for demand (at least, non-specified) from their prior experience, given that “[past] pleasure stamps in the preference” for future media engagement (Zillmann & Bryant, 1985, p. 159) and thus, and in borrowing a bit more from Bucy (2004), it seems critical to not only consider player’s prior experiences and how they might impact the relative demand of any given video game, but we might also consider the a priori desires for differential levels of demand from video games systems (critical to mood management and regulation processes, see Bowman et al., 2013) as well as the violation of such expectations. One example of the violation of gamer’s demand expectations can be found in the debate around the earlier-mentioned “No Russian” level—while the programmers designed the level to be emotionally demanding, many players felt surprised and even a bit shaken by the level (Klepek, 2015). Of course, expectancy violations are not always negative (see Burgoon, 2015) and to this end, more attention should be given to the sort of cognitive, emotional, physical, and social engagements that players are anticipating when they enter a player-program dialogue. In the early 1960s, the Kluge Room hackers felt compelled to design a demanding program to tax the limitations of the PDP-1 and, in return, they ended up with a program that continues to demand from its users. Their SpaceWar! rages on far beyond the life-span of the PDP-1 (an emulated version of the original software is available online at http://spacewar.oversigma.com/), and as video games continue to become increasingly interactive, they continue to become increasingly demanding of their users. The player-program dialogue that the Kluge Room launched is a complex one and to this end, this opening chapter takes one well-aimed shot around the gravity well of extant work and toward the end-goal of sparking future work.

Ludography Call of Duty: Modern Warfare 2. (2009). Los Angeles, CA: Infinity Ward. Dead Space. (2008). Redwood City, CA: Electronic Arts. Final Fantasy. (1987). Tokyo, Japan: Square. Mortal Kombat. (1992). Chicago, IL: Midway. Pong. (1972). Sunnyvale, CA: Atari. Resident Evil. (1996). Osaka, Japan: Capcom. SpaceWar! (1962). Cambridge, MA: Steve Russell. Super Mario Bros. (1985). Kyoto, Japan: Nintendo. World of Warcraft. (2004). Irvine, CA: Blizzard Entertainment.

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Note 1 We should note here that Bowman (2016) had originally labeled this source of demand as being behavioral in nature, under the assumption that the player has to engage various behaviors in order to cause on-screen action. However, the challenge from Eden and colleagues (Chapter 6, this volume; referred to in the section above on “Cognitive Demand”) was sobering on this point as they suggested that the label of behaviors might implicate the in-game actions of the players as the demand source, more so than the physical actions of the players.

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Grizzard, M., Tamborini, R., Lewis, R. J., Wang, L., & Prabhu, S. (2014). Being bad in a video game can make us morally sensitive. Cyberpsychology, Behavior, & Social Networking, 17, 499–504. doi:10.1089/cyber.2013.0658 Grodal, T. (2000). Video games and the pleasures of control. In D. Zillmann & P. Vorderer (Eds.), Media entertainment: The psychology of its appeal (pp. 197–213). Mahwah, NJ: LEA. Haraway, D. (1991). Simians, cyborgs, and women: The reinvention of nature. New York, NY: Routledge. Hart, S. G. (2006). NASA-Task Load Index (NASA-TLX); 20 years later. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 50(9), 904–908. doi:10.1177/154193120605000909 Hartmann, T., Toz, E., & Brandon, M. (2010). Just a game? Unjustified virtual violence produces guilt in empathetic players. Media Psychology, 13, 339–363. doi:10.1080/15213269.2010.524912 Hemenover, S., & Bowman, N. D. (2017, May). Video games, emotion, and emotion regulation: Bridging the gap. Paper presented at the annual convention of the International Communication Association, San Diego, CA. Huh, S., & Bowman, N. D. (2008). Perception and addiction of online games as a function of personality traits. Journal of Media Psychology (online), 13(2), 1–31. Retrieved from www.calstatela.edu/faculty/sfischo/Bowman%20online%20 game%20addiction-final.doc Ivory, J. D. (2015). A brief history of video games. In R. Kowert & T. Quandt (Eds.), The video game debate: Unravelling the physical, social, and psychological effects of digital games (pp. 1–21). New York, NY: Routledge. Jansz, J. (2005). The emotional appeal of violent video games for adolescent males. Communication Theory, 15(3), 219–241. doi:10.1111/j.1468-2885.2005.tb00334 Joeckel, S., Bowman, N. D., & Dogruel, L. (2012). Gut or game: The influence of moral intuitions on decisions in virtual environments.  Media Psychology, 15(4), 460–485. doi:10.1080/15213269.2012.727218 Jones, M. B. (1984). Video games as psychological tests. Simulation & Games, 15(2), 131–157. doi: 10.1177/0037550084152001 Jung. C. G. (1921). Psychological types (trans. by H. Godwyn Baynes). Retrieved from http://psychclassics.yorku.ca/Jung/types.htm. Juul, J. (2011). Half-real: Video games between real rules and fictional worlds. Cambridge, MA: MIT Press Klepek, P. (2015, October 23). That time Call of Duty let you shoot up an airport. Kotaku. Retrieved from https://kotaku.com/that-time-call-of-duty-let-youshoot-up-an-airport-1738376241 Kowert R. (2017). Final Fantasy. In R. Mejia, J. Banks, & A. Adams (Eds.), 100 greatest video game franchises (pp. 65–66). Lanham, MD: Rowman & Littlefield. Kowert, R., Domahidi, E., & Quandt, T. (2014). The relationship between online video game involvement and game-related friendships among emotionally sensitive individuals. CyberPsychology, Behavior, and Social Networking, 17(7), 447–453. doi:10.1089/cyber.2013.0656 Kowert, R., & Oldmeadow, J. A. (2013). (A)Social reputation: Exploring the relationship between online video game involvement and social competence. Computers in Human Behavior, 29(4), 1872–1878. doi:10.1016/j.chb.2013.03.003

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Kowert, R., & Oldmeadow, J. A. (2014). Playing for social comfort: Online video game play as a social accommodator for the insecurely attached. Computers in Human Behavior (online), 53, 556–566. doi:10.1016/j.chb.2014.05.004 Lang, A. (2000). The limited capacity model of mediated message processing. Journal of Communication, 50, 46–70. doi:10.1111/j.1460-2466.2000.tb02833 Lang, P, Bradley, M. M., & Cuthbert, B. N. (1998). Emotion, motivation, and anxiety: Brain mechanisms and psychophysiologiy. Biological Psychiatry, 44(12), 1248–1263. doi:10.1016/S0006-3223(98)00275-3 Lazarus, R. S. (1991). Emotion and adaptation. New York, NY: Oxford University Press. Li, W., Garland, E. L., O’Brien, J. E., Tronnier, C., McGovern, P., Anthony, B., & Howard, M. O. (2017). Mindfulness-oriented recovery enhancement for video game addiction in emerging adults: Preliminary findings from case reports. International Journal of Mental Health and Addiction. doi:10.1007/s11469017-9765-8 Lin, J-H. Bowman, N. D., Lin, S-F., & Chen, S. (2017, May). Setting the digital stage: Defining game streaming in the scope of game studies. Paper presented at the annual convention of the International Communication Association, San Diego, CA. Lynch, T., & Martins, N. (2015). Nothing to fear? An analysis of college students’ fear experiences with video games. Journal of Broadcasting & Electronic Media, 59, 298–317. doi:10.1080/08838151.2015.1029128 Mahood, C., & Hanus, M. (2017). Role-playing video games and emotion: How transportation into the narrative mediated the relationship between immoral actions and feelings of guilt. Psychology of Popular Media Culture, 6(1). doi:10.1037/ ppm0000084 Martinez-Garza, M. M., & Clark, D. B. (2017). Two systems, two stances: A novel theoretical framework for model-based learning in digital games. In P. Wouters & H. van Oostendorp (Eds.), Instructional techniques to facilitate learning and motivation of serious games (pp. 37–58). Cham, Switzerland: Springer. McGloin, R., Farrar, K. M., Krcmar, M., Park, S., & Fishlock. J. (2016). Modeling outcomes of violent video game play: Applying mental models and model matching to explain the relationship between user differences, game characteristics, enjoyment, and aggressive intentions. Computers in Human Behavior, 62, 442–452. doi: 10.1016/j.chb.2016.04.018 McGonigal, J. (2011). Reality is broken: Why games make us better and how they can change the world. New York, NY: Penguin Press. McLuhan, M. (1964). Understanding media. New York, NY: McGraw-Hill. Meier, S. (2012, March). Interesting decisions. Presentation and the Game Developers Conference, San Francisco, CA, March 5–9, 2012. Nath, T. (2016, June 13). Investing in video games: This industry pulls in more revenue than movies, music. Nasdaq. Retrieved from www.nasdaq.com/article/ investing-in-video-games-this-industry-pulls-in-more-revenue-than-moviesmusic-cm634585 Noyes, J. (1983). The QWERTY keyboard: A review. International Journal of Man-Machine Studies, 18(3), 265–281. doi:10.1016/S0020-7373(83)80010-8 Oliver, M. B., Bowman, N. D., Woolley, J. K., Rogers, R., Sherrick, B., & Chung, M-Y. (2015). Video games as meaningful entertainment experiences. Psychology of Popular Media and Culture, 5(4), 390–405. doi:10.1037/ppm0000066

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Oliver, M. B., & Raney, A. A. (2011). Entertainment as pleasurable and meaningful: Identifying hedonic and eudaimonic motivations for entertainment consumption. Journal of Communication, 61, 984–1004. doi:10.1111/j.1460-2466.2011.01585 Olson, C. K. (2010). Children’s motivations for video game play in the context of normal development. Review of General Psychology, 14, 180–187. doi:10.1037/a0018984 Panksepp, J. (1982). Toward a general psychobiological theory of emotions. Behavioral and Brain Sciences, 5, 407–467. Parisi, D. (2015). A counterrevolution in the hands: The console controller as an ergonomic branding mechanism. Journal of Games Criticism, 2(1), 1–23. Previte, E. A. (2003). Insert coins to slay! Regulating children’s access to violent arcade games. Villanova Sports & Entertainment Law Journal, 1, 69–102. Raney, A. A. (2004). Expanding disposition theory: Reconsidering character liking, moral evaluations, and enjoyment. Communication Theory, 14(4), 348– 369. doi:10.1111/j.1468.2885.2004.tb00319 Ravaja, N., Saari, T., Salminen, J., Laarni, J., & Kallinen, K. (2006). Phasic emotional reactions to video game events: A psychophysiological investigation. Media Psychology, 8, 343–367. doi:10.1207/s1532785xmep0804_2 Reisinger, D. (2011, October 11). 91 percent of kids are gamers, research says. CNet. com. Retrieved from www.cnet.com/news/91-percent-of-kids-are-gamers-researchsays/ Rogers, R., Bowman, N. D., & Oliver, M. B. (2015). It’s not the model that doesn’t fit, it’s the controller! The role of cognitive skills in understanding the links between natural mapping, performance, and enjoyment of console video games. Computers in Human Behavior, 49, 588–596. doi:10.1016/j.chb.03.027 Rutledge, P. B. (2013). Arguing for media psychology as a distinct field. In K. E. Dill (Ed.), The Oxford handbook of media psychology (pp. 43–58). New York, NY: Oxford University Press. Schell, J. (2013). The future of storytelling: How medium shapes society. Game Developers Conference. Retrieved from www.gdcvault.com/play/1018026/ The-Future-of-Storytelling-How Sherry, J. L. (2004). Flow and media enjoyment. Communication Theory, 14, 328–347. doi:10.1111/j.1468-2885.2004.tb00318 Sherry, J. L., Lucas, K., Greenberg, B., & Lachlan, K. (2006). Video game uses and gratifications as predicators of use and game preference. In J. Bryant & P. Vorderer (Eds.), Playing video games: Motives responses, and consequences (pp. 213–224). Mahwah, NJ: LEA. Skalski, P., Tamborini, R., Shelton, A., Buncher, M., & Lindmark, P. (2011). Mapping the road to fun: Natural video game controllers, presence, and game enjoyment. New Media & Society, 13(2), 224–242. doi:10.1177/1461444810370949 Square Enix. (2017, January 31). Square Enix kicks off Final Fantasy 30th anniversary celebration. Press Release. Retrieved from http://press.na.square-enix.com/ releases/905/square-enix-kicks-off-final-fantasy-30th-anniversary-celebration Steinkuehler, C. A., & Williams, D. (2006). Where everybody knows your (screen) name: Online game as “third places.” Journal of Computer-Mediated Communication, 11(4), 885–909. doi:10.1111/j.1083-6101.2006.00300 Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 4(4), 73–93. doi:10.1111/j.1460-2466.1992.tb00812

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Stromer-Galley, J. (2004). Interactivity-as-product and interactivity-as-process. The Information Society, 20(5), 391–394. doi:10.1080/09172240490508081 Sundar, S. S. (2004). Theorizing interactivity’s effects. The Information Society, 20(5), 385–389. doi:10.1080/01972240490508072 Sundar, S. S., Jia, H., Waddell, T. F., & Huang, Y. (2015) Toward a Theory of Interactive Media Effects (TIME): Four models for explaining how interface features affect user psychology. In S. S. Sundar (Ed.), The handbook of the psychology of communication technology (pp. 47–86). Chichester: John Wiley & Sons. Tamborini, R., & Bowman, N. D. (2010). Presence in video games. In C. Bracken & P. Skalski (Eds.), Immersed in media: Telepresence in everyday life (pp. 87–109). New York, NY: Routledge. Tamborini, R., Bowman, N. D., Eden, A., Grizzard, M., & Organ, A. (2010). Defining media enjoyment as the satisfaction of intrinsic needs. Journal of Communication, 60, 758–777. doi:10.1111/j.1460-2466.2010.01513 Tamborini, R., Grizzard, M., Bowman, N. D., Reinecke, L., Lewis, R., & Eden, A. (2011). Media enjoyment as need satisfaction: The contribution of hedonic and non-hedonic needs. Journal of Communication, 61(6), 1025–1042. doi:10. 1111/j.1460-2466.2011.01593 Tan, E. S. (2008). Entertainment is emotion: The functional architecture of the entertainment experience. Media Psychology, 11(1), 28–51. doi:10.1080/​ 15213260701853161 Thomas, W. I., & Thomas, D. S. (1928). The child in America: Behavioral problems and programs. New York, NY: Knopf. Totilo, S. (2012, August 2). The designer of Call of Duty’s “No Russian” massacre wanted you to feel something. Kokatu. Retrieved from https://kotaku.com/5931235/ the-designer-of-call-of-dutys-no-russian-massacre-wanted-you-to-feel-something Walther, J. B. (1996). Computer-mediated communication: Impersonal, interpersonal, and hyperpersonal interaction. Communication Research, 23(1), 3–43. doi:10.1177/009365096023001001 Walther, J. B., & Bazarova, N. N. (2008). Validation and application of electronic propinquity theory to computer-mediated communication. Communication Research, 35(5), 622–645. doi:10.1177/0093650208321783 Wowhead.com (n.d.). The art of persuasion. Wowhead. Retrieved from www. wowhead.com/quest=11648/the-art-of-persuasion Wulf, T., Breuer, J., Bowman, N. D., & Velez, J. (2017). Once upon a game: Gaming nostalgia, need-satisfaction, and well-being. Mediapsychology 2017, 11–12. Landau: University of Landau-Koblenz, Germany. Yee, N. (2006). Motivations for play in online games. Cyberpsychology & Behavior, 9(6), 772–775. doi:10.1089/cpb.2006.9.772 Yee, N., Ducheneaut, N., & Nelson, L. (2012). Online gaming motivations: Development and validation. Proceedings of SIGCHI Conference on Human Factors in Computing Systems, pp. 2803–2806. doi:10.1145/2207676.2208681 Zillmann, D., & Bryant. J. (1985). Affect, mood, and emotion as determinants of selective exposure. In D. Zillmann & J. Bryant (Eds.), Selective exposure to communication (pp. 157–190). New York, NY: Routledge.

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2 VIDEO GAMES AND COGNITIVE SKILLS C. Shawn Green

As video games have become ever more popular, there has been a concomitant increase in interest in the extent to which video game play is capable of altering fundamental aspects of our humanity—including our social behaviors, our emotions, and our cognitive skills. Simultaneously, the rise of many so-called brain training games, and the corresponding backlash that has occurred as ever more evidence has accrued suggesting that many such paradigms had made claims that could not be backed up by science (Lorant-Royer, Munch, Mescle, & Lieury, 2010; Owen et al., 2010; Schute, Ventura, & Ke, 2015), has resulted in skepticism that modern technology can alter our cognitive abilities. Here, I will review the evidence that enhancements in cognition can be produced through video game play. However, critical in this, is the idea that not all games are created equal with respect to changing cognitive function. Instead, the current literature suggests that only a subset of video games, specifically those that place significant demands on the cognitive system, are capable of inducing long-term increases in cognitive function. In discussing this literature, I will begin with a few fundamentals of cognitive learning. This includes the fact that while inducing enhancements in the ability to perform individual cognitive tasks is easy, producing enhancements that generalize to new tasks is much more difficult. I will then turn to the question of how this tendency for learning to be task specific can be overcome and why one subtype of video game, which we call action video games, has exactly those properties that could produce such general learning outcomes. Next, I will consider the typical research methods that have been used to examine the impact of action video games on cognitive skills, followed by an examination of the types of cognitive changes that have been seen to arise via action video game

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training, including not just lab-based measures, but real-world measures as well. I will conclude by discussing future directions for the field, including the need to alter research methods and research questions to take into account the myriad ways that both video games and video game players have changed over the past 15 to 20 years.

Plasticity, Learning, and the Curse of Learning Specificity For much of the 20th century, the dominant view in the domain of cognitive neuroscience held that the brain, once it reached an adult-like state, was reasonably fixed (Hubel, Wiesel, & LeVay, 1977). Over the past two decades though, this view has been thoroughly supplanted, with the prevailing view now positing that the brain retains an immense capacity for plasticity even into old age (Bavelier, Levi, Li, Dan, & Hensch, 2010). Such research indicating the power of the brain to reorganize and adapt in response to experience throughout the entirety of the lifespan (likely in concert with the baby-boomer generation just beginning to hit the age range in which perceptual and cognitive skills begin to naturally decline) has in turn resulted in a surge of interest in the development of behavioral training regimens to improve perceptual and cognitive function (Green & Bavelier, 2008). The excitement around the potential for such training regimens has been further buttressed by the fact that research in perceptual and cognitive learning has consistently shown that humans tend to show improvement on most perceptual and cognitive tasks given appropriate training (Sagi, 2011). Indeed, through dedicated long-term training, human performance on measures of perceptual and cognitive skill can often reach seemingly astounding levels. Take, for instance, one classic task in the perceptual learning literature called the Vernier acuity task. This task is conceptually very simple. On each trial of the task, participants are shown two lines, one above the other, with the top line being very slightly displaced either to the right or the left of the bottom line. The participant’s goal is to correctly indicate the direction of displacement. Given sufficient practice on this task, most participants will show marked improvement— eventually learning to resolve offsets of just a few seconds of arc (Fahle & Edelman, 1993). To give a tangible feel for how fine a visual judgment this is, it is roughly the width of a pencil if viewed at the distance of a mile! And this is far from an isolated case. The literature is literally filled with examples of participants learning to make remarkably fast, accurate, detailed perceptual task judgements and/or to process and respond to enormous amounts of complex cognitive information given appropriate training on the individual tasks at hand (Bavelier, Green, Pouget, & Schrater, 2012; Ericsson, Krampe, & Tesch-Romer, 1993; Sagi, 2011; Schmidt & Bjork, 1992). 26

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Unfortunately, though, while participants are clearly able to improve their ability to perform individual tasks, the benefits of such learning typically fail to generalize to any new tasks; participants improve on the one exact task they were trained on and nothing else. For example, in the case of Vernier acuity learning, although participants can reach incredible levels on their trained task, if a seemingly minor change to the experimental setup is then made—such as rotating the lines by 90 degrees, so they are horizontally aligned rather than vertically aligned—participants’ performance returns to untrained levels. In other words, their performance on the horizontal lines is the same as it would have been if they hadn’t received any training at all (Fahle, 2005; Snell, Kattner, Rokers, & Green, 2015). Because reaching the goal of real-world impact necessitates that any learning be broadly transferable,1 this tendency toward learning specificity has sometimes been referred to as the curse of specificity (Bavelier et al., 2012). It is with this “curse” in mind, that the cognitive and perceptual effects of playing certain types of video games, dubbed action video games for the balance of this chapter, has been of particular scientific interest. This interest is deserved, as it stems from promising empirical observations. To again give away the punchline right from the beginning of the chapter: action video game training has been repeatedly shown to produce not only improvements on the games themselves, but also to produce improvements on measures of perceptual and cognitive skill that look nothing like the trained games. In other words, action video game training produces generalizable enhancements in perceptual and cognitive function. However, before diving into the empirical findings in this domain, it is worth first taking a short detour to discuss a few key theoretical and methodological issues that arise when considering the perceptual and cognitive impact of this type of training.

Video Games: Too Broad a Category to Ask Questions About Behavioral Impact One of the most common questions that individuals who study the impact of video game play on human behavior faces when speaking, not only with lay audiences (e.g., parents, teachers, doctors, etc.), but even with colleagues who are not well versed in gaming, is the following: “In what ways does video game play alter behavior?”2 Implicit in this question is an important erroneous belief—namely that video games are a single entity, or at a minimum, that the label “video games” describes a set of experiences that are sufficiently similar to one another that they can be treated as such. In practice, nothing could be further from the truth. Video games are a superordinate category label, under which fall an incredibly large and variable set of experiences. For instance, the label of video 27

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games applies equally well to games with incredibly simple and cartoonish graphics—such as in Angry Birds (Rovio Entertainment, 2009)—to incredibly realistic graphics, with settings and characters rendered in exquisite detail—such as in Rise of the Tomb Raider (Microsoft Studios, 2015; down to hair/eyes/skin that shows visual changes in response to temperature and light). Video games can be solitary single-player experiences—such as in Bioshock—or can be played with hundreds or perhaps thousands of other individuals—such as in World of Warcraft (Blizzard Entertainment, 2004). Some video games can be completed in minutes; others require hours, weeks, or years to complete. Video games can require pro-social behaviors or anti-social/violent behaviors. Video games can be nothing more than a simple set of rules to be followed or can involve a complex narrative structure. In short, the extreme flexibility of the media allows for all kinds of experiences. Thus, because the behavioral outcome of an experience depends entirely on the nature of the experience (Adams & Mayer, 2014), a label that lumps so many exceedingly diverse experiences together is unlikely to have any predictive power whatsoever. To some extent, asking, “In what ways does video game play alter behavior?” is akin to asking, “In what ways does eating food alter the body?” Foods (as a superordinate category) can vary wildly in terms of their calorie count, in their distribution of proteins, carbohydrates, and fats, in the presence of vitamins and minerals, and in any number of other characteristics—and it is these specifics that determine the way in which a particular food will impact the body. The same is true of video games. Social psychologists who study aggression are generally not interested in the impact of video games—they are interested only in those video games that contain violent content. Educational psychologists who study academic content acquisition are generally not interested in the impact of video games—they are interested in educational video games. And finally, cognitive psychologists are generally not interested in the impact of video games—instead, the type of video game that has been of most interest in this domain has been what are commonly labelled action video games (cf. Green & Bavelier, 2006a, 2006b).

What Are Action Video Games? Most theories of learning generalization posit that generalization of learning is most likely to occur when the training task places processing load on the same underlying processes as the transfer task(s). Given this core idea, the type of games that would be most likely to enhance cognitive processes would thus be those that are associated with significant cognitive demands (with cognitive demands being one of several types of demands that video games are capable of exerting—see Bowman et al., 2016; Chapter 1 this volume). Within the literature on the perceptual and 28

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cognitive impact of video games, those games that do exactly this—that place significant demands upon the perceptual and cognitive systems have together been most commonly referred to as action video games (Spence & Feng, 2010). And while it is beyond our current ability to produce a set of quantitative rules that can be applied to perfectly separate the various video game genres, there are a set of qualitative features that all games that are given the label of action video games share. In particular, action video games are those that involve exceptional speed (both in terms of the velocity of moving items and the brevity of transient events). These games also involve extraordinary perceptual load (e.g., the individual must track many independently moving objects; critical objects often appear in the far periphery), cognitive load (e.g., there is the need to consider many possible outcomes; there is significant temporal and spatial uncertainty that must be dealt with), and/or motor load (e.g., there is the need to create and constantly re-evaluate multiple action plans; see Chapter 1, this volume, for a review of evidence for these types of demands). The most common types of games that fit these criteria are so-called first-person shooter games such as the Call of Duty (Activision, 2005), Battlefield (Electronic Arts, 2002), and Medal of Honor series (Electronic Arts, 1999), and third-person shooter games such as the Gears of War (Microsoft Studios, 2006) and Grand Theft Auto series (Rockstar Games, 1997). As we will see, these games produce positive impacts on perceptual and cognitive skills that are not seen as a result of playing other types of games (e.g., from playing simulation-style games).

How Do We Study the Impact of Action Video Games on Perception and Cognition? Most research examining the relationship between perceptual/cognitive skills and action video game play has utilized one of two general scientific approaches: (1) the cross-sectional approach and (2) the intervention approach. In a typical cross-sectional study, researchers take advantage of the fact that there is substantial natural variation in the extent to which individuals do/do not play action video games as part of their daily life. Two extreme-experience groups are recruited. One group consists of individuals who naturally choose to avidly engage with action video games (e.g., have played five or more hours a week of action games for the past year). These are referred to as action video game players or AVGPs. The other group consists of individuals who essentially never play action video games and generally do little gaming of any type. These are referred to as non-action video game players or NVGPs. The groups are either recruited overtly (e.g., from posters that indicate the lab is looking for individuals who are heavy action gamers or who are non-gamers) or covertly (e.g., in many introductory psychology research participation pools in the US, individuals fill out a large survey at the beginning of the semester and 29

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participants can be selected based upon their responses to game-related questions put in this survey without their being aware that this determined their selection).3 The final step in this type of study is simply to measure the perceptual or cognitive skill(s) of interest in the two groups using well-validated tasks and determine whether there is a significant difference between the AVGPs and NVGPs. Critically, the tasks that are employed in such studies bear little to no resemblance to any commercial video games; instead, these studies utilize basic psychophysical tests and their associated stimuli. This is important if the goal is to show that any differences between the groups are at the level of core perceptual/cognitive function, rather than reflecting a simple difference in the extent of prior experience with the tasks/stimuli. The tasks themselves usually involve a simple yes/no or A/B-type judgement (i.e., “Did you see this target shape or not?”; “Did you see Target Shape A or Target Shape B”?), while the stimuli are most commonly lines, black and white gratings, alpha-numeric characters, or simple shapes presented on white or gray backgrounds in order to best isolate individual perceptual or cognitive functions. It is thus the case that any differences observed between AVGPs and NVGPs would represent broader “transfer” than is typically observed via perceptual or cognitive training. Indeed, the difference between an action video game and a black and white grating is far greater than the difference between a vertical line and a horizontal line. It would thus be of significant interest if training on action video games produces enhancements in tasks that involve black and white gratings, while training on tasks that involve vertical lines alone produces no benefits on tasks that involve horizontal lines alone. The second study type is the intervention study design. While correlational (cross-sectional) studies have value in addressing many scientific questions, they cannot be used to demonstrate a causal relationship between action game playing and changes in cognitive or perceptual abilities. Indeed, potential confounds such as population bias (e.g., perhaps individuals who are born with better perceptual skills are drawn to playing video games) are always a concern with cross-sectional work. Thus, in order to establish that the act of playing action video games causes enhancements in perceptual and/or cognitive skills, an intervention study (i.e., a true experiment) is performed. Participant recruitment is similar to the recruitment of NVGPs in cross-sectional designs (i.e., individuals are selected who have minimal video game experience). All participants next undergo a series of pre-test measures of the cognitive/ perceptual skills of interest (again, as described above—validated measures of core perceptual/cognitive abilities and that employ simple sterile stimuli that bear no physical resemblance to the types of scenes seen in video games). The full set of participants are then randomly assigned to one of two conditions—the experimental condition or the active control 30

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condition. Participants assigned to the experimental condition are asked to play a commercial action video game for some pre-determined number of hours. Most studies in the field have used between ten and 50 hours of total training time (reflecting evidence suggesting that the processes of interest are not necessarily amenable to change given extremely short training durations; Bediou et al., 2018). And because video game training follows the general principles seen in all learning studies, proper study design dictates that this training be distributed in time (Baddeley & Longman, 1978). In our research group, we typically allow no more than one hour per day of training and no more than five hours per week. A 50-hour training study will therefore take a minimum of ten weeks to complete. Participants assigned to the control condition are asked to play a non-action commercial video game according to the same schedule as above. Critically, the non-action video game is selected to contain no, or at least minimal, “action” content (i.e., minimal speed, minimal perceptual, cognitive, and/or motor load—in all minimal cognitive demand), while being matched with the action video game in terms of engagement and entertainment value. This allows researchers to rule out subtle confounds, such as the possibility that engaging activities alone are sufficient to produce cognitive improvements. A host of different games have been used as active control games in the literature to-date including: Tetris (Various, 1984; research by Green & Bavelier, 2003; Strobach, Frensch, & Schubert, 2012), games from The Sims series (Electronic Arts, 2000; research by Green & Bavelier, 2007; Green, Pouget, & Bavelier, 2010), Restaurant Empire (Enlight Software, 2003; research by Bejjanki et al., 2014), and Ballance (Atari, 2006; research by Feng, Spence, & Pratt, 2007). Finally, after participants have finished their assigned number of video game training hours, they are given the same basic tests as they completed at pre-test. Critically, these tests are always given at least 24-hours after the final video game training session in order to ensure that any transient changes in the participants’ internal state that could be induced by playing their respective video games have had time to dissipate. Indeed, this is one major difference between the experimental studies examining the perceptual/cognitive consequences of video game play (where we are not interested in transient changes related to arousal) versus studies examining the short-term impact of violent video games on social behaviors such as aggression (where many of the primary mechanisms of interest are linked to transient changes in arousal). The final measure of interest is whether the experimental group showed larger improvements on the abilities of interest than the active control group from pre-test to post-test. Importantly, because both the experimental and control conditions are entertainment video games, if the experimental training (i.e., action video game play) produces larger gains than control training (non-action video game play), it conclusively demonstrates, at a minimum, that the observed 31

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enhancements are not an effect of all “video games”—but instead, are an effect of certain types of video games (in particular, those games that we a priori believed were associated with significant cognitive demand). Given this broad methodology, we next turn to the question of what exact abilities have been seen to be enhanced via action video game training.

Cognitive Benefits Seen to Arise via Action Video Game Play While researchers have examined the potential for action video games to impact a wide variety of perceptual and cognitive functions, for the purposes of this chapter, three core areas will be reviewed—perception, top-down attention, and executive function. Together, these represent the domains where the most work has been done and thus are the domains where the strongest conclusions can be drawn (in a somewhat circular fashion, because these are the domains in which action video games are believed to place the most significant demands, they are the domains where the potential impact of action video game play has most thoroughly been investigated). However, this short review cannot hope to do justice to the full literature and as such, interested readers are directed to a number of more thorough reviews and meta-analytic analyses of the literature (Green & Bavelier, 2012; Hubert-Wallander, Green, & Bavelier, 2011; Powers & Brooks, 2014; Powers, Brooks, Aldrich, Palladino, & Alfieri, 2013). Perception. Perception, in particular visual perception, is one domain where a large amount of research has been conducted examining the potential impact of action video game play. For example, Li and colleagues (R. Li, Polat, Makous, & Bavelier, 2009) examined the impact of action video game play on contrast sensitivity. Contrast sensitivity, or the ability to detect small changes in luminance in adjacent parts of the visual scene, is classically considered to be one of the fundamental building blocks of visual perception. Indeed, without the ability to detect the fact that adjacent parts of the visual world differ in brightness, higher-level visual functions such as object segmentation and recognition would be impossible. As is commonly seen in this literature, the researchers first conducted a cross-sectional study, comparing contrast sensitivity in AVGPs and NVGPs. The task that was employed to measure contrast sensitivity was a simple two-interval forced choice target detection task. A low contrast target (a “Gabor”—or a black and white sine-wave grating blurred via a Gaussian filter to ensure that the target contains no hard edges) appeared in one of two temporal intervals. The participant simply had to indicate in which interval (first or second) they saw the target. The contrast of the target was controlled dynamically, such that when the participant got the answer correct, the target contrast was reduced (i.e., made more difficult to see) and when the participant got the answer incorrect, the 32

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target contrast was increased (i.e., made easier to see). Through this procedure, the investigators could estimate the target contrast that resulted in approximately 75% correct performance. When comparing this measure in AVGPs and NVGPs, they found that AVGPs showed significantly superior contrast sensitivity—in other words, AVGPs could see the target at lower levels of contrast than the NVGPs. Then, to establish that the act of action video game play causes improved contrast sensitivity, a 50-hour intervention study was conducted. While no improvements were seen from pre-test to post-test in the group trained on control, non-action video games (The Sims 2), the group trained on action video games, in this case, the first-person shooter games Unreal Tournament 2004 (Atari, 2004) and Call of Duty), showed significant gains in contrast sensitivity. Similar results have been found for a range of other core perceptual skills beyond contrast sensitivity. This includes enhancements in peripheral vision (Buckley, Codina, Bhardwaj, & Pascalis, 2010) and in the ability to process moving stimuli (Hutchinson & Stocks, 2013)—although both of these studies only included a cross-sectional component. And while the vast majority of the research focus has been in the link between action gaming and visual skills, the research that exists on the topic suggests that there are enhancements in other sensory modalities as well. For instance, using a cross-sectional design, Donohue and colleagues (Donohue, Woldorff, & Mitroff, 2010), presented AVGP and NVGP participants with visual and auditory stimuli in rapid succession. On some trials, the visual stimulus led the auditory stimulus (by a very small amount of time), while on other trials, the auditory stimulus led the visual stimulus. AVGPs demonstrated a superior ability to determine the correct temporal order of the visual and auditory stimuli, which the authors argued is indicative of enhancements in multi-sensory integration abilities in AVGPs. Top-down attention. All visual tasks, by definition, involve “perceptual” processes. However, an additional constraint inherent in the tasks that will be discussed under the category of top-down attention is the need to allocate resources toward task-relevant information and away from task irrelevant information. As such, all of the individual tasks considered will be linked by presence of some amount of distracting/task-irrelevant information in addition to the target/task-relevant information. This, in turn, necessitates the ability to select and enhance the processing of the task relevant information, while reducing the extent to which task irrelevant information is processed, processes that are not needed in the more “pure perceptual” measures discussed in the section above (where targets/ task-relevant information were largely presented in isolation). One such task that has been used repeatedly in the literature on action gaming, is the Useful Field of View task (Ball, Beard, Roenker, Miller, & Griggs, 1988). In this task, participants are required to locate a target that is very briefly presented somewhere in the visual periphery (in some 33

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versions of the task very far in the visual periphery—up to 30 degrees away from fixation) amongst a field of distracting non-target stimuli (sometimes referred to as visual “clutter”). Numerous studies, including both cross-sectional and intervention designs, have shown a significant advantage in AVGPs/those trained on action video games as compared with NVGPs/those trained on non-action video games (Dye & Bavelier, 2010; Feng et al., 2007; Green & Bavelier, 2006a). Similar enhancements in spatial top-down attention have been found using a multitude of other tasks, including crowding tasks (i.e., that examine how close distracting information can be placed next to task-relevant information before it begins to interfere with task performance [Green & Bavelier, 2007]), and with more standard visual search tasks (where participants attempt to find a target from amongst a field of distractors as quickly as possible [Hubert-Wallander, Green, Sugarman, & Bavelier, 2011]). Perhaps not surprisingly then, the same general trend has also been found in tasks that measure temporal, rather than spatial aspects of topdown attention (i.e., where the distractors appear distributed through time, rather than space). This is true, for instance, when looking at performance on the attentional blink task. Here, participants are presented with a rapid stream of black letters, one after another, in the center of the screen. At some point in the stream, a white letter appears, which the participant will need to indicate the identity of at the conclusion of the trial. Then, on 50% of trials, at some point after the white letter, the black letter “X” will appear. The participant will also, at the conclusion of the trial, need to indicate whether or not they saw an “X.” The typical finding is that when the “X” is presented close in time to the white letter target, it is very commonly missed (i.e., attention is drawn to the white letter, this causes an “attentional blink,” and if the “X” is presented during this blink, it will be missed by the participant). Again, action video game play has been linked with enhanced temporal top-down attention (i.e., a reduced “blink” period) both in cross-sectional and intervention designs (Green & Bavelier, 2003). Finally, the same advantage has been seen in tasks that involve topdown attentional control in both space and time. For instance, in the Multiple-Object Tracking Task, participants are shown a number (e.g., from 1 to 7) of blue target circles, moving in the same area as a number of non-target distractor yellow circles. After two seconds, the blue circles change color to yellow (meaning that they are now visually indistinguishable from the non-target distractor circles). The participant must continue to track the previously blue target circles for several seconds, at which point all the circles stop moving and one circle is changed to white. The participant must indicate yes/no, was this white circle one of the originally blue target circles. Both cross-sectional and intervention designs have revealed an action gaming advantage on this task—with 34

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AVGPs/individuals trained on action games being able to successfully track a larger number of target circles than NVGPs/individuals trained on control games (Dye & Bavelier, 2010; Green & Bavelier, 2006b; Trick, Jaspers-Fayer, & Sethi, 2005). Executive functions. The final body of work that will be reviewed here focuses, broadly speaking, on what has been dubbed “executive function” or “cognitive control” tasks. These tasks typically involve coordination of many different subprocesses, including those related to perception, memory, and planning. For example, one very common class of tasks within this domain are “task-switching” tasks. Such tasks involve having participants perform two different tasks on the same basic set of stimuli. For instance, on each trial, participants may be presented with a digit from one to nine (excluding five). On some trials, the participants will be cued to indicate whether the digit is greater than or less than five. On other trials, the participants will be cued to indicate whether the digit is odd or even. One consistent finding in the literature is that participants are slower to make a choice on trials where the task has switched from the previous trial (e.g., Trial 1 = greater/less → Trial 2 = even/odd) than on trials where the task has remained the same as the previous trial (e.g., Trial 1 = greater/less → Trial 2 = greater/less). This slowing is referred to as the “switch cost.” The basic finding in the literature, now replicated across many independent laboratories and using a variety of stimuli and switching conditions, is that AVGPs/individuals trained on action games show a reduced “switch cost” relative to NVGPs/individuals trained on non-action control games (Colzato, van den Wildenberg, Zmigrod, & Hommel, 2013; Colzato, van Leeuwen, van den Wildenberg, & Hommel, 2010; Green, Sugarman, Medford, Klobusicky, & Bavelier, 2012; Karle, Watter, & Shedden, 2010). A distinct, but related aspect of cognitive control is dual-tasking/ multi-tasking. In this class of tasks, participants are given multiple tasks to perform at overlapping points in time (i.e., “at the same time” as opposed to given different tasks in temporal sequence). For example, Strobach and colleagues (2012) made use of a dual task design wherein participants were presented with both a visual and an auditory stimulus, offset by a variable temporal delay. When the delay is large, it is easy to complete the tasks in sequence. When the delay is very short though (to the limit of the tasks being presented simultaneously), it becomes more difficult to complete both tasks—in particular, the second task. And in both correlational and intervention designs, action gaming was shown to result in improved performance on this dual-tasking skill.

Potential for Real-World Impact Clearly, given the evidence discussed above, action video game play is capable of overcoming the “curse of specificity” and instead engenders 35

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benefits on a wide variety of very dissimilar tasks. This, in turn, has resulted in interest in whether action video games can be utilized for realworld impact. And while some of the tasks described above are themselves at least linked with real-world outcomes (e.g., better performance on the Useful Field of View task has been associated with reductions in driving accidents; Goode et al., 1998), the better studies in this vein have gone beyond an examination of tasks that are correlated with real-world outcomes, and instead have examined actual real-world effects. For example, recent research has shown that the broad enhancements in perceptual and attentional abilities seen as a result of action video games may make these games effective platforms for rehabilitating vision in individuals with visual deficits (e.g., individuals with amblyopia, sometimes called “lazy eye” [R. W. Li, Ngo, Nguyen, & Levi, 2011]) or ameliorating some deficits associated with dyslexia (as some deficits in dyslexia seem linked to improper use of visual attention [Franceschini et al., 2013]). Similarly, the enhancements in visual, cognitive, and motor skills stimulated by action video game play have proven useful in jobs where these skills are at a premium, including in the training of laparoscopic surgeons (Rosser Jr. et al., 2007; Schlickum, Hedman, Enochsson, Kjellin, & Fellander-Tsai, 2009) and military drone pilots (McKinley, McIntire, & Funke, 2011).

Challenges Going Forward While the research that has accrued over the past several decades has clearly outlined the capacity of action video games to produce broadly generalizable enhancements in cognitive function, the field is not without challenges going forward. First, like all scientific domains, there is the constant need to further refine methodology, to replicate core findings, and to produce better theory (for in-depth discourses on these issues see: Boot, Simons, Stothart, & Stutts, 2013; Green et al., 2014, 2017). However, given the topic of this volume, it is worth considering the challenges that are uniquely related to video games and video game players (see Dale & Green, 2017, for a more extended discussion of these issues). Changes in the games themselves. A number of changes in terms of video games themselves have occurred over the past 15 years that have induced a series of challenges (and perhaps opportunities) for those that study the cognitive and perceptual impact of video games. One such challenge is the fact that “genre” is an ever more imperfect cue to video game content (Apperley, 2006). Indeed, in the earliest days of this literature, “action video games” were basically perfectly synonymous with “first-person shooter” (and maybe “third-person shooter”) video games. Genres other than the shooter-genres contained minimal action mechanics/dynamics/content (e.g., strategy games were largely slower and turnbased, as were fantasy/role-playing games). Thus, individuals performing 36

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a cross-sectional study on AVGPs and NVGPs could easily separate individuals based on whether they played shooter-genres. Gaming today though has seen the rise of many so-called “hybrid” genres. As the name implies, these are genres that contain the core features of more than one genre. Importantly, many of these hybrids are action+ hybrids. For instance, one increasingly popular genre is the action-RPG (action-roleplaying game). Such games contain many of the same shooting mechanics as a first-person or third-person shooter, while at the same time, containing many elements of role-playing games (such as skill trees, character progression, dialog trees, etc.). The action-real-time strategy (action-RTS) genre has similarly exploded in popularity (sometimes these games are referred to as MOBA games—or multiplayer online battle arena games). Such hybrid genres create a real challenge for the classification of individuals as AVGPs/NVGPs, both for researchers and the players themselves (e.g., if the option for a hybrid genre is not given on a survey, individuals may use either the “action” or “role-playing” label for an action-RPG, which is obviously a substantial issue). A related problem is the increasing degree of choice/flexibility seen in modern video games. Many games have adopted a so-called “sandbox” or “open-world” style. In such games, the player is allowed to move through the world however they would like, they can approach missions in the manner (and order) of their choosing, and they can often implement any one of a perhaps infinite number of play-styles and strategies to meet objectives (Bowman et al., 2016; Oliver et al., 2015). As a simple example, in the Elder Scrolls game Skyrim (Bethesda Softworks, 2011), players can complete missions using a “hack-and-slash” approach (wherein the player runs at enemies and hits them with a melee weapon), a “tank shooter” or “run-and-gun” approach (wherein the player uses projectile-based weapons from short-to-medium distances), or a “tactical shooter” or “sniper-based” approach (wherein the player uses long-range projectile weapons). Perhaps more problematically, players can adopt different strategies across different missions, or even within a single mission. It is even the case that fundamental game facets such as visual perspective can be under the control of the player. Indeed, Skyrim can be played as a first-person game or as a third-person game, with some players choosing one or the other perspective and staying with that choice throughout the game, while other players switch back and forth depending on the game circumstances. Each of these differences is critical for the study of cognitive impact as these differences will likely (or in many cases will certainly) alter the cognitive demands associated with playing the game (e.g., in whether it is necessary to monitor the near or far visual periphery, in the fineness of motor movements that are required, in the number of enemies that are encountered simultaneously, and so forth). Again, because all existing 37

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theories in our field posit that the cognitive and perceptual consequences of game play will depend upon the cognitive and perceptual processes that are tapped by game play, and because the different play styles listed above (which do not even scratch the surface of possible play-styles) will implicate very different perceptual and cognitive functions, this presents an enormous challenge for researches in the domain. In a nutshell, it is increasingly the case that not only does the “genre” that a game belongs to tell us little about the mechanics/dynamics/content of the experience, but even knowing what specific game was played also tells us very little. Two individuals can play 20 hours of the exact same action-RPG game—with one player avoiding all role-playing elements and focusing mainly on the shooting-components, while the other does the exact opposite. This presents both a challenge to the field—particularly in cross-sectional work, where it will be increasingly important to attempt to measure previous game experiences rather than simply measuring games or genres of games played—but also potentially an opportunity, in that if our base theory is sufficiently well-described, then these differences in experience should produce predictable differences in behavioral abilities. Changes in the gamers. Several key changes in the participant population have occurred over the past 15 years, which also presents a number of challenges going forward. First, and foremost, is the fact that most young adults of the type that are often participants in experimental studies (e.g., college students), now have a full lifetime of gaming experience (Association, 2015). However, often in studies of the impact of gaming, we only attempt to measure the past year of gaming activity. This will increasingly be insufficient. Returning to the analogy of food, the types of food an individual has consumed just over the past year is likely to be an incredibly poor predictor of their current physiological state. And like physiological state, one’s perceptual and cognitive skills are (at least partially) a cumulative function of all of one’s previous experiences. They are not just a function of experience over the past year. In fact, given that the brain is far more plastic during childhood than in adulthood, it is likely that gaming habits during childhood and adolescence will prove to be much stronger predictors of current abilities than gaming habits during the past year as an adult. This lifetime of experience also makes it more difficult to find non-gamer participants—as the vast majority of individuals have some gaming history. Another major change in gamers is the severe reduction in single-genre gamers. Most gamers today play games from a wide variety of genres (and, as noted above, an ever-increasing number of games do not fit into pure genres). This, in turn, makes it difficult to attribute any observed differences in perceptual or cognitive skills to any single genre. And although one might imagine that advanced statistical techniques could isolate the variance associated with each genre, in practice, we have found 38

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that individual self-reports of gaming are (1) biased and even worse, are (2) non-linearly biased in a way that depends upon how many genres they play (i.e., individuals who play more genres tend to overestimate their weekly gaming by more than individuals who play fewer genres). Because the self-reports of multi-genre gamers are so unreliable, the classic statistical idiom—“garbage in leads to garbage out”—means that until better measures of game play habits become available, advanced statistical measures are of essentially zero value (see Green et al., 2017, for additional commentary on this issue). How can these challenges be overcome? Both issues mean that it is increasingly important that we attempt to gather full gaming history. While this is no easy task, particularly because individuals have notoriously poor autobiographical recall for this type of daily activity, we may be aided in this endeavor by the fact that gaming is increasingly online. Because of this fact, gaming activity is typically similarly stored online via gamer accounts that could potentially be accessed by researchers. These resources could in turn provide accurate quantitative data about an individual’s game play history, in many cases, going back years or more.

Conclusion Unlike many standard perceptual or cognitive training paradigms, action video game training produces enhancements in skills that generalize well-beyond the trained environment. In fact, the benefits are so broad that off-the-shelf action games are already starting to be deployed to produce real-world impact—from retraining vision in individuals with a lazy eye, to enhancing the skill set of laparoscopic surgeons or pilots. However, it is important to keep in mind that in studying the impact of video games on perception and cognition, we are studying a dynamic phenomenon. As such, it is important to always keep in mind the way in which games are changing, the way in which gamers are changing, and constantly be titrating our methods to best match the present state of affairs.

Ludography Angry Birds. (2009). Espoo, Finland: Rovio Entertainment. Ballance. (2006). New York, NY: Atari. Battlefield series. (2002–present). Redwood City, CA: Electronic Arts. Bioshock series. (2007–2013). Novato, CA: 2K Games. Call of Duty series. (2005–present). Woodland Hills: CA: Activision (Infinity Ward). Gears of War series. (2006–2016). Redmond, WA: Microsoft Studios. Grand Theft Auto series. (1997–present). New York, NY: Rockstar Games. Medal of Honor series. (1999–2012). Redwood City, CA: Electronic Arts.

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Restaurant Empire. (2003). Cuyahoga Falls, OH: Enlight Software. Rise of the Tomb Raider. (2015). Redmond, WA: Microsoft Studios. Skyrim. (2011). Bethesda, MD: Bethesda Softworks. Tetris. (1984–present). Various. The Sims. (2000–present). Redwood City, CA: Electronic Arts. Unreal Tournament 2004. (2004). New York, NY: Atari. World of Warcraft. (2004–present). Irvine, CA: Blizzard Entertainment.

Notes 1 After all, what real-world good would it do for an elderly individual suffering from poor eye sight to improve their ability to resolve just vertical lines, but nothing else? 2 Sometimes phrased in the form of “Is playing video games ‘good’ or ‘bad’ for you?” 3 These types of recruitment methods have various pros and cons, which are particularly related to participant bias, expectation effects, and so on, that are discussed more fully in Boot et al. (2013) and Green, Strobach, and Schubert (2014).

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Oliver, M. B., N. D., B., Woolley, J. K., Rogers, R., Sherrick, B., & Chung, M.-Y. (2015). Video games as meaningful entertainment experiences. Psychology of Popular Media Culture, 5(4), 390–405. Owen, A. M., Hampshire, A., Grahn, J. A., Stenton, R., Dajani, S., Burns, A. S., Howard, R. J., Ballard, C. G. (2010). Putting brain training to the test. Nature, 465(7299), 775–778. Powers, K. L., & Brooks, P. J. (2014). Evaluating the specificity of effects of video game training. In F. Blumberg (Ed.), Learning by playing: Frontiers of video gaming in education (pp. 302–329). Oxford: Oxford University Press. Powers, K. L., Brooks, P. J., Aldrich, N. J., Palladino, M. A., & Alfieri, L. (2013). Effects of video-game play on information processing: A meta-analytic investigation. Psychonomic Bulletin and Review, 20(6), 1055–1079. doi:10.3758/ s13423-013-0418-z Rosser Jr., J. C., Lynch, P. J., Cuddihy, L., Gentile, D. A., Klonsky, J., & Merrell, R. (2007). The impact of video games on training surgeons in the 21st century. Archives of Surgery, 142(2), 181–186. Sagi, D. (2011). Perceptual learning in Vision Research. Vision Research, 51(13), 1552–1566. doi:10.1016/j.visres.2010.10.019 Schlickum, M. K., Hedman, L., Enochsson, L., Kjellin, A., & Fellander-Tsai, L. (2009). Systematic video game training in surgical novices improves performance in virtual reality endoscopic surgical simulators: A prospective randomized study. World Journal of Surgery, 33(11), 2360–2367. Schmidt, R. A., & Bjork, R. A. (1992). New conceptualizations of practice: Common principles in three paradigms suggest new concepts for training. Psychological Science, 3(4), 207–217. Schute, V. J., Ventura, M., & Ke, F. (2015). The power of play: The effects of Portal 2 and Lumosity on cognitive and noncognitive skills. Computers and Education, 80, 58–67. Snell, N., Kattner, F., Rokers, B., & Green, C. S. (2015). Orientation transfer in vernier and stereoacuity training. PLoS One, 10(12), e0145770. Spence, I., & Feng, J. (2010). Video games and spatial cognition. Review of General Psychology, 14(2), 92–104. Strobach, T., Frensch, P. A., & Schubert, T. (2012). Video game practice optimizes executive control skills in dual-task and task switching situations. Acta Psychologica, 140(1), 13–24. Trick, L. M., Jaspers-Fayer, F., & Sethi, N. (2005). Multiple-object tracking in children: The “Catch the Spies” task. Cognitive Development, 20(3), 373–387.

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3 T H E RO L E O F E N G AG E M E N T I N FAC I L I TAT I N G G A M E S - B A S E D P E RS UA S I O N Brett Sherrick

Researchers who analyze video games as texts—attempting to determine the meaning within—tend to look in one of two places: the narratives of the games or the rules and procedures of the games. Although the two perspectives are not incompatible, they have given rise to two separate forms of humanistic games research: narratology and ludology. Taking a narratological viewpoint, for example, Aarseth (1997) defined games as “ergodic literature,” suggesting that games have narratives that are actively constructed by the player. Conversely, a ludologist might describe games as algorithmic (Galloway, 2006) or procedural (Bogost, 2007). Juul (2005), combining the two perspectives, argues: “To play a video game is therefore to interact with real rules while imagining a fictional world, and a video game is a set of rules as well as a fictional world” (p. 1). Understanding both the narrative and gameplay elements, then, is important in fully understanding video games and the (persuasive) messages they convey. In some cases, the narrative and gameplay may present conflicting messages. The oft-discussed Spec Ops: The Line (2K Games, 2012), for example, presents an anti-war narrative while simultaneously requiring the player to engage in violent, warlike gameplay. Player or character deaths can also act as potential breaking points between narrative and gameplay, such that the many deaths of characters—who are then respawned—have meaningful gameplay ramifications but are typically inconsequential for the narrative (Aarseth, 1994; Sherrick, 2009). More commonly, however, narrative and gameplay coincide to present a cohesive message. Unlike Spec Ops, most war games include narratives in which violence and war

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solve problems while also allowing players to feel the power of violence and war through gameplay features that reward bellicose actions and punish or are agnostic toward more peaceful actions. Similarly, games like those in the Fire Emblem series (Nintendo, 1990–present) treat character deaths caused by unsuccessful gameplay as narratively permanent—​ permadeath—melding the gameplay and narrative consequences of character death (e.g., Sherrick, 2009). Other games and game genres frequently converge their narrative and gameplay arguments. For example, games in the Professor Layton (Level5, 2007–present) series rely on puzzle-based gameplay, showing the value of intelligence and critical thinking to solve problems, while also telling stories about the value of thoughtful consideration and intelligent decision making. Recent games in the NBA 2K series (2K Games, 1999–present) have included narrative “MyCareer” modes that tell stories about the often conflicting comradery and rivalry of team sports, and the basketball gameplay reinforces this through simultaneous reliance on teammates and competition against opponents. And the indie hit, Papers, Please (Lucas Pope, 2013), highlights the complexity of applying border-control policies both through the narrative (which tells the story of a border-control agent and many different border crossers) and the gameplay (which requires the player to make careful decisions about how and when to investigate those border crossers). Through convergent narrative and gameplay messaging, these games should be able to reinforce their focal arguments and should therefore be more successfully persuasive than games with divergent narrative and gameplay messaging, even if their primary goal is not necessarily persuasion. Persuasion is the process through which a message changes the attitudes or behaviors of the audience (e.g., Perloff, 2010). Through narrative and gameplay elements, games present the player with one or more potentially persuasive messages, which the player can either reject or accept. If the player accepts the message(s) and changes attitudes, beliefs, or even behaviors because of the message of the game, that game has persuaded the player and is persuasive. Some games are actively persuasive, making personal, political, or commercial statements that are intended to change the player’s mind about the subject. Examples include: advergames such as Chex Quest (Digital Café, 1996), a game made by a cereal company to improve attitudes toward the Chex brand (and built on the Doom computer game platform; id Software, 1993); Darfur is Dying (Susana Ruiz, 2006), a game designed to persuade people to care about and help prevent genocide in the African region Darfur that was created in collaboration with MTVU; or any number of games designed by the company Persuasive Games, which was co-founded by persuasive games scholar Ian Bogost. These persuasive games fit into the category of serious games—games

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with a primary purpose other than entertainment, but commercial, offthe-shelf games designed with entertainment in mind can also persuade. The goal of this chapter is to examine how games can persuade game players through both gameplay and narrative mechanisms. Specifically, it describes how the psychologically engaging states of flow and transportation can facilitate games-based persuasion through gameplay and narrative, respectively. It also examines the role of cognitive demand in this persuasive process, arguing first that a game’s level of cognitive demand is an important determinant of its ability to engender engaging states like flow or transportation. A game’s persuasiveness is also likely to depend— at least in part—on the game’s degree of cognitive demand, as increasing cognitive load should lower the player’s ability to resist the game’s persuasive message. In short, the degree of cognitive demand presented to the player by a game is likely to impact both the game’s immersiveness and its persuasiveness.

Persuasive Games and Engagement Research investigating the persuasiveness of games typically considers health-based games, branded games presenting commercial messages, or political games. In summarizing existing research on health-based games, Baranowski, Buday, Thompson, and Baranowski (2008) said that “playing most of these [health-related] behavior-change video games led to a broad spectrum of desirable outcomes from knowledge increases, to attitude changes, behavior changes, and other health-related changes” (p. 77). Similarly, in summarizing research on in-game advertising and advergames, Terlutter and Capella (2013) found general support for the effectiveness of games-based advertising. Research on political games is fairly limited, but results thus far have supported the supposition that games can change political attitudes or beliefs (e.g., Alhabash & Wise, 2012; Peng, Lee, & Heeter, 2010). One of the most common arguments for how games persuade is that they do so by engaging players through gameplay and/or narrative. Speaking to the persuasiveness of gameplay, Bogost (2007) argues that games can be persuasive via the procedures and rules of the game. He calls this procedural rhetoric: “the practice of persuading through processes in general and computational processes in particular” (p. 3). He argues that procedural rhetoric has advantages over other forms of rhetoric because it involves the player in the argument by requiring “user action to complete their [games’] procedural representations” (p. 45). Research has shown that games can be persuasive (e.g., Alhabash & Wise, 2012; Lee, Peng, & Klein, 2010; Peng, 2009; Peng et al., 2010), but no identified research has examined the procedural rhetoric of games, in particular. Additionally, games may be persuasive via narrative (e.g., Baranowski et al., 2008; Lee et al., 2010; Sangalang, Johnson, & Ciancio, 2013), although this 46

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supposition has received only limited empirical support in research on games (Lu, Thompson, Baranowski, Buday, & Baranowski, 2012), parallel research examining other media has fairly consistently demonstrated that narrative is a strong route to persuasion, when compared with non-narrative messaging (e.g., Escalas & Stern, 2003; Green & Brock, 2000; Wentzel, Tomczak, & Herrmann, 2010). While there are likely to be a number of factors that determine the persuasiveness of a specific game, a game’s ability to engage players is likely to have a strong influence on the degree to which the players buy-in to the game’s argument. Engagement with, or immersion in, media is an important variable for media scholars, but the engagement construct has been described in different ways in different contexts. For example, video game scholars have described engagement as presence (e.g., Nelson, Yaros, & Keum, 2006) and flow (e.g., Sherry, 2004). Similarly, persuasion scholars have described engagement as transportation (e.g., Green & Brock, 2000), narrative engagement (e.g., Busselle & Bilandzic, 2009), and outcome-​ relevant involvement (e.g., Petty, Cacioppo, & Goldman, 1981). Given the conceptual and, often, empirical (Schmierbach, Limperos, & Woolley, 2012b; Sherrick, 2015; Wissmath, Weibel, & Groner, 2009) overlap between these various engagement and immersion variables, the present chapter focuses on flow and transportation, as those concepts have been most closely aligned with gameplay (e.g., Limperos, Schmierbach, Kegerise, & Dardis, 2011; Sherry, 2004) and narrative (e.g., Busselle & Bilandzic, 2009; Green & Brock, 2000; Lu et al., 2012), respectively. As the ludology versus narratology debate described previously suggests, gameplay and narrative are key loci for meaning in games, including persuasive games, so understanding how gameplay and narrative connect to the engagement variables of flow and transportation is valuable to understand how games can persuade through engagement. Explorations of video game engagement are often aimed at establishing them as mediators between game exposure and some intended outcome, typically either enjoyment or persuasion. The concept of flow has been connected to enjoyment since its inception; in fact, Csikszentmihalyi (1974) stated that his exploration of flow was aimed at discovering “why people enjoy things for which they get little or no material rewards” (p. 1). Green, Brock, and Kaufman (2004) also argued that narrative transportation can lead to enjoyment by, for example, allowing for new experiences and emotional connections with characters. Similarly, scholars have argued that game engagement can facilitate persuasion (e.g., Green et al., 2008; Jin, 2011; Waiguny, 2013; Waiguny, Nelson, & Terlutter, 2012). A primary goal of this chapter is to extend this line of reasoning by exploring two potentially unique paths to games-based persuasion: (1) from gameplay features through flow to persuasion and (2) from narrative features through transportation to persuasion. 47

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Figure 3.1  Theorized model of games-based persuasion via engagement.

In sum, games create persuasive messages through both narrative and gameplay features. The degree to which those messages persuade players is likely to depend on a number of factors, including—perhaps centrally— the player’s engagement with the game. Because of this, games that are more engaging are likely to be more persuasive. Based on prior conceptualizations of engagement, gameplay features are most likely to trigger the engaging state of flow, and narrative features are most likely to trigger the engaging state of transportation. Figure 3.1 represents these general relationships. Finally, cognitive demand plays an important role in these relationships as cognitive demand can be an important antecedent of engaging states, and as will be discussed later, it can influence the success or failure of persuasive messaging.

Gameplay, Flow, and Persuasion According to Nakamura and Csikszentmihalyi (2002), people in a flow state are likely to show an intense focus on or engagement with the task they are performing. Those people will also feel complete control over the task, a lack of self-awareness, that their actions are immediately linked to their thoughts, a sense that time passes very quickly, and intrinsic motivation to continue and a great sense of reward from completing the task. For these reasons, Csikszentmihalyi (1990) characterized flow as the “optimal experience”—one that is supremely engaging, enjoyable, and productive. Csikszentmihalyi and others have identified a number of activities that can engender flow, including tasks like working, having sex, creating art, and others. Early on, Csikszentmihalyi (1974) argued: “Games are the most obvious kinds of flow activities, and play is the flow experience par excellence” (p. 59). Csikszentmihalyi (1974) was referring primarily to non-digital games, but Sherry (2004) updated his argument for the video-game age, arguing that “video games possess ideal characteristics to create and maintain flow experiences in that the flow experience of video games is brought on when the skills of the player match the difficulty of the game” (p. 340). Although the flow state has been documented in a number of varying contexts (e.g., painting, rock-climbing, everyday work, sex), consuming 48

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media—particularly reading (Csikszentmihalyi, 1990)—may be the activity most likely to induce flow in everyday life. Sherry (2004) provided an influential explanation of how media consumption could lead to flow. He argued that different media texts provide different levels of challenge and that different media consumers have different levels of media literacy skill. For example, children’s fiction is likely to be easier to consume than academic research reports; similarly, children are likely to have less skill in reading and understanding media texts than media scholars. According to Sherry (2004), the primary determinant of the level of challenge for a media text is its consistency with existing conventions of that medium (e.g., grammatical norms of written texts, widespread camera techniques for film, common tropes of video games). In the creation and distribution of games, varying the degree of gameplay and narrative difficulty is often a purposeful decision. For example, educational games are often designed to be relatively easy so that students of all skill levels can complete the game and therefore the lesson. Classic arcade games, on the other hand, were often considerably more difficult, as player failure was more profitable because it often resulted in another quarter going into the machine. As described above, most commercial, off-the-shelf games provide a range of difficulties to ensure they appeal to players off all abilities. While these decisions may have financial impetus, existing research also suggests that they impact the ability of games to engage players in either flow or transportation. Moreover, research also suggests that these decisions about game difficulty can impact both the immersiveness and the persuasiveness of games. Cognitive demand and flow. Following Sherry’s (2004) argument, the clearest determinant of whether or not a game is likely to be engaging may be its degree of difficulty. To provide initial support for this position, Sherry (2004) provided evidence that female and male gamers prefer games that consist of tasks for which women and men, respectively, have cognitive advantages. For example, men have performed consistently better on 3D rotational tasks, which may explain the male preference for intense and detailed 3D games (Sherry, 2004). After Sherry (2004), many researchers examined the effect of game difficulty or challenge on flow or other engagement experienced while playing games (Jin, 2011, 2012; Schmierbach, Chung, Wu, & Kim, 2012a; Schmierbach, Wu, & Sherrick, 2012c). Jin (2012, Study 1) showed that success in a game and competence—both of which could be construed as challenge/skill balance—were positively correlated with flow, as measured via Novak, Hoffman, and Yung’s (2000) explanation-and-question method. Jin (2011, Study 2; 2012, Studies 2 and 3) further demonstrated an interactive effect between self-reported challenge and self-reported skill on self-reported flow. Specifically, players who reported high levels of skill were more likely to enter flow if they also reported high levels of 49

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challenge. Less consistently, players who reported medium levels of skill were more likely to enter flow if they also reported medium levels of challenge. One of the major shortcomings of Jin’s (2011, 2012) program of research is that all variables tend to be assessed via self-report measures after gameplay, so temporal ordering is difficult to establish. It is possible that participants reported matching levels of skill and challenge because they were in a flow state. To help untangle this relationship, Schmierbach and colleagues (2012a, 2012c) have directly manipulated challenge in experimental designs. Through a manipulation of game difficulty, they found that game challenge has a negative indirect effect (via competency) on the skill/challenge balance component of flow (Schmierbach et al., 2012a). In other words, to the degree that the more difficult version of the game inhibited feelings of competency, it also inhibited a state of flow. Relying on Csikszentmihalyi’s (e.g., Csikszentmihalyi, 1974, 1990; Nakamura & Csikszentmihalyi, 2002; Sherry, 2004) argument that tasks that match challenge with the participant’s skill level are more likely to induce flow, it seems likely that modifying game difficulty to match the player’s skill level may be a likely way to induce flow or other forms of engagement. Therefore, matching the difficulty of gameplay with player skill is likely to cause flow. Gameplay difficulty. Many video games begin with a simple choice: easy, medium, or hard? When the player makes a selection, the game code adjusts in-game difficulty accordingly. For example, selecting easy in a shooting game may lead to fewer or less dangerous enemies, or selecting medium in a basketball game may lead to a computer-controlled opponent with an average shooting percentage, or selecting hard in a puzzle game may lead to decreased time between important decisions. These different scenarios describe varying degrees of difficulty as represented by elements of the game. This is often how game difficulty is defined: as an aspect of the game that can be increased or decreased with modifications to the gameplay. Game designers, for example, will alter specific characteristics (time limits, damage dynamics, resource availability, etc.) of a game to lower or increase its level of difficulty (e.g., Buotros, 2008). This conceptualization has also carried over into social science research, as researchers have investigated how people will differentially respond to games with different difficulty characteristics based on industry-created operationalizations of difficulty (i.e., the existing easy, medium, and hard modes of a game); while this is a logical starting place, it comes with significant limitations (i.e., lack of control and lack of variability). Even so, existing research using game difficulty illuminates some potential avenues for defining game difficulty. For example, Schmierbach and colleagues (2012c) argued that difficulty can vary through in-game characteristics: “Games may present 50

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more enemies on screen, provide fewer resources, require faster reflexes, or otherwise increase the likelihood of player failure.” Similar studies have operationalized game difficulty by manipulating the distribution and duration of enemies (Orvis, Horn, & Belanich, 2008), number of in-game distractions (Proaps & Bliss, 2011), the number of actions required (Cox, Cairns, Shah, & Carroll, 2012, Experiment 1; Sharek & Wiebe, 2011), the amount of time allotted to perform game tasks (Cox et al., 2012, Experiments 2 and 3), and the number of possible actions in a puzzle game (Sherrick, 2017). Importantly, Schmierbach et al. (2012b) suggest that these different dimensions of game difficulty may have distinct perceptual effects because, for example, complete failure may hinder self-reported enjoyment while increased enemies on screen may increase enjoyment. Any definition of game difficulty is, therefore, likely to need multiple dimensions. For example, Cox et al. (2012) argue that a game can be physically difficult (i.e., by increasing the number of actions required) or cognitively difficult (i.e., by increasing the number of problems to be solved). Similarly, Aponte, Levieux, and Natkin (2011) argue that difficulty can be sensitive (i.e., “to make useful game objects hard to find by the player”), logical (i.e., by requiring complex decisions), or motor (i.e., by placing time and space restraints on player action). Finally, work by Bowman (2016), including this book (see Chapter 1), suggests four dimensions of game demand or difficulty: cognitive, emotional, physical, and social. Flow and persuasion. Flow has not commonly been connected to persuasion (Appel & Richter, 2010). In fact, research that examines the persuasiveness of flow comes primarily from the literature on video games (e.g., Jin, 2011; Mau, Silberer, & Constien, 2008; Waiguny, 2013; Waiguny et al., 2012). Jin (2011, Studies 2 and 3) found that flow reported from playing a game was predictive of intentions to play that game again—a form of persuasion that Bogost (2007) would label “partial reinforcement” (p. 47). Waiguny et al. (2012) demonstrated that challenge experienced while playing an advergame could positively influence attitudes toward the advertised brand. Waiguny (2013) also found that a nutrition-based game could increase both flow and favorable attitudes toward nutrition but did not test the role of flow in changing these attitudes. Mau et al.’s (2008) research, however, did not support the supposition that flow could ease persuasion related to product placement in a video game. Again, the research on immersion-aided persuasion in games is still inconclusive. Moreover, flow is not necessarily expected to ease persuasion (Appel & Richter, 2010), but to the degree that flow is a psychological state characterized by a pleasant experience and cognitive demand, it should theoretically be able to facilitate persuasion. The positive associations created with a media text that generates a flow state should transfer to any persuasive messages, which should make those persuasive 51

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messages more appealing. And, as will be discussed in more detail later, if a flow state consumes a player’s cognitive resources, that player should have fewer cognitive resources to evaluate the persuasive message independently from the positively evaluated gameplay experience.

Narrative, Transportation, and Persuasion Transportation is a psychologically engaging or immersive state, expected to specifically result from a narrative and described as “a convergent process, where all mental systems and capacities become focused on events occurring in the narrative” (Green & Brock, 2000, p. 701). People who are transported into a narrative world are more connected with the narrative than the real world. Green and Brock (2000) specifically tied transportation to persuasion, arguing that people “return from being transported somewhat changed by the experience” (p. 702); they argue that this change is a form of persuasion. In other words, because transported people are invested in the narrative world, they internalize the message(s) of the narrative world and can be persuaded by them, even in their return to the real (i.e., non-narrative) world. These narrative worlds can exist and be created by many media, including books, movies, and—importantly— video games. Transportation could theoretically be an unmediated experience (as could flow), but research so far has typically couched narratives within some form of media (i.e., written stories, film, or video games). Cognitive demand and transportation. Green et al. (2008) found that people high in need for cognition were more transported by reading and that people low in need for cognition were more transported by watching a narrative. They used this evidence to argue that transportation—like flow (e.g., Csikszentmihalyi, 1974, 1990; Nakamura & Csikszentmihalyi, 2002; Sherry, 2004)—was more easily entered into when the relative challenge of processing the narrative matched with the person’s willingness to put forth effort (perhaps, similar to skill) in processing the narrative. A similar test showed that need for affect moderated the relationship between transportation and persuasion (Appel & Richter, 2010). Following the logic of Green et al. (2008), it may be that people high in need for affect are more skilled at processing narratives and were therefore able to meet the challenge of the transportative narrative presented in the study. In short, to the degree that the challenge (i.e., consistency with conventions or cognitive/affective complexity) of a media text matches the skill level of a media consumer, that media text may induce transportation. Narrative difficulty. Although less often foregrounded in games, games and other media can also prove relatively difficult through narrative (Green et al., 2008; Sherry, 2004). For example, most readers would find the narratives of Shakespeare’s plays more difficult or cognitively demanding than the narrative of Good Night Moon or other children’s books. 52

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Similar patterns of relative narrative difficulty are present in video games as well. At a broad level, these distinctions often mirror genre differences; puzzle games might have limited or even no narrative elements, limiting their narrative difficulty, whereas RPGs (especially JRPGs) often contain notoriously in-depth narratives that require great cognitive effort and time on the part of the player. Specific games also display variation of narrative difficulty. The games in the Mario franchise (Nintendo, 1981–present), for example, are relatively less narratively difficult than those in the Bioshock series. Mario’s story is generally pretty straightforward: the evil Bowser kidnaps Princess Peach and Mario sets off to save her. There is a bit of narrative surprise, as the princess is often in another castle, but the general plot involves a good hero (Mario) defeating evil enemies (Bowser, Goombas, Koopa Troopas, etc.) to save a princess (Peach)—the plot largely serving to progress through each level, from left to right, avoiding ludic challenges along the way (cf. Bowman, 2016). The Bioshock games, on the other hand, provide much more complex narratives in which good and evil are not so clearly identified, narrative deception is central to the plot, and prior knowledge of world history and societal context is needed to fully understand the presented themes. To fully understand the narrative of a Bioshock game, the player is required to engage in great cognitive effort by, for example, tangling with nebulous ethical choices, such as whether to save or harvest Little Sisters, young children that can give the player greater power if harvested. These ethical challenges are one way that games and other narrative texts can increase the required cognitive effort of the audience member, who is asked to make sense of those challenges. Transportation and persuasion. Historically, transportation has been more strongly connected with persuasion than flow. In fact, Green and Brock (2000) initially proposed the transportation concept as a causal mechanism explaining the ability of narratives to encourage story-consistent beliefs. Transportation through narrative is thought to ease persuasion via identification and empathy with characters and reduced resistance to the implicit arguments within the narrative (e.g., Dal Cin, Zanna, & Fong, 2004; Green & Brock, 2000). Empirical evidence has largely confirmed these suppositions (e.g., Appel & Richter, 2010; Escalas & Stern, 2003; Wentzel et al., 2010). In games research, transportation-based persuasion is most commonly explored via identification (or role-playing) with game characters (Alhabash & Wise, 2012; Lee et al., 2010; Peng, 2009; Peng et al., 2010). In Alhabash and Wise’s (2012) study, participants played either as a Palestinian or Israeli leader, and results showed that playing as a Palestinian was more effective at eliminating uneven evaluations of the two groups. They did not directly measure identification, but they argue that this is likely the process through which their results were produced. Peng et al. (2010) directly measured identification and tested it as a mediator between game play and persuasive outcomes. Their results 53

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were mixed: in Study 1, identification did mediate this relationship, but evidence from Study 2 did not corroborate this result. Sangalang et al. (2013) measured both transportation and persuasion after exposure to a persuasive game, but they did not find that the two were correlated. However, Lu et al. (2012) argued that transportation—brought about by identification—explained differences in the persuasiveness of a game played by children of different demographic characteristics. Their game was found to be more persuasive for African-American and Hispanic children, who were more transported by the game than were Caucasian children. When transportation was controlled, the differences in persuasion changed to non-significant. In sum, the limited evidence connecting games-based transportation and persuasion does not mirror the consistent relationship shown in other media; however, this phenomenon still needs further research, as transportation into narrative (game) worlds is theoretically likely to ease persuasion (e.g., Green et al., 2004; Lu et al., 2012).

Cognitive Demand and Persuasion Engagement with gameplay (flow) and with narrative (transportation) may explain—at least in part—the success of persuasive games in persuading their players. Transportation theory provides the clearest explanation for why this might be the case. Specifically, transportation theory argues that engaging media can be persuasive because (1) it engenders positive affective responses that might be affiliated with the persuasive message (e.g., Escalas & Stern, 2003; Green & Brock, 2000) and (2) the cognitive load that goes hand-in-hand with engagement might limit reactance to, and/or counterarguing of, a persuasive message (e.g., Dal Cin et al., 2004; Green & Brock, 2000). Although these arguments come from research on transportation, they fairly easily port onto flow, as it is also associated with positive affect and characterized by intense cognitive attention (e.g., Csikszentmihalyi, 1974; Nakamura & Csikszentmihalyi, 2002; Sherry, 2004). For this chapter, the role of cognitive load or demand in immersive persuasion is most relevant. According to research on reactance, people are psychologically inclined to distrust and discount arguments that are clearly persuasive because persuasion can threaten people’s sense of autonomy (e.g., Brehm, 1966; Dillard & Shen, 2005). In other words, when people encounter persuasive arguments, they put their guard up and specifically attempt to not be persuaded. One goal of persuasive messages, then, is to overcome this reactance, and according to the transportation literature, narrative arguments are one potential way to do so (e.g., Dal Cin et al., 2004; Green & Brock, 2000). Dal Cin et al. (2004) provide a few explanations for why narratives may limit reactance and/or counterarguing (e.g., that narratives may not be recognized as persuasive, narrative arguments are often implied rather than 54

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explicit), but for this chapter, the most relevant explanation is that “the cognitive and emotional demands of absorption into a narrative leave readers with little ability or motivation to generate counterarguments” (p. 178). Both transportation (e.g., Green & Brock, 2000) and flow (e.g., Nakamura & Csikszentmihalyi, 2002) are considered cognitively demanding states; if cognitive resources are consumed by transportative narrative or flow-inducing gameplay, those resources are not available to counterargue with, or question, a persuasive message. Wentzel et al. (2010) provide some evidence of this effect in response to narrative persuasion. First, they showed that increasing cognitive demand, through a distraction task, inhibited people’s ability to identify a clearly persuasive message as persuasive; further, they showed that people with high cognitive demand from the distraction task were more persuaded by a clearly persuasive narrative message than those with low cognitive demand. Peña and Yoo (2014) show some evidence of how this might work in games. Again, using a distraction task, they manipulated cognitive load and then had people interact with an avatar in either white or black clothing. People with low cognitive load perceived the avatar in white clothing as more trustworthy, consistent with existing stereotypes; however, when placed in a cognitively demanding situation, people did not distinguish between the avatars’ trustworthiness. Peña and Yoo (2014) argue that the cognitively busy people may not have been unable to apply an existing stereotype about clothing color because they had limited cognitive resources to devote to an evaluation of the avatar. Similarly, if a persuasive game demands cognitive resources through engaging narrative or gameplay, the player’s ability to actively challenge the message of the game should be limited, which should ease persuasion.

Conclusion: The Importance of Optimal Demand The present argument is not meant to suggest that games that are more cognitively demanding will necessarily be more engaging and more persuasive. In fact, a game that is overly demanding will more likely lead to frustration instead of flow, narrative confusion rather than transportation, and negative associations with any persuasive messaging. Overly easy games, on the other hand, are likely to lead to boredom with gameplay or narrative and reactance to persuasive attempts. Instead, games need to reach an optimal level of cognitive demand. To be optimally engaging, games should match their cognitive demand with players’ skill levels (e.g., Green et al., 2008; Nakamura & Csizksentmihalyi, 2002), and to be optimally persuasive, games should provide enough cognitive demand to distract from their persuasive intent without alienating players. Unfortunately, for both game designers and games researchers, the optimal level of cognitive demand is likely to vary from person to person. 55

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A novice, picking up a game controller for the first time, is likely to find even the simplest of games to be overly challenging, while more experienced players may breeze through the highest difficulty settings for certain games. Similarly, a player with limited skill in processing narrative will have difficulty with complex or overly robust narratives, but a literary scholar may find simple narratives to be juvenile or uninteresting. Moreover, as players learn a specific game, their skill with that game is likely to increase, thereby requiring a higher difficulty level to match their improving skill (or, perhaps, adaptive or dynamic difficulty; e.g., Chen, 2008). This makes specific prescriptions about the impact of challenge on engagement or persuasion unhelpful. A more challenging game is not necessarily more engaging or persuasive than a less challenging game, but an optimally challenging game—one that matches the player’s gameplay and narrative skills and consumes enough cognitive resources to limit reactance to persuasion—is likely to be more engaging and more persuasive.

Ludography Bioshock series. (2007-2013). Novato, CA: 2K Games. Chex Quest. (1996). Minneapolis MN: Digital Café. Darfur is Dying. (2006). Los Angeles, CA: Susana Ruiz. Doom. (1993). Richardson, TX: id Software. Fire Emblem series. (1990–present). Kyoto, Japan: Nintendo Mario series. (1981–present). Kyoto, Japan: Nintendo NBA 2K series. (1999-present). Novato, CA: 2K Games. Papers, Please. (2013). Lucas Pope (3909, LLC). Professor Layton series. (2007–present). Fukuoka, Japan: Level-5. Spec Ops: The Line. (2012). Novato, CA: 2K Games.

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Bogost, I. (2007). Persuasive games: The expressive power of video games. Cambridge, MA: The MIT Press. Bowman, N. D. (2016). Video gaming as co-production. In R. Lind (Ed.), Produsing theory in a digital world 2.0: The intersection of audiences and production in contemporary theory ( Vol. 2, pp. 107–123). New York, NY: Peter Lang Publishing. Brehm, J. (1966). A theory of psychological reactance. Oxford: Academic Press. Buotros, D. (2008). Difficulty is difficult: Designing for hard modes in games. Gamasutra. Retrieved from www.gamasutra.com/view/feature/132181/difficulty_is_difficult_ designing_.php Busselle, R., & Bilandzic, H. (2009). Measuring narrative engagement. Media Psychology, 12(4), 321–347. doi:10.1080/15213260903287259 Chen, J. (2008). Flow in games (MFA thesis). Retrieved from www.jenovachen. com/flowingames/Flow_in_games_final.pdf Cox, A. L., Cairns, P., Shah, P., & Carroll, M. (2012). Not doing but thinking: The role of challenge in the gaming experience. Paper presented at CHI, Austin, TX. Csikszentmihalyi, M. (Ed.). (1974). Flow: Studies of enjoyment (PHS Grant Report No. RO1 HM 22883–02). Chicago, IL: The University of Chicago. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York, NY: Harper & Row. Dal Cin, S., Zanna, M. P., & Fong, G. T. (2004). Narrative persuasion and overcoming resistance. In E. S. Knowles & J. A. Linn (Eds.), Resistance and persuasion (pp. 175–191). Mawah, NJ: Erlbaum. Dillard, J., & Shen, L. (2005). On the nature of reactance and its role in persuasive health communication. Communication Monographs, 72(2), 144–168. Escalas, J. E., & Stern, B. B. (2003). Sympathy and empathy: Emotional responses to advertising dramas. Journal of Consumer Research, 29, 566–578. Galloway, A. R. (2006). Gaming: Essays on algorithmic culture. Minneapolis, MN: University of Minnesota Press. Green, M. C., & Brock, T. C. (2000). The role of transportation in the persuasiveness of public narratives. Journal of Personality and Social Psychology, 79(5), 701–721. doi:10.1037//0022-3514.79.5.701 Green, M. C., Brock, T. C., & Kaufman, G. F. (2004). Understanding media enjoyment: The role of transportation into narrative worlds. Communication Theory, 14(4), 311–327. doi:10.1080/15213261003799847 Green, M. C., Kass, S., Carrey, J., Herzig, B., Feeney, R., & Sabini, J. (2008). Transportation across media: Repeated exposure to print and film. Media Psychology, 11(4), 512–539. doi:10.1080/15213260802492000 Jin, S.-A. A. (2011). “I feel present. Therefore, I experience flow”: A structural equation modeling approach to flow and presence in video games. Journal of Broadcasting & Electronic Media, 55(1), 114–136. doi:10.1080/08838151.2 011.546248 Jin, S.-A. A. (2012). “Toward integrative models of flow”: Effects of performance, skill, challenge, playfulness, and presence on flow in video games. Journal of Broadcasting & Electronic Media, 56(2), 169–186. doi:10.1080/08838151.2 012.678516 Juul, J. (2005). Half-Real: Video games between real rules and fictional worlds. Cambridge, MA: The MIT Press.

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Schmierbach, M., Chung, M.-Y., Wu., M., & Kim, K. (2012a, June). No one likes to lose: Game difficulty, motivation, immersion, and enjoyment. Paper presented at International Communication Association, Phoenix, AZ. Schmierbach, M., Limperos, A. M., & Woolley, J. K. (2012b). Feeling the need for (personalized) speed: How natural controls and customization contribute to enjoyment of a racing game through enhanced immersion. Cyberpsychology, Behavior, and Social Networking, 15(7), 364–369. doi:10.1089/​cyber.​ 2012.0025 Schmierbach, M., Wu, M., & Sherrick, B. (2012c, August). Fighting death: The effects of punitive difficulty on video game enjoyment, immersion and need satisfaction. Paper presented at Association for Education in Journalism and Mass Communication, Chicago, IL. Sharek, D., & Wiebe, E. (2011). Using flow theory to design video games as experimental stimuli. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 55, 1520–1524. Sherrick, B. (2015, August). Comparing flow and narrative engagement scales in the context of a casual health game. Paper presented at Association for Education in Journalism and Mass Communication, San Francisco, CA. Sherrick, B. (2017, April). Narrative and gameplay as unique instigators of immersion-​ based persuasion. Paper presented at Broadcast Education Association, Las Vegas, NV. Sherrick, B. I. (2009). Some disassembly required: Understanding the deaths of the player-character self in Call of Duty 4 (Master’s thesis). Retrieved from Google Scholar. Sherry, J. L. (2004). Flow and media enjoyment. Communication Theory, 14(4), 328–347. Terlutter, R., & Capella, M. L. (2013). The gamification of advertising: Analysis and research directions of in-game advertising, advergames, and advertising in social network games. Journal of Advertising, 42(2–3), 95–112. doi:10.1080/0 0913367.2013.774610 Waiguny, M. K. J. (2013). Investigating the entertainment-persuasion link: Can educational games influence attitudes toward products? In S. Rosengren, M. Dahlén, & S. Okazaki (Eds.), Advances in advertising research (Vol. IV): The changing roles of advertising (pp. 173–186). Wiesbaden: Springer Gabler. Waiguny, M. K. J., Nelson, M. R., & Terlutter, R. (2012). Entertainment matters! The relationship between challenge and persuasiveness of an advergame for children. Journal of Marketing Communications, 18(1), 69–89. doi:10.1080/1 3527266.2011.620766 Wentzel, D., Tomczak, T., & Herrmann, A. (2010). The moderating effect of manipulative intent and cognitive resources on the evaluation of narrative ads. Psychology & Marketing, 27(5), 510–530. doi:10.1002/mar.20341 Wissmath, B., Weibel, D., & Groner, R. (2009). Dubbing or subtitling? Effects of spatial presence, transportation, flow, and enjoyment. Journal of Media Psychology, 21(3), 114–125. doi:10.1027/1864-1105.21.3.114

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4 R E S E A RC H O N T H E E M OT I O N S CAU S E D B Y V I D E O G A M E S D E M A N D S I N T E G R AT I O N Matthew Grizzard and C. Joseph Francemone

In 1948, Bernard Berelson summarized the state of knowledge surrounding the effects of communication messages on public opinion as follows: “Some kinds of communication on some kinds of issues, brought to the attention of some kinds of people under some kinds of conditions, have some kinds of effects” (1948, p. 172). Although accurate, such a statement is completely and utterly nondescript, which was Berelson’s intent. Berelson lamented that the field lacked synthesis and the research conducted seemed to fall into small unconnected camps, which precluded substantive progress. Multiple researchers were discovering similar patterns, but to Berelson, their findings were isolated from both each other and general mechanisms leading to the field “withering away” (see Berelson, 1959). Today, Berelson’s statement could be revised slightly to reflect research on the emotional responses produced by video games: “Some video gamers playing some kinds of games experience some kinds of emotions.” However, readers should not assume that our adaptation of Berelson’s famous conditional statement reflects any sort of pessimism on our part. Indeed, the last three plus decades of work on video games and their effects on emotion have yielded important findings. However, similar to Berelson’s diagnosis of early research in communication, we believe the findings related to the emotional nature of video game play remain isolated and unconnected to the processes that underlie the human experience of emotions. But all is not lost. The current chapter seeks to provide an overview of the current state of the literature regarding video game play and the emotions it elicits. But rather than simply recount the progress made by social science researchers, this chapter attempts to describe productive paths forward

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for researchers interested in examining how video games elicit emotions and what the effects of those emotions on other psychological processes might entail. Specifically, we attempt to explicate the larger processes at play, connecting the previous findings related to video games to mechanisms underlying emotional experience. Furthermore, we extol the virtues of considering video game research on emotional experiences as a pathway for understanding emotion rather than emotion as being a pathway for understanding video games. In other words, studying video games is interesting not for what we can learn about games, but rather what it can teach us about ourselves. Substantive progress toward this goal can only be made by integrating video game play into psychological models of emotion in a careful manner that values consistency with the assumptions of psychological models over descriptions of the unique features of video game play.

Video Games as Toys and Distractions Although the conceptual roots of video games can be traced to 1948 (Goldsmith & Ray, 1948), video games did not reach mainstream popularity until the 1970s. The first commercially successful video game, Atari’s Pong (1972), was released to bars, restaurants, and other public venues in 1972. These early video games, however, were drastically different from today’s games. They were essentially computer-mediated analogs to other competitive leisure activities, such as billiards, foosball, and air hockey (see Ivory, 2015). Game play focused on competition between two players or a player versus a computer, with the content of such games being mostly non-narrative. Rather than controlling some virtual being within the game and completing some kind of narrative-dependent quest, players instead sought to achieve a predetermined goal (e.g., being the first to 11 points). The concept of lives determining play length and high scores would not enter the video game vernacular until around 1978, with the introduction of Space Invaders (Taito, 1978; see Ivory, 2015, for an overview of the historical development of video games). Because most early games were so similar to other forms of competitive play, the emotional effects of video games were not considered particularly unique or intrinsically interesting. They were simply the outputs of another form of play and distraction. Eventually, the content of games moved beyond pure competition analogs and began to feature quasi-narrative content. The introduction of narrative and imaginative role-playing also started to generate public concern over how games might be corrupting youth. For example, the video game Death Race (Exidy, 1976) was similar to Pong and other early games in that gameplay length was determined by a timer and players competed

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against each other. However, rather than simply moving a paddle across the screen to hit a bouncing pixel, players controlled a “car” and chased humanoid characters, running them over to earn points. As the player ran over the stick-figure characters, tombstones appeared in their place. Bowman (2015) points to this game as the beginning of a moral panic regarding video games’ impact on society, in particular, with respect to video games and aggressive outcomes. Notably, the simple addition of symbolic meaning onto an action seems capable of increasing societal concern (see Best, 1998). Regardless, the focus on content and how players interpret the content drove much of the early research on the effects of video games. Similar to research on TV and movies, the symbolic meaning of games began to be considered the catalyst for their psychological impacts on players.

Video Game Research on Emotions Most scholarly perspectives within communication and psychology consider video games to be capable of eliciting emotional responses within players and most players today would not challenge the claim that emotions are felt when playing games. Although this claim may seem uncontroversial today, it was not always the case—particularly in popular understandings. The killing of characters within games was no different than taking pawns in chess, according to gamers (see Hartmann, Toz, & Brandon, 2010). Consequently, virtual actions should not be particularly emotion inducing due to their lack of real-world consequences. This perspective of course seems to ignore the numerous familial conflicts induced by board games such as Monopoly (Hasbro, 1935). Landing on Boardwalk when your sibling has a hotel on it may hold no real-world consequence, but nevertheless, it has caused numerous “rage quits,” accompanied by boards and all the pieces flying through the air. The belief that the emotions induced by games are somehow less rich or meaningful than other forms of media can be seen in other arenas as well. For example, Steven Spielberg posited that games were not a storytelling artform and that they could only be considered so “when someone confesses that they cried at level 17” (Breznican, 2004, para. 5). Why crying should be considered the ultimate indication of whether a form of media is art is unclear. Of course, scholarly perspectives, such as the media equation (Reeves & Nass, 1996), have suggested that video game content should be capable of eliciting emotions. Yet, the biases within popular culture and even among some scholars against video games has led many researchers to devote considerable resources and time to demonstrating that yes, video games are indeed capable of eliciting a wide range of emotions. These emotions are not simply limited to pleasure, hedonism, or

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frustration, but extend the range of human emotional experiences, including being moved, touched, amused (see Oliver et al., 2016), and even guilt over virtual misdeeds (see Hartmann et al., 2010). If we accept the premise that video games are capable of eliciting emotional experiences, the scholarly questions asked by researchers can move into a more useful direction. Rather than seeking to provide evidence that video games can elicit a specific emotion, research can shift its focus toward what elements of the video game play experience are responsible for eliciting emotions. These shifts have already occurred in design fields; for example, computer science researchers studying user experience have suggested that video game developers should consider the temporal and spatial design of a game as it relates to the emotions they elicit (see Callele, Neufeld, & Schneider, 2008). This work, as well as past work in communication and psychology, suggest several theoretical perspectives governing emotion elicitation.

Mechanisms of Emotion Elicitation in Video Game Play Various models exist regarding how video game play might relate to emotional experiences. One of the earliest references to video game play and emotional responses comes in a paper examining outcomes of pediatric patients undergoing chemotherapy (Kolko & Rickard-Figueroa, 1985). In a longitudinal baseline-introduction-withdrawal-reintroduction design, playing video games during chemotherapy sessions served to reduce anticipatory and post-treatment distress. The mechanism suggested by this research is that the act of playing video games is capable of suppressing emotional responses associated with other stimuli. Patients felt less distress associated with chemotherapy when they were playing video games as compared with when they were not. Why video games were capable of suppressing the emotions is not entirely clear. Several processes seem reasonable. For example, video game play may have exhausted cognitive resources distracting the patient from considering the potential discomfort they were about to experience. This explanation is generally consistent with mood management theory (Zillmann, 1988; Zillmann & Bryant, 1985; see also Reinecke et al., 2012). It is also possible that video game play may have provided a positive cognitive label to which patients could have attributed physiological arousal. This explanation is consistent with appraisal theories of emotion (Schachter & Singer, 1962) and excitation transfer theory (Zillmann, 1983). These theories argue that the cognitive labeling of arousal ultimately determines how the experience is conceptualized. Although receiving chemotherapy may have increased arousal and negative affect, positive affect elicited by gameplay could coopt the arousal leading to perceptions of an overall stronger emotional response.

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Regardless of the specific mechanism, it is important to note that the content of the game is nearly irrelevant for the Kolko and Rickard-Figueroa (1985) study. In fact, there was little concern over the content of the games as indicated by the wide variety of games used in the study. Other research focuses on the act of playing games as an elicitor of an emotional response rather than simply an emotional suppressor. For example, Przybylski, Deci, Rigby, and Ryan (2014) found that less intuitive control schemes elicited frustration. In a somewhat novel argument, Przybylski et al. (2014) argued that the content of games was not particularly important for eliciting emotional responses. They found that violent and non-violent games did not lead to differential aggressive responses; however, frustration inducing controls did. In this manner, Przybylski et al.’s research concludes that it is not simply violent games that elicit aggression, it is frustration-inducing video games, whether they include violent content or not. This conclusion is mirrored in some of the earliest research on the effects of video game content. For example, Chambers and Ascione (1987) examined “the effects of a prosocial and aggressive video games on children’s prosocial behavior” (p. 499). Although the outcomes of their study were behavioral rather than emotional (i.e., donating and helping behaviors), Chambers and Ascione’s focus was on the content and context of the games played (either aggressive fighting in a competitive boxing game Boxing [Atari, 1980] or altruistic helping in a cooperative Smurfs game [Coleco, 1982]) as being the catalyst for the hypothesized effects. When the prosocial game failed to elevate donations as hypothesized, the authors speculated that negative mood induced by the difficult control scheme of the Smurfs game—one player controlled the movement of the character while another controlled its jumping—might have suppressed the effect of the content. In an approach that somewhat reconciles the different mechanisms (video game play as elicitor versus video game play as suppressor), Bowman and colleagues (see Bowman & Tamborini, 2015; see also Reinecke et al., 2012) link video game difficulty to mood repair. Players who are stressed tend to select easier games, whereas players who are bored tend to select harder games. These selection differences are driven by a similar motivation: the desire to reduce or eliminate an unpleasant affective state. Difficulty in this work was manipulated through controller complexity with harder difficulties requiring more advanced controller manipulations by the player. This process differs somewhat from the earlier discussion of mood management theory in that video game play does not simply distract a player from their current negative affect, rather it provides players a mechanism to address the cause of the negative state. If players were simply trying to distract themselves, they should have all selected higher difficulties, as this would have provided the most cognitively taxing experience. 64

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Thus far, our discussion has focused on elements of video game play and interaction that might elicit emotions. At the same time, the content of games is also considered important with regard to emotional experiences. There are numerous studies examining violent video games and their influence on aggressive affect (see the following meta-analyses, Anderson & Bushman, 2001; Anderson et al., 2010; Ferguson, 2007; Greitemeyer & Mügge, 2014; Sherry, 2001). Notably from the perspective of some researchers, violent content is the inciter of aggressive affect. Violent visual elements seem to have a preeminent focus in most research on the aggressive impact of video games rather than simply the inclusion of violent themes (see Bartholow, Bushman, & Sestir, 2006). Still, other researchers question the importance of visual elements to the act of playing. In a novel theoretical approach, Breuer, Scharkow, and Quandt (2014) propose that gamers employ “tunnel vision” while playing. Video game graphics are often simply a visual cue that distracts players from enacting the specific button presses necessary for success. Thus, through repeated play, gamers learn to ignore the superficial graphics in order to more accurately and precisely enact the various behaviors required for play (see Eden and colleagues, Chapter 6, this volume). Finally, it is worth noting that many current approaches examine the elicitation of specific emotions from game play. As previously mentioned, Hartmann et al. (2010) explicated logic suggesting that the narrative context of video game actions could lead players to feel guilty for virtual actions. They found that committing unjustified violence in a game as compared with justified violence led to increased feelings of guilt; they also found that when characters had backstories that humanized them (e.g., number of children they had, their likes and dislikes), players felt more guilt than when those characters did not have such backstories. Notably, the manipulations Hartmann et al. used essentially altered the motivation for the behavior rather than the behavior itself. That content interacts with motivation led Grizzard and Ahn (2017) to propose that exo-game manipulations (i.e., manipulations of content outside of the game, such as character backstory presented through instruction manuals) could be as effective as endo-game manipulations (i.e., manipulations of actual content) for eliciting emotions. Other researchers have also focused on specific emotions elicited by game play and how elements of the game’s content might magnify them. For example, Lynch and Martins (2015) have focused on how elements of game play might elicit fear and fight-or-flight reactions. Similarly, Possler and colleagues (Chapter 5, this volume) have explicated how video game graphics might elicit feelings of awe. Much of the research on specific emotions has served as a “proof of concept” justifying the possibility that video games can elicit specific types of emotions that previously were considered to be irrelevant to video game play. 65

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A Call to Action Since the mid-1980s, there has been a consistent interest in the empirical literature on video games and their emotion-related effects. Despite the general consensus that video games can elicit both basic emotions (such as anger and fear) as well as more cognitive-dependent emotions (such as guilt and awe), little consensus exists among researchers regarding the exact mechanisms of emotional experiences and which models are the most useful for understanding them. The goal of this chapter is thankfully not to resolve these controversies. In fact, we are fairly agnostic to which model we think best exemplifies the experience of emotion. This is not to say that researchers should be ambivalent about what model they select or that they should ambiguously combine various models when they do their research. In fact (and this criticism applies equally to our own research), more care should be placed on understanding what each model of emotion implies and what assumptions the model makes. We feel fairly confident in declaring that all current scientific models of emotion are—if not incorrect—at best incomplete. However, there is great value in holding the assumptions of whatever model we as researchers choose to a high standard. This means declaring explicitly which model of emotion we are using, considering whatever model we choose to be complete, and being consistent in our research with the assumptions of that model. If we as researchers fail to strictly adhere to the assumptions of a model, we risk failing to see disconfirmatory evidence when it presents itself and we risk failing to make a substantive contribution to the literature on emotion, even if we are focused (at least in the scope of a given investigation) only on making a contribution to the literature on video games. With these ideas in mind, this section of the chapter seeks to explain relevant models of emotion and how research on video games might more carefully utilize these models in advancing our understanding. Defining emotions consistently. In general, cognitive and social psychologists typically define emotion as “feeling” or “affect.” Most definitions of emotion also incorporate some variance in magnitude: emotions can be felt strongly or weakly. Emotions are generally differentiated from other psychological processes of interest, such as cognition (i.e., thinking) and behavior (i.e., doing). However, whether emotion is entirely distinct from cognition and behavior is debated and the historical development of the various approaches indicates that each holds implicit assumptions that differ from each other. For example, Scarantino (2016) differentiates three traditions—the feeling tradition, the motivational tradition, and the evaluative tradition—for emotion research. Each of these traditions arise from different conceptual understandings of the functional nature of emotions. In a similar approach as Scarantino, Oatley and Johnson-Laird (2014) differentiate action-readiness, core-affect, and communicative theories

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of emotion. Both Scarantino’s approach and Oatley and Johnson-Laird’s approach for differentiating current understandings of emotion hold promise. Examining the origins of the current state of emotions can provide insight into the implicit assumptions guiding theory. Two broad theories of emotion that hold import for understanding video games are the appraisal theories and the basic emotion theories. Appraisal theories of emotion tend to assume that the subjective label attached to biophysiological responses determines the experience of emotions (see Schachter & Singer, 1962). From these perspectives, emotional responses depend on an individual experiencing heightened physiological arousal and subsequent cognition (i.e., thinking) regarding what that arousal signifies. The same arousal response can therefore be interpreted as various emotions depending on the environment and elicitor of the arousal, which determine the cognitive label placed on the response. Thus, emotions are not distinct from cognition but rather a specific kind of cognitive process that is directly related to the elicitation and labeling of arousal. Some of the aforementioned studies can be viewed as consistent with appraisal theories. For example, the Kolko and Rickard-Figueroa study (1985) could be considered consistent with this approach. Variance in video game play and content leads to cognitive labels to which players can ascribe their biophysiological responses. Basic emotion approaches assume that biological bases exist for discrete emotional states. In other words, emotions are not simply the result of appraisal whereby any emotion can be ascribed to the same biophysiological response. Rather discrete cognitive/affective states exist separate from appraisal. Thus, the attribution of a specific biophysiological response to another label is unlikely to occur. For example, Ekman (1992a) extended Darwin’s work on the evolutionary origins of facial expressions to describe six basic emotions: happiness, surprise, fear, sadness, anger, and disgust. These emotions exist at the biophysiological level and can be dissociated from each other. At the same time, it is important to note that although Ekman argued that basic emotions existed as distinct psychological states associated with specific environmental triggers and automatic appraisal, emotions were not entirely separated from cognition and behavior. For example, Ekman (1977, 1992a, 1992b) argued that observers could infer an emotion was occurring when a combination of signals were present (e.g., facial expression, skeletal movement, changes in arousal, and behavior responses). In this way, the signals themselves were diagnostic for determining which discrete emotion was occurring. Notably, Ekman’s propositions preceded the use of functional magnetic resonance imaging (fMRI) in humans to examine neuro-psychological processes. Thus, Ekman’s empirical evidence for emotional responsiveness was limited to a behavioral and autonomic nervous system response. It is important to note that the signals described by Ekman are not emotions 67

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themselves but rather correlates of emotion. Therefore, their diagnostic utility is inherently limited by the strength of the correlation between the emotion and the indicator. This limits the reliability with which emotions can be identified, especially when the correlation between the emotion and indicator is weak, or when the behavioral indicator is suppressed by the individual. More recently, fMRI research has allowed for more direct observation of neural activity in specific brain regions and emotional responses (see Clark-Polner, Wager, Satpute, & Barrett, 2016, for an overview). Just as with appraisal-based theories, prior research could be considered consistent with discrete emotion research (Hartmann et al., 2010). Although guilt is not one of the six basic emotions indicated by Ekman, guilt is thought to be a specific type of emotion with its own elicitor— the recognition that one’s behavior violated a moral or social standard (see Tangney, Stuewig, & Mashek, 2007). Guilt is also considered to be a self-conscious emotion; in other words, individuals are consciously aware of their experience of the emotion and can self-report it. Research examining the ability of video games to elicit specific emotions can be seen not only in the work of Hartmann et al. (2010), but also in the work of Possler and colleagues (Chapter 5, this volume). Possler and his coauthors connect the virtual experience of large open spaces with feelings of awe. At the same time, past research has been somewhat loose with declaring which model of emotional experience it is adopting. Although this does not preclude the research from providing insights on the effects of video game play, it does prevent the research from providing insights into the emotional models. Findings from the studies can be interpreted by various researchers as being simultaneously consistent or inconsistent with a favored or disfavored approach. For example, both the state hostility scale (Anderson, Deuser, & DeNeve, 1995)—used often in violent video game/aggression research—and the intrinsic motivation inventory (Ryan, 1982)—used often to examine enjoyment/pleasure as a response to video game play—confound various models of emotion. For example, the composite created by the state hostility scale includes the combination of items such as “angry,” “disgusted,” and “friendly” (reverse-scored). Similarly, the intrinsic motivation inventory’s enjoyment subscale combines items measuring both “interest,” which on the face is closer to a cognitive state of attention than emotion, and “fun” (a proxy of “joy”). These measures prevent studies from fitting neatly into any current model of affective science. They are too specific to fit into a dimensional model, which would require that each state is linked to positive/negative affect, high/low arousal, and a cognitive label linked to this experience. Simultaneously, they fail to provide enough separation between the various emotions to fit into a discrete model of emotions; enjoyment comprises several different emotions (e.g., joy, interest) as does aggressive affect 68

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(e.g., anger, frustration, disgust). Thus, the research utilizing these scales is more closely defined as topic-based research as compared with research on mechanisms. Advancing the study of emotions in games. How then should we advance? We believe there are several ways to advance research on video games and their emotional impact. First and foremost, researchers should narrow their focus to a specific model. Additional proof-of-concepts studies that do not explicitly declare which model of emotion they are using no longer seem necessary to warrant that a video game can elicit a specific type of emotion. As games are simulations of reality, and simulations are capable of eliciting the same processes as real events (see Reeves & Nass, 1996), it is safe to assume that if a real event can elicit a specific type of emotion, video games can as well. Indeed, this was a core claim offered by Grodal (2000) when talking about the phenomenological similarity between a person encountering a hunger tiger “in real life” and having the same encounter in a video game; feelings of helplessness and fear likely take over, as the human perceptual system is tuned to orient toward the perceived existential crisis. For players of Tomb Raider (Eidos Interactive, 1996), they will remember the thrilling-yet-frightening encounter with the game’s first major antagonist: an adult Tyrannosaurus Rex that charged after the titular character at a time in which the player was only armed with a light pistol and a mediocre understanding of the game’s action affordances (for jumping and avoiding harm). Second, researchers should not stop at emotion. In other words, emotion should not be the final variable in a model. Research from psychology indicates that behavioral and cognitive consequences exist for various types of emotions. For example, success by oneself or an affiliate can lead to a behavioral phenomenon of “basking in reflected glory” (BIRGing); similarly, failure by oneself or an affiliate can lead to “cutting of reflected failure” (CORFing; Cialdini et al., 1976). Researchers interested in how or whether video games can elicit specific emotions should attempt to link those emotions to known behavioral and cognitive correlates of that emotional state. In this manner, emotions should serve as a mediator within most models, not the final endogenous variable. Third, researchers should not start from an agnostic position regarding what feature of games or gameplay elicits emotions. If researchers are assuming that it is game play that is determining the emotional responsiveness of the player, they should explicitly state this. If they believe that game play is suppressing emotional responsiveness, they should explicitly state this. Broadly, researchers must declare how and why content elicits or suppresses emotion and link that explanation to a specific model of emotional reactivity. Again, this means narrowing the focus of studies and being specific and explicit in the assumptions guiding the research. We believe that Possler et al.’s approach to awe (Chapter 5, this volume) 69

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does an exquisite job of doing just this. They link the emotion of awe to environmental cues in video games and do so using an integrated and specific model of emotion.

Conclusion This chapter lays down a gauntlet to all video game researchers interested in emotion, including ourselves. We do not want this chapter to be read as criticism to what has come before. Indeed, the perspective advanced in this chapter would not have been possible without the work of a host of researchers—including (but not limited to) those cited in our writing. In addition, this chapter is not without its limitations. We purposefully avoid some perspectives (e.g., motivation) as we wanted to limit our discussion to the emotional byproducts of video game play. This was purposeful in that we argue for more precision rather than more breadth in research. The future is bright. It is time for video game researchers to stop asking the questions of the past. Do video games increase aggression? Probably in many instances. Do video games reduce aggression? Also, yes. The questions that we should, nay must, start asking are not these. We must ask how and what features of game play lead to specific emotional responses. We see the forest. Now, let’s start looking at the trees.

Ludography Boxing. (1980). Sunnyvale, CA: Atari. Death Race. (1976). Fremont, CA: Exidy. Monopoly. (1935). Pawtucket, RI: Hasbro. Pong. (1972). Sunnyvale, CA: Atari. Smurfs: Rescue in Gargamel’s Castle. (1982). West Hartford, CT: Coleco. Space Invaders. (1978). Tokyo, Japan: Taito. Tomb Raider. (1996). London, UK: Eidos Interactive.

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5 G A M I N G I S AW E S O M E ! A T H E O R E T I CA L M O D E L O N COGNITIVE DEMANDS AND THE E L I C I TAT I O N O F AW E DU R I N G V I D E O G A M E P L AY Daniel Possler, Christoph Klimmt, and Arthur A. Raney

Video games offer users rich entertainment experiences. Playing games is not only an enjoyable activity (Vorderer, Klimmt, & Ritterfeld, 2004) but may also contribute to players’ personal-growth by providing “meaningful” experiences (appreciation; Oliver, Bowman, Woolley, Rogers, & Sherrick, 2015). Games’ emotional demand—their capacity to facilitate affective dynamics—plays a vital role for both forms of entertainment (cf. Bartsch & Oliver, 2016; Vorderer et al., 2004). One group of emotions that has recently been found to have a strong impact on the entertainment experience are other-praising emotions such as admiration or elevation (e.g., Janicke & Raney, 2016; Oliver, Hartmann, & Woolley, 2012). Among them, awe should be particularly relevant in video game entertainment for two reasons. First, video games should be highly suited to evoke awe, as they often contain potential elicitors of the emotion—stimuli that are perceptually vast and do not fit into established mental structures (see next section; Keltner & Haidt, 2003; Piff, Dietze, Feinberg, Stancato, & Keltner, 2015; Shiota, Keltner, & Mossman, 2007). In the material world, encounters with massive natural objects (e.g., the Grand Canyon) or vast buildings (e.g., cathedrals) evoke awe. But the virtual worlds of games also depict relevant elicitors (McGonigal, 2011)—such as vast landscapes (e.g., The Witcher 3: Witch Hunt; CD Projekt, 2015), large buildings (e.g., Assassin’s Creed II; Ubisoft, 2009), massive enemies (e.g., Shadow of the Colossus; Sony Computer Entertainment, 2005), or “awe-inspiring

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sound” (McGonigal, 2011, p. 107; e.g., tracks such as “Never Forget” in Halo 3; Microsoft Game Studios, 2007). Second, the experience of awe often shares important similarities with the entertainment experience resulting from playing video games, such as pleasure and enjoyment (see next section; Keltner & Haidt, 2003; Rudd, Vohs, & Aaker, 2012) as well as meaningfulness (see next section; Yaden et al., 2016). Hence, awe might positively contribute to game entertainment. Put simply, video games contain potentially awe-inspiring content and experiencing awe while playing games should enhance the entertainment experience. However, because video games place immense demands on limited attentional and cognitive resources of players (Bowman, 2016; Chapter 1, this volume; Bowman & Tamborini, 2012; Lang, 2006a), it is reasonable to assume that game-based task demands may interfere with the elicitation of awe. For example, players might not be able or willing to appreciate a panoramic view in the background if the game confronts them with fast-paced action requiring continuous button-mashing. Hence, the “mindfulness” that is required to experience awe as a part of game enjoyment and appreciation may conflict with the game’s cognitive demands and may compete with other sources of fun (such as performance and victory). Against this background, the present chapter aims to theorize the elicitation of awe while playing video games, giving special consideration to games’ cognitive demands as a precondition that might interfere with the process. While doing so, we focus on awe-experiences that are directly induced by game elements, as it is out of the scope of this chapter to consider all stimuli that might generate awe (vicariously) in a given gaming episode (e.g., the social situation of playing or fantasies and memories of the player; Scherer, 1998; Wirth & Schramm, 2007). In the following sections, we first give a brief overview on the psychological research on awe and point out theoretical links between the affective experience of awe, enjoyment, and meaningfulness. Next, we build on appraisal theories of emotions, especially the component process model (CPM; Scherer, 1984, 2001, 2009), and past research to conceptualize the elicitation process of awe in general and apply the model to video game play specifically. Finally, we present some concluding thoughts based on the model on awe’s capacity to contribute to game entertainment.

Introducing Awe: An Enjoyable and Meaningful Affective Experience Awe-related concepts have been discussed for a long time inter alia by philosophers such as Edmund Burke (1757/2015) or Immanuel Kant (1799/2011; for an overview: Keltner & Haidt, 2003). However, the emotion has drawn renewed scholarly attention in the past decade in the field

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of emotion psychology and positive psychology. One starting point was the foundational paper by Keltner and Haidt (2003), which combines past philosophical, sociological, religious, and psychological perspectives on awe and defines the emotion as a reaction to stimuli that are characterized by two features (appraisals; Shiota et al., 2007; see also Piff et al., 2015). First, awe is conceptualized as a reaction to perceptually vast stimuli—stimuli that exceed a person’s ordinary frame of reference or level of experience in some domain (e.g., power, size, perfection; Keltner & Haidt, 2003). Several studies found support for this appraisal (e.g., Campos, Shiota, Keltner, Gonzaga, & Goetz, 2013; Schurtz et al., 2012) and indicated that awe can be elicited by both the perception of symbolic vastness, for example, personal transitions (e.g., childbirth; Saroglou, Buxant, & Tilquin, 2008) and the perception of literal vastness, such as large trees (Piff et al., 2015; see also Van Elk, Karinen, Specker, Stamkou, & Baas, 2016). Second, Keltner and Haidt (2003) argue that awe-inspiring stimuli do not fit into established mental structures and, thus, require their adjustment. For instance, novel experiences, such as seeing the Grand Canyon for the first time, may challenge knowledge and expectations of what natural formations (such as erosion channels) can look like and how large they can be and require the adjustment of these cognitive structures. With reference to Piaget (1965), this process is labelled “accommodation” (Keltner & Haidt, 2003, p. 304). In accordance with this assumption, studies found that experiencing awe may challenge the worldview of a person (e.g., Gordon et al., 2017). However, empirical support for lacking mental structures as a generator of awe is less clear than the empirical support for perceptual vastness as an appraisal of awe (e.g., Campos et al., 2013; Schurtz et al., 2012). Based on this conceptualization, scholars in emotion psychology have examined the different components and correlates of awe. The emotion of awe has been linked to specific expressive behavior such as a distinct facial display (e.g., Campos et al., 2013) and a vocalization pattern (SimonThomas, Keltner, Sauter, Sinicropi-Yao, & Abramson, 2009). Moreover, distinct physiological reactions have been identified, such as a specific activation pattern in the autonomic nervous system (Shiota, Neufeld, Yeung, Moser, & Perea, 2011) or a strong link to goose bumps (Schurtz et al., 2012). However, to our knowledge, the largest amount of scholarly interest focused on the affective experience and cognitive processes related to awe, as the emotion was found to elicit profound changes in self-perception (e.g., Gordon et al., 2017; Piff et al., 2015; Rudd et al., 2012; Shiota et al., 2007; Van Elk et al., 2016), to activate various thought-repertoires (e.g., spiritual cognitions; e.g., Saroglou et al., 2008; Van Cappellen & Saroglou, 2012; Valdesolo & Graham, 2014), and even to facilitate behavior such as pro-social actions (Piff et al., 2015; Prade & Saroglou, 2016). It is beyond the scope of this chapter to provide a broad review on the current 76

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state of awe research—see Zhang and Keltner (2016) instead. However, in the following, we focus on those findings that help us to conceptualize the links between awe and two essential components of the entertainment experience—enjoyment and meaningfulness. At first, the awe experience was conceptualized to be located “in the upper reaches of pleasure and on the boundary of fear” (Keltner & Haidt, 2003, p. 297). In accordance with this assumption, it was found that awe experiences are mostly positively valenced (e.g., Campos et al., 2013) but can also contain negative flavors such as fear (Piff et al., 2015). Most recently, Gordon and colleagues (2017) found that 79 percent (recall of past emotional episodes) to 88 percent (daily diary study) of all awe-experiences are positive. Although these studies were mostly conducted with convenience samples and, thus, do not provide reliable numbers on the distribution of negative and positive awe episodes in general, they suggest that feeling awe is most often a positive experience. Accordingly, studies indicated that positive awe fosters happiness (Gordon et al., 2017) and awe in general increases momentary life satisfaction (Rudd et al., 2012). As media psychology traditionally understands enjoyment as a form of “pleasure” (e.g., Vorderer et al., 2004), the experience of awe with positive valence should most often be enjoyable. Due to this link with the entertainment experience, we focus on positive awe experiences in this chapter. A second important link between awe, enjoyment, and meaningful experiences is based on the emotion’s impact on a person’s self-perception. Awe may result in the feeling of being small and insignificant in comparison to the stimulus (Gordon et al., 2017; Piff et al., 2015; Shiota et al., 2007). This does not only include changes in a person’s body perception (Van Elk et al., 2016) but also “a reduction in attention to the often all-consuming self and its goals” (Haidt & Morris, 2009, p. 7688; see also Gordon et al., 2017; Piff et al., 2015). When experiencing awe, people seem to shift their attention from their self to the perceptually vast stimulus (Piff et al., 2015). This reallocation of attention often goes hand in hand with a feeling of connection with, or orientation toward, something larger or more important than ordinary concerns (e.g., “the beauty of nature”; “the universe”; Piff et al., 2015; Shiota et al., 2007). Initial studies indicate that these changes of self-perception, often labelled “self-transcendent experience” (e.g., Yaden et al., 2016, p. 5), allow people to temporarily forget their problems of daily life (Shiota et al., 2007). Hence, awe experiences with self-transcending qualities may result in escapist effects (Henning & Vorderer, 2001). Scholars in media psychology found that escapism is an important motive for using entertainment media (Vorderer et al., 2004), and may result in positive effects such as recreation or relief of stress (Klimmt, 2008), which were found to fuel enjoyment (Reinecke, Klatt, & Krämer, 2011). Hence, awe experiences should also be enjoyable due to escapist effects. 77

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Third, the orientation to, or connection with, a greater good outside of the self should be a highly meaningful experience. Especially strong awe-experiences such as seeing the Earth from space in person (overview effect; cf. White, 1987) have been reported to be highly meaningful and even transformative (Yaden et al., 2016). As Haidt and Seder (2009) put it: “Awe stops us dead in our tracks, and sometimes, when intense enough, acts like a reset button on the self” (p. 5). But even less intense experiences could be highly meaningful, as self-transcendent experiences in general and awe in particular have been found to activate spiritual and religious thoughts and intentions (Saroglou et al., 2008; Valdesolo & Graham, 2014; Van Cappellen & Saroglou, 2012; Van Cappellen, Saroglou, Iweins, Piovesana, & Fredrickson, 2013). Taken together, awe is an emotional response to vast stimuli that requires accommodation, and to feel awe should most often be positive, highly meaningful, and pleasurable experience. Interestingly, many studies in emotion psychology try to induce awe using movies or pictures, but media psychology has so far rarely investigated awe as part of media users’ and gamers’ (entertainment) experience. Hence, it is worthwhile to develop theoretical and empirical perspectives on the elicitation and effects of awe in the context of media entertainment.

Conceptualizing the Elicitation of Awe Before discussing the elicitation of awe in games, we present a general model of awe generation that may serve as a basis to understand the potential impact of video game particularities on the elicitation process. Upon the many different perspectives on emotions (for a brief overview see Gross & Feldman Barrett, 2011), appraisal theories have proved to be a useful framework to explain media-induced emotions (Bartsch, Vorderer, Mangold, & Viehoff, 2008). Especially the component process model (CPM) by Scherer (1984) has been successfully applied to mass media (e.g., Unz, 2010) and has been tested with video games (e.g., Lanctôt & Hess, 2007). According to the CPM, emotions consist of temporal, interrelated, and synchronized changes in cognitions, subjective feelings, physiological response patterns, motor expressions, and action tendencies (Scherer, 2001). The evolutionary function of these coupled changes is to enable individuals to flexibly adapt to their environment (Scherer, 2001, 2009). Hence, the CPM conceptualizes an external or internal stimulus as the starting point of any emotional episode (Scherer, 2001, 2009). However, it is not assumed that the objective characteristics of a stimulus evoke an emotional response. Rather, people’s’ subjective evaluation (or appraisal) of the stimulus is key (Ellsworth & Scherer, 2003; Scherer, 2001, 2009).

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Figure 5.1  The elicitation of awe from the perspective of the component process model (based on Scherer, 2009, p. 1308).

This cognitive component can essentially be regarded as the driver of the elicitation and differentiation of emotions, as it initializes changes in the other affective components (Scherer, 2009; Unz, 2010; see Figure 5.1). First, the cognitive appraisal results in changes of the motivational subsystem. Second, the motivational changes and cognitive processes cause physiological response patterns and motoric reactions. Third, all of these changes may reach (to some degree) the level of consciousness and result in a subjective feeling. As the components are all highly interrelated, changes in one component can affect the state of the anteceding components (see bi-directional arrows in Figure 5.1; Scherer, 2001). Thus, using the perspective of the CPM to model the experience of awe, it is crucial to understand how people cognitively evaluate a stimulus. Scherer (1984) proposes a set of criteria, called “stimulus evaluation checks” (SEC; Scherer, 2009, p. 1309), with which people appraise a stimulus and its probable consequences. Each emotion is related to a specific and stable SEC-profile (Scherer, 2001). However, research has not yet made clear which appraisal profile is related to awe. The present model thus includes a proposition to express the onset of awe in the logics of the CPM. The CPM argues that a stimulus requires at least some relevance for a person in order to attract attention and motivate further processing that could result in an emotional response (Ellsworth & Scherer, 2003; Scherer, 2001). This basic (and often unconscious) “selective filter” (Scherer, 2009, p. 1317) preserves cognitive resources and should therefore also be applicable to the elicitation of awe. A stimulus is characterized as relevant if it exceeds a certain threshold of novelty or intrinsic pleasantness/unpleasantness or importance for the goals and needs of a person (Scherer, 2001, 2009). Hence, the first appraisal we suggest is basic relevance detection.

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Second, because awe is triggered by vast stimuli (see previous section), perceptual vastness is proposed as an emotion-specific appraisal criterion (cf. Keltner & Haidt, 2003). Third, awe is elicited by impressive stimuli that requires people to adjust their mental schemes (see previous section). Hence, need for accommodation is suggested as the third awe-specific SEC (cf. Keltner & Haidt, 2003). Finally, theory and research argue that fear-related, negative and positive experiences of awe should be distinguished (Gordon et al., 2017; Keltner & Haidt, 2003; Piff et al., 2015; see prior section). Based on the work of Gordon and colleagues (2017) on threat-related negative awe, we suggest that SECs related to threat detection could further differentiate the two subtypes of awe. Overall, the elicitation of positive awe experiences is theorized from a CPM perspective by predicting positive awe to occur when a stimulus is rated high on the first three appraisals (relevance, vastness, need for accommodation) and low on the fourth (threat). To return to our example from earlier in this chapter, visitors to the Grand Canyon will inevitably find it relevant (e.g., assuming they have willfully made the trip), perceive its vastness (relative to other natural phenomena in the immediate surroundings or similar ones readily accessible in memory), and find it larger than “anything they have seen before” (i.e., that it is difficult to integrate it into existing cognitive structures), and most likely perceive the Grand Canyon to be no immediate threat.

Theorizing Positive Awe as a Gaming Experience In order to apply this general model of the elicitation of awe to the gaming experience, two particularities need to be considered. First, awe-inducing stimuli in games are artificial in that, as digital presentations they are restricted to a non-material and ephemeral nature. Second, games typically demand constant user input, which places rather high demands on players’ cognitive resources (Bowman, 2016; Chapter 1, this volume). Artificiality. One could argue that media content only rarely induces strong, direct emotions due to its artificial nature: Events and objects portrayed in the media most likely have no direct consequences and therefore no relevance for the audience. For example, an emperor encountered in a video game is an artificial character and, thus, does not really have vast political power (beyond the game world, at least). Such a situation should be rated rather low on many appraisal criteria (e.g., relevance, as the emperor’s virtual power is no threat for the player outside of the game), the end result of which would be a rather weak emotional experience. In contrast to this assumption, Hartmann (2013, 2011) suggests, with regard to different dual-process theories, that players experience video games through two distinct systems. In the experiential mode, users process games automatically, based on intuitive associations: in-game stimuli 80

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that are sufficiently familiar to memorized objects or events from the material world are automatically recognized and, thus, perceived to be non-artificial (ibid). Thus, players do not think and feel about a game, but rather do so within the game (Hartmann, Klimmt, & Vorderer, 2010). In contrast, the rational mode is built on analytic reflections, which means that players are aware of the artificial illusion. Although both modes may work in parallel, experiential processing is more dominant than rational processing while playing because it is the phylogenetically older mode, requires fewer cognitive resources, and facilitates the enjoyable experience of being immersed in a fictional world (Hartmann, 2013, 2011; cf. Lang, 2006a). Applied to the example above, a player encountering a powerful emperor in a video game would probably process the situation in an experiential fashion and, thus, perceive the emperor to be “real” and actions to have powerful consequences. As video games are interactive, players are required to actively deal with these seemingly “real” individuals, objects, and events—just like in the material world (Grodal, 2000). Hence, stimuli in games should be able to elicit strong emotions, including awe. In addition to the distinction of experiential and analytic processing, several different concepts of video game immersion have been proposed in media psychology (Hartmann et al., 2010), the integration of which is not a core focus of this chapter. However, one idea that all immersion concepts have in common is the broad assumption that players “get lost in” (ibid, p. 139) a video game, process the content in an experiential fashion (rather than a rational one), and perceive it to be non-mediated (ibid). As the different conceptualizations of immersion vary in their underlying mechanisms, the relevance of these concepts for the elicitation process of positive awe in a given gaming situation most likely depends on the fit of the underlying mechanism to the awe-elicitor—the specific stimulus, or in the case of a video game, the specific on-screen element of the game that one is reacting to. For example, spatial presence is conceptualized as the experience to be physically located in a mediated environment (Lee, 2004; Tamborini & Skalski, 2006; Wirth et al., 2007). As players feel “to be in” the game world, visual elicitors of awe presented in the game’s environment (e.g., vast landscapes, large enemies, huge buildings) should be perceived as more relevant and, thus, result in stronger awe experiences. In contrast, the concepts of transportation and narrative presence rest on the assumption that players “get lost in the story” of a game (Busselle & Bilandzic, 2008; Green & Brock, 2000; Green, Brock, & Kaufman, 2004). The content of the story almost feels real for the media user (Green et al., 2004). Hence, transportation and narrative presence should be especially likely to intensify the impact of symbolic, story-based elicitors of awe (e.g., non-visual descriptions of vast power, personal transitions). Finally, the concept of identification implies that players adopt the perspective of a video game protagonist and temporarily integrate characteristics of 81

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their avatar into their self-concept (Klimmt, Hefner, & Vorderer, 2009). Research shows that players thereby also take over cognitions and emotions of the character (Blake, Hefner, Roth, Klimmt, & Vorderer, 2012; Li, Liau, & Khoo, 2013). Hence, it can be assumed that during identification, players appraise in-game stimuli from the perspective of their character, which should increase the relevance of both symbolic, story-based elicitors, but also literally vast elements in the game world. However, as the immersion mechanisms conceptually overlap (Klimmt & Vorderer, 2003), these initial hypotheses on stimulus-concept-interactions have to be tested in future studies. Overall, we contend that awe experiences during game play will depend on the perceived reality (i.e., non-artificial impression; Scherer, 1998) of the stimulus, which, in turn, grows from experiential processing and immersion experiences. Put simply, while video games are rationally artificial environments, they are often experienced as real ones—as such, they have the potential to inspire awe. Cognitive demands. The elicitation process of awe as described previously requires the investment of cognitive resources, which may have implications for the formation of awe during game play. Most basically, affective responses require attention allocation to the stimulus (Gross & Feldman Barrett, 2011; Scherer, 2001): Detecting a stimulus can be regarded as “gateway to the emotional system” (Ellsworth & Scherer, 2003, p. 576). Moreover, the process of stimulus appraisal should require further cognitive efforts as different cognitive functions have to be carried out (Scherer, 2001, 2009). For example, awe is elicited by the perception that mental structures need to be updated (Keltner & Haidt, 2003; see above). To come to this conclusion, individuals most likely compare the stimulus with prior encountered objects or events. Hence, memorized information has to be retrieved, which requires the investment of cognitive resources (Lang, 2000). Although, in general, stimuli can be evaluated in a rather effortless fashion based on prewired response sets or learned schemata (Leventhal & Scherer, 1987), awe-stimuli do not fit into established mental structures per definition (Keltner & Haidt, 2003) and should, thus, call consciousness and effortful processing into action (cf. van Reekum & Scherer, 1997). To sum it up, awe experiences are only likely to occur if an individual is willing and able to spend a sufficient amount of cognitive efforts on perceiving and appraising the stimulus with awe-related attributes. However, playing digital games often consumes enormous amounts of cognitive capacity (Bowman, 2016; Chapter 1, this volume). If gamers are unable or unwilling to mobilize resources for detecting and appraising awe-inducing game elements because they are “busy” with “keeping the game going,” the intensity of their awe experience may be rather marginal. In contrast, if players are able and motivated to invest a sufficient

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amount of cognitive energy to perceive and appraise awe-inducing game elements, they are likely to reach a rather powerful level of awe. The question of how much cognitive effort players expend on a potentially awe-inducing stimulus can be explained by the Limited Capacity Model of Motivated Mediated Message Processing (LC4MP; Lang, 2006a, 2009; see Figure 5.2). Its basic assumption is that playing games requires users to invest cognitive resources for multiple processes (encoding, storage, and retrieval; Lang, 2000, 2006a). However, individuals only possess a finite amount of resources (Lang, 2000). If a task requires more assets than individuals invest, cognitive overload occurs and task performance suffers (Lang, 2000, 2009). Hence, the selective allocation of cognitive resources is “at the heart of the LC4MP” (Lang, 2009, p. 198). This reality is especially important for games, as players are confronted with a multitude of stimuli (Chung & Sparks, 2015; Lang, 2006a). Moreover, players are required to constantly monitor game events, make decisions, and react with suitable inputs (Bowman, 2016; Klimmt & Hartmann, 2006). According to the LC4MP, players can willingly decide which game elements they allocate their cognitive resources (top-down allocation; Lang, 2006a, 2009). Especially elements related to progress in the game are likely to be prioritized, such as threats or rewards (cf. Chung & Sparks, 2015). If an awe-inducing stimulus is part of such an element, users will likely perceive and appraise it and hence experience strong awe. For example, a vast vista in a game that allows the player to look out for enemies and prepare an attack helps him/her to make progress in the game. Thus, the

Figure 5.2  Theorized pathways of the elicitation of video game awe based on LC4MP.

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gamer should process the vista intensively, which, in turn, should result in a strong awe-experience. On the other hand, potentially awe-inducing stimuli in video games are often of secondary importance for pursuing the main game goal— for instance, vast landscapes unfolding as background scenery that is not accessible to the player. These peripheral elements should receive less priority for top-down resource allocation (Chung & Sparks, 2015), as those resources are likely allocated toward more task-relevant game play decisions. However, the LC4MP assumes that stimulus characteristics can also trigger an automatic allocation of resources through activating the basic motivation systems responsible for approaching positive and avoiding negative stimuli (Lang, 2006a, 2009; cf., Bradley & Lang, 2007). As awe-inducing events are perceptually vast and, thus, obtrusive as well as potentially dangerous (cf. Keltner & Haidt, 2003), these video game stimuli should be able to activate the motivational systems. This, in turn, should result in allocation of resources to the stimulus, which should ultimately result in attention allocation, appraisal, and a rather strong awe experience. However, if players’ primary activity (e.g., achieving progress in the game) requires too many resources—such as was demonstrated by Bowman and Tamborini (2012)—then sufficient assets may not remain to process an awe-inducing stimulus. Hence, the automatic resource allocation could result in cognitive overload (Lang, 2009). In this case, the perception and appraisal of the awe-inducing stimulus will be insufficient or rather superficial (Lang, 2009), and thus, most likely result in a weak emotional experience. Finally, experienced video game players have demonstrated strong abilities to willingly focus their attention and to be less susceptible to distractions (Chisholm, Hickey, Theeuwes, & Kingstone, 2010; Mishra, Zinni, Bavelier, & Hillyard, 2011). Hence, such players should be less susceptible to automatic reallocation of resources, which should also result in weak emotional experiences, if awe-relevant stimuli are merely “background elements” of a game.

Conclusion: Awe and Game Entertainment The outlined model predicts that awe is a specific emotional experience that can be part of the affective dynamics of video game play. It is, however, bound to several preconditions (i.e., experiential processing) and interacts with the cognitive demands that games impose on players (see Figure 5.3). In contrast to other affective reactions such as suspense (Klimmt, Rizzo, Vorderer, Koch, & Fischer, 2009) that presumably reoccur during playing at relatively high frequencies, one might argue that awe is probably a “rare” element in the affective experience that players go through. 84

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Figure 5.3  Model of the elicitation of awe in video games.

First, for games to evoke awe, game designs must offer awe-evoking stimuli. However, the industry is investing enormous resources to increase the “awe capacity” of games, such as stunning background graphics or meaningful story elements (McGonigal, 2011; Oliver et al., 2015). Thus, we argue that the primary reason why awe should be a “rare” element of game enjoyment is the heavy cognitive demand of playing; as a result, users are only rarely willing and able to actually enter strong and lasting awe experiences. Their mental resources are most often preoccupied by keeping game play going: solving problems, surviving, making smart and fast decision are activities that consume massive cognitive resources (Bowman, 2016; Chapter 1, this volume). According to the proposed model, it thus takes special circumstances to meet all preconditions of awe (e.g., players who master game play without depleting all of their cognitive resources, or the position of an awe-evoking element during a game phase with low cognitive demands, such as a scripted sequence). So, why should positive awe be important to understanding game entertainment? The answer lies in the defining characteristic of positive awe. Positive awe is in general a special emotion that does not occur very often (cf. Schurtz et al., 2012); most people rarely enter situations that overcharge their mental structures and are extremely vast. But if they do, they often find the experience radically different from normal life, appreciate it deeply, and remember it sustainably (Keltner & Haidt, 2003; Yaden et al., 2016). Hence, if a rare moment of awe occurs during game play, players are likely to experience it as a “special highlight” that adds to the overall enjoyment to a much larger degree than the next 20 micro-episodes of suspense and pride afterwards (Klimmt, 2003). So while some emotions contribute reliably to ongoing game enjoyment, awe is proposed as an important addition to the menu of video game affect, because it is special, powerful, and “hard to get.” 85

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Empirical research is required to test the outlined model. Experimental and survey research, both qualitative and quantitative, will help to verify the elicitation of positive awe in gamers, its assumed multiple preconditions, and its plausible consequences for video game enjoyment and experiences of meaning. Future research should also further differentiate the awe-elicitation process for different types of stimuli. We already assumed that the relevance of different immersion mechanisms on the elicitation of the emotion depends on the type of the stimuli (e.g., story-based vs. visual elicitor). Similarly, it could be argued that different types of elicitors require different amounts of resources in order to be thoroughly processed. For example, audio-only stimuli (e.g., orchestral music) might require fewer resources than audiovisual stimuli (e.g., a waterfall) as only one channel of presentation is used (cf. Lang, 2006b). Hence, some types of elicitors might be more able to evoke awe under conditions of higher cognitive load. Additionally, in this chapter we focused on video game users who actively play games. However, a large number of video game experiences are made by observing other gamers, be it co-located in one room or via game play videos and streams on platforms such as YouTube or Twitch (tandem play, see Consalvo, 2017; Chapter 9, this volume). Future research should investigate if this “passive form” of video game consumption impacts immersion and cognitive resources and ultimately the elicitation of awe. For example, it could be assumed that users who are not engaged in the effortful act of playing have more resources left over for experiencing awe. If future studies lend support to the present propositions, applications of the model may also help to assist game makers in designing unforgettable moments of awe, and thus, in further improving the entertainment value of their popular products.

Ludography Assassin’s Creed II. (2009). Rennes, France: Ubisoft. Halo 3. (2007). Redmond, WA: Microsoft Game Studios. Shadow of the Colossus. (2005). San Mateo, CA: Sony Computer Entertainment. The Witcher 3: Witch Hunt. (2015). Warsaw, Poland: CD Projekt.

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Van Cappellen, P., Saroglou, V., Iweins, C., Piovesana, M., & Fredrickson, B. L. (2013). Self-transcendent positive emotions increase spirituality through basic world assumptions. Cognition & Emotion, 27(8), 1378–1394. doi:10.1080/ 02699931.2013.787395 Van Elk, M., Karinen, A., Specker, E., Stamkou, E., & Baas, M. (2016). “Standing in awe”: The effects of awe on body perception and the relation with absorption. Collabra, 2(1), 1–16. doi:10.1525/collabra.36 van Reekum, C. M., & Scherer, K. R. (1997). Levels of processing in emotion-​ antecedent appraisal. Advances in Psychology, 124, 259–300. doi:10.1016/ S0166-​4115(97)80123-9 Vorderer, P., Klimmt, C., & Ritterfeld, U. (2004). Enjoyment: At the heart of media entertainment. Communication Theory, 14(4), 388–408. doi:10.1111/​ j.1468-2885.2004.tb00321.x White, F. (1987). The overview effect: Space exploration and human evolution. New York, NY: Houghton and Mifflin. Wirth, W., Hartmann, T., Böcking, S., Vorderer, P., Klimmt, C., & Schramm, H., et al. (2007). A process model of the formation of spatial presence experiences. Media Psychology, 9(3), 493–525. doi:10.1080/15213260701283079 Wirth, W., & Schramm, H. (2007). Emotionen, metaemotionen und regulationsstrategien bei der medienrezeption: Ein integratives modell. [Emotions, meta-emotions and emotion regulation during media consumption. An integrative model.] In W. Wirth, H.-J. Stiehler, & C. Wuensch (Eds.), Dynamisch-​ transaktional denken: Theorie und Empirie in der Kommunikationswissenschaft [Thinking in a dynamic-transactional way: Theory and empirical research in communication science] (pp. 153–184). Cologne: Halem. Yaden, D. B., Iwry, J., Slack, K. J., Eiechstaedt, J. C., Vaillant, G. E., & Newberg, A. B. (2016). The overview effect: Awe and self-transcendent experience in space flight. Psychology of Consciousness: Theory, Research, and Practice, 3(1), 1–11. doi:10.1037/cns0000086 Zhang, J. W., & Keltner, D. (2016). Awe and the natural environment. In H. S. Friedman (Ed.), Encyclopedia of mental health (2nd ed., Vol. 1, pp. 131–134). Waltham, MA: Academic Press.

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6 B E H AV I O R A L D E M A N D S A S B E H AV I O R A L A F F O R DA N C E S IN VIDEO GAMES Allison Eden, David R. Ewoldsen, Joomi Lee, and David Beyea

Past research has defined behavioral demands of video games as requirements a game makes on us physically. These demands may be via an input device—demanding users take on more button pushing, lever-pressing, or mouse-scrolling type tasks—or motivational demands such as via branching goal structures in the plot. In this chapter, we address these conceptualizations of behavioral demand and then move to discussing how game scholars can more broadly define behavioral demand by taking into consideration Gibson’s (1966) ecological perception theory and his (1979) notion of affordances. In simplest terms, the affordances of any given environment are simply those behavioral possibilities that it provides or furnishes to an agent. In terms of game worlds, we define affordances as behaviors that the virtual or game environment allows players to enact. Various game researchers have described game affordances in terms of the actions or behaviors players can take in a game space or as the negotiation of behavioral possibilities between player and game designer (Gaver, 1991). We review these conceptualizations and then discuss the relative advantages of considering behavioral demands as behavioral affordances in regard to the social affordances of games. After this discussion, we will touch on the notion that affordances can be understood independent of behavioral inputs. To illustrate, we will discuss the social affordances of games, specifically, the social possibilities afforded by, and supported in, a playful space (Sutcliffe, Gonzalez, Binder, & Nevarez, 2011).

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Behavioral Demand via Input Device Video games are inherently interactive, inherently “a lean forward media” (Jansz, 2005, p. 222). By this, it is commonly understood to mean that games require active and near-constant input from the user in order to drive the narrative, play, or exploration of a game world (Weber, Behr, & DeMartino, 2014). Some people argue that interactivity is inherently demanding of a user’s resources (Klimmt, Steinhof, & Daschmann, 2008; Kureshi & Sood, 2009; Lee & Faber, 2007; Yoo & Peña, 2011) based on limited capacity models of attention allocation (Lang, 2000, 2006). In other words, the more behavioral actions a game requires of the user, the less available attention exists for other tasks (Lang, 2006). Based on this understanding, behavioral demand in games can be defined perhaps most concretely in terms of specific types of controllers and input devices that let us translate our physical actions into game spaces with a greater or lesser degree of required attentional demand. This maps onto past technology-oriented conceptualizations of interactivity in video games (Weber et al., 2014). For example, Steuer (1992) defined interactivity as comprising three factors: speed, or the rate at which input can be assimilated into a media system; range as the number of actions available, and mapping as the extent to which the input devices map to changes in the environment. Targeted specifically to games, Klimmt (2003) defined the interaction with a game’s technology as input-output loops. Sellers (2006) listed perceptual or physical interactivity as part of his concept of video game interactivity. Raney et al. (2006) included control devices using different types of input and providing feedback as part of their definition of video game interactivity. Finally, Weber et al. (2014) defined controller responsiveness as one of their seven dimensions of video game interactivity, in particular, “the ease of use of a game interface and to the speed and appropriateness of a game system’s reactions to a player’s input.” (p. 84). What these definitions have in common is the understanding that games require some sort of action on the part of the player in order to be played, and that these actions may require varying amounts of attention and physical capability—what Bowman (2016) has termed “behavioral demand.” Although this is perhaps the most common and easily accessible understanding of “behavioral demand” in games, conceptualizing behavioral demand solely via input device is limited for three reasons. First, it suggests that game input devices that directly map onto the same behavior in a non-virtual space, that is, devices mapped to the human perceptual system (Biocca, 1997), will be less taxing on attentional resources. But, as Rogers, Bowman, and Oliver (2015) and Limperos, Schmierbach, Kegerise, and Dardis (2011) show, this is not always the case. Both studies illustrate

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that the naturally mapped controllers did not lead to greater presence or enjoyment of game play, leading to the conclusion that experienced players learn game-specific models of behavior tied to the physical controllers used by the game. Similarly, Bowman, Pietschmann, and Liebold (2017) compared gamer perceptions of traditional (gamepad) versus natural user interfaces (such as the Wiimote) and found that naturally mapped interfaces elected more negative comments about the lack of “natural feeling” in players. Clearly, the sequence of behaviors that are necessary to complete some actions within the game—specific to the game input device—will become automatized with practice. As these behaviors become automatized, they will require less cognitive resources. Therefore, the complexity of the input device, once automatized, will not disrupt a skilled players’ presence or enjoyment. To illustrate, the process of aiming and firing a gun in Halo (Bungie, 2001) using a standard Xbox controller, is not necessarily more attentionally or behaviorally taxing (particularly after extensive practice) than playing Duck Hunt (Nintendo, 1984) on the Nintendo Entertainment System using a toy gun as an input device, despite the better mapping of the gun onto real-world shooting mechanics. Thus, direct game experience with specific controllers is more important than direct physical mapping onto real world actions via input devices in terms of understanding demand. Thus, in defining “demand,” we must look beyond the pure physical input required to understand what that physical input means to specific players. Second, technology is always advancing, and designers are finding more ways for the virtual world to more directly subsume the senses. As Ijsselsteijn (2003) puts it: The search for the “Ultimate Display”, […] has been motivated by a drive to provide a perfect illusory deception, as well as the ancient desire for physical transcendence, i.e. escaping from the confines of the physical world into an ‘ideal’ world dreamed up by the mind. (p. 2) In other words, technological development of input devices will not stop until there is a complete absorption of the perceptual system by the technological, until, to paraphrase Ijsselsteijn, it will become possible to enter a perceptually perfect simulacrum limited only by the creativity of the game designer. Think of the HoloDeck on Star Trek, or the immersive digital world of the Matrix. At some level, we are always advancing toward this notion of the perfect simulacrum, one devoid of the need for perceived mechanical mediation via an input device. This being the case, limiting our notion of behavioral demand to specific input devices would 94

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temporally bound our definition to today’s input devices; when history suggests that these are in no way static technologies. Third, understanding of attention as a limited capacity resource that can be taxed uniformly by behavioral demands oversimplifies how humans can interact with their environment. As noted previously, when tasks become routinized, they require less cognitive effort to complete, and as technology advances, once-impossible tasks become commonplace. Also, humans are skilled at interleaving attentional focus, concentrating on multiple inputs and outputs in brief bursts of attention to each task. Finally, some tasks may actually benefit the user in terms of restoring depleted resources during play. Therefore, discussing behavioral demand in terms of limited capacity models both may shape the concept of demand and the concept of what is demanding in limiting ways.

Moving Beyond Input-Output Models If we move beyond controller input models as a measure of behavioral demands, then how can we consider what is “demanding,” for whom, in the complex intersection of terms and conflicting definitions? And how can any definition situated in today’s technology be appropriate for today, yet flexible enough for unforeseen changes in virtual experiences? One possible theoretical framework that could allow us to better understand behavioral demand is Lang’s (2014) dynamic human centered communication systems theory (DHCCST). Grounded in assumptions from Gibson’s (1979) ecological perception theory and dynamic systems theory (Kelso, 1995; Thelen & Smith, 1994), DHCCST defines communication as a “complex dynamic system consisting of a human, a message, a medium, and a location” (p. 60). According to this perspective, humans can be considered complex adaptive systems, self-organized as a function of initial conditions, order parameters, and control parameters (Thelen & Smith, 1994). Initial conditions are the starting conditions for any dynamic system, although due to the nature of dynamism, initial conditions are each themselves the starting point for subsequent “initial conditions.” Order parameters limit parts of the dynamic system by constraining what the system can do, thus limiting the degrees of freedom available to an organism at a given moment. In dynamic terms, order parameters shape the state space of the system. Under the influence of order parameters, a system is also more or less sensitive to certain external variables, called control parameters. Control parameters are variables that move the system through a different qualitative state in the state space. In the context of mediated message processing, a medium may act as an order parameter by providing hard limits on relevant sensory systems because that sensory system becomes essential for the processing of the message due to the nature of message. Lang (2014) offers the example of 95

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playing a racing video game. The audio part of the message constrains the auditory perceptual system. The audio and visual parts of the game constrain the visual perception system. The game controller constrains the motor system. The object, reward structure, and contents of the game constrain the motivational system, that is, limits the motivational system of the player to respond in specific, limited ways. Once the videogame affects a player’s nested systems in this fashion, the range of possible motivational, cognitive, or behavioral responses available to the player will be constrained by what the game offers. This said, the structure, content, and underlying mechanism of the game environment generate a sizeable number of behavioral patterns across all players at a general level by restricting available responses to them. Certainly, this will be the case with early exposure to a game and game system. For example, Weber, Behr, Tamborini, Ritterfeld, and Mathiak (2009) analyzed the second-by-second gameplay of 13 gamers playing an episode of the multiplayer first person shooter game Tactical Ops: Assault on Terror (Kamehan Studios, 2002). Despite the between-subject variance in specific actions, Weber et al. (2009) were able to isolate common playing patterns of game-play events. The 16 most common sequences of events (with three events linked in a specific causal sequence) accounted for 58.51% of all playing time (e.g., the sequence “equipment-safety-danger” accounted for 10.81% of total playing time). Although limited, to a certain extent, the player’s responses will still vary depending on levels of control parameters (e.g., structural or content changes in the game or the location) and initial conditions (e.g., skill level or mood before he/she starts playing). In other words, different players can end up with qualitatively different outcome states by playing the same game, or one player can exhibit different behavioral outcomes by playing different games or playing the same game in different contexts (Lang, 2014). For example, Matthews and Weaver (2013) demonstrated that players’ experience, familiarity with the game controller, and in-game success resulted in different experiences from the gameplay. Likewise, Lee and Lang (2016) investigated automatic aversive responses (i.e., startle reflex) to ambient darkness within the videogame Skyrim coupled with different environmental contexts, such as lighting (light or dark) and valence (pleasant or unpleasant) in both the virtual environment and the location (i.e., the laboratory). The result showed that the magnitude of the resulting startle reflex showed a combination of both the virtual environment and the location, implicating the importance of the environmental context in altering responses to the mediated environment. Taken together, these findings point to the complex and dynamic nature of the communication system influencing both the idiosyncratic nature of game play for individual players and the generalizable model of game behaviors that are bounded by constraints of the game, goals, and player 96

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environment. Therefore, identifying and conceptualizing these boundaries is important to understand potential behavioral demands of virtual worlds. Two main theoretical perspectives have been offered in past literature to describe or define behavioral constraints in virtual worlds: game mechanics and game affordances.

Game Mechanics as Behavioral Constraints Game mechanics are those things that “define and delimit the player’s interaction with the game” (Sherry, 2014, p. 110), and is often used by game designers to specify physical rules and avatar/player actions. As Sicart (2008) puts it, “Game mechanics are methods involved by agents for interacting with the game world.” For example, he details how a player may “take cover” in a virtual environment by pressing a button on a game controller. Sicart goes on to define game mechanics as verbs—that is, what can we do, hit, jump over, lift, or push, in a game—which differentiates mechanics from rules governing behavior and challenges that motivate players to enact specific actions. Sicart (2008) also ties game mechanics closely to input devices that enact specific behaviors (i.e., I “push” doors by pressing B on a gamepad). Therefore, one could think of game mechanics as governing the potential behavioral demand of the game. Game mechanics govern behavioral demand because they govern the player’s potential agency over what actions happen (what they can do, hit, jump, etc.). More agency over these action verbs is more demanding, both in terms of having to consider the choices of behaviors and to make those behaviors happen (via the controller). That said, one aspect of Sicart’s definition of game mechanics that is particularly important is the notion that game mechanics, as a function of the game system itself, are removed from specific player abilities. That is, if a bot were to play the game, it would be constrained by the same set of parameters in this action space as a human. See, for example, the evidence of a bot learning how to play Super Mario World (Nintendo, 1990) in 34 tries (Souppouris, 2015), or the success of Dota 2 OpenAI bot over reigning human Defense of the Ancients 2 (Dota 2; Valve, 2013) champion Danylo “Densi” Ishutin at The International in 2017. In this way, we can consider game mechanics as one of the fundamental underlying behavioral constraints of games, as noted by Lang (2014). However, Sicart’s (2008) approach also allows us to consider potential actions in games as things that simply exist, much like objects in a realworld environment. Grass, trees, fire, and landscapes exist independent of a human’s ability to perceive them (Gibson, 1979)—that is, the objects (or mechanics in a game world) are there even if they are not actively perceived by a person. That said, when a human does perceive these objects in the natural world, they unsurprisingly afford specific behaviors. For example, 97

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flat ground affords walking to a biped, and a horizon affords a goal. In a dynamic systems model, we examine the player, the constraints, and what the player perceives the constraints affording their play in a reciprocal and dynamic system over time. However, this becomes overwhelming in terms of scale. Therefore, if we think about objects in a virtual world based on the perceptible affordances they offer to a player, rather than try to categorize all the mechanics an object or decision path may allow, we may have a more parsimonious way to conceptualize in-game behaviors and possible actions.

Affordances in Game Environments In computer-mediated communication (CMC), the term “affordances” has been adopted to describe how individuals maneuver through a textbased, digital, social environment (see for review: Davis & Chouinard, 2017; Evans, Pearce, Vitak, & Treem, 2017). However, much of this work has focused on specific criteria defining technological affordances in social media and CMC, where people perceive affordances or features of affordances in a text-based environment. When we consider Gibson’s (1979) discussion of affordances, it is clear that they may map more closely onto a world wherein one may actually perceive, manipulate, and act upon objects versus text—even if those objects are virtual. This is in line with the classic Reeves and Nass (1996) argument that our perceptual systems evolved long before media, therefore, we have no reason to expect media perceptions to operate differently than the “real world” (Reeves & Nass, 1996). Conceptualizing mediated environments as having specific affordances for players is not unique. Gibson’s (1979) original conceptualization of affordances emphasize that affordances in the environment are real, perceivable, and typically perceived directly. However, in the world artificially created by technology (e.g., video games), the environment may not contain all possible information available in the real world. Indeed, Gibson notes that some forms of media, such as pictures and movies, contain only a portion of the invariants of the environment. Similarly, games constrain behavior of players in specific ways, designed to elicit or provoke expected or potential behaviors in players. Hunicke, LeBlanc, and Zubek (2004) describe potential behaviors in a game as action affordances. Action affordances are “various actions behaviors, and control mechanisms afforded to the player within a game context” (Hunicke LeBlanc, & Zubek, 2004, p. 3), and can be best defined as actions that a player can take in game. These types of action affordances may include physical properties imposed on the structure of the virtual environment, such as the portals in the game Portal, or affordances perceived by the player. For example, movement, threat, knowledge, and 98

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interaction would all be specific action affordances players derive from narrative, gameplay, or specific tasks set in the game world. These types of action affordances may be related to each other via causal relationships (if I move this lever, the door will open), spatial information (shooting a portal on this wall allows me to exit on that wall in Portal; Valve, 2007), and costs of alternative outcomes (ex. in Bioshock, if I kill the Little Sisters, I will gain immediate power, but the Little Sisters will not aid me later; 2K Games, 2007). Putting emphasis on the design side, Gaver (1991) defined technology affordances as “properties of the world that make possible some action to an organism equipped to act in certain ways.” (p. 80). However, in Gaver’s (1991) discussion of affordances, he specifically describes an aspect of affordances that has particular relevance for virtual environments and which we have already addressed previously; namely that affordances exist independently of perception and intention. This leads to the creation of four distinct situations combining the presence or absence of an affordance, and the perception of that affordance, as outlined in Table 6.1. First, perceptible affordances offer perceptual information about correct affordances—the door handle affords turning and the handle turns (e.g., interacting with a door in Skyrim opens said door). There can also be correct rejections of action where there is no perceptible affordance or action. Both of these types of perceptions and behavior in the virtual world match well onto real-world capabilities. However, there are also instances where perception and behavior do not match: either the perception leads players to perceive action where there is none, or to miss possible actions where they exist. These can also be false affordances, where there is perceptible information available that does not lead to actions (such as doors in games that do not open, as in The Witcher 3; CD Projekt, 2015), or hidden affordances, which must be inferred from other evidence. To clarify, in these cases, it is not the affordance that is false, but the perception that can be misperceived by players. For example, Gibson describes E. J. Gibson and Walk’s (1960) visual cliff experiment in which infants misperceived the affordance of a glass surface (which actually afforded support) and would avoid crawling on it. This is a hidden affordance, wherein the perception of a dangerous cliff prevented the real Table 6.1  Four distinct situations of affordance Perceptual Information

Affordance

Yes No

Yes Perceptible affordance Hidden affordance

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affordance of crawling. In virtual worlds, Cardona-Rivera and Young (2013) explored the notion of hidden affordances in games in terms of a cliff at the top of a steep hill in the game Elder Scrolls V: Skyrim (2011). Players may see the cliff and perceive that leaping off will lead to in-game death. However, in Skyrim lore, there is a legend of a bard who survived the cliff fall. If you remember this legend and leap off the cliff, your avatar will get bonus points and benefits, but there is no perceptible affordance of “cliff jumping.” Games and virtual worlds may use feedback in order to suggest false affordances to players, or to reveal hidden affordances, although how feedback and user perception interact to reveal potential behavioral opportunities in games has not yet been well explored. Another way to think about affordances in terms of game behavior is by broadening affordances to consider narrative structure in games. Gaver (1991) suggests that affordances may be linked in specific ways, either via being linked in time, such that action A leads to consequence B (e.g., rescuing the robot Ada in Fallout 4 [Bethesda, 2015] leads to gaining the ability to build robots) or linked in space (e.g., in Sexy Brutale, resetting the slot machines throughout a casino to a correct sequence will open a secret passage in a different part of the building; Cavalier Game Studios, 2017). Players need to learn these game affordances in order to move, interact with the objects and characters, and accomplish challenges in the game. Researchers note that enjoyment of playing video games can come from challenges of learning the affordances of the game (Boyan & Sherry, 2011; Sherry, Lucas, Greenberg, & Lachlan, 2006). Mateas (2001) suggests that we can consider either material affordances—opportunities for action presented to the player via direct prompt or via indirect allowance—as contrasted with formal affordances, which provide motivation to perform one particular action out of all actions. In addition to users’ basic actions and tasks performed throughout the gameplay, the narrative, challenges, or reward structure of the game can also guide users to adopt different play styles. Linderoth (2012) suggests that some people will adopt exploratory play styles—this type of play will yield knowledge about affordances in the game. Think of the practice stages of most RPGs or MMOs, where you spend time learning how to move, collect points, and interact with the game world. Linderoth (2012) contrasts this type of play with performatory play, wherein players use their knowledge to realize existing affordances in the game.

Benefits of Adopting an Affordance-Based Perspective on Behavioral Demand Gaming requires a theory of behavioral demand that can encompass past perspectives on game play design and behavior with future iterations of

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play. By describing action affordances as a combination of existing viewer perceptions and goals with the possibilities inherent in virtual environments, we gain a flexible yet bounded perspective on video game play that can adapt to future work on virtual environments. Using affordances to frame our discussion of demand means we can study behavior directly, and not rely on self-report. Although there are improved scales for interactivity and demand (see Weber et al., 2014), by viewing gamer behavior directly, we are able to circumvent issues with self-report data. A player will either perceive an affordance or not, and either act upon it, or not. For example, Lang (2014), and more concretely Lang and Bailey (2015), have suggested we define content in terms of their effect on automatic resource allocation and requirements, which can be based on our evolutionarily based ecological perception of the environment. We can also infer perception using more direct behavioral or physiological measures such as eye-tracking, or by tracking behaviors in games with unobtrusive recordings or the screen capture of player actions (for example, Weber et al., 2009). A focus on affordances allows researchers to look at the media of video games in more manageable chunks in order to examine specific behaviors and feedback loops players rely on in virtual environments. By looking at specific affordances, rather than entire games, researchers will be able to isolate and control for those affordances. Finally, researchers can manipulate goal states of players by emphasizing exploratory (i.e., information-gathering) versus performatory (i.e., utilizing) actions in games (Linderoth, 2012). Exploratory and performatory actions are not mutually exclusive, but rather create a loop; exploring and learning affordances of the game allow players to take performatory actions to achieve certain goals, and the performatory actions also yield information about further affordances to be learned. Researchers can facilitate either exploratory or performatory actions by manipulating in-game challenges, reward systems, or game interfaces in different stages of the game in order to elicit intended psychological/behavioral states at a given moment. This allows the scientific community to apply research to a variety of games and game genres. Although one could spend a career examining the perceptual boundaries of virtual affordances and their effect on player behavior, we would like to take a broader perspective on affordances in concluding this chapter. Up to this point, we have discussed affordances within the game itself, with the game environment as the primary focus. However, when reading Gibson (1979), it is clear that one of the motivations for his work was to force experimental psychology to focus beyond the particular organism to the larger environment within which the organism operated. Simply focusing on the affordances within the game, therefore, would not be true

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to Gibson’s approach. While the game does create a unique environment within which game play occurs, the game and the gameplay occur within a larger social environment that must also be considered for a complete understanding of virtual environments (Sutcliffe et al., 2011). We would move beyond Gaver (1991) and argue that players not only discover affordances within games, but they can create affordances to meet their own expectations and goals. In other words, we would argue— in true dynamic systems fashion—that affordances within a game develop to meet the affordances called forth by human behavior, because human behavior is the environment within which the game operates. That is, games must evolve to meet the affordances demanded by people’s game play. So players, by playing a game and learning its affordances, come to see the possibilities for further actions. If there are game mechanics already available, it means that they just discovered existing affordances. If there is no feature that supports the behaviors they would like to take, then that part of the game may be added or edited so the game affordances are altered or created by developers or modders. We would argue that a history of game play shows that this has exactly what has happened with cooperative game play.

Social Play as Game Affordance In one of the early studies to explore game players’ behaviors, Lawry et al. (1995) conducted a study at the Electronic Games Research Lab in Vancouver, British Columbia in 1993. In this study, researchers observed the interactions of children while playing video games. Additionally, children were interviewed regarding their thoughts and preferences about video games. During one interview, two boys, who had not previously known each other, explained to the researchers that they would prefer to play a video game that allowed them to be on the same team (e.g., to cooperate to win the game). During a separate observation of a moderately large group of 7- to 12-year-old boys, the researchers noted that the boys, who had not previously met each other, had created a system of turn taking. Additionally, older boys who had more experience playing video games were observed offering advice to other boys when they were unsure what to do within the game. Based on these observations and others like them, the researchers concluded that playing video games was clearly a social interaction, which could involve cooperative behaviors and helping behaviors (see also Velez & Ewoldsen, 2013). Moreover, the researchers noted that a long-held belief that playing video games was usually an action done alone was inaccurate, based on their findings. The date of the study is notable because at that time, there were virtually no commercial options for cooperative video game play.

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We see other examples where nominally single-player games are altered via game play to afford cooperative social interaction to the players. For example, Dance Dance Revolution (DDR; Konami, 1998) involves a dance pad with sensors on it, for single players to follow the prompts from the screen and touch the various spots on the pad. The dance pad is an input device designed for a single player. The winner does the best job of matching the indicated spots of the pad to the game signals. Fundamentally, DDR was designed as a game where a single person plays at a time in a competitive manner with other players. However, people have figured out ways to play DDR cooperatively. An obvious example is people dividing into teams that compete for the highest total scorer across individual games. But more creative examples of cooperative game play have evolved. For example, people will play with two-person teams where each person takes half of the dance pad and the team works together to master the dance moves. Or, one player will be making the moves while spectators shout out the upcoming patterns, to beat difficult combination patterns and scenarios. As a final example of cooperative game play emerging in video games, consider cooperative play of shooter games (Ewoldsen et al., 2012). Despite early academic consensus that these games are not played in a social fashion, survey data suggested otherwise, and indicated that people enjoy playing violent games cooperatively (Velez & Ewoldsen, 2013). Likewise, in a series of focus groups in 2005 of violent video game players, Boggs (2007) found that players viewed violent video games as a social activity, that involved extensive helping behavior and cooperation between players both when they were playing and when they were observing others. For example, players would handoff controllers to one another during game play so that everyone can engage in a cooperative activity where people play the part of the game they have specialized at playing. Of course, at this moment in game development and game styles, people do not have to create opportunities for cooperative game play because the majority of games provide opportunities for cooperative game play. Yet, we still see extensive evolutions of games to meet player’s needs, for example, in game “modding” communities where skilled players literally adapt the environment to better meet their emotional and physical needs (Sotama, 2010). What we hope the example of cooperative game play demonstrates is that affordances can be created by players in the game.

Conclusion and Further Questions Conceptualizing behavioral demand in terms of constraint systems and the action affordances allow players in games to have multiple advantages

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in terms of advancing understanding of interactivity, input, and player behavior over past conceptualization. This can be seen when we consider the idea that social gaming affords socialization to players, even in games where this is not the overt intent of the game designer nor the expectation of observers. That said, as interfaces evolve past input devices and become more naturalistic and immersive, we are left with several questions yet to consider. First is how do we define behavioral demands and affordances in games? Are affordances simply digital constraints on behavior or another way of conceptualizing game mechanics? Do goals, motivations, and player expertise interact in specific, predictable ways to offer particular affordances to particular players in particular games? How can we control and predict this dynamic interaction? Are we better off using a mechanics or dynamic framework rather than thinking in terms of perception and corresponding action in virtual worlds? How can we merge our understanding of perceptual affordances with what game designers are actually doing in terms of encouraging or discouraging specific types of behaviors and goals in games? Are there specific frameworks that will allow for merging the text-based technological affordances described in the CMC literature with the more perception-based affordances described in virtual worlds and does this matter? These questions and more need to be at the forefront of continued investigations into behavioral demands of games.

Ludography Bioshock. (2007). Novato, CA: 2K Games. Dance Dance Revolution. (1998). Tokyo, Japan: Konami. Defense of the Ancients (DOTA) 2. (2013). Bellevue, WA: Valve. Duck Hunt. (1984). Kyoto, Japan: Nintendo. Elder Scrolls V: Skyrim. (2011). Rockville, MD: Bethesda. Fallout 4. (2015). Rockville, MD: Bethesda. Halo: Combat Evolved. (2001). Bellevue, WA: Bungie. Portal. (2007). Bellevue, WA: Valve. Sexy Brutale. (2017). Guildford, UK: Cavalier Game Studios. Super Mario World. (1990). Kyoto, Japan: Nintendo. Tactical Ops: Assault on Terror. (2002). Kamehan Studios. The Witcher 3: Wild Hunt. (2015). Warsaw, Poland: CD Projekt.

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7 A P P LY I N G P SYC H O L O G I CA L T H E O RY TO I N - G A M E M O R A L B E H AV I O RS T H RO U G H THE DEVELOPMENT OF A PURPOSE-MADE GAME Sarah E. Hodge, John McAlaney, Christos Gatzidis, Eike Falk Anderson, Davide Melacca, and Jacqui Taylor

Much-publicized concerns have been raised in the past about the moral content of video games, such as the Grand Theft Auto series (GTA; Rockstar, 1997–2015), which includes content and activities such as nudity, prostitution, guns, drug dealing, and driving recklessly. Kocurek (2012) draws a parallel between GTA and Death Race (Exidy, 1976), an earlier game that raised considerable controversy, as they are both based on similar acts of violence and moral violations (such as running over pedestrians and damaging other vehicles). Furthermore, Kocurek (2012) explains that the reason Death Race received this controversy is due to the type of violent content it contained. Violent content that is related to war is more socially and culturally acceptable as it is a part of history, whereas violence toward innocent people, such as running over pedestrians, is outside the social and cultural norms (McKernan, 2013). It is important to note that Bowman (2016a) reports on how even early media and technology, including telephones and comic books, have caused controversy. However, one of the reasons for the specific controversy around video games is that, unlike other forms of media such as films, video games are more interactive and include a behavioral component. Bowman (2016a) highlights that it is the interactivity and the simulations of these behavioral acts that render video games controversial, particularly due to the violent content such as, notably, acts of murder. As video games have advanced as a medium, so have the graphical depictions

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and possibilities within them, creating this way additional concern over the content and the behaviors carried out in these virtual worlds. Games move beyond other media by not simply showcasing moral violations, but also providing players with the opportunities to both encounter morality and respond to it. Jesse Schell, a pivotal game designer, described how video game design needs to evolve to allow for the prospect of the medium to produce the equivalent of Shakespearean work, a notable example of literature (Miller, 2013). GTA has been suggested to be focusing more on moral themes within the gameplay (Oliver et al., 2015). In this spirit, and in reflection of the increased maturity of moral themes in video games (Limperos, Downs, Ivory, & Bowman, 2013; Oliver et al., 2015), for the following part of this chapter, we look to discuss the research, specifically related to the measuring of moral considerations of the players through designing and creating a bespoke video game.

Agency, Interactivity, and Behavior: Past Research Thomas (2006) notes that, compared with other media, there is a different level of involvement, agency, and interactivity in videogames. Agency is the feeling produced from the player’s perception of the level of control or choice they have in a video game (Frasca, 2001). For example, this highlights the difference between watching someone killed on-screen (i.e., a character being killed) and the individual taking action by pressing a button to kill the character. Thus, many video games provide the player the opportunity to make decisions and have in-game behavioral outcomes. These behavioral outcomes are a fundamental part of the video game experience. Agency is therefore not only unique to the medium of video games, but also directly related to the understanding of in-game behaviors. Other researchers have suggested that interactivity, as per above, but also presence too, are fundamental parts of video games and are aspects of what makes video games different from other forms of media (Grodal, 2000; Tamborini & Bowman, 2010). Interactivity has been defined as the degree to which the users (i.e., the players) can change and control the “form” and “content” within the environment (i.e., the game; Steuer, 1992). Other definitions have distinguished between the interaction produced by the player (i.e., interactivity as process) and the system/game (i.e., interactivity as product; Stromer-Galley, 2004). Salen and Zimmerman (2004) highlight the many definitions of interactivity, but similarly suggest it is the relationship between the game and player, as well as the choices the players make within the game. This interactivity in video games contributes to the player’s’ experience of immersion and engagement within the virtual world. Oliver et al. (2015) provide the example of how this can take place through the role of crying in video games, an action that the player could both cause and resolve. There has been much

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debate around the terminology used to describe immersion within video games. Brockmyer et al. (2009) suggest the term engagement encompasses the components of immersion (Frasca, 2001), presence (Tamborini & Bowman, 2010), and flow (Sherry, 2004). While an extended discussion of these constructs is beyond the scope of this chapter, for balance, we will use engagement to broadly describe these phenomena. Bowman (2016b) in particular highlights the role of the behavioral demand; as, in order to progress in video games, the player is required to make choices through pressing buttons, which are not only represented in the game play but also through the game’s set-up (such as navigating the menus). This process of making choices does also overlap with the cognitive demand through the thinking required about the choice(s), and consequently, the button(s) pressed. Bowman, Weber, Tamborini, and Sherry (2013) demonstrated this overlap between cognitive and behavioral demands of the game through the connection between skill and performance in video games. Gameplay effects. Much of the research into post-gameplay effects such as aggression has made the connection between in-game behaviors transferring into real-life behavior (APA, 2015). This has produced a long-standing debate within the literature as to whether this exists or not. It has been suggested that when an individual is in a virtual space, real-life norms may not apply and therefore this could explain virtual behavior, especially for those behaviors that would be considered morally violating in real life. This further connects to the concept of a magic circle (Huizinga, 1949). Applying this concept infers that video games are not constrained by the norms and rules of real life but, instead, are governed by the rules of the game that exist within it (Salen & Zimmerman, 2004). Thus, the implications of these behaviors do not apply to real life and are therefore not of concern. However, Consalvo (2009) argues against the existence of a magic circle, due to the overlap of real life and the gaming world, as players bring in reallife aspects into the game, such as expectations and interpretations from the gaming world. Meta-analytic work by Anderson et al. (2010) suggests problematic associations between violent gaming and aggression, yet, work from Sherry (2001) promotes smaller effects than similar research on television violence. Finally, Ferguson (2007) suggests that publication biases might inflate any effects of violent gaming. This has also led to the investigation of violent video games, aggression, and prosocial behavior, with the results suggesting a mixture of a negative relationship (Prot et al., 2014) and no relationship (Jerabeck & Ferguson, 2013) with prosocial behavior. Regardless, there is a continued debate around behavior in video games and, accordingly, the role of moral behavior. Gaming and morality effects. Research has started to investigate how an individual’s sense of morality in real life might relate to morality whilst playing video games. Much of this research has been done through the use of commercial games, due in part to recent patterns in game development 110

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and design that have favored the inclusion of more morally engaging and less hedonic moral decision making, as discussed previously (Christiansen, 2017: Miller, 2013). However, there are inconsistencies in the findings from the research using commercial games. For example, Weaver and Lewis (2012) examined moral decisions made in a video game using Fallout 3 (Bethesda, 2008) and the Moral Foundations Questionnaire (MFQ; Graham, Haidt, & Nosek, 2008) based on the Moral Foundation Theory (MFT; Haidt & Joseph, 2004, 2007). Weaver and Lewis (2012) observed that moral decisions in a video game were similar to moral decisions made in real life, similar to Consalvo’s (2009) critiques of the magic circle assumptions that players “leave behind” reality when entering a gaming space. In contrast, Hartmann and Vorderer (2010) examined the role of enjoyment and violent video games using the game Half-Life 2 (Valve Software, 2004). The results suggested that players were morally disengaged, that is, players appeared to selectively dissociate from the behavior that violates an individual’s moral codes (Bandura, Barbaranelli, Caprara, & Pastorelli, 1996). The results also suggested that more familiarity with the game resulted in less negative affect and guilt, and greater enjoyment. The authors suggest that it is through the mechanism of moral disengagement that potential immoral behavior could be carried out without detriment to enjoyment. Essentially, it could be suggested that players engage the “magic circle” of the game space, as harboring too many expectations of reality would hinder enjoyment of the action. Grizzard, Tamborini, Sherry, and Weber (2016) used Call of Duty: Modern Warfare 3 (Activision, 2015) and Operation Flashpoint (Bohemia Interactive, 2001) and observed that repeated exposure to the in-game violence reduced feelings of guilt during game play; that is, players felt less guilty when committing violent acts as they gained more experience with the game’s content. The study incorporated the use of two commercial games, which potentially improves the generalizability of its findings to other video games. As shown previously, there are inconsistencies regarding the role of moral behavior in video games, with some studies showing players react with moral sensitivity and others showing players suspend morality during gameplay. Yet, these inconsistencies could be due to methodological issues with using commercial video games as these contain biases such as familiarity with the game and favorite characters. Connected to familiarity is another potential bias, that of re-playability of the game; if, and how much, the game has been replayed and the amount of experience the player already has with the game itself. Some of these limitations were addressed in part by Grizzard, Tamborini, Lewis, Wang, and Prabhu (2014), who examined if being bad in a video game related to feelings of guilt and moral salience whilst playing a modified first-person shooter. Participants were either assigned to a memory recall task (either guilty memory or 111

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ordinary memory) or played a video game (either a guilt inducing level playing as a terrorist soldier, or a non-guilt inducing level playing as a UN soldier). After gameplay, the MFQ (Graham et al., 2008) and a threeitem guilt measure were completed by participants. The results suggested participants playing as terrorists felt significantly more guilt than those who played as UN soldiers. This was significantly associated with two of the five MFT foundations of Care/Harm (propensity for caring and dislike of harm to others) and Fairness/Cheating (desire for fairness and dislike of cheating), although not with the remaining three foundations of Loyalty/Betrayal (group membership and dislike of betrayal), Authority/Subversion (respect for authority and tradition), and Sanctity/Degradation (relating to purity and contamination) (Haidt & Joseph, 2004, 2007). Grizzard et al. (2016) suggest that antisocial behavior in video games could relate to prosocial behavior as the participants who violated the foundations could become more morally sensitive (as represented by higher ratings of guilt). Modifying existing commercial games ensures the game being played is similar to what participants would normally be experiencing and playing. However, there are still restrictions with this approach in terms of content that cannot be modified. Joeckel, Bowman, and Dogruel (2012) developed a game to specifically examine the role of morality using the same MFT foundations, as considered in Grizzard et al. (2014). The game was made using the Aurora engine within the game Neverwinter Nights (BioWare, 2002), a toolset that gave players the opportunity to develop their own adventure game scenarios (Greig, Muzyka, Ohlen, Oster, & Zeschuk, 2002). Such a procedure follows the recommendations of Elson and Quandt (2016), associated with using heavily customized versions of off-the-shelf video games. Six scenarios were created: five related to the moral foundations from Grizzard et al. (2014), and a sixth one, which was a foil scenario, used to reduce demand characteristics of players who might uncover that each scenario was specifically aimed at one particular aspect of morality (the sixth scenario, an amoral event, only involved a book falling accidentally into some mud: http://onmediatheory.blogspot.com/2012/03/morality-invideo-games-gut-or-game.html). Each scenario asked the player to interact with a NPC (non-player character, i.e., a computer-controlled entity similar to the human-player’s avatar in the game) who would share their troubles (similar to many popular role-playing games), and then asked the player to help make a choice to either violate or uphold the foundation connected with the scenario. The authors observed that moral foundations in the game were upheld when the particular moral foundation was salient to the player (salience is the importance of the foundations, the most salient foundation for all players in these results being Harm/Care), whereas non-salient foundations resulted in random, amoral decisions (Joeckel, Bowman, & Dogruel, 2013). The latter finding was compelling 112

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in that there was no evidence that players with low moral salience actively violated morality in-game. This is a finding in line with Lange (2014), who suggests that players have a preference for the “good option” and tend to avoid moral violations for fear of in-game reprisal. Tamborini et al. (2016) in a later study found similar results for the foundations that were upheld and violated. In Joeckel et al. (2013), developing a novel video game did reduce some of the biases, but a number of limitations were still present. For example, the moral decisions presented to players (and even the scenarios themselves) were text-based, which might not have been as engaging as using spoken dialogue. Also, the player was asked if another character should violate a scenario rather than the player violating a scenario themselves, thus the lack of agency could have been an issue. Some of these limitations could be attributed to restrictions within the Aurora engine but, nonetheless, they speak to a gaming experience that might have fallen short in terms of what modern gamers expect. Likewise, the Neverwinter Nights game was already nearly ten years old at the start of their study, which might have appeared somewhat dated to participants. Drawing on both the previous research and concepts discussed led us to the development of the current project, which will be discussed in the next section of this chapter.

Creation of a Theory-Driven Bespoke Morality Game This work described in the remainder of this chapter aims to draw from the disciplines of psychology and game development in order to create a game that measures morality. A purpose-made or bespoke game refers to a game that is designed and created with and/or to a specific specification. Creating and designing games for research allows for some of the biases of commercial games to be addressed, such as familiarity with the game and favorite characters. Therefore, using game engines to create games or similar interactive virtual environments (IVEs) is well-suited to research (cf. Elson & Quandt, 2016), as such systems provide complete control over every aspect of the virtual world and, accordingly, the variables that determine these aspects, which, in turn, allows for further rigor (Lewis & Jacobson, 2002). Thus, the aim of this purpose-made game was to create a stronger sense of moral agency and, at the same time, produce an experience similar to what participants would normally expect to have from traditional gameplay. Notably, the function and focus of a purpose-made game is not primarily for entertainment—similar to the concept of serious games. Serious games are developed for a purpose and function other than entertainment, usually with a strong focus on learning and behavior change (Connolly, Boyle, MacArthur, Hainey, & Boyle, 2012). Although taxonomies of serious games have been proposed (e.g., De Lope & Medina-Medina, 2016), taxonomies tend to focus on the player outcomes (such as the assessment and feedback) rather than the measured outcomes for researchers (De 113

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Lope & Medina-Medina, 2016). Whilst creating purpose-made games can on occasion fit the definition of serious games creation, due to the function being other than entertainment, when the focus of the design is on measuring psychological phenomena, this could be suggested to be taking a different approach to the definition of serious games previously mentioned by Connolly et al. (2012) and the taxonomies of serious games (De Lope & Medina-Medina, 2016). So, rather than developing games to invoke change in participants, the focus in this case is on developing a game to observe and record current behavior. Therefore, purpose-made games could be utilized more within research, specifically for the measurement of psychological phenomena. When creating a purpose-made game, an important consideration is the similarity to commercial video games. If the resultant game is very different from the commercial games participants would normally be playing, then the question of how generalizable the results really are would need to be considered. This can be addressed at the design stage as well as through comparing participants’ experiences with commercial and purpose-made games. At the design stage, research into commercial games supported the development of the game through representing key features of current commercial games, such as choice mechanics. During the testing phase of the game, the participants’ levels of engagement for the purpose-made game and commercial games were measured. Thus, a comparison was drawn between commercial games and the purpose-made game. This can then support the understanding of the aspects and factors that influence game behavior. For example, familiarity with the game has been previously found to influence affective outcomes (Hartmann & Vorderer, 2010). Therefore, a purpose-made game would be able to control for familiarity. This allows for the outcomes of commercial and purpose-made games to be compared. Additionally, this also has implications for the research methodology used in video game research and, specifically, for measuring behavior outcomes. Measuring moral intuitions and decision making. A literature review was conducted in order to identify theories of morality relevant for application within a video game. MFT, mentioned earlier in this chapter, was chosen as it has been used previously in related research (Grizzard et al., 2014; Joeckel et al., 2013; Weaver & Lewis, 2012) and scenarios could be developed from the moral foundations, as was specifically done in Joeckel et al. (2013) and used in later work by Tamborini et al. (2016). These moral foundations include the previously mentioned five—Care/Harm, Fairness/Cheating, Loyalty/Betrayal, Authority/Subversion, and Sanctity/ Degradation (Haidt & Joseph, 2004, 2007), plus the recent additional sixth foundation, that of Liberty/Oppression (relating to dominance and dislike of bullies; Haidt, 2012). These six foundations were useful for video game research, as the foundations are prevalent in many commercial video games (examples of games are provided in the next section), 114

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as well as providing structure of the moral domain and being able to create new scenarios. Furthermore, MFT suggests the process of moral decision making happens through both; moral intuitions that are quick gut responses and by deliberative rational responses (Haidt, 2001). The MFT has been incorporated into the Model of Intuitive Morality and Exemplars (MIME; Tamborini, 2011; Tamborini, 2013), a multi-stage model of how media content is processed and evaluated by the individual. This model is useful to apply to video games, as it highlights the reciprocal relationship between the individual and the environment, with specific focus on the influence of media. The model includes the process of decision making through short-term and long-term components and incorporates MFT and intuitive and rational decision making. In addition to this, Hartmann (2011) suggested two decision-making systems for virtual decisions: one system is experiential (automatic, fast, and intuitive) and the other system is rational (reflective, slower, and cognitive). Hartmann (2011) states that the rational system could be responsible for an individual’s assessment of reality, that is, if the actions could happen in real life, then the realism of the game is assessed by the individual. The experiential system is more primitive, in so far that what is experienced and perceived is believed. Although Hartmann (2011) provides examples of how both intuitive and rational systems could be activated, questions still remain around the decision-making process being intuitive or rational during gameplay. Therefore, this decision-making process is important as it demonstrates the behavioral and, accordingly, cognitive aspects of playing video games. Previous research has suggested that in video games, people make these intuitive decisions for salient foundations, whereas non-salient foundations suggested amoral and random decisions (Joeckel et al., 2013). On this, Bowman (2016b) suggested that more research is needed to understand the role of moral decision making in video games. Due to the previous results from the literature suggesting differences within each of the foundations and the dual theory of decision making, response times of the decisions appear to be an important consideration for the measurement of the intuitiveness of a moral decision (Tamborini et al., 2016). The development of the moral decisions in the game. In order to create moral content and decisions for our bespoke game, we analyzed around 30 previous commercial video games that included morality in the form of a narrative theme and/or the requirement of making moral choices. The following titles were shown to be particularly relevant: Until Dawn (Supermassive Games, 2015), the Fable series (Lionhead Studios, 2004– 2014), the BioShock series (2K-Games, 2007–2013), and Spec Ops: The Line (2K Games, 2012). These titles were selected as each contained moral content and choices that could be matched to each of the MFT foundations (i.e., BioShock’s “Little Sisters” and Care/Harm foundation), plus they also demonstrated morality in video game design (i.e., Spec Ops: The 115

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Line and Until Dawn how choices were designed and made in the game). Specifically, the analysis included what choices are presented to the player in the game plus what the consequences of these choices are (if applicable). Moral psychology theories were then used to evaluate and design game content accordingly, including the aforementioned MFT (Haidt & Joseph, 2004) and moral disengagement (Bandura et al., 1996). In addition to this, we considered that morality in video games is, for the most part, absolute (clear and certain choices), utilitarian (choices that involve thinking about the majority), and focused on the action (the outcome of the choice; Heron & Belford, 2014). Players are often presented with binary decisions in these games, and thus, binary decisions were identified as a typical feature of many video games and incorporated into the design of our purpose-made game. Developing the moral decisions for the game required the above considerations in order to create scenarios for each of the six foundations mentioned previously. Scenarios were developed in the form of vignettes to be foundation-specific; with only one foundation being triggered so that each moral foundation could be examined individually (similar to what was done by Joeckel et al., 2013 and Tamborini et al., 2016). More than one scenario was created for each foundation to pilot extra scenarios in the case of a failed manipulation, such as more than one foundation activating. To create vignettes, we considered prior work from Clifford, Iyengar, Cabeza, and Sinnott-Armstrong (2015), who created vignettes for each of the six MFT foundations. However, their vignettes were not appropriate to use due to having too many extraneous contextual details, such as references to family in scenarios that were not the Loyalty/Betrayal foundation (family being a critical component of Loyalty/Betrayal according to Haidt & Joseph [2004]). Also, the vignettes contained a considerable amount of gender-referential information, whereas we did not want to bias participants in our study. However, for the Care/Harm foundation, Clifford et al. (2015) focused on two types of Care/Harm scenarios, emotional (i.e., “You see a teenage boy chuckling at an amputee he passes by while on the subway”) and physical (i.e., “You see a woman throwing a stapler at her colleague who is snoring during her talk”). Due to the prevalent nature of harm in video games, physical harm was chosen. Dill, Gentile, Richter, and Dill (2005) found that 60% of the top selling games at the time contained violence. These vignettes were then used to generate new scenarios for our bespoke game. Vignettes were selected to keep the text short yet informative. “You see” was added to the beginning of scenarios for the pilot as this would help the participants create an image of a scenario from the written text. Each scenario and decision followed the same format to reduce biases, thus, the only difference was the content of the moral foundation. The scenarios were created with considered caution for the reduction of biases 116

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from situational cues. Also, the scenarios were developed within a word count (18–20) and character count (95–110) boundary. This was the same for the options presented for the choice, which both had a word count (7–10) and character count (39–58) boundary. This was in order to control for potential differences between each of the scenarios. The situations within the scenarios were developed to be unresolved and in need of resolution by the player. The scenarios were developed in this way for three reasons; the first being that if the situation was created to be too much of a violation, then the response could be different compared with a response to a triggering situation. As an example of the difference between violating and triggering for the Loyalty/Betrayal foundation; the trigger would be group membership, whereas a violation would be something that betrayed the group. The difficulty was creating scenarios that triggered the specific moral foundation enough, without being violating. Furthermore, scenarios that are highly violating, such as killing a child, would connect to moral taboos, which, in turn, could create another confound with the decisions made in the game (Young, 2013). Second, it meant that the player was part of the resolution and connects to their agency; this is because an on-screen behavioral outcome was required through making a choice. Third, if a violation has already taken place, then this would have compromised the choice, to violate or not, as this has already happened and, thus, removed player agency. Therefore, scenarios (listed in Table 7.1) were created to be as neutral as possible in order for choice to be required, and each involved at least one NPC. The development and programming of the game. The development of the game was part of a university-funded project as a form of collaboration with the relevant departments in the institution. For this, an undergraduate research assistant was hired to program the game. Unreal Engine version 4 (UE4) was selected as the development platform, that is, the infrastructure hosting the IVE, as it best fit the experience of the development team (Anderson et al., 2013) and the requirements of the project. UE4 is a contemporary and popular tool for game and IVE creation Table 7.1  Moral scenarios for theory-driven bespoke game Moral foundation

Scenario description

Care/Harm Fairness/Cheating Loyalty/Betrayal Authority/Subversion Sanctity/Degradation Liberty/Oppression

An injured NPC Two NPCs sharing coins A group of NPCs with a promise between them An order from an NPC General An NPC trying to fix a leaking sewage pipe An NPC trying to fix a free speech sign

NPC, non-player character.

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and the nature of the system meant that the prototype produced would still be playable and editable in the future (whereas other less supported engines can result in potential incompatibility). Many commercial games have used the Unreal Engine since its inception in the late 1990s, with some examples including the Unreal Tournament series (Epic Games, 1998–2007), Spec Ops: The Line, the BioShock and Mass Effect series (BioWare, 2007–2012), and many others. In 2014, the Guinness World Records, named the Unreal Engine the most successful game engine, which was attributed to the development of 408 games using this tool (Guinness World Records, 2014). The game development team constructed the IVE based on a real-life environment; namely a university type environment. This environment was created to appear similar to the real world and reasonably photorealistic for believability in order to compare video game choices with real-life moral reasoning (see Figure 7.1). The objective of this was to support realism of the game environment for the players and to encourage engagement and social presence within the game (Tamborini & Bowman, 2010). The design and interface of the game is similar to a first-person role-playing game (RPG). This was selected for its similarity to commercial video games that contain moral choices, which were discussed previously, such as the BioShock series. The genre also was suitable for the purpose of creating scenarios within a game environment. This is due to the characteristics of these games having strong narrative structures, again, as seen in commercial games such as Until Dawn. The game mechanics used usability principles such as keeping both the interface and gameplay simple and consistent, with enough information presented to players through the game (Pinelle, Wong, & Stach, 2008; Sicart, 2008). To assess the usability of the game and engagement within it, once it was complete, game testers were recruited (Schell, 2014). This was to ensure the development of an easy-to-use game that does not require previous experience of video games to play. In addition to this, a small tutorial was created in the game as this was deemed sufficient for the participants to be able to play the game. The aim of this is that the game remains an engaging experience and similar to a typical, commercial first-person RPG. During all stages of the game development, the primary researcher was cautious to avoid including content and factors that may induce moral disengagement (Bandura et al., 1996), such as avoiding dehumanizing the human NPCs that were created for the game. Rewards and motivational techniques were used cautiously, in order to avoid bias in the choices such as avoiding additional information that could be seen as rewarding. This further demonstrates the benefit of creating purpose-made games to measure moral behavior, because in commercial games, such as GTA, the player is rewarded, encouraged, and/or given no other option but to do antisocial actions (i.e., stealing). Therefore, assessing these in-game behaviors may not be valid, whereas purpose-made games can have these biases removed. 118

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Figure 7.1  Screenshots of the purpose-made IVE for each of the scenarios from the point of view of the player. Caption:  Top left: Liberty/Oppression; top right: Care/Harm; middle right: Authority/ Subversion; bottom right: Sanctity/Degradation; bottom left: Loyalty/Betrayal; middle left: Fairness/Cheating.

Due to binary choices being a typical feature of video games, this same approach was adapted for the format of a decision. The binary choice the participants were presented with was either to act in an antisocial way (creating a violating situation) or to act in a prosocial way (upholding the MFT foundation and resolving the potentially violating situation). In order for a decision to be made, the player has to interact with the main NPC in the room for the scenario. This would trigger the specific moral foundation related to the scenario. All scenarios involved an object that would either lead to a prosocial or antisocial outcome; this was to avoid hurting NPCs directly and triggering the Harm/Care foundation. For consistency with the other scenarios, even in the Harm/Care scenario, the object (in this case a bookcase) is used to harm (see Figure 7.2). This was important as it meant all the scenarios had an object rather than a character to represent the scenario; thus, ensuring all scenarios followed the same format. The violating antisocial choice was placed on the right 119

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side of the screen (with controls) and the upholding prosocial choice was placed on the left side of the screen (with controls; see Figure 7.2). This was selected as commercial games, such as the Mass Effect series, present choices in the same manner. Although counterbalancing the prosocial and antisocial choices between left and right would have reduced the potential response bias, there were two reasons as to why this design was not incorporated. First, it could have been confusing for participants when they made their decisions. Second, programming this into the game would have been considerably time-consuming, adding an additional level of complexity for the development, on a project that already had severe time restrictions. The game was developed to be able to record the choices of each of the six MFT scenarios, as well as the time taken to make the choice, as response times for the players’ decisions were taken to explore if the decisions and behaviors were more rational or intuitive. Data collection with the purpose-made game. Once the game had been developed and before the game was used with participants in the main study, participants who could not participate in the main study were gathered to pilot test and review the game. This was carried out for two reasons, the first being that most games need testing for bugs and problems (in this case this included making sure the data was recording properly, a key part of the process) and, second, in order to collect data on how the game was experienced (including usability) compared with commercial

Figure 7.2  Screenshots of the decision-making process in the purpose-made game for the Care/Harm scenario. Caption:  Top left: the vignette; top right: the choices presented; bottom left: outcome of the left prosocial choice; bottom right: the outcome of the right antisocial choice.

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games. This also gave the primary researcher experience of the procedure of administering this specific game to participants. The experiment took place in a psychology lab within the university. The participants were observed and recorded playing the game. Before playing the game, participants were given the MFQ (Graham et al., 2008) to measure real-life morality and compare this with the decisions made in the video game. After the game was played, participants completed a questionnaire asking them about their experiences and reasons for the decisions made in the game including the Positive and Negative Affective Schedule (PANAS; Watson & Clark, 1999) and Game Engagement Questionnaire (GEQ; Brockmyer et al., 2009) for the current game (rather than general engagement when playing video games). To measure post-game play prosocial and antisocial behavior, the Tangram help/hurt task was administered (Saleem, Anderson, & Barlett, 2015). Although this is not the focus of this chapter, initial analysis of the results shows that participants demonstrated a preference for choosing the prosocial option, but these decisions were suggested not to be intuitive. Furthermore, the in-game moral decisions were significantly predicted by the level of engagement within the purpose-made game (GEQ; Brockmyer et al., 2009), but not significantly predicted by the MFQ (Graham et al., 2008) and the other post-game measures: PANAS (Watson & Clark, 1999) and the Tangram help/hurt task (Saleem et al., 2015).

Conclusion In summary, this chapter discussed the development of a purpose-made game, with the specific intention of using it in research to measure behavioral outcomes through in-game moral decisions. The process of developing a purpose-made game for research required the consideration of psychological theory. Concepts including agency, interactivity, and engagement in video games with the implications for moral behavior were discussed. Then, an evaluation of how morality is currently applied in commercial video games and how this game content relates to theories of morality was carried out in order to develop a game. The role and definitions of purpose-made games in research were also explored. Although the focus of this chapter was that of moral behavior and the creation of a game to measure it, purpose-made games can be utilized to measure and investigate many types of psychological phenomena and have significant potential to further the area of psychology and video game research. Specifically, for moral choices in video games, other demands of playing video games, such as emotional and social involvement, as suggested by Bowman (2016b), could be explored. Thus, there are many possible avenues for future research relating to moral behavior when playing video games. 121

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Ludography BioShock series. (2007–2013). Novato, CA: 2K Games. Call of Duty series. (2005–present). Woodland Hills, CA: Activision (Infinity Ward). Death Race. (1976). Fremont, CA: Exidy. Fable series. (2004–2014). Guildford, UK: Lionhead Studios. Fallout 3. (2008). Rockville, MD: Bethesda. Grand Theft Auto series. (1997–2015). New York, NY: Rockstar Games. Half-Life 2. (2004). Bellevue, WA: Valve Software. Mass Effect series. (2007–2012). Edmonton, Canada: BioWare. NeverWinter Nights. (2002). Edmonton, Canada: BioWare. Operation Flashpoint. (2001). Prague, Czechia: Bohemia Interactive. Spec Ops: The Line. (2012). Novato, CA: 2K Games. Unreal Tournament series. (1998–2007). Cary, NC: Epic Games. Until Dawn. (2015). Guildford, UK: Supermassive Games.

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Haidt, J. (2012). The righteous mind: Why good people are divided by politics and religion: New York, NY: Pantheon Books. Haidt, J., & Joseph, C. (2004). Intuitive ethics: How innately prepared intuitions generate culturally variable virtues. Daedalus, 133(4), 55–66. doi:10.1162/​ 0011526042365555 Haidt, J., & Joseph, C. (2007). The moral mind: How five sets of innate intuitions guide the development of many culture-specific virtues, and perhaps even modules. The Innate Mind, 3, 367–391. doi:10.1093/acprof:oso/9780195332834.​003.0019 Hartmann, T. (2011). Players’ experiential and rational processing of virtual violence. In K. Poels & S. Malliet (Eds.), Moral issues in digital game play (pp. 135–150). Leuven, Belgium: Acco. Hartmann, T., & Vorderer, P. (2010). It’s okay to shoot a character: Moral disengagement in violent video games. Journal of Communication, 60(1), 94–119. doi:10.1111/j.1460-2466.2009.01459.x Heron, M. J., & Belford, P. H. (2014). Do you feel like a hero yet? Externalised morality in video games. Journal of Games Criticism, 1(2), 1–22. Huizinga, J. (1949). Homo Ludens: A study of the play element in culture: Boston, MA: Beacon Press. Jerabeck, J. M., & Ferguson, C. J. (2013). The influence of solitary and cooperative violent video game play on aggressive and prosocial behavior. Computers in Human Behavior, 29(6), 2573–2578. doi:10.1016/j.chb.2013.06.034 Joeckel, S., Bowman, N. D., & Dogruel, L. (2012). Gut or game? The influence of moral intuitions on decisions in video games. Media Psychology, 15(4), 460– 485. doi:10.1080/15213269.2012.727218 Joeckel, S., Bowman, N. D., & Dogruel, L. (2013). The influence of adolescents’ moral salience on actions and entertainment experience in interactive media. Journal of Children and Media, 7(4), 480–506. doi:10.1080/17482798.2013.781513 Kocurek, C. (2012). The agony and the Exidy: A history of video game violence and the legacy of death race. Game Studies, 12(1). Retrieved from http:// gamestudies.org/1201/articles/carly_kocurek Lange, A. (2014). “You’re just gonna be nice”: How players engage with moral choice systems. Journal of Games Criticism, 1(1), 1–16. Lewis, M., & Jacobson, J. (2002). Game engines in scientific research: Introduction to special issue. Communications of the ACM, 45(1), 27–31. Limperos, A., Downs, E., Ivory, J., & Bowman, N. D. (2013). Leveling up: A review of emerging trends and suggestions for the next generation of communication research investigating video games’ effects. Annals of the International Communication Association, 37(1), 349–377. doi:10.1080/23808985.2 013.11679155 McKernan, B. (2013). The morality of play video game coverage in The New York Times from 1980 to 2010. Games and Culture, 8(5), 307–329. doi:10.1177/1555412013493133 Miller, P. (2013). Jesse Schell’s search for the Shakespeare of video games. Gamasutra. Retrieved from www.gamasutra.com/view/news/189370/Jesse_Schells_​search_ for_the_Shakespeare_of_video_games.php Oliver, M. B., Bowman, N. D., Woolley, J. K., Rogers, R., Sherrick, B. I., & Chung, M. Y. (2015). Video games as meaningful entertainment experiences. Psychology of Popular Media Culture, 5(4), 390–405. doi:10.1037/ppm0000066

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Pinelle, D., Wong, N., & Stach, T. (2008, April). Heuristic evaluation for games: Usability principles for video game design. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 1453–1462). New York, NY: ACM. doi:10.1145/1357054.1357282 Prot, S., Gentile, D. A., Anderson, C. A., Suzuki, K., Swing, E., Lim, K. M., … Lam B. C. P. (2014). Long-term relations among prosocial-media use, empathy, and prosocial behavior. Psychological Science, 25(2), 358–368. doi:10.​ 1177/0956797613503854 Saleem, M., Anderson, C. A., & Barlett, C. P. (2015). Assessing helping and hurting behaviors through the Tangram help/hurt task. Personality and Social Psychology Bulletin, 41(10), 1345–1362. doi:10.1177/0146167215594348 Salen, K., & Zimmerman, E. (2004). Rules of play: Game design fundamentals. Cambridge, MA: MIT Press. Schell, J. (2014). The art of game design: A book of lenses. Boca Raton, FL: CRC Press. Sherry, J. L. (2001). The effects of violent video games on aggression.  Human Communication Research,  27(3), 409–431. doi:10.1111/j.1468-2958.2001. tb00787.x Sherry, J. L. (2004). Flow and media enjoyment. Communication Theory, 14(4), 328–347. doi:10.1111/j.1468-2885.2004.tb00318.x Sicart, M. (2008). Defining game mechanics. Game Studies, 8(2), 1–14. Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 42(4), 73–93. doi:10.1111/j.1460-2466.1992. tb00812.x Stromer-Galley, J. (2004). Interactivity-as-product and interactivity-as-process. The Information Society, 20, 391–394. doi:10.1080/01972240490508081 Tamborini, R. (2011). Moral intuition and media entertainment. Journal of Media Psychology, 23, 39–45. doi:10.1027/1864-1105/a000031 Tamborini, R., & Bowman, N. D. (2010). Presence in video games. In C. Bracken & P. Skalski (Eds.), Immersed in media: Telepresence in everyday life (pp. 87–109). New York, NY: Routledge. Tamborini, R., Bowman, N. D., Prabhu, S., Hahn, L., Klebig, B., Grall, C., & Novotny, E. (2016). The effect of moral intuitions on decisions in video game play: The impact of chronic and temporary intuition accessibility. New Media & Society. doi:10.1177/1461444816664356 Tamborini, R. C. (Ed.). (2013). Media and the moral mind. London: Routledge. Thomas, N. (2006). Video games as moral universes. TOPIA: Canadian Journal of Cultural Studies, 11, 101–115. Watson, D., & Clark, L. A. (1999). The PANAS-X: Manual for the positive and negative affect schedule – Expanded form. Iowa City, IA: University of Iowa. Weaver, A. J., & Lewis, N. (2012). Mirrored morality: An exploration of moral choice in video games. CyberPsychology, Behavior & Social Networking, 15(11), 610–614. doi:10.1089/cyber.2012.0235 Young, G. (2013). Enacting taboos as a means to an end; but what end? On the morality of motivations for child murder and paedophilia within gamespace. Ethics and Information Technology, 15(1), 13–23. doi:10.1007/s10676-0129306

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8 A C O M M U N I CAT I O N M O D E L OF SOCIAL DEMANDS IN VIDEO GAMES Jorge Peña

Social demands stem from playing video games in the presence of others. “Others” is meant in the broad sense as it implies playing or interacting with real people or artificial characters. This chapter articulates a broad framework to understand the many facets of social demands. According to Bowman (2016), “social demand” is related to social interactions and relationships with others. It refers to the degree to which people react to and are aware of other in-game social entities, such as avatars or player digital self-representations and synthetic agents or computer-controlled characters when playing video games. This conceptualization also stresses the “effects” dimension of social demands or the extent to which the presence of other social actors in video games trigger an implicit or explicit response in the player (Bowman, 2016). The goal of this chapter is to introduce a communication framework that encompasses the main lines of inquiry on the social demands of playing video games. This may aid in further expanding the breadth and depth of the concept of social demands. Communication models outline several factors involved in the process of exchanging and receiving information: message, medium, context, sender, receiver, feedback, and noise. I define each of these factors below and present social demand phenomena under each umbrella term, before presenting evidence supporting a definition of social demands as “any component of the communicative process (i.e., message, medium, context, sender, receiver, feedback, and noise) that has an impact on the quantity and quality of the social ties of players and game audiences.” The communication framework on social demands presented here was inspired by attempts to categorize human interaction in virtual worlds

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Table 8.1  Communication framework for social demands in video games Message

Medium

Context

Text, audio, image,  video

Bandwidth Co-presence

Motivations Playing alone or   audience presence   for playing

Content, amount,  rate

Visibility

Virtual location

Personality  traits

Playing with  friends

Social comparisons

Haptics

Audibility

Avatar appearance   and role

Gender Age

Playing with  strangers

Play co-construction Construct  validity

Kinesics

Instantaneity

Interdependence or  independence

Proxemics

Evanescence

Cooperation or competition

Paralanguage

Recordability

Human or  game-controlled  characters

Chronemics

Simultaneity

Anonymity or iden  tifiability

Physical appearance

In-group or out  group member  ship

Facial expression

Time spent playing

Olfactics

Senders

Receivers

Feedback

Motivations for Winning, losing,  stalemate  watching   others play

Playing family  members

Noise Sociotechnical  problems Measurement  error

Construct  reliability

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under the “mapping principle” (Williams, 2010), which examines the parallels between virtual worlds and real life and suggests that behaviors in one context may tell something about behaviors in the other. These parallels are assumed to operate as two-way communication because real world cognitive and behavioral processes may influence social demands in games and virtual settings, and vice versa (Williams, 2010). As discussed below, players apply social norms learned in real life to virtual contexts but events such as the spread of a plague in a massive online game (Lofgren & Fefferman, 2007) and players’ ability to loot, craft, sell, and purchase virtual goods (Castronova, 2008) may inform how humans would react to highly contagious diseases and shed light on basic economic processes. Because of the shared assumption that social demands operate as a two-way communication process between real and virtual contexts, the present framework and Williams’ both discuss the motivations and psychological profile of players, competition and collaboration, and self-representation using avatars. However, the present framework is more explicitly rooted in the different parts of the communicative process (i.e., message, medium, context, sender, receiver, feedback, and noise) identified by Lasswell (1960), Shannon (1948), and (Weiner, 1948). The present social demand communication framework may aid with the comprehension of each social phenomenon and the interplay between different parts of the model. In addition, this framework discusses emergent factors, such as social interactions with synthetic game characters, game video streams, and eSports. The present framework is summarized in Table 8.1 and its components are detailed below.

Message The social dimension of video games is grounded in the exchange of verbal and non-verbal messages between human players and game characters. For instance, players exchange verbal messages, be they text-based or audio. Verbal messages. In order to manage social demands, players exchange verbal and written messages with different content, amounts, and rates. When playing online maze games, the increased number of conversational turns between players correlates with higher interpersonal trust (Depping & Mandryk, 2017). In the context of Jedi Knight II: Jedi Outcast (LucasArts, 2002), players exchange more socioemotional messages (e.g., greetings, laughter) relative to task-oriented messages (e.g., questions and answers; Peña & Hancock, 2006). Players are more likely to comment about game events than to engage in conversations or ask questions (Peña & Hancock, 2006). The majority of Star Wars Galaxies (LucasArts, 2003) players did not gesture or exchange text messages, although players gesturing and messaging do so more frequently when in public contexts such 128

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as starports and cantinas (Ducheneaut & Moore, 2004). These studies imply that while shared play activity (e.g., looting, trading, and fighting) is ubiquitous in online games, engaging in verbal and non-verbal communication is produced by a subset of players and is comparatively less common than simply playing online games while remaining silent (McEwan, Gutwin, Mandryk, & Nacke, 2012). Non-verbal messages. Several forms of non-verbal communication apply to video games that depict virtual worlds in which players use avatars (Manninen & Kujanpää, 2002). For instance, Haptics reflect the use of touch and physical contact between player avatars, such as handshakes, pats, collisions between avatars, or even “teabagging” defeated foes (player avatars squatting repeatedly over their faces, to simulate rubbing their genitals on their foe; a crude mark of demasculinizing humiliation). Kinesics or body movements except touching, such as postures and gestures, may be used to communicate among players. In online games, avatars can perform animated gestures such as greeting, clapping, dancing, and yawning, among other gestures. Spatial behaviors or proxemics include standing close or apart, along with orientation or direction in which a virtual character is turning to. Occulesics refer to eye movement and eye contact, which depict the focus, direction, and duration of gaze. Proxemic and occulesic behaviors in video games and virtual words seem to resemble real-world conventions. People using avatars maintain interpersonal distances that resemble face-to-face communication, such as intimate and closer conversation and far-range or public distances (Krikorian, Lee, Chock, & Harms, 2000). Also, Second Life (Linden Lab, 2003) users’ avatars establish more eye contact in female-female avatar conversations than male-male avatar conversations (Yee, Bailenson, Urbanek, Chang, & Merget, 2007). In a massive online game, men stayed further away from their group relative to women but men who gender-switched (i.e., used female avatars) employed more jumping movements, perhaps in an attempt to exaggerate gender performances or receive more attention (Martey, Stromer-Galley, Banks, Wu, & Consalvo, 2014). Additionally, avatars with large pupils and slower eye blink frequency are perceived as more sociable and attractive (Weibel, Stricker, Wissmath, & Mast, 2010). Traditionally, paralanguage represents the use of voice in communication, but this term also refers to typographical marks with socially shared meanings (e.g., text-based emoticons such as :-), ellipsis, exclamation marks, CAPITALIZATION) in computer-mediated communication contexts (Lea & Spears, 1992). For example, more seasoned online players use more typographical paralanguage and abbreviations in an attempt to communicate more efficiently while playing (Peña & Hancock, 2006). In addition, chronemics involves the use and perception of time (e.g., pauses, fast vs. slow message reply). When playing a social dilemma 129

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game, more extraverted players have shorter pauses in between posts, and shorter pauses are associated with increased trust between players (Kalman, Scissors, Gill, & Gergle, 2013). Physical appearance and facial expression also transmits non-verbal information, and people seem to prefer fit and physically attractive avatars with anthropomorphic instead of animal faces and may also customize highly sexualized avatars (Martey & Consalvo, 2011; Nowak & Rauh, 2005). Avatar facial expression can be fixed or preprogrammed to react to player inputs or game outcomes (e.g., winning, taking damage, resting vs. combat). Recent advancements in augmented reality, such as “animojis” or animated idiograms that respond to users’ facial expressions may imply that future video game avatars may be able to transmit players’ facial expression. Olfactics reflect how scents, smells, odor, and perfumes communicate a message but video games cannot yet convey olfactory information (Manninen & Kujanpää, 2002). Olfactics is an underexplored dimension as there are persistent technical difficulties in emitting scent on demand and chemical difficulties in creating accurate and pleasant smells (Kaye, 2004).

Medium This dimension represents the medium or channel of communication employed to convey information. Medium is also used in reference to interactions taking place in face-to-face or through computer-mediated communication (Walther, 1994). While early online games were restricted to non-verbal and written communication, voice chat is also available for players to speak when coordinating and conversing. Studies looking at medium effects in video games assume that channels transmit different amounts and rates of information and social cues (i.e., bandwidth), and thus text messages are assumed to be “leaner” in comparison to “richer” channels such as voice, audio, and video (Walther, Van Der Heide, Ramirez, Burgoon, & Peña, 2015). A month-long comparison between players adopting voice chat versus players continuing to use text messages, documents increases in trust and positive feelings toward players in the same group for voice chat users (Williams, Caplan, & Xiong, 2007). Increased use of voice chat is also linked to small but reliable increases in trust toward other guild players, which is congruent with the assumption that communication channels that transmit more cues (i.e., aural or visual information) facilitate social presence and trust by enhancing the transmission of information (Ratan, Chung, Shen, Williams, & Poole, 2010). Voice chat may aid with the coordination of social demands but it may also become distracting, just as boosting cues within a medium can also force more attentional demand to those cues.

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In general, the features of a medium of communication are expected to influence how players establish common ground or mutual knowledge (Clark, 1996; Clark & Brennan, 1991). For example, co-presence refers to communicators sharing the same environment. Co-playing video games in physical proximity is different from playing online while players are far apart. Playing in front of others may put pressure on players to entertain others by means of their game actions instead of suspenseless alone play-throughs in which players would instead take their time with the game and read in-game text with lore (Begy, Consalvo, Scully-Blaker, & Ganzon, 2017). In addition, the presence of physical others boosts arousal, which boosts performance for skilled players. This is linked to social facilitation effects in which the presence of others boosts excitement, which, in turn, may increase performance when executing a well-learned task but decrease performance in unrehearsed tasks (Bowman, Weber, Tamborini, & Sherry, 2013). Visibility is also important, as players may be less able to coordinate if they cannot see each other’s avatars, text messages, and so on. Audibility or the ability for players to hear each other also affects social demands as it allows players to coordinate more easily relative to typing text messages (Williams et al., 2007). Instantaneity, or the ability to perceive other player’s actions at no perceptible delay, also affects common ground. For instance, players complain, get distracted, and even frustrated with lags and connection rate drops in online shooter games (Wright, Boria, & Breidenbach, 2002). Evanescence refers to an action fading quickly, while recordability refers to an action leaving a record or artifact. Players may be more capable of coordinating and anticipating events if avatar footsteps do not fade or gestures and text-messages are keep onscreen for longer. In addition, simultaneity refers to the ability to send and receive at once, and it may influence social demands by increasing the amount of information for players to attend to. For example, players may continuously spam text-messages and clutter each other’s screens (Ducheneaut & Moore, 2004) and voice-chat can be distracting if players speak all at once and no one knows who is talking (Halloran, Fitzpatrick, Rogers, & Marshall, 2004).

Context Humans communicate with each other in social situations defined by space and time, along with the real and physical features of such situations (e.g., public/private, interpersonal/organizational, long-term/short term interactions, warm/inhospitable places). Likewise, a number of contextual features exert social demands on video game players. People

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play video games alone or in front of an audience (e.g., friends, partners, YouTube channels, eSports, see “Receiver” section in this chapter). As noted previously, playing in the presence of others boosts arousal, which impacts game performance and enjoyment (Bowman et al., 2013) and increases demands on players to entertain viewers via game actions (Begy et al., 2017). It is likely that the arousing qualities and entertaining performances involved in watching others play video games may attract audiences to new venues and practices, such as eSports and streaming. In addition, the associations raised by virtual spaces may raise the salience and appropriateness of social demands. Participants who create avatars for blogging purposes craft virtual characters more similar to their real physical appearance, whereas those who create avatars for dating emphasized physical attractiveness (Vasalou & Joinson, 2009). This implies that game contexts can influence players’ visual self-presentation when crafting avatars. Additionally, people getting to know human partners in a virtual library perceive self and partners as more formal relative to people meeting each other for the first time in a virtual café (Peña & Blackburn, 2013). Along these lines, players of a massive online game express more social gestures such as smiling, cheering, and clapping in a game cantina but use more thanks, bows, and waving gestures in a starport (Ducheneaut & Moore, 2004). These studies suggest that the associations raised by virtual environments activate contextual norms learned in real life (e.g., looking the part for a date, silence in the library, waving and bowing in ports to greet and say farewell), thus implying that the virtual context primes social demands on players. Another contextual element is the association raised by players’ avatar appearance (e.g., attractive, evil, agile). Players can customize their characters but, in some games, they are assigned to a single character with a defined role (e.g., hero, soldier, wizard, etc.). In support of the prediction that avatar height and attractiveness gives an advantage to players, using tall and attractive characters is linked to higher performance in a massive online game (Yee, Bailenson, & Ducheneaut, 2009). Compared with a control group, players assigned to superhero avatars offer more chocolate to a partner whereas those assigned to a supervillain avatar pour more hot sauce (Yoon & Vargas, 2014). Congruent with the assumption that thin and obese avatars may prime concepts linked to agility and sluggishness, women and men randomly assigned to obese avatars show decreased physical activity relative to those assigned to thin avatars in virtual tennis matches (Peña, Khan, & Alexopoulos, 2016; Peña & Kim, 2014). In sum, avatar appearance may exert learned social demands on players’ behavior. Player interdependence is an important contextual social demand. Online games are structured so that players are forced to interact, and thus they feature teams and factions, roles, classes, and skills, quests, raids, and hang-out and trading spaces such as lobbies, waiting areas, 132

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bars, stores, and cities (Ducheneaut & Moore, 2004). In this sense, social demands are sometimes part of a game’s design and structure. Interdependent tasks include raiding with other players and coordinating with squad mates in order to achieve a collective task. Independent tasks include running and gunning in multiplayer “free for all” Call of Duty franchise games (2005) or soloing in a massive online game. In general, interdependent tasks require more communication and coordination (e.g., questions and answers, opinions, and commands) than independent tasks (Straus, 1999), and thus interdependent game contexts may increase social demands. Contextual demands for interdependence and coordination may stem from game design features because online games may have different classes with particular skills that need to coordinate with each other, for example, medics and marksmen (Ducheneaut & Moore, 2004). However, players ultimately decide whether to play as a team or to play individualistically. In the Battlefield franchise (2002), players can play as snipers and rack up individual points, but their team may still lose the match if snipers played as “lone wolves” and did not coordinate efficiently. In support of this, players who reported increased coordination, specialized knowledge, and trust in other players’ expertise (i.e., transactive memory systems) were more likely to win instead of losing in multiplayer online battle arena games (Kahn & Williams, 2015). Interdependent and independent games can be cooperative or competitive, and the cooperative and competitive nature of the game context may influence social demands. Playing games with others involves categorizing players into in-group and out-group members (e.g., us vs. them) and, in general, players behave more positively toward in-group players (Velez, Greitemeyer, Whitaker, Ewoldsen, & Bushman, 2016). Cooperative video game contexts also activate expectations that individual in-group members will respond to favors (i.e., prosocial reciprocity). In comparison to standalone and competitive aggressive games, playing cooperative aggressive games resulted in lower aggression between game partners and non-game partners (Velez et al., 2016). In order to isolate the effects of interdependence-dependence and cooperation-competition on social demands, Depping and Mandryk (2017) tested for the effects of four separate versions of the same game. Collaborative mechanics facilitate trust between players more efficiently than independent play and, in addition, the cooperative and the interdependent version of the game increases player enjoyment (Depping & Mandryk, 2017). Based on large-scale player surveys, competitive gaming should not be construed as opposite to community. There are numerous player communities devoted to competitive gaming showing that these two factors are not opposed and that positive social demands may emerge in competitive games (Yee, 2017). In addition, players may show high levels of perceived competence (i.e., need for a challenge), relatedness (i.e., need to connect with others), 133

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and autonomy (i.e., sense of control), thus showing that competence and relatedness are not opposite factors (Tamborini, Bowman, Eden, Grizzard, & Organ, 2010). Whether other players or characters are human-controlled or computer-​ controlled is also a contextual factor of importance. This factor is either studied as an objective feature of the situation (e.g., players interact with real humans or synthetic characters) or as an expectation existing in players’ minds. In general, players show increased social demands when playing with human instead of artificial partners. Playing against a human-controlled opponent reported more social presence, flow, and enjoyment relative to those playing against a computer-controlled opponent, although in reality, participants played against the computer (Weibel, Wissmath, Habegger, Steiner, & Groner, 2008). Players also experience more pre-fontal cortex activation when winning against a human rather than a computer, although in reality, participants played against a human player (Kätsyri, Hari, Ravaja, & Nummenmaa, 2013). This shows that information (or misinformation) about whether the social gaming context involves real or artificial partners influence social demands (see also how artificial characters affect morality choices, Chapter 7, this volume). Communicating in anonymous or identifiable game contexts also influences social demands. Anonymity may increase disinhibited and deregulated behavior (e.g., “flaming,” sexism) (Spears, Lea, Postmes, & Wolbert, 2011), and so anonymous players are expected to behave more negatively based on deindividuation mechanisms (i.e., loss of public self-awareness and reduced inhibitions). On the other hand, the social identity model of deindividuation effects (SIDE; Lea & Spears, 1992) predicts that anonymity may also enhance liking and positive in-group biases in contexts where shared identity is contextually noticeable (Spears & Postmes, 2015). For instance, visually anonymous players experience more enjoyment when using avatars, implying a shared group identity by featuring the players’ school colors (Peña et al., 2017). This effect is related to avatars wearing participants’ school colors being able to enhance identification with players’ online group and perceived player-avatar similarity (Peña et al., 2017). In addition, anonymous interactions may facilitate strategic gender-identity performances. For example, women varied avatar choice for it to match online discussion topics, thus selecting male and gender-neutral avatars when discussing masculine-domain topics and more feminine avatars when conversing about female-domain topics (Spears et al., 2011). Although early frameworks conceptualize anonymity as a feature of the communication medium and its ability to transmit information (see “Medium”), more recent work focuses on how anonymity highlights or obscures contextual norms, thus giving rise to cognitive (i.e., anonymity affects the salience of group identity) and strategic effects (i.e., selective self-presentation, low accountability allowing disinhibited behaviors) (Spears & Postmes, 2015). 134

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Finally, context is not only defined by space but also by time. In particular, time spent playing games also exerts social demands, which brings to the fore enduring concerns about how technology use displaces or augments social capital, community involvement, and personal relationships (Shen & Williams, 2011). For instance, increased social online video game play was associated with smaller and lower quality offline social circles (Kowert, Domahidi, Festl, & Quandt, 2014). In addition, more time spent playing an online game was associated with loneliness, lower family communication quality, but an increased sense of online community. Spending more time playing online games with family members was linked to increased family communication time but playing with strangers was linked to lower family communication quality (Shen & Williams, 2011). According to Shen and Williams (2011), the social outcomes of time spent playing online games is modulated by motivations for playing video games (see “Senders”), playing with friends or strangers (see Receiver), and the quantity and quality of online communication among players (see “Message”/“Feedback”).

Senders There is a vast literature documenting individual differences in how players experience social demands and are motivated to form relationships in video games. These studies envision players as motivated to establish, maintain, and terminate social relationships with other players. In doing so, they assume players as communicators in the sense of active agents with clear and defined social goals or motivations to play video games. Although this section focuses on social relationships with other players, there is a growing focus on player-avatar relationships. While some players see their avatar as a simple tool or object, others regard their avatar as a full extension of the player, as a mask or costume symbiotically intertwined with the player, or even as a distinct social entity separate from the player (Banks, 2015). Bartle (1996) classified online gamers into player types, such as socializers (e.g., players motivated by social relationships and teamwork), achievers (e.g., players motivated by game advancement, mechanics, and competition), explorers (e.g., players motivated by charting the game world), and killers (e.g., players motivated by disrupting and trolling others). Although Bartle (1996) did not empirically test his classification scheme as it was not intended to be an exhaustive or theory-based taxonomy, but rather a convenient way of discussing players during the game design process, data-based player typologies in part confirm his propositions but also find that players use online games for escapism purposes or as a getaway from real life, and show that those with higher escapist tendencies spend more time playing online games (Yee, 2006). Players with 135

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increased sociability and achievement motivations also spend more time playing a massive online game (Williams, Yee, & Caplan, 2008). Other studies conceptualize social demands as linked to sender individual differences, such as personality, social skills, and attachment style. In a survey of World of Warcraft players (Blizzard Entertainment, 2004), players with a higher need for socializing also show higher extraversion (i.e., interest in interacting with others), agreeableness (i.e., being friendly and cooperative), neuroticism (e.g., emotional instability and negative emotions), and openness scores (e.g., affinity to learn new things and experiences), whereas more achievement-oriented players were also high on extraversion and neuroticism but also low on agreeableness and conscientiousness (i.e., being organized and methodic) (Graham & Gosling, 2013). Players also use avatar physical appearance and clothing to express their gender, racial, and sexual identity (Martey & Consalvo, 2011). Introverted women and men were more likely to craft attractive avatars in Neverwinter Nights 2 (2006; Dunn & Guadagno, 2012). Additionally, players with low self-esteem select lighter skin tones than those with high self-esteem, and players with higher openness to new experiences scores customize avatars with more skin tone variations (Dunn & Guadagno, 2012). In regard to social skills and attachment style, increased involvement with playing online video games is linked to lower player social expressivity skills and diminished ability to receive and interpret non-verbal communication from others (Kowert & Oldmeadow, 2015). Players with higher concerns of being rejected by others (i.e., attachment avoidance and anxiety) also show increased tendencies to play online video games when feeling negative emotions (Kowert & Oldmeadow, 2015). Finally, demographic factors such as gender and age are also related to social demands. Younger players prefer competitive games and running and gunning in online shooters, whereas women prefer long-range stealth and games with more defined social components (Embaugh, 2017). In general, women dislike video games that lack meaningful social interaction and show less preference for games featuring violent content and sexual gender role stereotyping compared with men (Hartmann & Klimmt, 2006).

Receivers There are many ways that players are recipients of social demands. For example, players receive and mentally process information from game events and narratives, and may apply this information to other contexts (see Chapters 2 and 4, this volume). There is also ongoing research into whether exposure to violent game characters and narratives affect subsequent prosocial and antisocial behavior (Anderson, Gentile, & Dill, 2012). 136

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There is also increased attention on why people watch other people play video games. In this way, active players become more passive receivers of game-related information (e.g., game streamers or broadcasters, Twitch or YouTube play videos, eSports tournaments, reviews, podcasts, etc.). For example, users of live internet broadcast services such as Twitch spend more hours, watch more broadcasts, and follow more broadcasters to escape everyday life, release tension, increase companionship and peer recognition, learn more about game strategies, and for enjoyment purposes (Sjöblom & Hamari, 2016). In addition to game broadcasts, people also watch eSports or multiplayer video game competitions between professional players; eSports borrows from organized competitive sports by featuring star players, teams, and arena tournaments with prizes. Frequency of watching eSports was linked to acquiring game knowledge, escaping everyday life, enjoyment of macho posturing and player hostility, and novelty (Hamari & Sjöblom, 2017). This category also attempts to represent social demands in regard to who players communicate with (e.g., strangers, friends, or family members). For example, in massive online games, players either frequently play with prior teammates or play with strangers most of the time (Huang, Ye, Bennett, & Contractor, 2013). As noted previously, playing online with strangers can take away from family communication time but it may allow people to form a sense of online community (Shen & Williams, 2011). In addition, playing online games using services such as Xbox Live allows people to maintain relationships and feel close with friends and family members, especially when people cannot see each other in person that often (Ledbetter & Kuznekoff, 2012). In sum, there are social demands associated to why players expose themselves to gaming content (casters, eSports). Players also engage in interaction and exchange information with different audiences (e.g., friends, strangers), and audience type is related to different social effects.

Feedback Feedback occurs when parts of a system affect each other such that system outputs are routed back as inputs in a cause-effect loop. Weiner (1948) conceptualizes feedback as representing how people and systems adapt to the information and messages they receive. As such, this dimension represents how player behavior results in specific outcomes (e.g., positive or negative outcomes such as winning or losing) that, in turn, affect social demands. For example, winning against an opponent in competitive games is more rewarding than losing. Winning may activate players’ reward systems whereas losing may be interpreted as an aversive event or even as punishment (Kätsyri et al., 2013). When performing poorly, low-skilled players were more hostile toward a female-voiced competitor 137

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compared with a male-voiced competitor (Kasumovic & Kuznekoff, 2015). Players also made more negative statements when dying more frequently in the game and made fewer negative statements when performing well in the game (Kasumovic & Kuznekoff, 2015). In comparison to participants who played a non-violent game, those who played a violent game imparted longer retaliatory noise blasts, especially after previously losing a previous trial (Anderson & Dill, 2000). This implies that negative feedback (e.g., player or team losses) may trigger antisocial behavior. There is comparatively less information about the feedback effects of games that end in a stalemate, likely because the majority of video games are designed to present with a win or lose end state. In another example of how people adapt to social information in video games, consider how players compare themselves with each other. Players may size up their own skills, performance, character level, and avatar appearance and game assets (e.g., armor, weapons, etc.) in relation to another player skill, level, gear, and assets. In doing so, players engage in upward (i.e., player has lower real or perceived skill in comparison with an opponent), downward (i.e., player has higher skills than an opponent), or lateral social comparisons (i.e., player and opponent have equal skills (Harris, Anseel, & Lievens, 2008; Suls & Wheeler, 2000). Social comparisons allow players to acquire information about hierarchies and skill levels, which can inform calculations of who has the upper hand, how much effort to put in when competing, and anticipate wins and losses. When playing a motion-controlled tennis match against a thin game character, female and male players randomly assigned to use obese avatars show decreased physical activity relative to those assigned to thin avatars (Peña & Kim, 2014; Peña et al., 2016). This implies an upward social comparison effect in which players put in less physical energy when they do not expect to do well against their opponent. In addition, when playing against an obese game character, women assigned to obese avatars also show decreased physical activity (Peña & Kim, 2014). Female players also show increases in physical activity when assigned to thin avatars playing against thin game characters (Peña & Kim, 2014). In sum, female players strive harder when their avatar and game opponent were both thin but show less effort when assigned to obese avatars and opponents. Overall, the body ideals implied by players’ avatars can make social demands more salient. Players use self and opponent avatar bodies to make inferences and adapt their behaviors based on social comparisons between self and game opponents. Live streaming presents an interesting context for the study of feedback. Game casters may play in front of a YouTube or Twitch audience while the audience provides feedback to streamers in the form of advice, comments, emotional reactions, donations, and so on. Future research should focus on the social demands associated with audience and players 138

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co-constructing play-throughs and making choices together. For instance, Twitch streamers feel as if they are not only playing for an audience but also as if playing in tandem with other people as chat comments allow audience members to influence the actions of game streamers in real time (Scully-Blaker, Begy, Consalvo, & Ganzon, 2017).

Noise According to Shannon (1948), noise is a chance variable that perturbs the transmission of a message such that the received information is not the same as what the sender initially transmitted. Congruent with this definition, one source of noise stems from socio-technical problems that players face when managing social demands. As noted previously, co-presence, visibility, audibility, instantaneity, evanescence, recordability, and simultaneity may affect players’ capacity to achieve common ground. In addition, the cognitive and emotional demands described in this volume should also influence players’ ability to perceive and respond to social demands— in a sense, we can assume that the re-allocation of attentional resources required by attending to the game’s challenges, the emotions stemming from game content, and even the physical and behavioral requirements to make in-game choices can all be signals—sources of noise—that pull away from one’s ability to attend to social others (see Bowman, 2016; Chapter 1, this volume). The present framework assumes that social demands are measurable, and thus another source of noise is the mismeasurement or incomplete assessment of social demands. Noise could stem from measuring one part of the model without accounting for another part of the model. For example, a study may focus on social content in player messages while overlooking players’ motivations. However, it is also common for researchers to test parts of a model instead of trying to account for all factors within a single study (Walther et al., 2015). As all factors cannot be examined within a single study, perhaps the best we can do is to select the factors of importance as informed by theory and/or previous research, and also select valid and reliable measurement tools to assess social demands linked to message, medium, context, sender, receiver, and feedback. This conceptualization of noise as mismeasurement resonates with calls for carefully attending to construct validity and reliability issues when mapping the connection between real and virtual social processes (Williams, 2010).

Conclusion The present framework is an attempt to catalog the different ways in which social demands take place in video games, the social behaviors and 139

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outcomes of interest, and the variables that affect social communication in video games. Cataloging these processes and effects begins the construction of an initial framework that can be filled by other scholars (see Williams, 2010). By cataloging the different parts of the communication process (see Table 8.1), social demands are defined as a multidimensional phenomenon that affects social interactions afforded by video game technology. Social demands are defined here as any part of the communicative process (i.e., message, medium, context, sender, receiver, feedback, and noise) that has an impact on the quantity and quality of the social ties of players and game audiences. This expands on current definitions of social demands that focus on how players seek social interactions with “others” (i.e., players or game characters) based on individual needs or personality traits (see “Senders”) and game outcomes such as winning or losing (see “Feedback”; Bowman, 2016). As discussed, several other factors may trigger social demands, including the communicative context, medium features, message, and receiver characteristics, while noise may influence players’ ability to understand each other but also researchers’ ability to draw conclusions about social demands. A common risk of taxonomies is representing dynamic processes as static categories. To be sure—and in the case of the present communication-based taxonomy—online gamers under social demands may take turns in sending and receiving messages, feedback may or may not be available, players may or may not attend to feedback or adjust their behavior to it, and players may use a single medium to communicate or may employ a sequence of media (e.g., text, voice, video). The categories presented here are meant to be expanded and are not mutually exclusive. It may be hypothesized that sender personality traits may affect the content of communication, among other interactions between the different factors in the present framework. In conclusion, this chapter expanded the breadth and depth of social demands in video games and outlined various dynamic factors that can be meaningfully represented using classic communication models. In doing so, we are left with an extended definition of social demands that is rooted in the various part of communicative models attempting to represent how people exchange social information in video games along with the outcomes of such a process.

Ludography Battlefield series. (2002–present). Redwood City, CA: Electronic Arts. Call of Duty series. (2005–present). Woodland Hills: CA: Activision (Infinity Ward). Jedi Knight II: Jedi Outcast. (2002). San Francisco, CA: LucasArts. Neverwinter Nights 2 (2006). New York, NY: Atari. Second Life. (2003–present). San Francisco, CA: Linden Lab.

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Star Wars Galaxies. (2003). San Francisco, CA: LucasArts. World of Warcraft. (2004-present). Irvine, CA: Blizzard Entertainment.

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9 TA N D E M P L AY: T H E O R I Z I N G S O C I A L I T Y I N S I N G L E - P L AY E R G A M E P L AY Mia Consalvo, Jason Begy, Sarah Christina Ganzon, and Rainforest Scully-Blaker

When most of us think about playing games with others, multiplayer games—particularly competitive ones—are what come to mind first. Yet, players have a long history of engaging with single-player games together too, helping one another along and sharing the experience of achievement as they progress through the game. In this chapter, we suggest that the study of sociality or multiplay experiences found in relation to single-player games has been largely ignored by scholars and we present an overview of a series of studies aimed at addressing this gap. This work also extends the theorization of videogames as a demanding co-production accomplished by both game developers and game players (Bowman, 2016). In particular, Bowman argues for considering how games can be “socially demanding” of players, offering rewards as well as costs in terms of sociality, group cohesion, and the like. This chapter makes a similar argument—that even single-player games can be socially demanding in a variety of ways, which can include the need to negotiate elements such as turn-taking and decision making along with broader elements such as managing a pre-existing relationship (as both friends and/or romantic couples) or even engaging as strangers in the shared activity of gameplay.

Sociality and Play We know sociality via single-player gameplay has existed as long as we have been playing games together. For example, in her early study of the rise of videogames in America in the late 1980s and the concomitant

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development of transmedia entertainment, Marsha Kinder references such activities. She writes that with respect to children, early Nintendo games did not isolate players from one another, but rather, players often helped one another in joint play sessions, and: [I]nstead of choosing to play against each other or just to take turns, [children] may agree to let the one who is the most advanced in a particular game do most of the playing so the others can watch and learn new moves, or else they will let the novice do most of the playing while the more advanced player coaches. (Kinder, 1991, p. 115) Likewise, Mitchell found in her study of how the Atari 2600 system had been integrated into family homes, that: [C]hildren of all ages in families played the games together … they gave tips to each other for improving strategies … Older sisters were sometimes seen as “bossy,” especially when they tried to tell their younger brothers how to play. Older brothers, however, were viewed as nurturing and helpful toward younger sisters when they did the same thing. (Mitchell, 1985, p. 129) Most past research that focuses on play in multiplayer contexts has studied the cultures and groups formed around massively multiplayer online games (MMOGs). Scholars have investigated how player cultures differ based on nationality (Eklund, 2012; Nardi, 2010) how players create culture surrounding game spaces (Consalvo, 2007), how different styles of play evolve (Taylor, 2006), how game economies function (Castronova, 2005), and how in-game groups form and dissolve (Chen, 2004). Other researchers looking at online games have studied those who play casual and social games with others (Boudreau & Consalvo, 2014; Vázquez & Consalvo, 2015), women players (Sundén & Sveningsson, 2012), and players of e-sports (Taylor, 2012; Witkowski, Hutchins, & Carter, 2013). Probably the most useful work for this study comes from scholars who attempt to define particular acts of play or ways of playing that are distinct, in ways that impact gameplay as well as the space that surrounds that activity. For example, Taylor’s work on “power gamers” or those who are extremely instrumental in their gameplay in MMOGs explicates the unique qualities they bring to gameplay, such as: [A] focus on efficiency and instrumental orientation (particularly rational or goal-oriented), dynamic goal setting, a commitment to

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understanding the underlying game systems/structures, and technical and skill proficiency. (p. 72) The concept of the power gamer gives us a theoretical lens that focuses on activities rather than reifying demographic markers, yet mostly centers on the act of playing itself. Taylor’s work on power gamers is extended by Christopher Paul’s (2011) work on theorycrafters in World of Warcraft (Blizzard, 2004; Paul, 2011). Paul explains about theorycrafting as follows: [It] is a way of playing WoW that depends on work and analysis outside the game and a set of user mods and discussion within the game. The point where being a “good” WoW player intersects with theorycrafting is worth investigation, as it changes the terrain upon which players engage games. (para. 3). Theorycrafters push the boundaries of the game and its systems, figuring out how to gain optimal results from various actions. In response, they create guides and rules for how to successfully play WoW, such that high-level play now depends on following those dictates. Theorycrafters not only determined the optimal way for their own play, they ended up influencing how play for those at high levels of the game should (or must) proceed. Concepts such as power gamers and theorycrafters move us beyond identity-bound ways to understand play in multiplayer games, and in particular how high-level play is enacted and regulated by a broader player community. What these studies fail to tell us is how people play single-player games together and what type of a social experience this is or can be. We need more theorization of other types of sociality in play, but also in relation to single-player games. As a way to untangle this and investigate further, we began a series of studies centered on the question: “In what ways do individuals play single-player videogames with or alongside other people?”

Initial Investigation: Exploring Tandem Play In answering the question above, our chapter presents an overview and interpretation of data from two different study conditions—an initial research project (Consalvo, Begy, Ganzon, & Scully-Blaker, 2016) and a follow up study (Consalvo et al., 2018). Both conditions involved having individuals play a game together as pairs and having individuals stream a single-player game via the live streaming service, Twitch.tv. Both conditions were chosen to see how individual players would choose to interact (or not) with other players or spectators, live or via streaming service. 148

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To see how such interactions possibly changed over time, we chose the Bioware role-playing game Dragon Age: Inquisition (Bioware Edmonton, 2014) for individuals and pairs to play—a game selected due to its rather long main story (about 45 hours of game time) and varying difficulty and play styles, which we thought would appeal to a variety of audiences and engaged them over multiple gaming sessions. We recruited 15 individuals to participate, with ten being put into pairs and asked to play the game in a “couch co-op” style1—playing together in collocated space. The remaining five participants live streamed their play via Twitch.tv on a lab PC that allowed them to chat live within a public Twitch channel, and for the participants to stream their gameplay along with an audio/video feed of themselves (using those modes as they individually preferred) as they played. During each session, two researchers were present, observing and taking field notes. The researchers also participated in streaming chat with the streaming participants, a decision made after initial sessions resulted in few outside observers watching the broadcasts and no chat being observed. The researchers also engaged with the couch co-op participants when asked a direct question or if there were technical issues but played more of a passive role with them overall. All participants engaged in three play sessions of approximately 90 minutes each in duration, and all completed an in-depth exit interview with one of the team’s researchers that lasted from 30 to 60 minutes in length. Of the 15 participants, seven identified as female and eight identified as male, and ages ranged from 20 to 42 years old.

Themes of Tandem Play One of the central goals of this study was to determine how individuals play single-player games together and how sociality was an element in that activity. We do not claim our results are representative, but rather, they are exploratory and raise questions for more systematic work to follow (some of which, we address in this chapter). We have refined the definition of our concept of tandem play based on our observations, interviews, and interpretations of what our participants both did and said. Based on that data, we define tandem play as when two or more players engage with a single-player game together, moving through the game with a variety of potential motives. Below, we discuss the observations that formed the genesis of this definition. Histories of tandem play. Most of our participants confirmed that playing games with others, even single-player games, was something they had experienced from childhood through the present day. For example, Winston2 explained that some of the first games he ever played were collaborative activities, including “Myst [Brøderbund, 1993] because it was so hard—we would just all bash our brains together and try to get through it.” Nathan also mentioned Myst and how his family would play 149

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it together, with one person controlling the game and others “back seat driving” their participation. In terms of more recent experiences, Nadine told us of how she had asked a friend to play certain segments of Silent Hill (Konami, 1999): “she helped me on all the hard parts.” Nadine went on to say that even if she was not sharing the controller with her friends, she greatly enjoyed having people around while playing, such that “if I don’t socialize, I feel really alone so, playing a game alone, even an RPG, its enjoyable but it feels lonely in the end.” Owen told us he played such sessions a lot in his free time with friends and “we’ll pass it [the controller] back and forth and figure it out. I really enjoy this style of gaming.” Overall, participants had varied experiences playing games with other people, with tandem play being one subset of that activity, and one that people tended to enjoy for a variety of reasons. Holding the controller means having the power. How participants shared controllers (or not) was a key element in understanding how tandem play took shape and how individual pairs (in couch co-op) negotiated their play sessions. We had asked participants to play the game “together” as mentioned earlier, but made no mention of if, how (often), or when controllers should be shared. Without prompting, and during all 15 gameplay sessions, each pair passed the controller back and forth to varying degrees, but we never witnessed any explicit discussion of how often or when to do so—there seemed to be an implicit arrangement at work, even among strangers. When asked about their sharing strategies, participants gave us similar answers. They often looked for breaks in the action (such as a new scene or area) as a way to pass along control, and no one mentioned looking at the clock and keeping rigid track of how frequently or infrequently sharing happened. We observed that sharing sometimes took place for functional reasons— during one session each member of the pair had their cell phone ring, and so each passed off the controller to the other person without comment while they took the call. During another session, one member of the pair arrived late after working that day and had not finished her dinner—the other participant took up the controller without question to start playing the game. None of our participants said they had any disagreements about controller sharing, although sometimes they felt they had held the controller too much, such as Kevin, who commented that during his last session with Winston, “I spent way more of the time with the controller in my hand.” When asked why he thought that was, he pointed out that Winston had played the game before (it was new to Kevin) and possibly “he was trying to share the game with me.” One participant, Nathan, noted that he had received the controller a lot from his partner Alice, “sometimes when I didn’t really want it.” Nathan made a critical point about controller sharing in that:

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whoever has the controller has an advantage … when they reach a point they don’t really want to deal with, they hand over the controller. When you don’t have the controller, you just wait. Most of our participants were strangers to each other and so politeness likely played a role in how they went about sharing, trying to divide up their time “equally” or in some other way to ensure a pleasurable experience. Winston felt their sharing evolved over the sessions, so that during the opening with the tutorial scenes: we’ll switch between each other every time there’s a bit of an engagement or something and whenever one of us feels like, ok I’ll give it back to you or I know there’s a boss fight coming … I’ll give it back to him. As Denise summed up, “I think whoever was in control of the controller was the person deciding for the most part.” Players repeatedly mentioned how the person holding the controller can drive forward the action in a way that the other person cannot. We did witness players occasionally exerting “veto power” over another player’s choices, but we witnessed no real disagreements when one player had strong feelings of one sort or another. The physical controller functioned as (obviously enough, perhaps) symbolic of control over the game’s larger direction. Because participants were often not friends prior to our sessions, they were likely on their best behavior when interacting with their partner. Thus, they were highly aware of cues the other person might have been giving off—acting bored, expressing frustration, and so on, as signals for a switch to occur. Yet players seemed—unless they had a very strong opinion about something—to defer to the wishes of the person holding the controller, at least until they could take their own “turn.” Tour guides and “no spoilers!” Although many of the pairs in the couch co-op sessions were strangers to one another, they usually quickly exchanged information about their past experiences as players, and their history with the Dragon Age series of games in particular (perhaps due to its narrative focus). Several pairs (by our design) included a person new to Dragon Age: Inquisition partnered with someone who had previously played the game. This led to a particular style of tandem play that differed from sessions where both players were novices. In such cases, one player usually took on the role of “tour guide” for their partner—without prompting—as a way to show the other player what was in the games. Such behavior replicates Woods, who found that experienced players often shift their styles when introducing newer players to the game (Woods, 2012). For the experienced players, this resulted in a balancing act, as

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they usually did not want to “spoil” the game’s narrative for the novice partner, but they wanted to introduce them to fun elements of the game, as well as have an enjoyable experience on their own, and not simply repeat the beginning elements of the game over again. At the same time, novice players were aware of their relative inexperience, and wanted to learn more about the game, but also not “bore” their partner by repeating content they feared was unexciting to them. For example, Kevin (a novice player) mentioned that he “deferred to [Winston, an experienced player] entirely” and further that his partner Winston was “the boss when it came to picking quests.” Winston also admitted that he took charge in order to “help [Kevin] discover the game”—such findings replicate the instrumental narratives offered in Jenkins and Fuller’s account of early Nintendo games and “new world travel” writing (Fuller & Jenkins, 1995). Tour guides were conscious that they were trying to show off the game, as Denise explains, “the only time that I ever told him to go towards something was when I thought it would be something that [AJ, the novice player] would find interesting.” Guides often put their own enjoyment after their partner, mentioning that some of the sessions “felt a bit tedious to go through everything again.” Streamers engaged in tandem play could also be tour guides, depending on their level of experience or interest in the game. Adam, an experienced gamer, saw his role as trying to “see something funky and alternative that I can do in this game that will keep them entertained,” and similar to Denise, even showed elements of the game that he did not find particularly enjoyable on his own. Ash enjoyed talking about her gameplay while streaming, often responding to our questions and comments in chat with verbal responses about battle strategy. Streamers could also position their audience members as potential tour guides, particularly if the streamer had no prior experience with the game, either because they needed some orientation (novice player Rick needed directions) or because they did not want to have any spoilers from the audience (Olivia, who was playing Dragon Age 2 on her own, was very adamant that she did not want help from other viewers—constantly reminding us “no spoilers!”). For both streamers and couch co-op pairs, having a tour guide present resulted in play with a different purpose than other players. While it was still enjoyable (mostly), it was also an opportunity to show off a game they enjoyed and try to elicit excitement and further interest in novice players. Tour guides thus took pleasure in playing the expert—displaying their gaming capital (Consalvo, 2007). And in response, novice players had easy access to expert help, an excuse to ignore more tedious parts of play, and a “quick start” tour of the game that often covered far more ground than we witnessed from pairs or streamers who were novices. People play games differently when they play with other people. Overall, we saw a shift in the goals for play with both streamers and couch co-op 152

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pairs from what players (say that they) do when playing alone. With the introduction of other people, players’ goals shifted to performance and playfulness rather than progress or advancement through the game Players (particularly those in couch co-op sessions) related to us that they were not particularly invested in making progress through the game, but rather decided to focus on making their own fun rather than following quest directives. Other participants also played around with the game, as we noticed in the pair of Alice and Nathan, who were intentionally going everywhere except where they have to, according to our field notes. In that case and others, tandem players seemed more interested in being playful than in trying to make meaningful progress. This was especially prominent in a narrative-driven game such as Dragon Age: Inquisition, which when individuals would play alone, would see them usually reading much more of the lore and history found in the game world, as well as exploring more of the dialogue options. As Alice stated, in a previous session, she had wanted to read much more of the text “but the text got really long and I felt bad for Nathan, so I just skipped it all.” Such deferrals demonstrate how players renegotiated their goals, balancing their own interests with the perceived interests of other players or viewers. It is key to note that most pairs and streamers did not ask their partners (or audiences) what they would find interesting—they simply assumed that they would not share the same interests. As stated by Nathan: “in the same way that a pickup game of basketball would be fun if you’re into basketball, which I’m not. … you play for the activity without the bigger picture in mind.” Streamers approached the changed situation slightly differently as they had a (potentially) larger digital and pseudo-anonymous audience to consider, with its own unknown expectations. Rick explained that for him, the difference between playing alone and streaming was that “when you are playing by yourself, you’re just doing it for your own fun or something like that and [when] you’re streaming, you’re also playing to have fun but you’re trying to entertain some people.” Adam acknowledged the same impulse to entertain, but added that the process also enhanced his own enjoyment: in the sense that I could sort of comment on some of the more absurd quirks of the world and sort of have some fun with them instead of just being on my own and having to go forward without really expressing my interest in those things. Streamers also needed to negotiate how much to interact with their audience and how much input to accept about their gameplay decisions. Even though their audience was not physically present, they felt their influence in various ways. Streamers ranged from more nervous beginners to relatively experienced practitioners. More experience generally led to more 153

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enjoyment of the practice, with one participant conceptualizing the experience as “playing with others” where “we can all have fun together.” She also remarked that the experience made her feel “more outgoing all of a sudden,” while a beginner streamer felt that “it took a while for me to adjust and think about it in a camaraderie way, like these are just people who are hanging out, they’re not here to judge what you’re doing.” Daniel, the avatar. Finally, a major shift for most players happened via their relationship with the avatar they were using for play. This became obvious from the very start of their sessions as we observed the avatar creation process. Many players told us after playing that they normally invest a great deal of time in creating their avatars, but when playing (a) with other people and (b) for a limited time, both streamers and couch co-op players felt less investment in those creations that research has found in other gaming scenarios. As Winston explained: I generally role play to a certain extent and that means I get very invested in my characters and the thing is when you kind of collaboratively create a character unless the two parties kind of put immense amount of effort to make the character belong to them both, I would say the character becomes a neutral zone. Another player pointed out that in his experience, “in a multiplayer situation … plot and story just tend not to work as much. I find when you’re in multiplayer, you just want to get to gameplay.” So playing with others is a different type of experience, one where story—and presumably character—can be more difficult to engage with. When pairs did actively collaborate on creating their avatar they often went for amusing or silly avatars. One pair named their avatar “Daniel”—a ridiculous sounding name for a character in a high fantasy world, and another pair accidentally created the avatar “Edric” when they hit the “accept” button too quickly in the character creation screen. Players were hardly invested in these characters, and often referred to them distinctly in the third person (the “avatar as other” orientation of Banks, 2015). As Nathan remarked about Edric in our interview: he thinks he’s some sort of parkour master but he actually really sucks at it so he tries to jump on things and then falls down and occasionally dies as a result. And he has this thing on his hand that he really ought to get checked out by a doctor.3

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another easily engaged in turn-taking behaviors to share the game’s controller and decision making, that more experienced players often acted as “tour guides” for players newer to the game, and that the game selected for that initial study had particular impacts on our findings. To address those impacts and further build theory, this section builds on those findings by briefly discussing a second study condition that further refines the concept of tandem play. In doing so, it also investigates the linkages between tandem play and social TV viewing and challenges the player/ spectator dichotomy that much game research perpetuates. The setting for phase two was the same, however, we had subjects play Telltale Games’ Game of Thrones: A Telltale Games Series (Telltale Games, 2014)—an episode-based single-player game with multiple decision points, which was short enough to complete over six gameplay sessions. For this case study, we only recruited two subject pairs, one that played for six hours and finished the first three episodes, and a second pair that played for 12 hours, finishing all six episodes. Game of Thrones (GoT) is very linear—although there are a few short quick-time events, and a few brief periods where players can move a character about the environment, the majority of the gameplay is choosing what to say in a conversation and most of these conversations are timer-based.

(More) Emerging Themes of Tandem Play Even with the smaller pool of participants, the changed study conditions immediately presented us with additional social elements to explore and to more systematically investigate in future studies. For example, the differences between play partners who were strangers, friends, and romantic couples became salient in multiple ways. Also, the second condition, which featured a game with more immediate moral dilemmas, coupled with known pairs, led to dramatic changes in how players approached moral and ethical dilemmas in game. Finally, the game space itself as a space for play was sometimes overridden by the demands of the social space created by the pair, who would at times use the play experience as a springboard for being social, rather than focusing exclusively on playing or even winning. Who we play with matters. A key difference in our second study was that both of the pairs we recruited knew each other prior to the study. One pair was a married couple and the other pair were good friends, which was in contrast to the first study where only one pair of the five knew each other beforehand (that pair was also a romantic couple). Both Game of Thrones pairs were therefore far more comfortable interacting with one another, evident in their relaxed conversational styles, references to shared past histories, and their body language. Each pair had a different strategy for managing the controller during their sessions, which was 155

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either negotiated when play started or was an artifact of the pair’s prior play history together. As our prior study found, holding the controller meant having the power to do multiple things—engaging in Quick Time Events (QTEs) for battles and some actions, driving characters around scenes, and (the major part) directing the choices that the various characters would make in each episode. Here we saw pairs much more actively conferring with one another as well as pause the game at times to make sure they had the input of their partner before continuing. Because GoT is so narrative driven, and the pairs had the option to finish the entire season, they took their playthroughs more seriously than Dragon Age: Inquisition I pairs, at least in terms of determining a “style” or theme for their playthrough of the episodes. For example, both pairs engaged in oftentimes extensive as well as multiple discussions about how to play the overall game as well as specific situations and characters. Our findings echo and extend work from Downs, Vetere, and Howard (2013), who studied groups engaged in physical console gaming in home settings. They found that in addition to serving as players and spectators, “various types of playful behavior emerge” during gameplay (p. 697). They point out that such behaviors are “both enabled and mediated by factors such as the game’s design, the gaming technology, pre-existing social relationships, and the superlusory goals of the session” (p. 697). They concluded that the “active player” or the person holding the controller “was no longer the sole controller of the gameplay any more than they controlled the physical game space” (p. 698). Giving you license to be bad? Tandem playing as mean and sassy. Despite prior research showing that a majority of players tend to choose the side of “good” or to play as “better versions of themselves” during games that feature moral choices, the two playthroughs we witnessed were decidedly “meaner” than what that evidence would suggest. One pair had decided early on to create a “sassy” playthrough, while the second pair were also fairly tough on the characters, although we only saw them play three episodes. Both pairs agreed in the first episode of Game of Thrones that when young Ethan Forrester is confronted with a choice of how to punish a thief (send him to The Wall; chop off three of his fingers; or let him go), their choice was to take three fingers, with Michael stating “I was ready to chop off his head” and Miranda and Rose showing no hesitation in choosing the same option. Both pairs also commented often on how unsympathetic they were being in how they made decisions. These preliminary findings do suggest interesting options to explore in future research—if single players do enjoy acting as “the hero” in games with moral dilemmas, what happens when more than one person is present? It is possible at that point that the pair (or group) defers to one 156

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person’s style or perhaps they ramp up the action and go for the shocking, the mean, and the outrageous options instead. In those cases, it might be the case that “being evil” is something that a group can more easily engage in, as players might give each other “permission to be bad” as they are all choosing the actions, and so no one player alone is implicated as being the “bad person.” Thus, similar to the sociality that has been found to occur around multiplayer games, single-player games can also be sources for entertainment for multiple people, as prior researchers have also found (Giddings & Kennedy, 2008). Social viewing and playing. In their study of “social television,” Oehlberg et al. had small groups watch TV to study how they interacted (Oehlberg, Ducheneaut, Thornton, Moore, & Nickell, 2006). The researchers found that viewers helped one another, such as when, during lulls in programming, newcomers are caught up on “what happened and is currently going on in a program” (p. 5). Much like such forms of social television viewing, tandem play was a rich and rewarding experience for the players we studied, with individuals extracting meaning and entertainment from a variety of game options—including the experiences offered within the game space of a game like Dragon Age: Inquisition, or around the game, as with jokes about the options and choices offered by Game of Thrones. Although interactions could be prompted by both such situations with either game, in contrast to the centrality of avatar-based freedom and actions in Dragon Age: Inquisition, in Game of Thrones, players rarely had this level of control over the characters. Perhaps as a result, the social aspect shifted: subjects put more effort into discussing (and mocking) the game. For example, Michael would often mimic certain characters’ speech, putting on exaggerated accents to draw laughs from Emiko and the researchers. Rose once compared Lady Forrester to Lieutenant Uhura from Star Trek, and both Miranda and Rose during their fourth session began rating and judging characters based on whether or not they had a “bowl-style” of haircut: determining that “everyone” with a bowl-cut will inevitably betray them as protagonists. This also builds on past research on group console gaming, where Voida and Greenberg found that “the primary motivation for group console gaming was not the games, themselves, but the social interactions afforded by the collocated gameplay” (Voida & Greenberg, 2009, p. 1564). As part of that activity, “sharing in the gaming experience may mean sharing in other activities related to the games and not necessarily the games, themselves.”

Conclusions While other researchers have investigated social console gameplay mainly in relation to multiplayer games, and in particular physical controller-​ based games, this research program demonstrates that single-player 157

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games can also serve as rich material for friends and couples to socialize around. Much like Voida and Greenburg, we found that pairs seemed to privilege sociality over gameplay itself, even though the game was the primary motivation to get together. This research is also in line with findings about social television viewing, where participants seem to create unspoken rules for how and when to communicate with each other, and how to use the viewing material as “content” for further social interactions— either as jokes, as a way to offer expertise or knowledge, or as a way to comment on one’s relationship(s) to others in the group. This research also further builds the theory of tandem play, demonstrating how even very linear single-player games that feature little action or exploration can be entertaining material for multiple players to engage with. It also raises the question of how the tandem or group-playing situation might change how individuals approach ethical decisions during gameplay, as they are playing with another person, and not simply “as themselves” or only as they might wish to play the game. Further research is needed to determine how ethical content and tandem play intersects. Finally, this study shows that pairs who have a prior history together approach tandem play as a “natural” style of interaction and play, and indeed engaged in this activity regularly outside of our study conditions. This research provides further evidence that being social in and around games can be accomplished no matter whether the chosen game is a single or a multiplayer title.

Ludography Dragon Age: Inquisition. (2014). Edmonton, Canada: Bioware Edmonton. Game of Thrones: A Telltale Games Series. (2014). San Rafael, CA: Telltale Games. Myst. (1993). Novato, CA: Brøderbund. Silent Hill. (1999). Tokyo, Japan: Konami. World of Warcraft (2004–present). Irvine, CA: Blizzard Entertainment.

Notes 1 “Couch co-op” is a relatively common term in game culture, used to define gameplay that involves cooperative games (where players must work together in the game to achieve a particular goal) and that requires more than one player, who are gathered together on a couch—therefore most likely using a game console—in order to play. 2 All names used are pseudonyms. 3 We should point out that such clear demarcations between avatar and participant were not always the case. But they suggest that when players share an avatar, that avatar is less likely to function as a placeholder or embodiment for the player him/herself within the game world and story than if it were theirs alone.

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References Banks, J. (2015). Object, me, symbiote, other: A social typology of player-avatar relationships. First Monday, 20(2). Retrieved from www.ojphi.org/ojs/index. php/fm/article/view/5433/4208 Boudreau, K., & Consalvo, M. (2014). Families and social network games. Information, Communication & Society, 17(9), 1118–1130. doi:10.1080/13691 18X.2014.882964 Bowman, N. D. (2016). “For this much work, I need a Guild card!”: Gaming as coproduction. In R. Lind (Ed.), Produsing 2.0: The intersection of audiences and production in a digital world (pp. 107–123). New York, NY: Peter Lang. Castronova, E. (2005). Synthetic worlds: The business and culture of online games. Chicago, IL: University of Chicago Press. Chen, M. (2004). Addressing social dilemmas through role-playing identities in computer games. Proceedings of DiGRA 2005, Vancouver, Canada. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.109.7095&rep=​ rep1&type=pdf Consalvo, M. (2007). Cheating: Gaining advantage in videogames. Cambridge, MA: MIT Press. Consalvo, M., Begy, J., Browne, P., Ganzon, S., Scully-Blaker, R., & Waldie, R. (2018). Finding sociality in single player games: A case study of tandem play amongst friends and couples. Proceedings of the Hawaii international conference on system sciences, Kona, HI. Consalvo, M., Begy, J., Ganzon, S., & Scully-Blaker, R. (2016). Tandem play: Theorizing sociality in single player gameplay. Presented at the International Communication Association annual conference, Fukuoka, Japan. Downs, J., Vetere, F., & Howard, S. (2013). Paraplay: Exploring playfulness around physical console gaming. In: P. Kotzé, G. Marsden, G. Lindgaard, J. Wesson, & M. Winckler (Eds.), Human-Computer Interaction – INTERACT 2013. Lecture notes in computer science (vol. 8119, pp. 682–699). Berlin, Heidelberg: Springer. Retrieved from http://link.springer.com/chapter/10.1007/​ 978-3-642-40477-1_47 Eklund, L. (2012). The sociality of gaming: A mixed methods approach to understanding digital gaming as a social leisure activity (doctoral thesis). Stockholm: Stockholm University. Retrieved from www.diva-portal.org/smash/record. jsf?pid=​diva2:574218 Fuller, M., & Jenkins, H. (1995). Nintendo and new world travel writing: A dialogue. In S. Jones (Ed.), Cybersociety: Computer-Mediated communication and community (pp. 57–72). Thousand Oaks, CA: Sage. Giddings, S., & Kennedy, H. (2008). Little Jesuses and *@#?-off robots: On cybernetics, aesthetics, and not being very good at Lego Star Wars. In M. Swalwell & J. Wilson (Eds.), The pleasures of computer gaming: Essays on cultural history, theory and aesthetics (pp. 13–32). Jefferson, NC: MacFarland. Kinder, M. (1991). Playing with power in movies, television, and video games: From Muppet Babies to Teenage Mutant Ninja Turtles. Berkeley, CA: University of California Press. Mitchell, E. (1985). The dynamics of family interaction around home video games. Marriage & Family Review, 8(1–2), 121–135. doi:10.1300/J002v08n01_10

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Nardi, B. A. (2010). My life as a night elf priest: An anthropological account of world of warcraft. Ann Arbor, MI: University of Michigan Press, University of Michigan Library. Oehlberg, L., Ducheneaut, N., Thornton, J. D., Moore, R. J., & Nickell, E. (2006). Social TV: Designing for distributed, sociable television viewing. In Proc. EuroITV (Vol. 2006, pp. 25–26). Retrieved from www.ducheneaut.info/ wp-content/uploads/2012/08/SocialTVConf.pdf Paul, C. A. (2011). Optimizing play: How theorycraft changes gameplay and design. Game Studies, 11(2). Retrieved from http://gamestudies.org/1102/articles/paul Sundén, J., & Sveningsson, M. (2012). Gender and sexuality in online game cultures: Passionate play. New York, NY: Routledge. Taylor, T. L. (2006). Does WoW change everything?: How a PvP server, multinational player base, and surveillance mod scene caused me pause. Games and Culture, 1(4), 318–337. doi:10.1177/1555412006292615 Taylor, T. L. (2012). Raising the stakes: E-sports and the professionalization of computer gaming. Cambridge, MA: MIT Press. Vázquez, I. S., & Consalvo, M. (2015). Cheating in social network games. New Media & Society, 17(6), 829–844. Voida, A., & Greenberg, S. (2009). Wii all play: The console game as a computational meeting place. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 1559–1568). New York, NY: ACM. Retrieved from http://dl.acm.org/citation.cfm?id=1518940 Witkowski, E., Hutchins, B., & Carter, M. (2013). E-sports on the rise?: Critical considerations on the growth and erosion of organized digital gaming competitions (pp. 1–2). New York, NY: ACM Press. doi:10.1145/2513002.2513008 Woods, S. (2012). Eurogames: The design, culture and play of modern European board games. Jefferson, NC: McFarland & Co.

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10 SOCIAL DEMAND IN VIDEO GAMES AND THE SY N C H RO N I Z AT I O N T H E O RY O F F L OW Kevin Kryston, Eric Novotny, Ralf Schmälzle, and Ron Tamborini

During video gameplay, our minds are a frenzy of activity. To succeed in these virtual environments, we must engage in a vast array of activities, such as visual-motor coordination, spatial reasoning, rapid decision making, and planning. Games simultaneously impose cognitive, emotional, behavioral, and social demands on players (Bowman, 2016); demands that require coordination and attention. Such demands can be overly challenging and frustrating, overly simple and boring, or as in the story of Goldilocks and the three bears, just right. In this just right phase of video gameplay, the challenge perfectly matches the player’s ability. This balance of challenge and skill is held to facilitate flow, a state of mind in which attention is tightly focused on the task at hand, and which is experienced as pleasant (Csikszentmihalyi, 1990). These pleasant flow experiences are central to the reinforcing nature of gameplay, such that many people devote substantial time to it and sometimes sacrifice primary reinforcers such as food or sleep to continue playing. According to the synchronization theory of flow (STF: Weber, Tamborini, Westcott-Baker, & Kantor, 2009), which focuses on the phenomenon flow during video gaming, flow experiences result from enhanced connectivity between large-scale networks involved in attention and reward. Support for this comes from neuroimaging studies that capture brain activity during video gameplay while manipulating the match between cognitive demands and the player’s ability (Huskey, 2016). When playing at the “maximum level” of a player’s individual skill (i.e., if the

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game was any harder, they would consistently lose), regions associated with attention, specifically controlled focus, synchronized with regions involved in reward processing. Following gameplay, players stated they had the most fun during the phases of enhanced connectivity between attention and reward networks, as predicted by STF. Like most research on video games and flow, evidence for the STF comes mainly from studies that define challenge in terms of visuo-motor task demand, but neither research nor theory has closely considered how flow is affected by social-task demands. Modern video games increasingly include and capitalize on social interaction among players (e.g., multiplayer online games, team-based shooters), which in some cases is a central part of the game itself. In such games, visuo-motor and social-task demands co-occur, and likely affect flow in a distinct way from games that feature visuo-motor tasks alone. For this reason, it is crucial to identify potential similarities between visuo-motor and social-task demands, and to demonstrate how these similarities extend our understanding of demand’s role in determining synchrony and resulting enjoyment. Furthermore, to the extent that social-task demands differ from visuo-motor task demands, it is important to ascertain how these differences alter our understanding of the underlying mechanisms that determine how synchrony and flow emerge from these different demands. The current chapter outlines the synchronization theory of flow (Weber et al., 2009), its previous applications to the visuo-motor task demands of video games, and how it can be applied to examine the influence of social-task demands associated with video games in future research.

Synchronization Theory of Flow The STF has its origins in Csikszentmihalyi’s (1990) flow theory. In brief, flow refers to experiences characterized by a tightly focused attention to a task that balances the challenge of the task and one’s germane skill, and an accompanying loss of one’s sense of time. Originally, flow theory was developed to explain why artists and musicians often love their craft even in the absence of any extrinsic rewards. Researchers found that people most enjoyed performing when they were mentally absorbed in their chosen craft and were neither bored by (under-stimulated) nor anxious about (over-stimulated) the task. Csikszentmihalyi concluded that this so-called flow state is intrinsically rewarding in that it is enjoyable, exciting, and encourages well-being. The STF expanded upon flow theory by applying a neurophysiological perspective to explain the phenomenon of flow. Specifically, Weber at al. (2009) conceptualized flow as an inherently pleasurable experience in which brain networks involved in attention and reward-related functions

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become synchronized during task performance. Synchronization is understood in terms of enhanced functional connectivity, an evaluation of the dependency of brain activity between different regions. The theory postulates that flow experiences result from the joint engagement of attentional and reward-related processes, which can be examined via functional neuroimaging. Attention. As William James (1890) stated: Everyone knows what attention is. It is the taking possession by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought. Focalization, concentration, of consciousness are of its essence. (Cited by Evans, 1970, p. 74) In this vein, everyone knows what attention is, and it is hard to imagine how we would navigate our daily life without this fundamental mental capacity to attend. Even so, getting a strong theoretical grip on the ubiquitous function of attention remains difficult, yet several taxonomies have attempted to add clarity to the concept (e.g., Chun, Golomb, & TurkBrowne, 2011; Posner, Inhoff, Friedrich, & Cohen, 1987). Perhaps the most prominent model divides attention into three functional categories: alerting (the ability to sustain focus and vigilance); orienting (the selective filtering of information); and executive attention (controlled and conscious processing, planning, and error detection; Posner & DiGirolamo, 1998; Posner et al., 1987). The neural systems that underlie these functions are distributed throughout the brain, and attention is best conceived as a networked process (cf. Rosenberg, Finn, Scheinost, Constable, & Chun, 2017). Key nodes of networks involved in executive attention—the most relevant type for focused gameplay—lie in prefrontal and parietal cortices, and activity in these regions increases when confronted with diverse cognitive demands (Cole & Schneider, 2007; Duncan, 2010; Seeley et al., 2007). Critically for our arguments, the importance of attention to achieving a flow state has been demonstrated in a media context. Video games place high demands on attentional networks (Green & Bavelier, 2013), and diligent focus on these demands is critical while playing. For example, research has found that when video game players are distracted from the game’s motor tasks, connectivity decreases in executive attention networks (Weber, Alicea, Huskey, & Mathiak, 2014). The authors interpret this as evidence that extreme disruptions to players’ attention interrupted synchronization of activity in these networks. Reward. Attention alone, however, is insufficient to achieve flow. Many cognitive battery tasks probe attentional functions, but none is particularly attractive or flow-inducing. Neither is proofreading a paper, washing

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windows, or playing the notoriously terrible E.T. game (1982; see Smith, 2015). It seems that flow requires reward-related processes to become simultaneously engaged with focused attention. Reward, like attention, is quite intuitive to grasp, but the psychological taxonomy and underlying neural basis of reward are more difficult to identify. In short, reward is something that both (a) produces positive emotions (pleasure) and (b) motivates behavior by reinforcing actions (Haber & Knutson, 2010). Due to its fundamental role for motivated behavior, research on reward is dispersed across various topical domains, including addiction, sex, and food consumption (Kringelbach & Berridge, 2010), as well as playing video games (Huskey, 2016; Klasen, Weber, Kircher, Mathiak, & Mathiak, 2012). While we often speak of “a reward” or “a rewarding stimulus,” it is important to note that rewards are not inherent to things that exist in the environment: rather, rewarding functions are realized inside the brain. As such, although the contexts in which reward is studied differ on an experiment-to-experiment basis, the general principles of reinforcement are likely universal and rely on similar neural regions involved in reward processing. Scholars have determined a few somewhat separable subcomponents of reward (Kringelbach & Berridge, 2012), but reward is better thought of as a distributed and networked process that includes key reward nodes such as the nucleus accumbens in the ventral striatum and other regions (cf. Berridge & Kringelbach, 2015; Schultz, 2015). The synchronization of attention and reward networks. According to the STF, flow states occur when attentional and reward networks become functionally connected or synchronized. When these networks are in disharmony, the mental effort needed to fully focus on an activity is immense. However, when a task is appropriately demanding to the performer, the attention and reward networks become more tightly coupled compared with a situation where task demands and skill level are incompatible. This balance of challenge and skill requires prolonged motivated effort to attend that taxes cognitive and affective processes. If the task were too difficult, players would have been overwhelmed to the point of tuning out—and even if they kept trying, the resulting experience could not be pleasurable. On the other hand, if the task were too easy, then it would not require enough attention to get excited. For example, consider a game that involves simple finger tapping, a relatively automatized motor routine that barely requires executive attention. To adults, this would likely be boring, as even though the task would require motor skill, it would not require executive attention. Conversely, to young children for whom even simple motor tasks require executive attention, the task may provide the match between skill and difficulty that is conducive to flow. Weber and colleagues (2009) further argue that emerging system behavior during flow may be energetically efficient. They use the analogy of the Bak Sandpile Model (see Bak, Tang, & Wiesenfeld, 1987) to describe how 164

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this system behavior emerges. Imagine an hourglass. Once overturned, grains of sand continuously fall, and usually their effect on the resulting pile is minimal. Yet at some point, a small number of grains result in a cascading effect that sparks large-scale avalanching changes to the structure of the pile. The cascading effect might apply to the STF—relatively small changes to the synchronization of attention and reward neurons might lead to large-scale changes to the organization of the cognitive system and experiential correlates, in this case experienced as “flow.” Weber et al. (2009) further posit that during states of enhanced connectivity (i.e., synchronization), task execution seems fluent and effortless, even if the task is challenging. As such, moments during which attention and reward networks synchronize may represent the discrete conscious experience of intrinsically motivated and inherently rewarding flow states.

The STF and Video Games Video games are highly conducive to flow states for multiple reasons (see Chen, 2007). First, successful performance in a video game puts high demands on attention. Second, most games have alterable difficulty settings that allow a player to match his or her skill with the difficulty of the game. If a seasoned player is inured with a game they find too easy, s/he can turn the computer’s skill level from “novice” to “master.” When the criteria of intense focus and a balance of challenge and skill are met, synchronization of attention and reward networks is likely. Sherry (2004) noted these characteristics when he theorized that flow states during media exposure are enjoyable. He argued that similarly to other leisure activities originally studied by Csikszentmihalyi (1990; Csikszentmihalyi & Lefevre, 1989), video games offer a unique form of heightened sensory immersion that increases the likelihood of experiencing flow. Although Weber et al. (2009) highlight conceptual and operational problems in research examining self-reported flow during media engagement (see also Finneran & Zhang, 2002), studies indicate that engaging video games that balance challenge and skill produce flow-like experiences (Keller & Bless, 2008; Weibel & Wissmath, 2011). The STF suggests that these experiences occur because video games create optimal conditions for the synchronization of attention and reward networks. Much of the empirical evidence supporting the STF and its central hypotheses related to attention and reward system activity stems from functional magnetic resonance imaging (fMRI) research measuring brain activity during video gameplay that predominantly tested players’ visuo-motor skills. For example, a study that had players push a button as quickly as they could after seeing randomly inserted laser light flashes intended to distract them found that up to a point, functional connectivity rose within executive attention networks despite increasing levels of distraction (Weber 165

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et al., 2014). However, when distraction rose to a certain threshold, connectivity between regions of this attentional network was reduced (i.e., desynchronized). The authors concluded that below the threshold point, connectivity within attentional networks were robust and unperturbed by distractors. This is an indication of full attention on the source. Desynchronization occurred at the threshold, perhaps a marker of optimal attention. At this point, the light hindered a player’s ability to focus on the game. Other studies have tested the STF’s hypotheses related to attention and reward network activity. A multi-experiment study collected behavioral, self-report, and fMRI data related to attention and reward during easy, hard, or user-tailored difficulty of gameplay (Huskey, 2016). In all cases, the player had to respond to random secondary tasks like those mentioned previously while playing. Slow reaction times to the task indicated full attention to the game. All data followed similar patterns; reaction times were slowest, self-reported flow was highest, and attention and reward networks were active and synchronized in moments of high attention when the game’s challenge was tailored to a player’s individual skill. Specifically, the cognitive control network, a network involved in executive attentional functions (Cole & Schneider, 2007; Seeley et al., 2007), was simultaneously engaged (i.e., synchronized) with reward-related regions. Similarly, increased attention and reward activation have been observed during moments of gameplay that reflect conceptual correlates of flow states (Klasen et al., 2012). During in-game conditions likely to hold a player’s focus, visuo-motor attentional networks were most active, and regions associated with distractions were suppressed; the game was all that mattered. Concurrently, regions of the reward network activated when the game’s challenge and player skill were likely balanced. These findings support the STF. To date, all studies examining the STF have focused on visuo-motor tasks in video games as benchmarks for measuring the challenge and skill implicated in flow experiences. However, visuo-motor tasks are not the only type of cognitive demand placed upon players in games. We suggest that social aspects found in many games may produce a unique form of demand upon players that induce flow states. If flow states derived from motor- and social-task demands are identical, STF can be extended to include social tasks as facilitators of flow. Conversely, if motor- and social-task demands differ both in terms of the flow experience and the mechanisms associated with it, scholars could examine these differences and their unique outcomes.

The Unique Demands of Social Tasks Humans are a social species and thus motivation and cognition linked to social interaction pervade almost all aspects of human life. In fact, playing 166

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social games is key to normal human development (Pellegrini, 2011; Power, 2000) and is omnipresent in all cultures. Accordingly, it is no surprise that social aspects are an integral part of many video games, where they demand considerable attention and may serve as a powerful source of reward. Social affordances in games come with markedly different neurocognitive demands than visuo-motor tasks. To succeed in visuo-motor tasks found in games, people need to excel at translating complex visual information into accurate motor behaviors. However, to master a game’s social tasks, people need to coordinate with others and engage in successful social interactions. These social demands include perceiving, interpreting, and responding to the various social signals that are central elements of modern-day multiplayer video games. In addition to verbal communication, other cues for social perception include facial expressions, vocalics, and body movements, among others (Adolphs, 2009). To understand and act on this rich information, a particularly relevant skill is mentalizing, sometimes also referred to as theory-of-mind processing (Schaafsma, Pfaff, Spunt, & Adolphs, 2015). In brief, mentalizing involves simulations of other peoples’ mental life to infer their thoughts, emotions, and intentions (Dunbar, 1998; Frith & Frith, 2006). Numerous studies document the human tendency to perceive social agency and attribute mental life to inanimate objects, ranging from the simple moving shapes studied by Heider and Simmel (1944) to the “characters” in modern animated films and video game avatars (Alcalá-López et al., 2017; Banks, 2015). Furthermore, literature has documented how people come to understand others’ actions from observation, suggesting a link or loop between a sender’s motor action and an observer’s perception (Hasson & Frith, 2016). In sum, the social elements in video games recruit social-cognitive processes beyond those involved in visuo-motor tasks in single-player games (see Figure 10.1). The field of social neuroscience has identified brain regions involved in these social-cognitive processes (Lieberman, 2007; Schilbach et al., 2013). Recently, researchers have made substantial progress toward identifying neurobiological mechanisms of face and voice perception (Belin, Zatorre, Lafaille, Ahad, & Pike, 2000; Kanwisher, McDermott, & Chun, 1997), two powerful cues for attracting and holding social attention (Kingstone, 2009; Klein, Shepherd, & Platt, 2009). Although the social brain remains far from understood, a large body of work has focused on the brain basis of mentalizing, which commands activity in the bilateral temporo-parietal junction, the precuneus, and medial prefrontal cortex (Lieberman, 2007; Schmälzle et al., 2017; Schurz, Radua Aichhorn, Richlan, & Perner, 2014). This mentalizing network overlaps with the so-called default mode network, which subserves crucial functions relevant for social cognition more broadly (Mar, 2011; Spreng & Andrews-Hanna, 2015). The regions of this network are distinct from those involved solely in motor 167

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Figure 10.1  Your brain on video games—the neural networks involved in gaming. Caption:  Video games pose complex and dynamic demands on the human brain. (A) is an illustration of the single- and multiplayer gaming situation, and B) represents the task demands of video games that prompt coordinated responses across distributed brain systems. The left figure illustrates the networked nature of brain activity and the accompanying maps depict several large-scale brain networks that are likely to be engaged during game play. The synchronization theory of flow holds that flow occurs when networks related to attention and reward become synchronized. Social aspects of video games create distinct demands that can be met by recruiting brain systems dedicated to social processing, thereby offering added potential for flow-like experiences. The schematic brain network was created using BV BrainTutor (www.brainvoyager.com) and BrainNetViewer (Xia, Wang, & He, 2013), and the brain network maps are based on data from Yeo et al. (2011) and Choi, Yeo, and Buckner (2012), accessed via NeuroSynth (Yarkoni, Poldrack, Nichols, Van Essen, & Wager, 2011).

performance. In the context of video games, tasks that require interaction with social agents who exhibit appropriate social cues should engage this network, even if the agent is a nonhuman avatar. The STF and social tasks. Despite STF research’s focus on the attentional demands of motor behaviors, flow can be created via activities that require more than motor skills. Flow experiences generated during group activities require social skills that place high demands on attention and offer high reward. For example, team cooperation and communication have been found to influence flow experiences and performance during team-based competition (Aubé, Brunelle, & Rousseau, 2014). Specifically, teams that interacted more and experienced more flow performed better 168

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than others, suggesting that in interactive goal-oriented activities, failure to pay attention to social aspects leads to suboptimal performance. Thus, although motor skills and focus alone may be sufficient to produce flow during individual tasks, members of groups need to pay social attention to succeed. Social task demands in multiplayer video games. The influence of social interaction on flow has been studied in many contexts, including musical performance and team sports (Csikszentmihalyi, 1975; Jackson & Marsh, 1996; O’Neill, 1999). Although some neuroscientists speculate that social interaction during video game play might facilitate flow (Harris, Vine, & Wilson, 2017), this proposition remains unexamined. The mechanisms through which flow arises during video games likely depend on game design, as different types of games require a different set of skills. Although the STF research focuses on the way motor skills in single-player games stimulate attentional activity necessary for flow, the theory can be extended to consider the influence of social skills in multiplayer games. Weber et al. (2009) define skill as “how accurately an individual’s mental models represent embedded game rules and the mechanic of how toggles or keypads manipulate virtual environments” (p. 401). For example, a mental model for playing darts might feature the motor skills necessary to hit a bullseye as learned from prior behavior, whereas a mental model for speed dating might feature social skills learned through past successful or failed attempts to pitch woo. Similarly, Tetris (Various, 1984) requires hand-eye coordination and quick reaction, but for teambased games like League of Legends (Riot Games, 2009), social skills such as those related to mentalizing become more important. In video games, mental models help players navigate the emotional and communicative elements of the game environment. For example, in single-player games with dynamic narratives, players’ prior experiences— both in the real world and with similar games—will guide how they progress through the game and interact with game characters (Tamborini & Skalski, 2006). By similar logic, we speculate that in multiplayer games featuring other human players, past communication experiences guide how players interact with other human players to accomplish shared goals. Indeed, many games limit single-player achievements, requiring interaction and coordination among multiple players to overcome game challenges. Appropriate mental models of task-related social interactions are needed to succeed. Importantly, these mental models are not static; they are activated dynamically and continuously adapt as the game unfolds. A player must constantly assess where teammates are, the knowledge they possess, and their specific skill sets. Using this information, players must then determine the appropriate next steps to coordinate and accomplish the team’s common goal. Ineffective inter-player communication would make successful gameplay impossible, and quickly terminate attentional 169

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activity necessary for flow. Thus, we suggest that the attention mandated by social interaction might result in a rewarding experience, producing flow via the mechanisms detailed by the STF. The unique attentional demands of multiplayer games. When completing single-player games that emphasize motor skills and muscle memory, cognitive skills such as hand-eye coordination and targeting ability are sufficient to succeed (Bowman, Weber, Tamborini, & Sherry, 2013; Huskey, 2016). Conversely, in multiplayer games, social tasks engage regions associated with the awareness of cues to participate in joint interaction that are central to shared attention, such as a gesture to an object (Tylén, Allen, Hunter, Roepstorff, & Vogeley, 2012). Attention to these cues enables the accurate perspective-taking that is needed to understand others, thereby promoting successful interaction and regulation of the social structures that emerge during the game. These demands are like those found in other group activities such as sports or music, often used to exemplify flow, and the social skills needed to win in multiplayer games may be as important to eliciting flow as the capacity to control a ball or an instrument (Aubé et al., 2014; Walker, 2008). Multiplayer games require various social skills from players that revolve around the ability to infer and understand other human player’s actions. Specifically, players’ ability to dynamically react to in-game challenges and each other’s responses to these challenges are crucial to successful cooperation (Williams & Kirschner, 2012). Such social skills require significant attentional focus in multiplayer games (Kim, Oh, & Lee, 2005). This research examining whether the challenges associated with social interaction in multiplayer games leads to flow indicated that interactions with other human players predicted more attention to gameplay than interacting with the game’s interface or coping with system performance. If the forms of social task-related attention found in multiplayer games are distinct from single-player games, then multiplayer games might induce unique forms of synchronization unexamined by STF to date. Available evidence suggests that attention to social tasks produces success in multiplayer games that players find rewarding. Kim et al. (2005) demonstrated that attention resulting from social interaction predicted success and flow, and Kahn and Williams (2016) illustrated that coordination between teammates who understood each other’s intentions (i.e., mentalized more accurately) won more. This association of attention to social aspects and rewarding results coincides with the key elements of the STF. Although these studies illustrate that attention to social tasks leads to the extrinsic reward of winning, the STF would predict that flow would result from the intrinsic reward expressed by an optimal match between social demands posed by these games and a player’s social capabilities

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and communication skills. This experience is comparable to a party where people are immersed in smooth, interesting conversations, and take pleasure from these social interactions. The rewards of social tasks and their implications for multiplayer games. Due to their fundamental relevance for humans as social beings, social activities are intimately interwoven with reward networks in the brain (Feldman, 2017; Harlow, Dodsworth, & Harlow, 1965). For example, being smiled at is intrinsically rewarding and affiliation is a basic human need (Lieberman, 2013; Panksepp, 1998). Although we expect that the social tasks found in multiplayer games produce more paths to reward than visuo-motor tasks found in single-player games, we expect no difference in how reward-related networks become engaged. Certain “hedonic hotspots” (cf. Kringelbach & Berridge, 2012) become engaged during social interactions associated with both appetitive and consummatory behaviors. Based on observations that the behaviors of perceived agents sparked appetitive reward network activity, scholars have concluded that social cues are interpretable as invitations to rewarding social interactions (Kampe, Frith, Raymond, & Frith, 2001). Related research demonstrates that positive social feedback, such as seeing a smiling face, is neurologically comparable with most well-known consummatory rewards, such as acquiring money (Izuma et al., 2008; Spreckelmeyer et al., 2009). This research illustrates that social tasks can prompt brain activity in reward-related regions. Although it remains unclear whether social tasks differ from visuo-motor tasks with respect to the strength or motivation to pursue these rewards, some evidence suggests that this may be the case. First, social information possesses an especially powerful ability to grab and hold attention (e.g., Kingstone, 2009); second, social tasks might be rewarding in multiple ways; and third, the easily terminated nature of social-task rewards might command more diligent player attention to social behaviors than in single-player tasks. For instance, when media are consumed alone, the consumption experience is altered by breaks in attention. However, the medium itself—the book, movie, or song—is not altered by these breaks. In a single-player game, external distractions might break attention and momentarily affect the gameplay experience, but these distractions do not alter the player’s ability to master the game and experience competence-related rewards. It might bother someone if their neighbor’s dog is barking while that person is playing Super Mario Bros. (Nintendo, 1985), but the Mushroom Kingdom will not change, the princess will still be in another castle, and the player can still defeat Bowser at the end (regardless of whether you are distracted). As such, when consumers allow their attention to wander in single-player games, the risk of forfeiting reward is relatively low.

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By contrast, in multiplayer games, the consumption experience and the activity itself are altered by breaks to attention, thus increasing motivation to diligently focus. Because the social rewards stemming from coordinated behavior may be particularly strong, any distraction that might prevent obtaining those rewards may be very costly. Failure to attend in a multiplayer game will not only reduce competence-related rewards (as coordination is necessary to win), but also irreversibly diminish rewards derived from social interaction. Unlike competence-related rewards stemming from visuo-motor tasks, rewards from social interaction must be achieved in real-time, not the game’s time. If one player stops playing, the game does not pause for the rest of the team, and the entire team misses out on reward. The person who stopped playing is eliminated from all potential rewards simply by not playing. As the loss of this player makes gameplay more difficult for the remaining players, they suffer loss of competence-related rewards and risk a blow to social status. Even if the player returns, s/ he may be blamed, shamed, and ostracized, greatly damaging the potential rewards of social interaction. Such social sanctions—or even the threat of social sanctions—might explain why multiplayer gamers take a considerable amount of time ensuring teammates are ready before a long battle, and will even take breaks before entering combat if players need to eat or use the restroom to relieve themselves (Ducheneaut, Yee, Nickell, & Moore, 2006; Williams & Kirschner, 2012). These players indicate that social interaction is a primary motivation to spend long hours playing (Chen, Duh, Phuah, & Lam, 2006; Cole & Griffiths, 2007; Yee, 2006) and consider attention to social interaction a crucial determinant of successful play (Kahn & Williams, 2016). In sum, there may be more motivation to attend to social tasks because there is considerably more at stake if one fails to diligently focus while playing a multiplayer game. Such diligent focus to social tasks might produce the neural synchronization detailed in the STF.

Conclusion Research on flow has attracted considerable attention among video game researchers since Sherry (2004) first introduced the concept to the field. Early research focused on the balance between challenge and skill, and the STF added a neuroscientific perspective arguing that the intrinsically motivating experience of flow results from coordinated recruitment of brain networks involved in attention and reward. Evidence supporting the STF comes mainly from studies of video games taxing fine motor skills, but research to date has failed to consider how social-task demands in games affect flow experiences. The commercial video game market is flooded with multiplayer games. The genre’s success indicates that social games are attractive to players. Social-task demands thus likely play an important and potentially 172

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distinct role in experiencing flow during gameplay. As such, examining how social-task demands versus visuo-motor task demands engage brain networks related to attention and reward presents a promising avenue for research. Researchers should explore (a) if patterns of activity in attentional and/or mentalizing networks arising during multiplayer gameplay might oscillate with reward systems to produce forms of synchronization previously unexamined; (b) if such synchronization is experienced as “flow” or a different state associated with reward and positive affect; and (c) whether synchronization of neural networks related specifically to visuo-motor tasks as opposed to social tasks is associated with different intuitive needs (e.g., competence versus relatedness). Insights gained through such work will improve our understanding of the mechanisms that make video games challenging, absorbing, and generally fun to play.

Ludography E.T. the Extra-Terrestrial. (1982). Sunnyvale, CA: Atari. League of Legends. (2009). Los Angeles, CA: Riot Games. Super Mario Bros. (1985). Kyoto, Japan: Nintendo. Tetris. (1984–present). Various.

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11 E X P L I CAT I N G T H E E L E C T R I C I T Y O F E S P O RT S : M OT I VAT I O N S F O R P L AY A N D C O N S U M P T I O N Kenon A. Brown, Andrew C. Billings, Melvin Lewis, and Kimberly Bissell

Competitive computer gaming has rapidly evolved into recognizable sport. Carr (2016) reports that eSports emerged from fledgling status in the 1990s to become an entity that is selling out tournaments at major stadiums. To wit, the eSports League of Legends Season Three World Championship sold out the Los Angeles Staples Center in an hour (Tassi, 2013), with 11,000 fans seizing the opportunity to cheer on gamers during the eSports event (Cubarrubia, 2013). Games like League of Legends (Riot Games, 2009, a free-to-play strategy game) are wildly popular. Meanwhile, full-time players, teams, coaches, trainers, broadcasters, and corporate sponsors have now been established (Carr, 2016). Emphasizing fan growth and global attention, Dota 2 2016 International Championships filled the 17,500-seat Key Arena in Seattle, Washington, to witness players vying for $20.7 million, the biggest purse in eSports history at the time (Gies, 2016). The eSports phenomenon has attracted the attention of numerous sport fans, professional sports organizations, corporate sponsors, and government entities. With the official eSports tournament for Riot Games League of Legends now recognized as a professional sport by the US State Department, League of Legends players born outside the US are now able to live and work in America under the same visa as any other professional athlete (Makuch, 2013). Several former professional athletes have taken notice of the opportunity, joining the growing wave of eSports. In December 2015, three-time NBA champion Rick Fox bought an eSports team previously known as

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Gravity Gaming, renaming it Echo Fox. The team focuses on the gaming franchise League of Legends (Heitner, 2016). Moreover, seven-year NBA veteran and self-proclaimed video game enthusiast Jonas Jerebko purchased the eSports franchise Renegades in 2016 (Manning, 2016). The organization has different sections for several video games and franchises, including Counter-Strike: Global Offensive (Valve, 2012), Call of Duty (Activision, 2005), Halo (Microsoft, 2001), and Overwatch (Blizzard Entertainment, 2016). With this mind, the desire to be engaged in eSports continues to reach both sport and gaming consumers by offering a competitive intersection of the two worlds. This study compares and contrasts the uses and gratifications of eSports for these consumers, focusing on differences that emerge between the reasons one participates via active game play and the reasons one opts to witness others participating. In sporting terms, this study contrasts the participants from the fans—in an eSports arena that inherently blurs such distinctions much more than within other sporting realms.

The Legitimization and Development of eSports The passion and excitement of playing eSports has become a phenomenon for millions worldwide, with 205 million individuals playing or watching eSports in 2014 (Cassleman, 2015). Formally defined as an area of sport activities in which people develop and train mental or physical abilities in the use of information and communication technologies (Seo, 2013), eSports is now recognized as a mainstream computer gaming activity (Martoncik, 2015). However, advancing eSport as “sport” had led to questioning of the foundational assumptions of what constitutes a sport in its most primitive conception (Jenny, Manning, Keiper, & Olrich, 2016). Assuming one adopts such a stance in favor of the eSport moniker, a useful differentiation can be offered between eSport and game streaming, with eSport being a subset of the game streaming phenomenon. With the rise of Twitch, a video-streaming site acquired by Amazon in 2014 (formerly Justin.tv), live game streaming—video of gaming-related media in real-time via the internet—has become immensely popular. Twitch is one of the world’s leading social video platform and community for gamers. Monthly, more than 100 million community members gather to watch and talk about video games with more than 1.7 million broadcasters (Twitch, 2016). Furthermore, Twitch’s live and video on-demand platform accommodates the entire video game industry, including game developers, publishers, media outlets, events, casual content creators, and the complete eSports sector (Twitch, 2016). Additionally, Twitch offers the community of gamers a platform to post their own streams for other viewers to watch. These live steams can include gamers playing

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a particular game, strategy walkthroughs for inexperienced gamers, or eSports competitions, to name a few examples. According to Lee and Stewart (2016), the eSports demographic population skews toward males (82 percent) and millennials (75 percent). Specifically, Zalik (2015) highlights that MOBA (multiplayer online battle arena) games, like League of Legends, and first-person shooter games, like Call of Duty, have more than 70 percent of males, with fighter games, like Mortal Kombat (1992, Midaway), exhibiting a slight tendency toward more gender balance. According to Zalik (2015), players are also more often drawn to team games rather than one-on-one fighter genres. Clearly, the eSports landscape is multifaceted and ripe for expansion into other arenas more akin to embodied sport fandom, and media entities have rapidly facilitated those desires. In 2015, the eSports (r)evolution attracted Turner Broadcasting and William Morris Endeavor/IMG to create a partnership called eLeague (Proctor, 2016) with live games of Counter Strike: Global Offensive on Turner Broadcasting System (TBS) on Friday nights with additional media companies involved in the ecosystem as well. More recently, ESL, the world’s largest eSports company, is offering its live channel eSports TV, for Playstation Vue subscribers (Regan, 2017). Consumption of the competitive gaming sector online accounts for a 10 percent share of the time Americans in the US spend online, making its influence on social interaction and friendships intriguing (Trepte, Reinecke, & Juechems, 2012), as scholars endeavor to understand the social and psychological tenets impacting competitive gamers (see Witkowski, 2012). Gaming, as classically configured, has expanded considerably as it is “no longer confined to one’s time in front of the television set or computer monitor, game controller in hand” (Baerg, 2014, p. 245). This evolution of a gaming community with heavy social elements (Blight, 2016), has resulted in a massive expansion in the study of game studies based on constituencies that blur the lines of solo, dyadic, and group configurations. Put simply: One of the most interesting and perhaps important shifts has been in recognizing how we play games together in new and old ways—not simply on a couch or gathered in a persistent virtual space like World of Warcraft—but even with small, single-player games as well as with large and small communities from around the block and around the world. (Consalvo, 2017, p. 84) As competitive gaming has become a major leisure activity through online means, the nature of eSports has become more accessible to casual gamers

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and fans, and therefore, attention must be paid to fundamental influences of online social capital and whether online social capital increases offline social support (Trepte et al., 2012). Additionally, eSports followership enhances the subcultural components of consumption, strengthening boundaries between social worlds. The process of eSports incorporates other cultural meanings (see Taylor, 2012) and the recent influx of professional eSports teams—as well as their increased opportunity for media exposure—might create unique consumption paths and heightened awareness of the eSports industry. Applied uses and gratifications within eSport play and consumption. A number of theoretical underpinnings could be used to communicatively explore the rapid growth of eSports as well as the relationships to media consumption—specifically within traditional sports media. However, the uses and gratifications approach (Katz & Blumler, 1974; Katz, Blumler, & Gurevitch, 1973) perhaps best applies in this case because it pertains to the desire for—and selection of—innovative media formats. Focusing particularly on the gratifications sought versus gratifications obtained, the approach was founded in the motivational influence of different social and familial networks on media selection habits (see Katz & Lazarsfeld, 1955). Given the interactive, social, nature of eSport participation, uses and gratifications becomes a particularly pertinent lens for exploring motivations for play and consumption and the relationships therein. Severin and Tankard (2000) expand uses and gratifications by articulating five reasons for people selecting one form of media over another, including: (a) knowledge enhancement; (b) relaxation; (c) social interactions/companionship; (d) diversion; and (e) escape. Differentiating these elements further, Papacharissi and Mendelson (2010) provide seven gratification-based prongs: (a) relaxing entertainment; (b) expressive information sharing; (c) escapism; (d) cool and new trend; (e) companionship; (f) social interaction; and (g) habitual time pass. These elements can be used to explain the appeal for not only eSports players but also eSports media consumers (watching content of other people playing in eSports competitions)—yet in presumably different measure. For instance, one assumes more social interaction occurs within playing such games, but perhaps relaxation is lessened in comparison to the vicarious participation afforded by eSports media viewing. Much of this work could be seen as akin to sports play versus sports viewing; those who cannot understand the appeal of watching people play videogames as eSports need only to recognize that watching other people play games is what often yields the highest of all media ratings (see Billings, 2011). Thus, streaming of eSport produces many of the same gratifications as watching other athletes and teams play: masses witnessing professionals

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performing skills at the highest levels (Kaytoue, Silva, Cerf, Maira, Jr., & Raïssi, 2012). Cheung and Huang (2011) note that from: spectators gathering in the park to watch chess champion Garry Kasparov or audiences watching game shows on television … the presence of a large spectating audience can generate more attention to the game, drive sales of the game, increase advertising revenue, and even improve the experience for the players themselves. (para. 1) While the authors acknowledge that the player (and game) are primary to the experience, it would be naive to suggest players are the only performers within the circle of watching—for example, the audience members often engage each other just as much as they engage the streamer, and often they do so in a high public and performative manner that fits the general tone or content of the hosted game-stream (Lin, Bowman, Lin, & Chen, 2017). Focusing on the motivations for play and consumption could, thus, be viewed as akin to gratifications sought, with a view similar to that of Ruggiero (2000) and Rubin (1994) who illuminated the role of social and psychological factors in the selection of media. The fact that media options have never been more prevalent (see Anderson, 2006) only underscores how these factors could be used to explain media choices, as one can more finely hone one’s media options to personalized preferences in a manner never before deemed possible. Katz and Blumler (1974) note that uses and gratifications approach has three primary assumptions: (a) audiences are goal-oriented in their behavior; (b) they are active in their media use; and (c) audiences are aware of their needs and use specific media to gratify those needs. It is here where the notion of player versus fan (or playing the game versus live streaming) must unfold within complementary yet different parameters. Both player and viewer would best be characterized as active, social, and engaged; moreover, each are seeking satisfaction based on the three aforementioned assumptions (e.g., Katz & Blumler, 1974). Nevertheless, the person playing the game is experiencing higher levels of arousal and sensation seeking while the streaming participant (viewer) shares in the escapism, yet is ultimately in the digital space for other social reasons. For instance, escapism, game-based knowledge acquisition, novelty, and aggressiveness positively predicted eSport spectating frequency (Hamari & Sjöblom, 2017), with another study forging more direct ties to desired parasocial interaction, undergirded by self-determination theoretical principles, to create belonging (Peng, Lin, Pfeiffer, & Winn, 2012). Taking the desire for parasocial interaction further in explicating the game viewer, Blight (2016) found that both parasocial interaction and fandom mediated relationships bolstered the sense of community as well as gratifications of 182

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relaxing entertainment, expressive information sharing, and escapism. As Consalvo (2017) articulates regarding sites such as Twitch: While most of those viewers and streamers are engaged in competitive individual and team-based eSports games like League of Legends and CounterStrike: Global Offensive, a significant number of streamers also play through single-player games, sometimes to see how fast they can complete them (the community of speed-runners) and sometimes simply to enjoy, comment on, and critique them publicly. (p. 85) Regardless, Katz and Blumler’s (1974) essential notion of purposeful selection seemingly indicates that ascertaining data related to motivations for play and media viewing of eSport products is possible via survey methods. Indeed, such an approach has been applied to the broader game streaming phenomenon, in extant work from Blight (2016), Gros, Wanner, Hackenholt, Zawadzki, and Knautz (2017), and Sjöblom (2015). Those studies generally found game streaming to be motivated by the prospect of social interaction and a release from reality. Yet, they did not focus on the specific case of eSports, which leaves a critical gap in the literature—notably given that eSports is a distinct, highly competitive subset of eSports that warrants its own examination. For this reason, the balance of our chapter reports on a survey project aimed precisely at this gap, examining the motivations behind eSports participants’ attitudes and behaviors, particularly investigating the differences in the motivations behind competing in eSports compared with that of a spectator.

Uncovering Motivations of eSport Participation: A Survey To learn more about the relationship between motivations and tendencies to participate in eSports competition and consume eSports-related media among eSports participants, quantitative measures were developed addressing demographic information, eSport experience, consumption of eSports-related media, and motivations to participate in eSports competition. Measures were also used to measure satisfaction with eSports participation and future desires to watch eSports media competitions. Participants and recruitment. Active eSports participants in the US (defined as anyone who reported having participated in or watched some form of eSports in the last six months) were recruited using a convenience sample of members of several eSports-related forums. Notably, players must have received some form of reward or compensation for participating in an online or local competition to be considered an eSports participant (i.e., cash, trophy, online store points, etc.). Participants were 183

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recruited via several online message boards and mobile applications directly relating to eSports, particularly through forums on Reddit related to eSports. Once eSports players agreed to participate, they followed a hyperlink (included in all recruitment material) connecting them to the online survey instrument. A sample of 1,319 eSports participants was recruited. The sample consisted of 1,291 males (97.9 percent) and 28 females (2.1 percent). The sample was predominately Caucasian (860 participants, or 65.2 percent), with Asian (201 participants, or 15.2 percent) and Hispanic (139 participants, or 10.5 percent) being the highest represented minority groups. The mean age of the respondents was 21.67 years (SD = 4.04). The majority of respondents lived in suburban areas (738 respondents, or 56 percent), with 447 respondents (33.9 percent) living in urban areas, and 134 respondents (10.2) in rural areas. Variables and measurement. An online questionnaire was managed using Qualtrics, an online survey and data management software. The questionnaire was distributed via Reddit using a web link that directed participants to the Qualtrics questionnaire. Participants were asked how many hours per week they (a) participated in eSports competition and (b) consumed eSports-related media using two open-ended questions. Although the sample was heavily male, gender did not have a significant effect on participation hours (Mmale = 15.33, SDmale = 15.11; Mfemale = 14.21, SDfemale = 11.89; F(1, 1317) = 0.151, p = 0.697) or consumption hours (Mmale = 16.28, SDmale = 18.44; Mfemale = 14.87, SDfemale = 18.96; F(1, 1317) = 0.159, p = 0.69). To measure motivations, participants were asked to identify their level of agreement or disagreement to statements using a seven-point Likert scale (anchored by 1 = Strongly Disagree and 7 = Strongly Agree). Motivation items were adapted primarily from Billings and Ruihley (2013, 2014) analyses of traditional sport and fantasy sport motivations for play, as these items appeared most applicable to the eSport player experience. Possible motivations for eSports enthusiasts were measured using separate three-item, seven-point Likert scales (citations refer to foundational literature for each motivation). A confirmatory factor analysis (CFA) provided evidence that the measurement model was a good fit for the data (χ2/df = 2.64, RMSEA = 0.06, NFI = 0.902, TLI = 0.934, CFI = 0.94). Those specific motivations included: • •

eSports as a source of eustress, with the assumption that eSports provides fans with a positive arousal that stems from a welcomed level of stress (Wann, 1995; α = 0.83) eSports as a source of providing camaraderie and stronger connection among fellow eSports enthusiasts (Seo & Green, 2008; Ruihley & Hardin, 2011; α = 0.76) 184

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• • • • • • •

eSports as a source of competition and positive reinforcement for their success or the success of the players and teams they follow as spectators (Ruihley & Hardin, 2011; α = 0.70) eSports as a source of escape from reality and their normal, daily routine (Seo & Green, 2008; α = 0.77) eSports as a way to pass time when unoccupied or busy (Seo & Green, 2008; α = 0.81) eSports as a way to build one’s self-esteem through a sense of achievement and acceptance (Spinda & Haridakis, 2008; α = 0.70) eSports as way to encourage a sense of social sport through opportunities for discussion and debates (Hur, Ko, & Valacich, 2007; α = 0.80) eSports participation or consumption as a way to affirm their fanship for eSports (Seo & Green, 2008; α = 0.85) eSports participation or consumption as a way to gain a sense of Schwabism, or a feeling of having superior knowledge about eSports compared with their peers (Ruihley & Hardin, 2011; α = 0.75)

Overall satisfaction with eSports activities was measured using a threeitem scale adapted from Ruihley and Hardin (2011; α = 0.85). There was not a significant difference in overall satisfaction between males and females (Mmale = 5.91, SDmale = 1.01; Mfemale = 5.69, SDfemale = 0.71; F(1, 1317) = 1.363, p = 0.243). Participants’ intention to return to participate in eSports activities was measured using a three-item scale also adapted from Ruihley and Hardin (2011) (α = 0.82). There was not a significant difference in future intent between males and females (Mmale = 5.72, SDmale = 1.07; Mfemale = 5.75, SDfemale = 0.76; F(1, 1317) = 0.018, p = 0.893). Instrument and procedure. Interested participants were prompted to use a distinct web address to access the questionnaire. After reading and agreeing to the informed consent statement, participants were asked to provide the numbers of hours per week they participate in eSports and consume eSports media using open-ended questions. After the time duration questions, participants answered the motivation, satisfaction, and future behavioral intention items. After completing the scale items, participants received a thank you message and were asked to complete demographic questions. The questionnaire was pretested using 47 eSports participants in order to test scale reliability and validity, as well as face validity and editing of items, but no significant changes were made to the questionnaire as a result of the pretest.

Anatomy of the eSport Participant In order to get to the heart of what motivates eSports enthusiasts, we first inquired which motivations influenced the number of hours a participant 185

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dedicated to participating in eSports activities. In other words, why are eSports enthusiasts participating in eSports competitions? To answer this question, a multiple regression was conducted, and the analysis revealed that competition (β = 0.157, t = 4.433, p < 0.001, partial R2 = 0.01), passing time (β = 0.066, t = 2.172, p = 0.03, partial R2 = 0.004), and Schwabism (β = 0.165, t = 4.28, p < 0.001, partial R2 = 0.01) had a significant, direct association to the number of hours devoted to eSports participation (R2 = 0.07, F(9, 1309) = 11.492, p < 0.001, Durbin-Watson = 1.914). So, the number of hours that participants dedicated to participating in eSports activities was positively associated to their desire for participating in eSports activities for competition, passing time, and for Schwabism. Next, we inquired which motivations would influence the number of hours devoted to consuming eSports-related media. In other words, why are eSports enthusiasts following eSports in the media? A multiple regression was conducted, and the analysis revealed that only fanship (β = 0.231, t = 5.186, p < 0.001, partial R2 = 0.02) had a significant, direct association to the number of hours devoted to eSports media consumption (R2 = 0.09, F(9, 1309) = 14.326, p < 0.001, Durbin-Watson = 1.975). So, the number of hours participants dedicated to following eSports in the media was positively associated to their desire for participating in eSports activities for fanship. To get a deeper understanding of the motivations behind eSports fandom, we also inquired which motivations would influence eSports participants’ satisfaction with eSports activities, or more simply put, what makes eSports enthusiasts satisfied with the sport? A multiple regression was conducted to answer this research question. The model revealed that camaraderie (β = 0.115, t = 5.346, p < 0.001, partial R2 = 0.02), arousal (β = 0.487, t = 17.639, p < 0.001, partial R2 = 0.19), and fanship (β = 0.239, t = 8.525, p < 0.001, partial R2 = 0.05) had a significant direct association with participants’ satisfaction with eSports activities. In addition, escape (β = −0.046, t = −2.431, p = 0.015, partial R2 = 0.004) had a significant, inverse association with participants’ satisfaction with eSports activities (R2 = 0.64, F(9, 1309) = 255.564, p < 0.001, Durbin-Watson = 1.98). So, participants’ satisfaction with eSports activities was positively associated with their desire for participating in eSports activities for camaraderie, arousal, and fanship. Also, their satisfaction with eSports activities was actually negatively associated with their desire for participating in eSports activities for an escape. Finally, we inquired which motivations would influence future intention to participate in eSports activities: why would eSports enthusiasts participate in the future? A multiple regression was conducted, and the analysis revealed that camaraderie (β = 0.075, t = 3.193, p = 0.001, partial R2 = 0.008), arousal (β = 0.483, t = 15.991, p < 0.001, partial R2 = 0.16), fanship (β = 0.148, t = 4.834, p < 0.001, partial R2 = 0.02), and 186

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Schwabism (β = 0.121, t = 4.59, p < 0.001, partial R2 = 0.02) had a significant, direct association with participants’ future intent to participate in eSports activities (R2 = 0.57, F(9, 1309) = 190.073, p < 0.001, Durbin-Watson = 1.999). So, participants’ willingness to participate in future eSports activities was positively associated with their desire for participating in eSports activities for camaraderie, arousal, fanship, and Schwabism.

Into the Great Wide Open: eSport, Communities, and Gratifications of the Future As one of the fastest growing areas of sports, eSports communities have expanded and evolved, involving more than 200 million people (Cassleman, 2015). This rise in involvement and participation in eSports has led to enormous jumps in advertising, pushing researchers and advertisers to better understand eSport communities. This chapter applied a uses and gratifications approach to the study of eSports consumers’ reasons for participating in active game play, further examining participation differences (in terms of satisfaction) by fans. The uses and gratifications approach is especially pertinent for this examination because of the specific desire for and selection of innovative media formats in a sporting context. Using a sample of just over 1,300 eSports participants from the US that largely fit the demographic profile of eSports enthusiasts from most estimates (Lee & Stewart, 2016), we sought to examine the motivations behind participants’ satisfaction with eSports competition, the motivations behind participants’ current experience and future intent to participate, and the motivations behind participants’ consumption of eSports related media. From the macro-level perspective, it appears that a hierarchy of demands are presented within the domain of eSports. Bowman (2016) classifies demands within the contexts of cognitive, emotional, social, and physical. While nearly every other type of sport has physicality within the core elements sought, this study presents an entirely new conception, with the social demands being primary and cognitive demands arguably being the most noteworthy secondary elements. As such, the social elements afforded via online contexts seemingly make eSports even more inherently communal than what is found in other realms of sport, even those unfolding in primary online contexts such as fantasy sports (Billings & Ruihley, 2013, 2014). Physical desires appear to be superseded by the need to connect as well as the need to understand the game, as elements of eSports appears to morph and shift much more dramatically than in traditional sports. Findings suggest that several of Severin and Tankard’s (2000) reasons for selecting one form of media over another were, indeed, factors driving participants’ motivations influencing eSports satisfaction among 187

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participants. Camaraderie, or social interaction and companionship, was a significant, positive predictor of satisfaction with eSports participation along with arousal and fanship. Findings indicate that escape was a negative predictor of satisfaction with eSports activities, which does not align with the uses and gratifications approach. However, given the competitive nature of sports in general and, more specifically, eSports, it is possible the drive to be competitive reduces the perception that participation is, indeed, an escape. Results further suggest that similar factors were also significant predictors of participants’ likelihood to participate in eSport activities in the future—camaraderie, fanship, arousal, and Schwabism. Yee (2006) reported that several overarching factors were significant predictors of player motivations in online games—the achievement component, the social component, and the immersion component. Several of these factors tie directly into the uses and gratifications approach, further supporting the underlying findings of the present study: (a) users seek out ways to compete and subsequently experience achievement and satisfaction with eSports; (b) users seek out companionship via the social nature of eSports; and (c) via the immersive nature of eSports, gamers are essentially experiencing arousal and, sometimes, escape. Cole and Griffiths (2007) further support the finding that the social interactions found in many eSports communities are a significant component of user enjoyment and ultimate satisfaction with game play and participation. While the present study was descriptive in nature, it did yield a greater insight into the motivations behind participant involvement and intended involvement in eSports. Results could also help shape future studies that might be more appropriate for a closer examination of individual factors of participants. Findings from the present study suggest that participant gratification from eSport involvement is related to continued and projected future engagement. However, future studies should more closely examine consumer or participant transformations within the eSports communities and further tap into the psychology of participant engagement as Ruggiero (2000) and Rubin (1994) suggest. Future studies could also more closely examine the demographic factors of serious or professional eSports participants with those who are more involved for leisure purposes. This type of psychographic analysis could prove useful to the advertising and marketing literature specific to eSports. Studies of this nature could broaden our understanding of self-concept, self-perception, and the social dynamics resulting from participation in eSports in the context of contemporary consumer culture. Involvement in eSports will only continue to increase and become more prevalent globally; therefore, continued empirical examination of the motivations sought and gratifications acquired from eSports participation

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continues to be warranted. The present study of the determinants of satisfaction tie directly to motivations for current and continued engagement with eSports, further justifying its examination.

Ludography Call of Duty series. (2005–present). Woodland Hills: CA: Activision (Infinity Ward). CounterStrike: Global Offensive. (2012). Bellvue, WA: Valve. Halo series. (2001–present). Redwood, CA: Microsoft. League of Legends. (2009). Los Angeles, CA: Riot Games. Mortal Kombat. (1992). Chicago, IL: Midway. Overwatch. (2016). Irvine, CA: Blizzard Entertainment.

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12 LIVE STREAMS AND REVENUE STREAMS: TWITCH AS A HYBRID G A M I N G C U LT U R E John A. Velez, Melissa R. Gotlieb, Geoffrey Graybeal, Alan Abitbol, and Jonathan A. Villarreal

Despite concern over declines in dutiful forms of citizenship (e.g., voting, working for political parties, following the mainstream news), the image of the socially isolated, antisocial, and civically disengaged youth has largely been reduced to a myth (Bennett, 2008; Dalton, 2009). This is evidenced by the emergence of digital forms of citizenship supported by social media platforms that allow for creative expression and social relationship building (Bennett, Freelon, & Wells, 2010). These social media platforms, including those centered on social networking (e.g., Facebook, Twitter, Instagram) and video sharing (e.g., YouTube, WorldStar), as well as online gaming (e.g., World of Warcraft, Blizzard, 2004; and other massively multiplayer online games), have been described as enabling the formation of participatory cultures that bring users together based on a shared interest (Bennett et al., 2010; Jenkins et al., 2008). Participatory cultures can be defined as: culture[s] with relatively low barriers to artistic expression and civic engagement, strong support for creating and sharing one’s creations, and some type of informal mentorship whereby what is known by the most experienced is passed along to novices. (Jenkins et al., 2008, p. 3) Those centered on online gaming, in particular, have been lauded for their ability to provide users with the kinds of civic experiences previously

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thought to be lacking among young citizens. For example, according to Steinkuehler and Williams (2006): By providing spaces for social interaction and relationships beyond the workplace (or school) and home, such virtual [gaming] environments have the potential to function as new (albeit digitally mediated) third places similar to pubs, coffee shops, and other hangouts. (p. 889) Moreover, participatory cultures centered on online gaming have also been celebrated for their ability to provide users with voice and agency. Media scholars have argued that participatory cultures are the inevitability of new media technologies that subvert and invert traditional topdown mediaspheres (Bruns, 2008). Mediaspheres are the collective spaces “where citizens can voice their opinions and experiences and interact with other voices” afforded by the media (Carpentier, Dalgren, & Pasquali, 2013, p. 288). The traditional top-down hierarchy of influence and power stemming from the concentration of scarce production resources, as found in cable television, is eroding as the monetary barriers to media production dissolve. Online games provide free admittance to participatory cultures in which everyone enjoys unfettered access and opportunities to contribute and participate (i.e., equipotentiality). Indeed, terms such as “produsers” (Bruns, 2008) are used to represent the newly empowered public who are capable of both media production and consumption. For example, Second Life (Linden Lab, 2003), and other virtual worlds, affords gamers (or residents) the ability to be their own architects, who are “empowered by the ability to create, residents act with dedication and purpose, often overcoming tremendous obstacles to acquire new skills and knowledge to make their world their own” (Ondrejka, 2008, pp. 230–231). By enabling the formation of participatory cultures, online games hold enormous potential to provide young citizens with the resources, skills, and competencies, as well as opportunities, to meaningfully engage in public life (Jenkins et al., 2008; see also Mäkinen, 2006). However, as the social media platforms that support online games become more multifaceted in terms of their features and functional capabilities, more recent questions emerging in this line of research center on whether the increasing social demands placed on gamers enhance or undermine the civic potential of these new participatory gaming cultures. Indeed, social video game play has entered a new era with the proliferation and popularity of live streaming websites that bring online gaming together with social networking and video sharing in one space. Platforms such as Twitch.tv, the focus of the present chapter, enable gamers to broadcast video game play to thousands of viewers. Such live streaming 194

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sites are rich in opportunities for interactivity, placing greater demands on both the individual players (or streamers) and the community of gamers (or viewers) surrounding the various games and streamers. Previously, participatory cultures that existed outside the games were mainly relegated to message boards (e.g., Reddit) and recorded videos (e.g., YouTube), but more multifaceted platforms like Twitch allow for larger and more active social environments via gaming voyeurism. This has changed the nature and meaning of participation as well as paved the way for media conglomerates, seeking new sources of revenue, to monetize such participation (e.g., Postigo, 2014). Our aim in the present chapter is to discuss how the innovative features and functional capabilities of Twitch have increased social demand and altered the nature of participation in such a way that encouraged its commodification. This, in turn, has allowed for the emergence of a hybrid gaming culture that blends aspects of both participatory cultures centered on video games and traditional top-down media. We begin by classifying these features and functional capabilities according to their social affordances, illustrating how they contribute to the formation of the various types of participatory cultures described by Jenkins and colleagues (2008). However, in doing so, we also suggest how the social affordances of this hybrid gaming culture impose constraints on participants’ access, voice, and agency.

Twitch: A Live Streaming Social Gaming Platform Twitch challenges our current notions of media consumption, creation, and participation. It is a social media center, allowing video game players to broadcast themselves live to an internet audience. Viewers can interact with each other and streamers in real time. Viewers can even subscribe to streamer channels and be notified when the streamer goes online. Many streamers even earn a living just by broadcasting themselves playing video games thanks to subscription and donation features. In short, Twitch constitutes a unique combination of mass and interpersonal communication phenomena, as Burroughs and Rama (2015) put it: “The streaming space of Twitch is both ‘real’ and ‘virtual,’ blurring the boundaries between the game space, social networks, and face-to-face communication” (p. 2). The popularity and demand for such online spaces resulted in Amazon purchasing Twitch.tv for $970 million (MacMillan & Bensinger, 2014). Prior to this purchase, Twitch already boasted viewer numbers that outranked series finales of popular television series at the time, such as Breaking Bad and The Sopranos (MacMillan & Bensinger, 2014). As of 2015, Twitch was estimated to be worth over $3.8 billion (Brightman, 2015). In 2014, Twitch made up over 43% of all online live video streaming with its nearest competition (World Wrestling Entertainment) coming in 195

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at over 17% (Eadicicco, 2014). In 2016, Twitch boasted over 2.2 million monthly streamers on average as well as over 292 billion minutes streamed (Twitch, 2016). Additionally, over 14 billion messages were sent in 2016 alone. (Twitch, 2016).

Twitch Features and Functional Capabilities In an effort to illustrate how the features and functional capabilities of Twitch contribute to its civic potential as a participatory culture, we draw from Tuten and Solomon’s (2013) typology of social media platforms. This typology organizes social media platforms into four zones according to their social affordances: social community, social publishing, social entertainment, and social commerce. These zones illustrate a social media platform’s potential to enable social relationship building, content sharing, collaborative play, and communal shopping experiences, respectively. Although intended as a tool to help organizations select appropriate social media platforms to meet their marketing objectives, the typology can also be applied more broadly to define and understand any social space, especially one that includes multiple features and functional capabilities associated with live game streaming. Whereas the first three zones comprise the types of social media platforms that overlap with the types of participatory cultures identified by Jenkins and colleagues (2008), the fourth zone—social commerce— illuminates additional features and functional capabilities of social media platforms that correspond to the various ways that participatory cultures have become commodified. In the space below, we illustrate some of the most prominent features and functional capabilities of Twitch that classify it as a melded social media platform that blends social affordances across all four zones (see Table 12.1) and explain how this allows for the emergence of participatory cultures centered on affiliation, expression, circulation, and collaborative problem solving (Jenkins et al., 2008). Social community. Social community platforms bring users together as part of an “imagined” community (Anderson, 1983) centered on a shared interest. These include social networking sites, discussion forums, wikis, and other platforms that allow for “two-way and multiway communication, conversation, collaboration, and the sharing of experiences and resources” (Tuten, 2013, p. 42). In classifying it as a social media platform that affords social community, Twitch may be viewed as a participatory culture centered on opportunities for affiliation. On Twitch, video game players can choose to live stream, and viewers can choose to join their favorite streamer and/or game community. Twitch offers unprecedented real-time interaction among viewers and streamers via features such as streamer webcams, chat boxes, and whispers (i.e., direct messaging). In addition to these communicative features, Twitch also affords the use 196

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Table 12.1  Twitch features and functional capabilities organized by Tuten and Solomon’s (2013) four zones Zone

Twitch.tv features and capabilities

Social community

Chat box     Whispers (direct messaging)     Collaborative gaming experiences   (e.g., Twitch Plays Pokémon)    Polls Live streams    Developer streams    Game development     Advanced game access to streamers    User-generated content View live stream game play    eSports events    Charity gaming events     Collaborative gaming experiences   (e.g., Twitch Plays Pokémon) Subscriptions to streamers and/or channels w/ perks (e.g., private access and special chat emotes)     Twitch Prime (e.g., exclusive items/loot)    Donations to streamers    Cheer bits    Sponsorships of streamers    Streamer merchandise (e.g., T-shirts)

Social publishing

Social entertainment

Social commerce

Note: According to Tuten and Solomon’s (2013) framework, opportunities for collaborative gaming could be classified as both an affordance of social community (e.g., opportunities for collaboration) and social entertainment (e.g., online gaming) social media platforms.

of polls, enabling viewers to make important decisions as a group (e.g., deciding as a community which game the streamer will play next or how the streamer should proceed at crucial points in the game; Hamilton, Garreston, & Kerne, 2014). Twitch also encourages collaborative game play among streamers and viewers. For instance, the streamer “Sacriel” often hosts custom matches in the video game Player’s Unknown Battlegrounds (Bluehole Studio, 2017) in which viewers are invited to join and either play with the streamer or have the streamer comment on the match for other viewers. Collaborative game play can also occur without an overseeing streamer such as in 2014 when millions of gamers watched tens of thousands of participants collectively play Pokemon Red (Nintendo, 1996) for two weeks. A shared sense of identity developed as participants shared memes, fanart, and lore. Following this event, Twitch added a new collaborative gaming feature called “Twitch Plays,” which allows streamers to host games where participants 197

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can play the game collaboratively (e.g., Twitch Plays Dark Souls [Bandai Namco Entertainment, 2011]). Such opportunities for interaction contributes to a strong sense of community among streamers and viewers. This occurs, at least in part, due to a concerted effort among streamers to create a sense of community among their viewers. Hamilton et al. (2014) observed that many streamers “make special efforts to recognize every person at least once in their streams” (p. 1319). Twitch exhibits the key characteristics of community— emotional engagement, self-identification, cultural competence, auxiliary consumption, and production—identified by Tuten and Solomon (2013). Specifically, viewers may become emotionally engaged fans of streamers, identify with other viewers who share interest in the same streamers, have a critical understanding of the game being played by the streamer, collect and consume items related to the streamer (e.g., purchase Twitch streamer apparel), and have the option to create chat rooms, polls, and other content related to the stream. Indeed, Twitch functions as a viable “virtual third place, in which informal communities emerge, socialize, and participate” (Hamilton et al., 2014, p. 1315). As such, Twitch holds the potential to provide its viewers with the types of civic experiences that Putnam (2000) believed to be lacking among the younger generations. In providing an informal space to interact with an “imagined” community (Anderson, 1983) of likeminded others who share a similar passion for the streamer and/or game, Twitch, like other virtual gaming environments (e.g., massively multiplayer online games), allows for the generation of bridging forms of social capital (e.g., Steinkuehler & Williams, 2006) that facilitate the flow of information and enable community members to organize and take action (Granovetter, 1973; Putnam, 2000). Social publishing. Social publishing platforms allow users to create, edit, share, and more recently curate content (Tuten, 2013). These include video sharing sites, blogs, and other platforms that afford users the ability to take a more active role as producers of content. As a social media platform that affords social publishing, Twitch may be viewed as a participatory culture centered on opportunities for expression and circulation. First and foremost, as mentioned above, Twitch enables video game players to live stream to an audience as well as distribute video recordings to an audience for later viewing. This allows them to express their values as streamers and connect with their viewers (Hamilton et al., 2014). Streamers also have the ability to develop their own games and share them with their viewers. Additionally, due to its nature and popularity, Twitch has become a popular platform for game developers to announce new games and reveal new gaming content. Popular streamers are often given advanced copies of unreleased games by the developers in order to generate hype and interest. Streamers get the opportunity to try out a new game and viewers get to learn about it. 198

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Participants who view streamers can also engage in social publishing. Participants often create content revolving around a streamer, a game, or a specific stream event to share with the community. Links to user-generated content (UGC) are commonly placed in chat boxes and accompany donations to streamers. Streamers often take advantage of UGC from their communities and incorporate them into the stream such as using graphics or edited videos to announce live streams or as the background to streams. Many streamers simply view and discuss UGC as part of their stream and encourage participants to engage in social publishing. The ability to live stream as well as participate in UGC provides streamers and participants, respectively, with the opportunity to express their values (Hamilton et al., 2014) and perform for an audience, as well as collaborate with others (via polls) to make decisions in real time. According to Östman (2012), these expressive, performative, and collaborative aspects of content production provide young citizens with the opportunity to develop key skills and competencies needed for active engagement in public life (see also Jenkins et al., 2008). Social entertainment. Social entertainment platforms provide “opportunities for play and enjoyment,” and include online gaming, virtual worlds, social music, and social art (Tuten, 2013). Research suggests Twitch users are motivated by its ability to provide affective—“emotional, pleasant, or aesthetic experiences” (p. 3)—and tension release affordances, with the latter representing the largest predictor of Twitch users’ time spent on the website (Sjöblom & Hamari, 2017). Twitch offers users a window into games on platforms that may be unavailable to them or to experience game play that is beyond their skillsets. Streamers who are known for their personalities instead of their game skills likely provide performances akin to comedians or variety entertainment. In addition to regular gaming streams, Twitch also hosts larger gaming events, including major eSports tournaments (e.g., 2017 Capcom Pro Tour) as well as charity gaming events that bring streamers together with the larger gaming community to play various games, often under special conditions, to raise money for charity. For example, Games Done Quick is a “speed running” biannual charity event that draws thousands of gamers to participate and millions of viewers from across the globe, all watching as players try to beat games in the fastest time possible. Games Done Quick has raised over 12 million dollars for numerous charities (e.g., Doctors Without Borders, Prevent Cancer Foundation) in its seven-year history (Games Done Quick, n.d.). The community donates various items to be raffled as incentives for viewer donations, which range from gaming accessories to fan-made gaming items (such as artwork). This mixture of entertaining game play and performances are couched within the social contexts discussed in the social community and publishing zones of the Tuten and Solomen (2013) framework suggesting new online spaces like Twitch will continue to grow due to their social entertainment value. 199

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As a social media platform that affords social entertainment, Twitch may be viewed as a participatory culture centered on opportunities for learning and collaborative problem solving. In gratifying the entertainment needs of viewers, watching live streams, eSports tournaments, and charity events may also gratify important social learning needs through legitimate peripheral participation (LPP). “LPP is the idea that people learn best when they spend time with people who have mastered the skills they wish to learn” (Ondrejka & Lab, 2008, p. 242). In fact, many viewers report the desire to learn as a primary motivation when they first started watching a stream (Hamilton et al., 2014; Sjöblom & Hamari, 2017). Moreover, opportunities for collaborative game play on Twitch, like with virtual gaming environments, provide streamers and viewers with the opportunity to strategize and coordinate with others via heterogeneous learning, which brings together “learners of all ages into a single, shared space where each produces and shares knowledge” (Ondrejka & Lab, 2008, p. 243). Social commerce. Finally, social commerce platforms facilitate social interactions and user contributions that “assist in the acquisition of goods and services” (Liang & Turban, 2011, p. 5). These include, for example, product review sites, deal sites, and online retailers (Tuten, 2013) in which users’ interactions with each other center around a purchasable commodity. Twitch allows for numerous examples of social commerce. As anyone can follow a streamer for free, users have the opportunity to “window shop.” However, if they want to receive special perks (e.g., giveaways, opportunities to play with streamers available only to subscribers, unique emoticons and username icons) that increase their opportunities for social interactions with others within the community (see Sjöblom & Hamari, 2017), they can also pay a fee to subscribe to a streamer’s channel. Additionally, they can support their favorite streamers in the form of donations as well as by supporting their favorite channels by “cheering,” in which a special emote is purchased for use in the chat box. Use of these cheering emotes earns viewers Cheer Chat Badges, which shows support for that particular channel. Often times, subscriptions and donations are announced by streamers eliciting a social interaction with the streamer and other viewers, particularly with donations that allow users to attach a short message to their announcement. These examples all occur in support of users’ favorite streams and communities to ensure their survival and thus, users’ continued access to valued benefits. Many streamers begin broadcasting as a hobby and have traditional jobs to support them. However, given enough support and participation by users on Twitch, nascent streamers can become affiliated with Twitch and earn the opportunity to receive advertising revenue, subscriptions, and donations. According to nowloading.co (O’Shea, 2017), average professional streamers earn between $2000 and $5000 a month. 200

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Some of the top earners can make over $200,000 on subscribers alone, not taking into account ad revenue or sponsorships (O’Shea, 2017). Only after streamers receive enough attention and participation from users can they become “full-time” streamers, meaning their main source of income comes from broadcasting on Twitch and can thereby spend more time tending to their communities. Active participants in these examples of social commerce likely learn that civic engagement is required in order to receive and increase communal benefits. For example, Twitch users can observe and participate in grassroots community building that requires active participation and monetary support to cultivate a community they value and ultimately reap benefits they have helped sow. Twitch as a melded platform. Combining across the four zones, it is clear that the features and functional capabilities of Twitch hold enormous civic potential by providing users with the resources, skills, competencies, and opportunities needed for active engagement in public life. As Benkler (2006) explains, such active participation provides users with “an overall ‘greater capacity to recognize, challenge, and change that which we find oppressive, and to articulate, exchange, and adopt that which we find enabling’” (p. 300). However, the advantages of Twitch as an online space with civic potential come with new considerations for participatory cultures, particularly as they evolve and grow in the new media landscape. The four zones of Tuten and Solomon’s framework (2013) capture the benefits of melded social media platforms but they also illuminate potential disadvantages that may temper Twitch’s civic potential. Indeed, the marketing basis of this framework allows us to examine Twitch users as participants but also customers who can be solicited. The commodity being sold in this case is participation, suggesting a potential conflict with the original conceptualization of participatory cultures as offering free and equal access to participation (Jenkins et al., 2008).

Twitch as a Hybrid Gaming Culture As argued previously, these new and innovative features and capabilities of Twitch have altered the nature of participation and, with it, the social demands placed on community members—streamers must create communities while viewers must sustain communities monetarily (both the streamers directly, and the Twitch system indirectly through their value to advertisers). These increases in social demand, however, are a double-edged sword. On one hand, they provide unprecedented civic potential for viewers and streamers, but at what cost? The current chapter asserts the civic benefits of participatory cultures that were once free and available to everyone must now be bought through a business model previously untenable in the new media landscape. Melded platforms and their numerous and evolving social affordances, however, have opened the 201

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door to commodification by changing the structure of participatory cultures into a hierarchy, reminiscent of traditional top-down media. In the case of Twitch, this has occurred due to features that afford asymmetrical and synchronous participation among streamers and viewers. Asymmetrical and synchronous participation. It can be argued that streamers provide richer contributions to the community than viewers. This is not to say that viewers are shirking their participation responsibilities. Viewers can chat, donate, or even join the streamer in the video game if s/he allows it. However, the structure of live streaming websites imposes asymmetrical participation such that streamers have more tools at their disposal for contributing than those watching the stream. Streamers are the main contributors of content such that the power of production unequally resides with the streamers compared with viewers who, in comparison, are often restricted to text communication only. Thus, the direction of participation favors a flow from one member to many, which represents a divergence from traditional participatory cultures that allow equal contributions among all members. The structure of live streaming websites also imposes synchronous participation. In many examples of participatory cultures, participation follows an asynchronous format. That is, participation is not contingent on all community members being simultaneously present in an online space. For example, in the social network site Facebook, a person can post to a group page and members can decide to participate and contribute to this post at a time most suitable to them. In this sense, participation in many online communities is an additive process in which participants build on previous contributions of members across extended periods of time (e.g., days, months, and even years). However, live streaming has altered the nature of communication between streamers and viewers such that participants are inhabiting the same online space simultaneously, thereby encouraging more dynamic, quicker, and smaller contributions by community members. Participation supply and demand. Asymmetrical and synchronous participation allows the formation of top-down hierarchies that can be easily monetized, and thus, become easy targets for larger media industries. First, the asymmetrical nature of contributions creates a bottlenecking of participants because streamers cannot interact with all participants, particularly in larger communities where streamers have upwards of 20,000 viewers daily (the size of many sports stadiums), such as the one surrounding the streamer “Lirik.” Thus, participation that is specific to interactions between streamers and viewers occurs at a slow pace, if at all. Second, the synchronous nature of Twitch funnels much of the meaningful participation into a short amount of time (e.g., the length of the live stream). This exacerbates the bottlenecking of participants looking to contribute within the constrained time period compared with asynchronous participation 202

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that gives everyone the same opportunity regardless of conflicting schedules or slow internet access. As a result of asymmetrical and synchronous participation, a high demand for participation access occurs given the long line of viewers looking to directly interact with the stream and streamer. Where there is high demand there is an opportunity to capitalize on participants’ eagerness to reach the front of this participation line. Live streaming websites like Twitch are prime examples of an emerging business model in which companies control the supply of participation opportunities and sell access to this supply to community members. Twitch has several monetized mechanisms that allow viewers to increase their chances of directly participating and contributing to the stream and streamer. For instance, those with the most access to participation are users who have paid subscriptions to a streamer’s channel and have the financial means to donate money and cheer bits directly to streamers. Twitch and Amazon have found other ways to monetize access to participation for those without the financial means. For instance, Twitch provides users the opportunity to earn “cheer bits” to donate by watching advertisements and filling out surveys. Also, in an effort to cross-promote their services, Amazon prime included free subscriptions to Twitch.tv that provide special perks, as discussed previously (Totilo, 2016). These monetized mechanisms create a hierarchy of participation that categorizes participants according to their willingness and ability to purchase access.

Hybrid Gaming Cultures and Civic Potential Although hybrid gaming cultures exacerbate the current participation gap (see Jenkins et al., 2008), Twitch still fits original conceptualizations of participatory cultures and provides many of their civic benefits, as discussed previously. Moreover, everyone has the opportunity to enjoy at least a minimum level of access because viewers can watch any stream for free and utilize the free “Follow” button to join a streamer’s community. Participation can also be free when streamers have smaller communities, do not restrict chat participation to paying subscribers, and respond to more community members. Additionally, anyone can start a stream for free and create their own community with their own set of rules and access to participation. Therefore, the argument of the chapter is not that Twitch is excluded from the civic benefits associated with participatory cultures but rather that Twitch is a participatory culture with a traditional mediasphere hierarchy, a hybrid culture in which participation is metered, apportioned, and monetized. However, there are important implications worth considering regarding the quality of civic benefits for those willing and able to enter the participation hierarchy. The original conceptualization of participatory cultures discussed their positive impact on participants’ creative and 203

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artistic expression, suggesting that such cultures are places that foster and encourage people to develop media production skills. Twitch provides many examples of this process including viewers who create memes of streamers, graphics for streamers to use, and even merchandise for streamers to sell. However, the monetization of participation in hybrid cultures may diminish artistic expression and devalue media production skills. It seems that contributions can now be conceived as monetary contributions (e.g., subscriptions and donations), turning the previous creative and artistic value of participatory cultures into monetary value. Compared with traditional participatory cultures, it is possible that fewer participants are attempting to produce and share content while more are relying on providing monetary contributions. As a result, the social connections forged among participants may depend more on their willingness and ability to participate monetarily than the uniqueness and expression of their identity—the currency of traditional participatory cultures. As discussed previously, these potential issues related to hybrid gaming cultures likely occur within larger Twitch communities and become more problematic as the community grows. Regardless, these hybrid gaming cultures are likely to propagate along with their potential benefits and disadvantages. For instance, YouTube Gaming (https://gaming.youtube. com/) premiered in 2015 and has been steadily growing as a competitor to Twitch in popularity and financial success (Gaudiosi, 2016; Nutt, 2016). Moreover, a possibly growing trend among game developers is to introduce microtransactions into game play. In these “Pay to Win” models, players can buy advantages over other players in the form of unavailable items and characters; thereby introducing another participation hierarchy that favors those who can afford it. Therefore, participation hierarchies may be becoming more prevalent in the games themselves, possibly spurred on by the success of other hybrid gaming cultures.

Conclusion In classifying Twitch as a melded social media platform that blends aspects of Tuten and Solomon’s (2013) four zones of social media (i.e., social community, social publishing, social entertainment, social commerce), the present chapter highlights how its integration of online games with social networking and video sharing has further amplified the already well-suited conditions for video games to promote civic engagement. However, it also brings to light the possibility that the innovative features and functional capabilities of Twitch have altered the nature of participation in such a way that has placed greater social demand, and with it greater economic demand, on community members. More research is needed to understand how civic benefits are both fostered and impeded in such hybrid gaming cultures, especially as platforms such as Twitch continue to expand in 204

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scope. For instance, non-gaming channels such as the Creative (e.g., live streams of artists creating works) and IRL (In Real Life; i.e., live streams of people doing everyday non-video game activities) categories of Twitch may present other unique avenues of viewer participation and participation hierarchies separate from gaming-related channels. The present chapter also highlights the lack of attention given to media industries attempting to reestablish control and influence over media production. Participatory cultures have evolved since their inception and, arguably, have increasingly become targeted by media industries seeking to monetize such mediated spaces. As new technologies change the nature of participation (i.e., asymmetrical and synchronous participation) and as participatory cultures grow in size, it is argued here that such cultures are gradually becoming vulnerable to media industries who have begun adapting to “produsers’” demands. Twitch is one example of a participatory culture that provides civic benefits but also incorporates a top-down hierarchy resembling traditional mediaspheres that constrains access to participation. As a result, future scholarship should consider the potential shifts in broader civic outcomes, the positive and the negative, as hybrid gaming cultures become more common.

Ludography Dark Souls. (2011). Tokyo, Japan: Bandai Namco Entertainment. Player’s Unknown Battlegrounds. (2017). Seongnam, South Korea: Bluehole Studio. Pokemon Red. (1997). Kyoto, Japan: Nintendo. Second Life. (2003–present). San Francisco, CA: Linden Lab. World of Warcraft. (2004–present). Irvine, CA: Blizzard Entertainment.

References Anderson, B. R. (1983). Imagined communities: Reflections on the origin and spread of nationalism. New York, NY: Verso. Benkler, Y. (2006). The wealth of networks: How social production transforms markets and freedom. New Haven, CT: Yale University Press. Bennett, W. L. (2008). Changing citizenship in the digital age. In W. L. Bennett (Ed.), Civic life online: Learning how digital media can engage youth (pp. 1–24). Cambridge, MA: The MIT Press. Bennett, W. L., Freelon, D., & Wells, C. (2010). Changing citizen identity and the rise of a participatory media culture. In L. R. Sherrod, J. Torney-Purta, & C. A. Flanagin (Eds.), Handbook of research on civic engagement in youth (pp. 393–424). Hoboken, NJ: John Wiley and Sons. Brightman, J. (2015, July 9). Twitch outranks YouTube in $3.8 billion gaming video market – Superdata. GamesIndustry.biz. Retrieved from www.gamesindustry.biz/articles/2015-07-09-twitch-outranks-youtube-in-usd3-8bn-gamingvideo-market-superdata

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Bruns, A. (2008). Blogs, wikipedia, second life, and beyond: From production to produsage. Digital formations (p. 45). New York, NY: Peter Lang. Burroughs, B., & Rama, P. (2015). The eSports Trojan Horse: Twitch and streaming futures. Journal of Virtual Worlds Research, 8(2). doi.org/10.4101/jvwr. v8i2.7176 Carpentier, N., Dalgren, P., & Pasquali, F. (2013). Waves of media democratization: A brief history of contemporary participatory practices in the media sphere. Convergence: The International Journal of Research into New Media Technologies, 19, 287–294. Dalton, R. (2009). The good citizen: How a younger generation is reshaping American politics (Rev. ed.). Washington, DC: CQ Press. Eadicicco, L. (2014, August 25). 10 facts about Twitch, the company that Amazon is buying, that will blow your mind. Business Insider. Retrieved from www. businessinsider.com/statistics-about-twitch-2014-8 Games Done Quick. (n.d.). What is Games Done Quick? Retrieved from https:// gamesdonequick.com/ Gaudiosi, J. (2016). Twitch ups its game to compete with YouTube gaming. Retrieved from http://fortune.com/2016/02/26/twitch-ups-its-game-to-compete-​with-​ youtube-​gaming/ Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 5, 1360–1380. Hamilton, W. A., Garreston, O., & Kerne, A. (2014) Streaming on Twitch: Fostering participatory communities of play within live mixed media. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 1315–1324). New York: ACM. doi: 10.1145/2556288.2557048. Retrieved from https://dl.acm. org/citation.cfm?id=2557048 Jenkins, H., Clinton, K., Purushotma, R., Robison, A. J., & Wiegel, M. (2008). Confronting challenges of participatory culture: Media education for the 21st century. The John D. and Catherine T. MacArthur Foundation reports on digital media and learning. Cambridge, MA: The MIT Press. Liang, T., & Turban, E. (2011). Introduction to the special issue on social commerce: A research framework for social commerce. International Journal of Electronic Commerce, 16(5), 5–13. MacMillan, D., & Bensinger, G. (2014, August 26). Amazon’s play: Videogames as sport. Wall Street Journal, B1. Mäkinen, M. (2006). Digital empowerment as a process for enhancing citizens’ participation. E-Learning, 3, 381–395. Nutt, C. (2016). The stats on how YouTube affects game success. Retrieved from www.gamasutra.com/view/news/266684/The_stats_on_how_YouTube_affects_​ game_success.php Ondrejka, C. (2008). Education unleashed: Participatory culture, education, and innovation in Second Life. In K. Salen (Ed.), The ecology of games: Connecting youth, games, and learning. The John D. and Catherine T. MacArthur Foundation Series on Digital Media and Learning (pp. 229–252). Cambridge, MA: The MIT Press, 2008. O’Shea, M. (2017). How much money do video game streamers really make? A look at Twitch’s top earners. Retrieved from https://nowloading.co/p/howmuch-money-video-game-streamers-make/4266946

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Östman, J. (2012). Information, expression, participation: How involvement in user-generated content relates to democratic engagement among young people. New Media & Society, 14, 1004–1021. Postigo, H. (2014). The socio-technical architecture of digital labor: Converting play into YouTube money. New Media & Society, 18, 332–349. Putnam, R. (2000). Bowling alone: The collapse and revival of American community. New York, NY: Simon & Schuster. Sjöblom, M., & Hamari, J. (2017). Why do people watch others play video games? An empirical study on the motivations of Twitch users. Computers in Human Behavior, 75, 985–996. Steinkuehler, C. A., & Williams, D. (2006). Where everybody knows your (screen) name: Online games as ‘third places’. Journal of Computer-Mediated Communication, 11, 885–909. Totilo, S. (2016, September 30). Twitch starts phasing out original subscription plan in favor of Amazon-linked “Twitch Prime.” Kotaku. Retrieved from https://kotaku.com/twitch-starts-phasing-out-original-subscription-plan-in-​ 1787302282 Tuten, T. (2013, June). The zones framework: A different way of understanding the landscape of social media. Global CMO, 1(4), 41–43. Tuten, T. L., & Solomon, M. R. (2013). Social media marketing. Upper Saddle River, NJ: Pearson. Twitch. (2016). The 2016 retrospective. Retrieved from www.twitch.tv/year/2016

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13 DEVELOPMENT OF THE VIDEO G A M E D E M A N D S CA L E Nicholas David Bowman, Joseph Wasserman, and Jaime Banks

The middle 20th century saw the development and growth of an entertainment technology that allows users to actively interface with on-screen content. Video games, developed originally to demonstrate creative and unique properties of early computing systems (Graetz, 1981), quickly grew to a cultural and economic force, which was not unnoticed by media psychologists and other scholars curious about the motivations and consequences of their use. Video games are intriguing due to their interactivity: they are “a series of interesting decisions” (Meier, 2012) cast as lean-forward entertainment media (Jansz, 2005) that allow users to alter the form and content of on-screen portrayals (Steuer, 1992). Notably, while this interactivity is assumed critical to understanding gaming uses and effects, current understandings tend to be non-specific (see Weber, Behr, & DeMartino, 2014), and assume by proxy that increased interactivity necessarily leads to more positive entertainment outcomes. This is not always the case, however. For instance, media flow states (Sherry, 2004) are disrupted when games over-tax a user’s attentional resources (Lang, 2000; Bowman & Tamborini, 2012, 2015), and Bucy (2004) describes the expected curvilinear relationship between a desire for increased interactivity and eventual negative consequences (such as irritation and information overload). That is, interactivity can be enjoyable, but (as outlined throughout this volume) it is also demanding—a requirement is placed on the user to actively and constantly respond to on-screen displays in order to continue the digital experience (e.g., demanding of the user’s attentional, emotional, or other resources).1 Importantly, however, these various demands tend to be examined broadly (rather than as part of a comprehensive suite of tensioned demands, as we argue is appropriate), and there currently exists no comprehensive 208

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metric to capture the experienced demands of video game play. To address this gap, this chapter reports a study that (a) organizes the extant literature on interactivity and demand around four central themes—cognitive, emotional, physical, and social demands—in order to (b) explicate each and (c) propose a new, validated self-report metric to assess how they are experienced: the Video Game Demand Scale (VGDS). Using exploratory factor analysis (EFA) with oblique geomin rotation, a five-factor model reflecting cognitive, emotional, physical (controller and exertional), and social demand was retained. The predictive, convergent, and concurrent validity of this set of five VGDS factors were evaluated with exploratory structural equation modeling (ESEM), which incorporates EFA into a general latent variable modeling framework (Marsh, Morin, Parker, & Kaur, 2014). The implications of VGDS for video game scholarship are discussed.

Interactivity and Demand Among myriad definitions that we can offer for digital media interactivity, perhaps the simplest is that of Steuer (1992) characterizing the end user’s ability to alter the form and content of what is shown on screen. Such an approach tends to consider interactivity as an attribute of the medium—an objective affordance of a system. Other scholars (Sundar, 2004; Sundar, Jia, Waddell, & Huang, 2015) have argued that such an approach is superior to user-centered models in that it focuses our attention on objective properties of a given system. In particular, Sundar (2004) argues that: If we were to theorize about the psychological effects of interactivity using such a technologically independent conception of interactivity, then we would be building knowledge about people (i.e., theories of psychology) rather than about media. (p. 386) Sundar’s point is a critical one, as in most studies of human-computer systems (including studies of video games), the technological affordances are usually objective and constant properties of the system while the human users vary on several dimensions (such as skill and motivations for engagement). However, such an approach also assumes that all users necessarily experience these interactive affordances in the same way, which seems unlikely given the natural variance in user’s abilities to handle various elements of interactivity—a central point raised by Bucy (2004). We can borrow from discussions of telepresence in human-computer systems to guide our assumptions here, and perhaps draw attention to considering interactivity as a two-way dialogue between a user and the 209

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machine (see Haraway, 1991). Take, for instance, the phenomenon of experiencing presence (the illusion of non-mediation during a media experience; Lombard & Ditton, 1997). The affordances of particular technologies are likely to encourage a sense of presence in their users (Westerman & Skalski, 2010), for example, wearing head-mounted displays and using naturally mapped controllers may intensify the sense of being inside a digital space (Bowman, Leibold, & Pietschmann, 2017). On the surface, it makes sense that technological affordances are the chief driver of telepresence, yet evidence shows that users’ perceptions of the technologies, independent of their design, can have a major impact on how they are experienced—both Bowman et al. (2017) and Rogers, Bowman, & Oliver (2015) found naturally mapped controllers to be perceived as less natural than their abstract counterparts (i.e., gamepads). In short, both the interface and the user discretely contribute to the nature and experience of unfolding interactivity. Thus, and perhaps as best argued by Stromer-Galley (2004), we might suggest that an interactivity-​ as-process rather than interactivity-as-product approach is useful for understanding the phenomenology of—and demands associated with— gaming. Such a perspective somewhat privileges the player’s perceptions of demand over the technological affordances themselves and thus, their perceptions of other aspects of the gaming experience. As outlined in Chapter 1 of this volume, perceptions of demand may be most elegantly considered according to four principle requirements of game play: cognitive, emotional, physical, and social. Cognitive demand. Cognitive demand is conceptualized as the consumption of attentional and cognitive resources (Bowman, 2015; see Chapter 1, this volume)—in simplest terms, cognitive demand refers to how much (or how little) the video game made one think. These cognitive resources are limited (Lang, 2000) and, per the cognitive miser approach (Fiske & Taylor, 1991), conserved whenever possible. Notably, while cognitive resources are held in reserve, a critical component of video game play is that it implicitly requires the player to learn because games usually present players with a novel experience, which much be rationalized in order to be played effectively (Gee, 2003). That is, players are required to make sense of the digital environment in order to properly engage it. Green (Chapter 2, this volume) overviews extensive literature on the role of video games broadly, and action video games specifically, in strengthening cognitive skills. While understanding a game is therefore a cognitively intensive process, players also tend to resort to resource-conserving heuristics whenever possible (Martinez-Garza & Clark, 2017) in order to avoid overtaxing those resources (to avoid subsequent frustration; Bowman & Tamborini, 2012). More generally, it has been suggested that individuals seek a balance between cognitive ability and cognitive demand as an optimal media flow state (Sherry, 2004), and this demand/ability 210

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balance during video game play is experienced as intrinsically rewarding and motivating (Keller, Ringelhan, & Blomann, 2011). If we assume that video games have some requirement to engage the player’s cognitive resources as they make sense of the experience, we can define cognitive demand as the extent to which a video game requires the player to implicitly or explicitly rationalize the game. Emotional demand. Emotional demand is the instigation of an affective response in a player (Bowman, 2015; see Chapter 1, this volume)—at the most basic level, emotional demand refers to how much (or how little) the video game made one feel. Regardless of valence, more emotionally arousing experiences can be understood as more emotionally demanding ones. McGonigal (2011) discusses that during video game play, “we are intensely engaged, and this puts us in precisely the right frame of mind and physical condition to generate all kinds of positive emotions” (p. 28)— sentiments echoed by claims that pleasures of gaming are often associated with emotions such as exhilaration and joy (Grodal, 2000). At the other end of this spectrum are studies on violent video games, which often examine aggression-related emotions such as anger or hostility (Anderson et al., 2010). Yet, more recent research has begun to examine a broader set of emotions, such as fear (Lynch & Martins, 2015) and moral reactions related to guilt emotions (Grizzard, Tamborini, Lewis, Wang, & Prabhu, 2014; also see Grizzard and Francemone, Chapter 4, this volume)—as well as a broader set of theories of emotion (Hemenover & Bowman, 2018). Oliver et al. (2016) found that meaningful video game experiences lead to positive affect (amused, happy, humored, positive) just as much as enjoyable video game play experiences, but lead to more mixed affect (touched, moved, compassionate, inspired) and negative affect (angry, anxious, tense, negative) than more hedonic-based enjoyable video game play experiences. In short, emotional demand refers to the extent to which a video game causes the user to have an affective response to the game. Physical demand. Physical demand is related to physical input into a game via controller (Bowman, 2015; see Chapter 1, this volume), and in its simplest form, it refers to how much (or how little) the video game made one do something physically. Often measured in other contexts as whole-body exertion (DiDomenico & Nussbaum, 2008)—which is critically important to more recent advances in the use of whole-body gaming inputs such a Microsoft’s Kinect and Sony’s PlayStation Move systems, physical demand in video games can also involve fine-motor movements more aligned with handheld and/or button-based gaming inputs (controllers and keyboards, for example). As players physically manipulate controllers, players develop mental models that associate their movements with on-screen actions (Rogers et al., 2015), which might lessen their perceived physical demand. Moreover, more recent “naturally mapped” 211

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controllers—those that most closely mimic the simulated physical equivalent of the game actions (Skalski, Tamborini, Shelton, Buncher, & Lindmark, 2011)—should reduce physical demand by allowing players to apply their pre-existing mental models to gameplay (e.g., a held mental model of bowling with a bowling ball would easily map to use of a naturally mapped bowling video game controller). While some studies have shown naturally mapped controllers that mimic their real-world counterparts are perceived as natural and thereby increase perceptions of realism, immersion, and in-game success (Shafer, Carbonara, & Popova, 2014; McGloin, Farrar, Krcmar, Park, & Fishlock, 2016), others find that these same controllers are cumbersome and hinder performance, reducing feelings of competence (Tamborini, Bowman, Eden, Grizzard, & Organ, 2010) and inducing frustration (Rogers et al., 2015). Bowman et al. (2017) found that experienced gamers preferred traditional controllers over naturally mapped ones, finding the former to be less cumbersome and physically demanding and finding the latter to be imprecise and paradoxically more complicated. An explication of physical demand is the extent to which a video game requires the player to exert discrete or holistic physical effort(s) when playing the game. Social demand. Social demand is related to social interactions and relationships with others (Bowman, 2015; Chapter 1, this volume), and might be understood in its most basic form as how much (or how little) the video game made one react to and/or aware of other avatars, characters, or people. The more social interaction players engage in during gameplay or the more social others of whom they are aware, the greater their social demand, and this demand may emerge explicitly or implicitly. Regarding explicit social demand, players may be actively aware of and respond to other players or characters. Games provide a site for social interaction and relationship formation (Sherry, Lucas, Greenberg, & Lachlan, 2006; Yee, 2006; Cole & Griffiths, 2007), and online games for those individuals who might find face-to-face social interaction difficult or intimidating (Kowert, Domahidi, & Quandt, 2014). Other players also provide both audience and ambient social backdrop to gameplay, even when not directly engaged (Ducheneaut, Yee, Nickell, & Moore, 2006). Regarding implicit social demand, players may be influenced by the presence of other players or characters without actively devoting attentional resources to them. Building on extant work on social facilitation effects, Bowman, Weber, Tamborini, and Sherry (2013) found that the presence of others while playing can significantly boost arousal, which can impact both performance and enjoyment by triggering natural reactions to the mere presence of other social actors. Research finds that media users often engage computers and displayed content as social actors (Reeves & Nass, 1996), which might make more salient certain social norms (such as politeness), suggesting that social demand may be 212

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experienced in video games, even in the physical absence of other humans (Banks & Carr, 2018). An explication of social demand is the extent to which a video game triggers an implicit or explicit response in the player to the presence of other social actors.

Research Goals In the absence of a comprehensive metric to capture these phenomena, we sought to develop and offer initial validations for measuring demand in video games: the Video Game Demand Scale (VGDS). VGDS is designed to assess four sub-dimensions of demand (hypothesized to be cognitive, emotional, physical, and social) as a self-report survey metric for use either immediately following or in recollection of a focal video game experience (the latter done for the current study, in order to ensure a variety of play experiences via an online survey). In developing this scale, we (a) explored the latent factor structure of the proposed items using an oblique geomin rotation method and (b) examined the newly created scale’s predictive validity (with measures of effort exerted), concurrent validity (with respect to an established measure of task demand), and convergent validity (with measures of entertainment, ratings of video game experiences, and need satisfaction) using individual ESEM for each of the three validity types.

Method Participants were solicited via social media platforms (Facebook, Reddit, and Twitter) and email (to student accounts at the host university, as well as past research participants in other video game studies who had agreed to receive future research invitations via email) to participate in a survey on “how players engage video games on cognitive, emotional, physical, and social dimensions.” The 80 survey questions related to VGDS were embedded into a larger bank of open- and closed-ended items (used to conduct predictive, concurrent, and convergent validity tests); only closedended data are used for the validation analyses presented here. Before addressing the closed-ended question bank containing the proposed VGDS items, participants were first asked to specify and describe their most recent video gaming session (in order to ground responses in an ostensibly salient experience), and the title of the game played was automatically inserted into the directions for all scales for the remainder of the survey—this was done to focus the respondents’ attention on that one experience playing that one game. Participants were entered into a drawing for one of three $100 gift cards, with odds of winning fixed at no less than 1:500. The survey could be completed in 20 to 30 minutes (based on pilot-testing). 213

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Several methodology and analysis files, including a full copy of the survey given to participants, data analysis file (which includes all quantitative data used in this scale validation), Mplus syntax, and other files have been made available using a public Open Science Foundation project file, which can be assessed at https://osf.io/x5jch/.

Participants Of an initial survey response of 1,068, a total of N = 660 participants gave complete answers to the 80 VGDS pool items and thus were retained for analysis. Among these, n = 640 voluntarily answered a series of self-report demographic measures. The sample had an average age of M = 23.07 (SD = 5.98, range 18 to 62) with 70% of the sample (n = 464) reporting as male and 3.5% of the sample (n = 23) reporting a non-binary gender. Considering race, 84% of the sample (n = 538) self-identified as White or Caucasian, with the next-most represented ethnicity being Asian (2%). About 46% of the sample was currently enrolled in college or technical school (n = 304) with 23% (n = 152) as college graduates. The most popular genres of video game reported were shooters (n = 149, 22.6%), action RPGs (n = 94, 14.2%), sports (n = 80, 12.1%), and turn-based RPGs (n = 67, 10.2%), and 26 different genres were listed overall. Over 97% of the sample (n = 642) reported playing with a standard gaming controller or keyboard and mouse, and respondent’s most recent gaming session (which they were reporting on) was an average of M = 1.92 hours long (SD = 1.50). Just over half of the sample (n = 352, or 53% of respondents) indicated that they had played this game alone, with the other respondents indicating a variety of co-playing experiences (both online and offline); as an open-ended question, not all participants specified or elaborated on what they meant by “others” in their replies.

Measures VGDS. The primary focus of this study was to develop a multi-dimensional survey metric for assessing video game demand in terms of cognitive, emotional, physical, and social dimensions. To do this, we developed 80 total items—20 for each different type of demand—by consulting the literature reviewed earlier in this manuscript, consulting existing open-ended data from past data collections to cull players’ natural language about demand, and through deliberation within the research team. This 80-item bank was randomized and presented to participants, with items written in Likert-style with seven response options from “Strongly Disagree” to “Strongly Agree” (see OSF project space for survey metric). Table 13.1 of the “Results” section contains the finalized scale.

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Validation measures. We conducted several construct and predictive validity tests by analyzing the associations between the proposed VGDS sub-dimensions and other established measures of both demand (construct validity) and gaming outcomes (predictive validity). For predictive validity tests, we adapted Paas’ (1992) single item mental effort measure to assess—on a scale of 1 “very, very low” to 9 “very, very high”—perceptions of cognitive (M = 4.84, SD = 2.04), emotional (M = 4.86, SD = 2.84), physical (M = 3.64, SD = 1.95), and social effort (M = 5.29, SD = 2.26) exerted during play. Each effort item was expected to predict most substantially its respective VGDS dimension (e.g., cognitive demand was expected to predict cognitive effort). We note here that as a cross-sectional study design, causality via time-ordering is not observable. However, the logic here is that the demands of a system should drive the amount of effort that we invest to manage those demands.2 To evaluate VGDS’s convergent validity, we used a version of the NASA Task Load Index (NASA-TLX; Hart & Staveland, 1988) adapted for video game use (Bowman & Tamborini, 2012). Commonly used to measure subjective perceptions of workload, NASA-TLX consists of six items related to mental demand, physical demand, perceived success, and temporal considerations (i.e., feeling hurried or rushed). As in Bowman & Tamborini (2012), removal of perceived success resulted in a five-item solution of global demand, M = 4.36, SD = 1.46, although with a lower-​ than-expected α = 0.669 (α = 0.811 in Bowman & Tamborini, 2012). We expected VGDS cognitive and physical demand dimensions to be positively related to the overall NASA-TLX index, as these dimensions are most similar to the task load construct. For concurrent validity tests, we used an adapted version of the Affect Grid (Bowman & Tamborini, 2012) in which participants could mouseclick an on-screen grid with “affect” as the x-axis (from unpleasant to pleasant feelings, M = 338.19, SD = 62.67, and higher scores representing more pleasant feelings) and “arousal” as the y-axis (from low to high arousal, with lower scores representing less arousal, M = 146.94, SD = 77.21); scores for “affect” were able to range from 92 to 464, and scores for “arousal” were able to range from 35 to 376 (measuring pixels from the top-left of the image, recorded by the survey system using a specialized cursor). We expected emotional demand to be associated with increased affect (replicating Oliver et al., 2016) and physical demand to induce frustration as negative affect (replicating Bowman & Tamborini, 2012); that same study found nonspecific effects on increased arousal from increasing game difficulty. A three-item enjoyment measure (M = 6.40, SD = 0.827, α = 0.914), six-item appreciation measure (M = 3.98, SD = 1.46, α = 0.903), and single-item ratings of the game’s story/narrative (M = 54.66, SD = 35.20),

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gameplay mechanics (M = 84.20, SD = 17.17), controller scheme (M = 78.82, SD = 21.63), and overall game rating (M = 86.72, SD = 12.63; all on 100-point scales) were used from Oliver et al. (2016). We expected cognitive and physical demands to be associated with gameplay assessments, while emotional demands to be associated with story/narrative assessments, as in Oliver et al. (2016). Overall game assessments were explored, without a strong a priori expectation. Notably, given that over 95% of our sample reported enjoyment scores above 5.00 (the median score was 6.67 and the modal score was 7.00, n = 298 or 45% of our sample), participants in our study seem to have heavily biased themselves to report on recollections of highly enjoyable experiences. Finally, a player need satisfaction measure (Ryan, Rigby, & Przybylski, 2006) was used that included three items each for assessing felt autonomy (M = 5.39, SD = 1.27, α = 0.759), competence (M = 5.69, SD = 1.02, α = 0.746), and relatedness (M = 3.70, SD = 1.71, α = 0.883). Based on Tamborini et al. (2010), we expected competence to be positively associated with cognitive demands (gamers focused on in-game challenges), physical demands (gamers developing their play skills), and emotional demands (exhilaration from successful in-game performance; Bowman et al., 2013). Because Ravaja et al. (2006) suggest that feelings of relatedness are associated with social presence, we expected relatedness to be associated with social demands (for gamers interacting with other gamers).

Results VDGS Factor Analysis The primary purpose of this study was to develop the VGDS; that is, (a) exploring its factor structure to test the plausibility of its predicted four-factor structure and (b) reducing the initial 80-item pool to the best-performing items that both load strongly on a single primary factor and weakly on all other factors for the derived factor structure. Rather than use a confirmatory factor analysis to force a presumed four-factor structure3 and to identify poor-performing items post hoc with modification indices, the initial pool was instead subjected to an exploratory factor analysis (EFA) using maximum likelihood (ML) estimation with oblique geomin rotation. This approach allowed for the possibility that this item pool reflected more constructs than the four expected dimensions of demand. Because nothing was presumed a priori about relationships among demand dimensions, an oblique rotation method was used to allow factors to correlate. More specifically, geomin rotation was used because simulation studies suggest that geomin out-performs other alternative oblique rotation strategies in accurately estimating cross-loadings and factor correlations, especially when little is known in advance about the factor structure (Asparouhov & Muthén, 2009; Aksoy, 2017). 216

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Accurately estimating cross-loadings is especially important given this study’s goal of eliminating items with substantial cross-loadings. Additionally, ML estimation afforded the inspection of several indices for choosing the appropriate number of factors to extract: parallel analysis identifying the number of factors with eigenvalues greater than the 95th percentile of random-data eigenvalues, the smallest Bayesian information criterion (BIC), the fewest-factor solution with root mean square error of approximation (RMSEA) ≤ 0.05, and the fewest-factor solution with the lower-bound 90% confidence interval of RMSEA ≤ 0.05 (Cota, Longman, Holden, Fekken, & Xinaris, 1993; Preacher, Zhang, Kim, & Mels, 2013; Eijk & Rose, 2015). Additionally, factor solutions were examined for interpretability, rejecting solutions including factors with exclusively low (< 0.5) standardized rotated loadings. Neither Akaike information criterion (AIC) nor sequential chi-square model comparisons were used to evaluate number of factors to extract, as in this study they consistently appeared to over-extract numerous uninterpretable factors with exclusively weak primary loadings (see Preacher et al., 2013). These indices suggested the extraction of between five and seven factors at each step of the iterative analysis. Therefore, the ostensible four-factor structure was rejected. To reduce the item pool to only items that reflected their primary dimension of demand and not others (i.e., those best-performing items with high discriminant validity), poorly performing items were iteratively eliminated. Because indices suggested extracting between five and seven factors, items were eliminated by examining standardized rotated factor loadings across all of these factor solutions. Increasingly strict criteria for primary loadings and cross-loadings were applied to these items to eliminate weakly loading and cross-loading items, beginning with eliminating items with no loadings ≥ 0.32 primary loadings across all solutions and increasing ultimately to eliminating items without ≥ 0.6 primary loadings across two or more solutions or with ≥ 0.15 cross-loadings. We used this strict cross-loading cut-off rather than more common and more liberal cross-loading cut-offs (i.e., ≥ 0.3 or ≥ 0.4), because in this study, even cross-loadings as small as 0.15 were significant at p < 0.01. In the final iteration, one item with < 0.6 primary loading was retained so that every factor would contain four or more items. Four items per factor reduces potential issues with model estimation, including empirical under-identification (Kline, 2016). The final seven-factor solution was obtained after dropping 47 items, the final six-factor solution after dropping 50, and the final five-factor solution after dropping 54. Notably for all solutions, items had their strongest primary factor loadings with the demand dimension they were initially developed to represent. To select between the final five-factor, six-factor, and seven-factor solutions, their rotated loading structures were compared for interpretability. The seven-factor structure was rejected 217

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for over-factoring emotional demand into two dimensions that reflected positive- and negative-item wording rather than conceptual differences, χ2(318, n = 660) = 463.411, p < 0.0001, RMSEA = 0.026 (90% CI: 0.021, 0.031), CFI = 0.987, TLI = 0.979, SRMR = 0.014, BIC = 75788.884. The six-factor structure was rejected for over-factoring physical demand into three dimensions reflecting controller demand, amount of physical movement, and physical tiredness, the latter two of which were deemed too conceptually similar to merit this level of complexity, χ2(270, n = 660) = 390.905, p < 0.0001, RMSEA = 0.026 (90% CI: 0.020, 0.032), CFI = 0.989, TLI = 0.981, SRMR = 0.014, BIC = 68630.149. Therefore, we retained the most parsimonious five-factor solution, in which cognitive, emotional, and social demand factored in line with reviewed literature, and physical demand was factored into only two dimensions reflecting controller demand and physical exertion, respectively. See Table 13.1 for the retained five-factor EFA solution, which was obtained after 11 iterations of the aforementioned procedure, at which point BIC, RMSEA, RMSEA 90% CI, and parallel analysis all suggested retaining five factors. Although the hypothesis of exact fit was tentatively rejected, most global fit indices suggested acceptable global fit, χ2(205, n = 660) = 303.473, p < 0.0001, RMSEA = 0.027 (90% CI: 0.020, 0.033), CFI = 0.989, TLI = 0.982, SRMR = 0.015, BIC = 59914.294.4 Most VGDS factors shared small-to-moderate significant partial correlations with each other, with the exception of controller demand, which was only significantly correlated with exertional demand, as reported in Table 13.2. Predictive Validity To assess the degree to which VGDS dimensions were predicted by perceived effort, the set of VGDS EFA factors was regressed on all four single-item effort assessments using maximum likelihood estimation with robust standard errors (MLR). Although predictions were complicated by the emergence of two physical demand factors, as predicted, each dimension of VGDS was most substantially predicted by its respective effort item (see Table 13.3), and the overall model demonstrated acceptable fit, χ2(289, n = 660) = 514.578, p < 0.001, RMSEA = 0.034 (90% CI: 0.030, 0.039), CFI = 0.976, TLI = 0.964, SRMR = 0.020. The lone exception was controller demand, which was unrelated to any effort dimension (we might have expected an association with physical effort, although the high prevalence of traditional controllers in this data may have suppressed any such association). Surprisingly, emotional effort and exertional demand shared a slight positive association, which might be indicative of an arousal transfer effect.

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Table 13.1  Final VGDS sub-dimensions and standardized rotated factor loadings Factor Item text description 1. Cognitive demand (M = 4.10, SD = 1.43, α = 0.90) The game was cognitively demanding. I had to think very hard when playing the game. The game required a lot of mental gymnastics. This game doesn’t require a lot of mental effort. (R) The game made me draw on all of my mental resources. The mental challenges in this game had an impact on   how I played. The game stimulated my brain. 2. Emotional demand (M = 3.38, SD = 1.60, α = 0.89) The game tugged at my heartstrings. The game gave me the feels. I was moved by the game. I had a strong emotional bond with the game content. I had a lot of unexpected feelings during gameplay. 3. Controller demand (M = 2.43, SD = 1.24, α = 0.87) The controls were very natural to me. (R) The game’s controls were like second nature to me. (R) The game controls were easy to handle for me. (R) The game controls tripped me up.

Factor 1

2

3

4

5

0.807* 0.804* 0.759* 0.766* 0.703* 0.646*

−0.070* −0.049 0.007 −0.018 0.127* 0.138*

−0.060* 0.038 0.022 0.001 0.003 0.034

0.008 0.014 0.063* −0.090* 0.059 0.009

−0.005 −0.020 0.025 −0.046 −0.014 0.080*

0.622*

0.121*

−0.106*

−0.057

0.044

−0.035 −0.015 0.067* 0.022 0.019

0.886* 0.810* 0.766* 0.761* 0.632*

0.045* −0.011 −0.027 −0.110* 0.055

−0.011 −0.017 0.032 −0.024 0.110*

−0.032 −0.011 −0.019 0.026 0.069*

0.897* 0.811* 0.800* 0.686*

−0.053* −0.049* 0.050* 0.136*

0.043* −0.032 −0.013 −0.010

−0.042* −0.109* 0.059* 0.067*

0.004 −0.013 −0.031 0.042

(Continued)

Table 13.1  (Continued) Factor Item text description 4. Exertional demand (M = 2.12, SD = 1.14, α = 0.84) I was physically exhausted after playing. I felt strained after playing. My body felt drained after gameplay. The game was physically demanding. 5. Social demand (M = 3.69, SD = 1.58, α = 0.88) Socializing was an important part of playing this game. While playing, I was aware of others in the game. I was compelled to interact with others in the game. I felt obligated to others, while playing. Being around others in the game had an impact on how I  played. This game was socially demanding.   Eigenvalues

Factor 1

2

3

4

−0.069* 0.063* 0.025 −0.004

−0.013 −0.049 0.055* 0.030

−0.044* 0.083* −0.033 0.041

−0.009 −0.027 −0.046 0.064* 0.035

−0.017 −0.059* 0.099* 0.005 −0.022

0.018 −0.065* −0.040 0.054* −0.031

0.047 6.711

0.043 3.335

0.045 3.089

5 0.895* 0.666* 0.821* 0.583*

−0.031 −0.047 −0.009 0.050 0.032 0.071* 2.465

−0.019 0.082* −0.046* 0.091* 0.799* 0.780* 0.777* 0.715* 0.676* 0.652* 1.799

Note: Standardized rotated geomin loadings. Primary loadings are bolded. The item loading at 0.583 on factor four was retained so that this factor would contain four items. *p < 0.05.

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Table 13.2  Partial correlation matrix of VGDS latent factors Factor

1

2

3

4

1. Cognitive

– – 0.321 < 0.001 0.003 0.945 0.392 < 0.001 0.261 < 0.001

−0.074 0.063 0.235 < 0.001 0.167 < 0.001

0.173 < 0.001 −0.072 0.077

0.235 < 0.001

2. Emotional 3. Controller 4. Exertion 5. Social  

Note: First lines report partial correlation coefficients of latent factors (controlling for other VGDS latent factors), followed by p-values.

Table 13.3  Self-reported effort as a function of VGDS dimensions Outcome

Demand dimension

R2

Cognitive

Emotional

0.817

0.000

−0.026

−0.036

0.043

0.666

< 0.001 Emotional 0.080 effort   0.025 Physical −0.025 effort 0.581 Social 0.035 effort 0.304

0.990 0.627

0.367 0.014

0.314 0.088

0.123 0.146

0.535

< 0.001 −0.039

0.670 0.003

0.028 0.500

< 0.001 0.082

  0.258

0.309 0.116

0.945 0.066

< 0.001 −0.051

0.065 0.772

0.631

< 0.001

0.016

0.118

< 0.001

Mental effort

Controller Exertional

Social

Note: Standardized regression coefficients followed by p-values are reported. Largest coefficients within each row are bolded; the 95% confidence intervals around all coefficients above are +/− 0.11 or more narrow for all estimates.

Convergent Validity To evaluate VDGS’s convergent validity with an existing measure of perceived demand, the set of VGDS EFA factors was regressed on the NASATLX using MLR, yielding marginally acceptable model fit χ2 (335, n = 660) = 855.097, p < 0.001, RMSEA = 0.049 (90% CI: 0.044, 0.053), CFI = 0.943, TLI = 0.920, SRMR = 0.050 that could be improved by 221

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including NASA-TLX items as indicators of VGDS dimensions (which is not surprising given that both instruments are intended to measure similar constructs). As predicted, NASA-TLX was significantly associated with cognitive (β = 0.927, p < 0.001, R2 = 0.86) and exertional (β = 0.557, p < 0.001, R2 = 0.31) demand. To a smaller degree, NASA-TLX was also associated with both emotional (β = 0.318, p < 0.001, R2 = 0.10) and social (β = 0.412, p < 0.001, R2 = 0.17)—but not controller (β = −0.004, p = 0.950, R2 < 0.001)—demand. Concurrent Validity We also wanted to explore concurrent relationships of VGDS dimensions with measures associated with assessments of video games, such as affect and arousal, game ratings (discrete ratings of a game’s story, gameplay mechanics, controller scheme, and overall rating), entertainment outcomes (enjoyment and appreciation), and self-reported need satisfaction from play. As such, these measures were regressed on the set of VGDS EFA factors using MLR, yielding an overall model with acceptable fit χ2 (977, n = 660) = 1874.422, p < 0.001, RMSEA = 0.037 (90% CI: 0.035, 0.040), CFI = 0.946, TLI = 0.932, SRMR = 0.038 (see Table 13.4). As expected, emotional demand had a significant positive association with affect, while both controller and exertional demand were significantly and negatively associated with affect. For arousal, increased cognitive demand corresponded with an increase in overall arousal levels, similar to research on the increased attention that television viewers give arousing (versus calm) content (Koruth, Lang, Potter, & Bailey, 2015). With respect to game ratings, controller demand was negatively associated with control rating, and emotional demand was positively associated with story ratings, in line with Oliver et al. (2016). In terms of overall game ratings, emotional demand was positively associated with game ratings and controller demands were negatively associated, partially replicating findings by Bowman et al. (2017). Likewise, enjoyment scores were increased by cognitive and emotional demands, and decreased by both types of physical demand—controller and exertional. As expected, emotional demand was strongly associated with appreciation, although cognitive demand had a smaller, albeit significant, association with appreciation as well. Overall, these findings are copacetic with Oliver et al. (2016) and Bowman et al. (2017). In terms of need satisfaction, as expected, cognitive demand was a significant and substantial positive predictor of competence. Although controller demand was not part of our original predictions, it is not surprising that it substantially and negatively predicted competence. Also, as predicted, social demand was a substantial positive predictor of relatedness, as was emotional demand. Finally, cognitive and emotional demand were 222

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Table 13.4  Concurrent validity measures as a function of VGDS dimensions. Outcome

Demand dimension

R2

Cognitive Emotional Controller Exertional Social Appreciation Enjoyment Competence Autonomy Relatedness Story rating Gameplay  rating Controls  rating Overall  rating Affect Arousal

0.260 < 0.001 0.179 < 0.001 0.196 < 0.001 0.190 < 0.001 0.001 0.969 −0.068 0.109 0.126

0.686 < 0.001 0.166 < 0.001 0.143 0.001 0.375 < 0.001 0.432 < 0.001 0.605 < 0.001 0.043

−0.129 < 0.001 −0.414 < 0.001 −0.538 < 0.001 −0.224 < 0.001 −0.094 0.003 −0.003 0.927 −0.245

−0.043 0.240 −0.170 0.001 −0.116 0.024 −0.086 −0.098 −0.082 0.035 −0.191 < 0.001 −0.057

0.071 0.030 0.009 0.821 0.065 0.171 0.124 0.007 0.585 < 0.001 −0.061 0.109 0.072

0.005 0.142

0.271 −0.030

< 0.001 −0.351

0.327 −0.029

0.083 0.122

0.168

0.001 0.097

0.432 0.213

< 0.001 −0.356

0.556 −0.030

0.001 0.042

0.214

0.098 −0.015 0.753 0.262 < 0.001

< 0.001 0.176 < 0.001 0.018 0.684

< 0.001 −0.276 < 0.001 −0.044 0.306

0.452 −0.207 < 0.001 0.143 0.001

0.337 −0.050 0.266 0.152 < 0.001

0.695 0.277 0.401 0.313 0.605 0.337 0.095

0.164 0.179

Note: Standardized regression coefficients followed by p-values are reported; coefficients larger than 0.16 bolded to ease interpretation.

substantial positive predictors of autonomy, while controller demand was a substantial negative predictor.

Discussion The present study developed and validated a metric for assessing self-reports of perceived demands upon videogame players during a specific instance of gameplay—specifically, demands associated with being cognitively, emotionally, physically (via controller devices and via physical exertion), and socially engaged with the game. The final VGDS contained 26 items that assessed these demand dimensions and demonstrated expected associations 223

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with theoretically related assessments of gaming experiences. Given the exploratory nature of the measure, it is worthwhile to further interpret the constructs reflected by the retained items. The cognitive demand dimension items are principally about directed and purposeful thinking—perhaps most directly capturing the mental and rational aspects of video game play. While many of our initial discussions centered around creating items to measure meaning-making (e.g., was easy to comprehend and challenges were clear to me from the original item pool, see Appendix A), the retained items are more closely aligned with the extent to which a game engages the player’s mental faculties— similar to the notion of attentional demand (Bowman & Tamborini, 2012, 2015; as well as the extensive research of Green and colleagues overviewed in Chapter 2 of this volume). Cognitive demand items shared significant positive associations with arousal, as well as with autonomy and competence (one might expect these relationships to be more curvilinear, although this was not examined in the current dataset), echoing findings that (a) gameplay mechanics are strongly aligned with enjoyment (Oliver et al., 2016) and (b) a core motivation of gameplay is challenge and competition (Sherry et al., 2006). Games that are highly enjoyable (as were those reported in this study, with 95% of respondents reporting enjoyment scores higher than 5.00 on a seven-point scale) are those that are comparatively high in cognitive demand. Regarding emotional demand, the high factor loadings of items with colloquial references to game-induced affect are notable: the game tugged on heartstrings and gave me the feels. These items coalesced with items reflecting perceived player-centered emotions (being emotionally invested, moved, and having emotional responses) and context-centered emotions (in that emotions ran high and that emotions were unexpected). Emotional demand was strongly associated both with ratings of game story/narrative and ratings of in-game autonomy and relatedness, as well as feelings of appreciation, suggesting that non-hedonic appreciation of video games (Oliver et al., 2016) may be largely due to their emotional demands. Given the renewed focus on emotions in gaming both by industry (in terms of programming emotional experiences, see Schell, 2013) and researchers (in terms of understanding the motivational and appraisal-based emotional systems involved in gaming, see Hemenover & Bowman, 2018), the ability to measure emotional demand promises to advance understandings of the role of emotion in gaming—especially if these data were paired with discrete measure of emotion (see Grizzard & Francemone, Chapter 4, this volume). Two different types of physical demand emerged in our data, with game controls being very natural, second nature, and easy to handle being more associated with the discrete controller device (controller demand) and being physically exhausted and feeling drained after gameplay that seem 224

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to focus more holistically on involving the entire body in physical activity (exertional demand). Unsurprisingly, increases in either type of physical demand were negatively associated with most validation metrics—in particular, decreased enjoyment and increased negative affect—which makes sense given that these physical demand items seem to tap into generally undesired experiences, such as physical exhaustion and poorly mapped control systems. Indeed, difficulty with controller schemes appears to be substantially autonomy-thwarting. Given that 97% of our sample reported on gameplay experience involving traditional handheld controllers, one conclusion is that disrupting a player’s possible expectations regarding physical engagement with the controller will likely lead to a negative experience, as has been found in past literature in which gamers are given naturally mapped rather than traditional controllers, and they paradoxically self-report increased naturalness with the more traditional (i.e., familiar) device (cf. Tamborini et al., 2010; Rogers et al., 2015; Bowman et al., 2017). Finally, the social demand factor similarly comprised items indicating a convergence of items representing both game-induced sociality (it was an important part of the game) and player-initiated sociality (feeling obligated to others), as well as items suggestive of both explicit awareness of and response to others through concrete influences (they had an impact on how I played) and more heuristic assessments of their influence that may suggest more implicit social demand (being aware of others). Importantly, in the present study, the wording of the candidate social demand items requested that participants were asked to consider generalized “others” without articulating what type of others—humans (whether co-present or online, whether actively collaborating or merely observing) or non-humans (whether a controlled player-character, other player-character, or nonplayer character); this was done due to the fact that respondents would be reporting on a very broad set of gaming experiences. That the factor emerged in spite of this reference speaks to the flexibility of the metric; however, because all of these “others” could differently influence a player’s experience of social demand (see Banks & Carr, 2018) and because practical application is likely to focus on one type, validations of the metric should consider variations among relational agents. Implications and Utility of VGDS Notably for the current study, players generally reported on the remembered play experiences with an incredibly high level of fondness (as evidenced by high enjoyment and overall game rating scores). One conclusion we can draw is that the VGDS sub-dimensions seem to have linear relationships with positive game assessments (positive linear associations in the case of emotional, social, and cognitive demand; negative linear 225

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associations in the case of physical demand). Thus, the question as to whether or not we can conceptualize demand as a phenomenologically engaging experience or draining one (positive and negative, respectively) remains somewhat unanswered. It could be the case that emotional, social, and cognitive demands are experienced more as thresholds—that is, players are energized by (and somewhat expect) these aspects of an experience to be engaged “to a point,” similar to the logic of flow theory (Sherry, 2004). Perhaps these three demands are more tied to the player’s active agency—choosing to engage the emotions of an experience, or the social actors in the experience, or purposefully thinking through and rationalizing the game’s environment—and as such, players expect and anticipate these demands. Such a logic would align well with understanding video games as a lean forward medium (Jansz, 2005). Conversely, players in the current sample seem to approach the notion of physical demand as resource depletion under non-negotiable conditions (that is, we cannot change the controller itself in the same way we can change content on-screen) such that increasing physical demand has a net negative experience on gaming. Such arguments might align well with other studies reporting that advances in motion-sensor and other full-body controllers are not necessarily experienced as benefits to the gaming experience, as they both violate mental models of the gaming experience (Rogers et al., 2015; Bowman et al., 2017) while also inducing frustration and hindering performance (Tamborini et al., 2010; Rogers et al., 2015). Limitations and Future Research In order to attempt to get a variety of gaming experiences, participants in our study were asked to recall “their most recent gaming experience” rather than “their most memorable or enjoyable gaming experience” (as used in Oliver et al., 2016). However, respondents reported on overwhelmingly positive gaming experiences, which restricts the range of phenomenological experiences of gamers in our study (i.e., we have very few gamers reporting on negative experiences) and thus restricts our ability to (a) test for associations of our demand measures with enjoyment (due to a restriction of range in that variable) and (b) look for possible thresholds of demand (given that the associations between demand and gaming experiences with highly enjoyable experiences seem more linear). Thus, future research might look to more specifically induce a variety of negative and positive gaming outcomes (perhaps by manipulating relative levels of demand along multiple dimensions) via experimental design, perhaps replicating and extending studies such as Bowman and Tamborini (2012), in which attentional demand—by way of cognitive and device demand— was induced at low, medium, and high levels to predict performance and

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enjoyment outcomes (medium levels of demand resulted in the highest levels of both). In addition to using experimental methods to look for specific content and experience correlates with VGDS—we broadly expect demands to mediate the direct effects of content and effect—gameplay situations, VGDS should be further validated with other measures, such as openended qualitative data from players, observational metrics (both of demand levels and of demand outcomes, such as frustration or boredom), and psychophysiological indicators (such as hemodynamic indicators or other measures of arousal, attention, and emotion). Such data would be critical in establishing and extending the construct validity of the nascent VGDS metric. Given that physical demand items seem to conceptually cluster around understandings of both input devices or full body experiences, more attention should be given to this metric to further refine the concept to pick up on nuances associated with different controller schemes (such as comparisons between a two-button NES controller and an eight-button PlayStation controller; or games that use more or less button inputs). At the same time, the increased availability and popularity of augmented and virtual reality (AR/VR) platforms such as the HTC Vive and PlayStation VR might suggest that a focus on full body immersion and the ensuing exertional demands that such experiences bring with them might become increasingly relevant for game studies. Such a focus seems more conceptually aligned with Sundar’s (2004) focus on interactivity-as-product, while also allowing for a consideration of the users’ variable perceptions of those technological affordances provided by various input methods—be they a held device or the body itself. Physical demand is discussed here as a special case given recent developments in augmented and virtual reality technologies that focus on the player’s embodied experiences in the digital worlds, but other demand dimensions are also critical here. For example, Lin (2017) found that playing a horror survival game wearing a headmounted virtual reality display (the HTC Vive) led to significantly higher fear reactions, some with residual effects recalled as long as 24 hours after playing—such an effect might be explained by the immersive content triggering intense basic emotional reactions in the player (see Lynch & Martins, 2015). AR/VR technologies might also challenge player’s cognitive resources by immersing them in experiences in which details of a game’s environment that could normally be ignored might draw specific attention (that should be otherwise allocated for solving in-game goals), for example, the textures of a pathway that a player is traversing or background conversations between other players (which might or might not be relevant for achieving in-game goals). Such orientation effects could be explained through the moderate discrepancy hypothesis, in which we are

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inclined to attend to and understand stimuli that are familiar enough to have a basic comparison, but unique enough to draw attention (McCall & McGhee, 1977), but might be seen as disruptive from a cognitive demand perspective by overloading the player’s already limited cognitive capacity to process the game environment. Finally, the current analyses do not consider the potential of VGDS dimensions to vary as a function of the relationships between players and their avatars—as has been established by Banks and Bowman (2016). It is plausible that game genre conventions might favor or feature some demand characteristics over others and that players of some genres might see demand characteristics as a benefit to some games, but a disruption in others (one might expect high cognitive and physical demands in an action-based shooter, but not expect high emotional demand such as feelings of guilt for on-screen actions; Grizzard et al., 2014). Likewise, players adopting a more functional orientation toward their avatars in which the on-screen avatar is an asocial game piece might be more likely to engage cognitively with the game, whereas players embracing a more social and affective orientation (in which they see their avatar as an authentic and autonomous social agent) are more likely to experience and expect emotional and social demands (see Banks & Bowman, 2016).

Conclusion This study proposed a 26-item, five-factor Video Game Demand Scale, conceptualized as the implicit or explicit, interactivity-driven game requirements for players to affectively, cognitively, socially, and physically (controller and exertion) engage with game content. The metric’s validity (as evidenced by convergence with other demand/arousal measures), reliability (as evidenced by the factors’ internal consistency), and utility (as evidenced by its theoretically consistent associations with video game experience variables) were supported. Thus, the scale promises to be useful to advance empirical understandings of gaming uses, experiences, and effects.

Acknowledgements Previous versions of this manuscript were peer-reviewed and presented at the 2017 International Communication Association annual meeting in San Diego, CA, USA. We sincerely thank those reviewers, as well as other anonymous reviewers who read previous versions of this manuscript. In addition, audiences at Michigan State University (USA), University of Connecticut (USA), Catholic University of Leuven (Belgium), and Bournemouth University (UK) were instrumental in providing early feedback on this project. 228

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Notes 1 These theses are elaborated on in the preceding chapters of this volume, with a detailed discussion in Bowman (2015) as well as Chapter 1 of this volume. 2 We are grateful to an anonymous reviewer for this suggestion. 3 Although extant literature coalesces around the four expected dimensions, within our research team (as a result of various arguments), we determined that some manifestations of some demand categories could coalesce with some manifestations of others. For instance, feeling empathy for a doomed character could elicit perceptions of both social and emotional demand, ostensibly breaking down the four-factor structure. Likewise, it is plausible that some demand dimensions might have more than one factor related to them. 4 Comparing fit indices among these nested models indicate minimal loss of fit, and in some cases, improvement, when proceeding from the most complex seven-​ factor model to the most parsimonious model. Exact chi-square model comparisons, which are highly sensitive to sample size, are as follows: 7 vs. 6 Δχ2 = 72.506, Δdf = 48, p = 0.012; 6 vs. 5: Δχ2 = 87.432, Δdf = 65, p = 0.033.

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Weber, R., Behr, K-M., & DeMartino, C. (2014). Measuring interactivity in video games. Communication Methods and Measures, 8, 79–115. doi:10.1080/193 12458.2013.873778 Westerman, D., & Skalski, P. D. (2010). Presence and computers: A ghost in the machine? In C. Bracken & P. D. Skalski (Eds.), Immersed in media: Telepresence in everyday life (pp. 63–86). New York, NY: Routledge. Yee, N. (2006). The demographics, motivations, and derived experiences of users of massively multi-user online graphical environments. Presence, 15, 309–329. doi:10.1162/pres.15.3.309

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APPENDIX A S U M M A RY O F AC C E P T E D A B S T R AC T S F RO M T H E R E S E A RC H SY M P O S I U M

Abstracts below are presented in alphabetical order by title, from the program of the BEA 2017 Research Symposium, “Video Game: A Medium that Demands Our Attention.” The conference Call for Papers is archived online at: https://www.beaweb.org/wp/?page_id=3345

Activism in Video Games: A New Voice for Social Change Taylor Anderson-Barkley & Kira Foglesong, High Point University, USA With organizations such as Games for Change assisting video game designers in creating and distributing games for social change, activism in video games is steadily on the rise. These games, including Darfur is Dying, Balance of the Planet, as well as many, if not all, games on the Games for Change website, use their themes and mechanics to ‘campaign’ for social change. Video games offer a new voice for a new audience and given how the millennial generation in particular has a yearning for social change through different and current media, it is easy to see why video game activism is increasing. However, even though video game activism exists, what this paper investigates is whether or not it achieves the promotion of action throughout its viewers. Is video game activism effective in regards to promoting social change? Do these video games merely promote awareness and sympathy rather than incite action? By traversing through the history of video game activism, we can gain comprehension on this up and coming form of activism as well as its usefulness in today’s society. Expanding Synchrony as Holistic Understanding of Video Game Enjoyment Kevin Kryston, Michigan State University, USA Video games can provide intrinsic enjoyment to players. While many factors may influence game enjoyment, at the crux of a game’s ability 234

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to hedonically and meaningfully entertain players is the interactivity of the medium. Players can feel intrinsically rewarded by succeeding in the face of challenges to their sensory and motor skills, cognitive abilities, and even emotional and moral challenges to their self-concept. However, existing theories of media enjoyment such as flow, presence, and transportation have provided us with only fragmented understandings of enjoyment. Despite a limited field of inquiry, synchrony, a pattern of neurological activity occurring when the attention related to a behavior is immense, but is reciprocated by equally profound intrinsic rewards, has effectively predicted video game. Synchronous activity has also been observed while reading and watching narrative media, and most stimuli invoke firings of the behavioral, attentional, and reward regions of the brain. These findings and established, yet limited theories of enjoyment, hint that synchrony holistically represents enjoyment and appreciation of interactive gameplay. Explicating the Electricity of eSports: Motivations for Play and Consumption Kenon Brown, Andrew Billings, Melvin Lewis, and Kimberly Bissell, University of Alabama, USA Computer gaming has rapidly evolved into recognizable sport, with the eSports phenomenon attracting the attention of numerous sports fans, professional sports organizations, corporate sponsors and government entities. With this in mind, this study compares and contrasts the uses and gratifications of eSports among over 1,300 eSports participants, focusing on differences that emerge between the reasons one participates via active game play and the reasons one opts to witness others participating. Results revealed that similar factors – specifically, camaraderie, fanship and companionship – were predictors of participants’ satisfaction, current involvement and future intention to participate in eSports competition, and consumption of eSports-related media. The present study of these determinants of satisfaction tie directly to motivations for current and continued engagement with eSports, further justifying its’ examination. Exploring the Agency and Complexities of Avatar-Mediated Interactions via the PaaP Model Jaime Banks, West Virginia University, USA; Caleb Carr, Coffee Hound, USA Online games are understood to be legitimate spaces of social interaction. Despite the centrality of avatars in these interactions–as players engage the gameworld and its denizens through these digital bodies– in-game communication has been largely examined as player-to-player interactions. Extant research, however, suggests that gamers have variably 235

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social relationships with both their own avatars and other avatars in addition to other players. To synthesize these perspectives, we propose the “PaaP” (Player-avatar-avatar-Player) relational matrix model, in which an in-game interaction emerges through the distinct agency of four actors: two players and their two representative avatars. To test this model, WoW players were asked to engage in a simulated encounter by considering themselves, consider their own avatar, view a video of another avatar, and imagine a player behind that avatar; participants rated all four agents for perceived personhood and propinquity. Results generally support the model, suggesting players indeed assign personhood to all four agents, and that perceived personhood differs significantly among the four. Implications for research into gaming and online interactions more broadly are discussed. Exploring the Capacity of Tension-Filled Narrative-Based Games for Mood Repair Regan Mandryk, Max V. Birk, & Jason Bowey, University of Saskatchewan, Canada Mood management theory suggests that people choose their media to dissipate noxious moods (referred to as mood repair); by engaging our attention, immersing media (such as digital games) does not leave attentional resources free for rumination or worry. Narrative games foster deep immersion, making them great candidates for mood repair; however, it is unclear whether the negative affect produced by in-game tension or dark or sad themes compromise the capacity of narrative-based games for mood repair. In an experiment to investigate this potential dichotomy, we show that the transportability of the player (i.e., how susceptible they are to narrative transportation) increased experienced tension, which translated into increases in both negative and positive affect (which is a proxy for mood repair). Although one may expect that negative and positive affect should not increase in tandem, our work shows that although experiencing tension during a narrative-based game does increase negative affect, it does not compromise – but may actually contribute to – the potential of narrative-based games for mood repair. Gaming Is Awesome! A Theoretical Model on Cognitive Demands and the Elicitation of Awe during Video Game Play Daniel Possler & Christoph Klimmt, Hanover University of Music, Drama, & Media, Germany; Arthur A. Raney, Florida State University, USA Experiences of awe, the emotional response to vast stimuli that do not fit into established mental structures, have been found to be pleasurable and meaningful. Since elicitors of the emotion can frequently be found in video 236

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games, awe might be an important, yet not investigated contributor to game enjoyment and appreciation. However, games place rather high task demands on users, which may interfere with the elicitation of awe. In order to understand the impact of awe on the entertainment experience, the present paper theorizes the elicitation process of the emotion from the perspective of Appraisal Theories, with special consideration given to game-based cognitive demands. Implications for entertainment research are discussed. Investigating How Non-Player Characters Influence Socially-Strategic Moral Decisions Nicholas Matthews, Digipen Institute, USA Top paper, social demand track Perspectives such as character attachment (CA) and player avatar relationships (PAR) explain how the relationships players have with avatars are different from traditional parasocial relationships. Although research exists suggesting that people consider computers as social actors, it is unclear to what extent these player-to-character connections explain interactions with non-player characters (NPCs). Knowing the extent to which players perceive NPCs as valid social actors is important for those who wish to use games to simulate social scientific phenomena. The current study investigated players’ intuitive responses to NPCs using two competing theories of moral psychology: moral foundations theory (MFT) and dynamic coordination theory (DCT). The study observed how well NPCs could elicit socially-strategic side-taking behavior in players (in line with DCT) that interfered with their standard, morally-principled responses (in line with MFT). Results were mixed but suggest that side-taking cues from NPCs can alter players’ moral decisions. It’s About Time! Action Video Games’ Demand of Cognitive Skills During Prolonged Periods of Gaming Kevin Koban, Chemnitz University of Technology, Germany Contrary to their questionable reputation, fast-paced action video games (AVGs) are considered a promising training stimulus to improve various cognitive skills. Although numerous studies have demonstrated beneficial effects even after relatively short periods of training, skepticism has grown recently due to non-significant findings and methodological limitations. The current research proposal adds to this skepticism in a productive manner by focusing on AVGs’ demands for the player. However, while existing research has valued AVGs for their inherent demand for several information processing constructs, the present research proposal reasons for a player-oriented perspective. Based on well-established skill acquisition models, the paper, therefore, argues that players actively adapt 237

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to the requirements of a task and its conditions during prolonged periods of gaming. In defiance of stable demands induced by a game’s unique characteristics, this adaption mechanism results in a shift in players’ experienced demand during multiple gaming sessions, which then determines AVGs’ efficiency for cognitive training. Accordingly, the primary interest of this proposal is to specify how AVGs tap several processing domains (perception, attention, spatial cognition, and higher-order executive skills) over prolonged periods of gaming—both per se and depending on players’ familiarity with the task environment. Conclusively, some methodological considerations are presented regarding the planned study. Measuring Moral Decisions from a Purpose Made Video Game Sarah Hodge, Jacqui Taylor, John McAlaney, Davide Melacca, Christos Gatzidis, & Eike Anderson, Bournemouth University, UK Top paper, behavioral demand track; 2nd place, overall student paper A number of video games involve moral narratives or require the player to make moral decisions and research from psychologists has helped to understand the effects video game content can have on how individuals behave. Recent research has started to examine the role of morality in video games: however, there are many inconsistencies in the findings. Some of these inconsistencies in the findings could be due to using commercial video games for research purposes, which contain biases such as familiarity with the game and favorite characters. By developing a bespoke game designed specifically for the purpose of exploring morality these potential biases can be reduced. Before designing the game, morality in existing video games were critically analyzed using theories from moral psychology. From this a game was created to measure behavioral outcomes through moral decisions made; with the aim to reduce biases. Currently the game is being administered to university students to investigate how moral decisions are made in a purpose made video game. Narrative and Gameplay as Unique Instigators of Immersion-Based Persuasion Brett Sherrick, University of Alabama, USA Top paper, Cognitive Demand track This paper investigates the roles of narrative and gameplay in a persuasive casual health game, through two experimental studies. In Study 2, brand persuasion is also investigated. Results suggest that the game was persuasive, as both attitudes and behavioral intentions toward health and the brand improved; however, the cause of that persuasion is not clear, as manipulated narrative and gameplay (difficulty) factors don’t influence the persuasive outcomes, nor does the mediating variable flow. 238

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Playing with Emotion: A Framework for Investigating Emotion in Video Games Teresa Lynch, Indiana University School of Media, USA Top paper, emotional demand track; 1st place, overall student paper Conceptualizing emotion for virtual environments such as video games involves considering its multidimensional processes and considering it as an evolved and adaptive function of our bodies. At the same time, conceptualizing emotion requires the acknowledgement of its inherently social function, how our socialization influences its expression and our interpretations of what our bodies tell us when we emote. Finally, to understand how emotions in virtual spaces occur, we must consider what happens when we become immersed within a virtual environmental – having never left our physical or social environments – and consider how the lack of corporeal realities and consequences influence our experience of emotion. This review offers a framework for studying emotion in video games with the subjects of concern being the processes, experiential components, and outcomes of emotion. This proposed framework is based in a developmental, interactionist perspective of emotion and a dynamic, human centric perspective of media interaction. Sex-Based Stereotype Threat and Game Modality Joe Wasserman, West Virginia University, USA Games have been found to be effective instructional tools. They may not be effective for everybody, however. When negative stereotypes are associated with certain social identity groups, individuals may experience stereotype threat that inhibits their ability to learn by playing games. In particular, negative stereotypes associated with women and games are expected to induce stereotype threat when sex-based group identity is salient during gameplay. The proposed study will experimentally investigate differences in sex-based stereotype threat responses when playing a digital versus an analog version of the same game. Furthermore, it tests an explanatory mechanism of stereotype threat in which stereotype threat consumes cognitive capacities, thereby negatively impacting task performance.

Posters Computer Space: Virtual Spaces, Real-World Places, and Player Affect Chris Alton, York University, Canada The ways in which virtual environments are constructed and perceived is rarely a direct one-to-one experience. Using the foundational examples 239

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of Squaresoft’s Parasite Eve (1997) and Konami’s Silent Hill series (1999-​ present), I examine the ways in which real-world locations and approximations of such are represented within videogame worlds. I examine the methods through which videogames create spaces which evoke the conceptual idea of a given place, both through audio/visual and interactive means, without constructing a one-to-one simulacrum of the location. Thus, the player actively contributes in the transformation of an actionable virtual space into an actualized lived place. Taking a multi-disciplinary approach, my discussion draws on cinematic semiotic theory, by way of Christian Metz, in association with Wittgenstein’s examination of language as a foundation from which to proceed. These concepts are then incorporated into a broader discussion of theories more focused on videogame studies, such as Laurie Taylor’s Lacanian approach to the videogame avatar, William Cheng’s discussion of soundscape construction, and Mihaly Csikszentmihalyi’s theory of flow, to illustrate how video game locations may leave out large portions of their real-world referents and yet still be identified as said referents by the player. The choices for what to include/exclude are also examined from a socio-political perspective, allowing reflection on what is considered necessary for a representation of a real-world place. Further, the ways in which audio cues serve to construct and naturalize these environments, both real-world and fictional, is addressed—moving beyond the film theory foundation, in which sound is omitted. Exploring Factors Influence Consumer Intention to Watch eSports Min Xiao, University of Florida, USA The current study employs the theory of reasoned action to examine factors influence the behavior of watching eSports. A structural equation modeling analysis is performed to examine the interaction between intention to watch eSports, attitude toward watching eSports, subjective norms, behavioral beliefs, and normative beliefs. The results suggested that three behavioral beliefs related factors (aesthetics, drama, and escapism) and subjective norms were positively related to attitude toward watching eSports. Normative beliefs positively influenced subjective norms. Finally, attitude toward watching eSports and subjective norms positively influenced intention to watch eSports. Exploring the Phenomenology of Zero-History Specific Social Demand in a Multiplayer Environment Jaime Banks, West Virginia University, USA; Caleb Carr, Coffee Hound, USA Socializing with others is a key motivation for playing digital games, but associated gratifications require the presence of and interaction with other agents which may be inherently demanding. This demand can 240

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be characterized as emerging from intersections of implicit or explicit awareness of and implicit or explicit response to the social other. To explore phenomenological dimensions of this nascent concept, this study explored gamer’s subjective assessment of the demand of encountering an unknown avatar in a massively multiplayer online game (MMMO). After experiencing a survey-based, simulated encounter, players were asked to describe the ease or effortfulness of such an encounter. In these descriptions, grounded thematic analysis identified six key factors in degrees of experienced demand: individual differences in personality and skill, environmental and social contexts of encounters, awareness of identity and agency boundaries in the online environment, game culture norms for interaction, perceived interaction value, and anticipations for how an interaction would unfold. Findings suggest that while social demand has, to date, been characterized as emerging from the game itself, it may be best understood as a function of the intersection of micro-level (intrapersonal), meso-level (interpersonal), and macro-level (cultural/contextual) factors. Interrogating Immersion: What Forms Does It Take in Game Design? Stefan Hall, High Point University, USA In Rules of Play: Game Design Fundamentals, Salen and Zimmerman describe game design as “the process by which a designer creates a context to be encountered by a participant, from which meaning emerges.” Here “context” forms a game’s narrative, spaces, and objects; “meaning” occurs when players take initiative to perform an action. This encapsulates the goal of game design: to create “a system in which players engage in an artificial conflict, defined by rules, [resulting] in a quantifiable outcome”. But what makes designs more or less effective? Sid Meier famously said good games “are a series of interesting choices”, and in “Immersion, Engagement, and Presence: A New Method for Analyzing 3-D Video Games”, McMahan postulates that it anchors on the interaction between a player and a game’s world: “[Players] must have a non-trivial impact on the environment […] immersion is not […] wholly dependent on audio or photo realism”. Researchers often link immersion to the concept of attention, which “is a key element in controlling and directing appropriate behavior in response to sensory and internally generated input,” allowing players to respond and attend to a game’s specific features. “Immersion […] is therefore a cognitive state that allows for the filtering out of certain materials in order to attend to the game as a whole.” This complements Koster’s idea that games are about sensible, rewarding problem solving because any kind of good puzzle instigates the “cognitive state” of immersion laid out here by adequately directing and informing players. This presentation will look at the ways that designers attempt to structure games around 241

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design elements to maximize immersion as well as the different ways that immersion is discussed by both designers and players. Refocusing Video Game Research: From Uses and Gratification to Affordances David Beyea, Michigan State University, USA Uses and gratifications is the go to well for research into why and how individuals interact with video games. Yet, there are several issues which plague uses and gratification research into video games. Researching video games from an affordance perspective, on the other hand, provides several advantages. This paper examines and addresses the problems underlying a uses and gratifications approach to video game research, explicating a new model for video game research and typologies, based on affordances. What Is Information for Social Behavior: Social Affordance in Videogames Joomi Lee, Michigan State University, USA Online gaming environments nowadays provide a “third place” where individuals can engage in social interactions with other users beyond geographical limitation, allowing players to exhibit more and more various behavioral and social phenomena. Intuitively speaking, this happens with advancement of videogame and virtual environment technology; technological affordances supported by game mechanics these days are realistic and similar to the real-world environment. However, game mechanics are programmed to specify only some portion of real world environment, and users’ actions are defined and constrained under those rules. Within such constraints, how do individuals develop social interactions with others in videogames? Are they different or similar with emergence of social interactions in the real world? In order to address this issue, this paper uses the concept of affordances and attempts to conceptualize social affordances in videogames.

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APPENDIX B T W I T T E R H A S H TAG M A P O F # B E AG A M E S

The image below represents a network of 201 unique tweets using the #beagames hashtag from April 20, 2017 to April 27, 2017. During the

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symposium, 48 individual nodes (individual Twitter users) made 197 unique connections with each other. Names that are larger and more central to the diagram are participants who were more active in the Twitter conversation. An interactive version of this map is available online at http:// hawksey.info/tagsexplorer/?key=1a8OX7QBKOoa-E6bRf5zzPye8pTauF8li16Sf12KyWV8&gid=400689247&mentions=true&retweets=true. These tweets are also archived (and searchable) online at http://hawksey. info/tagsexplorer/arc.html?key=1a8OX7QBKOoa-E6bRf5zzPye8pTauF8li16Sf12KyWV8&gid=400689247.

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Page numbers for diagrams, pictures and tables are given in italics. Aarseth, E. J. 44 achievers 135 action affordances 98 action video game players see AVGPs action video games (AVGs): challenges going forward 36–9; cognitive benefits 32–5; cognitive skills 25, 27, 237–8; conclusions 39; demanding nature of 13; description 28–9; impact on perception and cognition 29–32; real-world impact potential 35–6 action-RPG 37 advergames 45–6 Affect Grid 215 affordance theory (Gibson) 7, 92, 99–104, 99 Ahn, C. 65 Akaike information criterion (AIC) 217 Alavi, Mohammad 10 Alton, Chris 239 Amazon 179, 195, 203 Anderson, Eike 110, 238 Anderson-Barkley, Taylor 234 Angry Birds 28 Aponte, M.-V. 51 appraisal theories 67–8 AR/VR technologies 227 arcade games 49 Ascione, F. R. 64 asymmetrical/synchronous participation 202–3 Atari 2600 system 147 Atari VCS 13 attentional demand 226–7 audibility 131

audio-only stimuli 86 audio-visual stimuli 86 avatars 15, 82, 129–32, 134, 136–8, 154, 228, 236, 241 AVGPs 29–37 awe: conceptualizing the elicitation of 78–80, 79; conclusions 84–6, 85; introduction 74–8; theorizing positive as a gaming experience 80–4, 83 Bailey, R. L. 101 Bak Sandpile Model 164–5 Balance of the Planet 234 Ballance (2006) 31 Banks, Jaime 5, 15–16, 228, 235, 240 Baranowski, J. 46 Baranowski, T. 46 Bartle, R. 135 Battlefield franchise (2002) 29, 133 Bavelier, D. 6 behavioral demands: affordance-based perspective 100–2; affordances in game environments 98–100, 99; conclusions 103–4; game mechanics as constraints 97–8; introduction 92; moving beyond input-output models 95–7; social play as game affordance 102–3; via input device 93–5 behavioral training regimens 26–7 Behr, K. 96 Benedetti, W. 9 Benkler, Y. 200 Berelson, Bernard 60 Beyea, David 242 Billings, Andrew 184, 235

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BioShock series (2007–2013) 28, 53, 115, 118 Birk, Max V. 236 Bissell, Kimberly 235 Blight, M. G. 182–3 Blumler, J. G. 182–3 Boggs, B. P. 103 Bogost, Ian 45–6, 51 Bowey, Jason 236 Bowman, Nicholas David 4–5, 6, 7, 9, 10, 12, 13–14, 18n1, 51, 62, 64, 84, 93, 94, 108, 110, 112, 115, 126, 146, 187, 210, 212, 215, 226 Boxing (1980) 64 Boyan, A. 5 brain training games 25 Breaking Bad (tv series) 195 Breuer, J. 65 Brock, T. C. 47, 52–3 Brockmyer, J. H. 110 Brown, Kenon 235 Bucy, E. P. 3, 5, 17, 208–9 Buday, R. 46 Burke, Edmund 75 Burroughs, B. 195 Cabeza, R. 116 Call of Duty (2005) 29, 133, 179–80 Call of Duty: Modern Warfare 2 (2009) 10 Call of Duty: Modern Warfare 3 (2015) 111 camaraderie 188 Capella, M. L. 46 Cardona-Rivera, R. 100 Carr, C. T. 16 Carr, W. 178 cataloging 140–1 Chambers, J. H. 64 changes in the gamers 38–9 changes in the games 36–8 character attachment (CA) 237 ‘cheer bits’ 203 Cheer Chat Badges 200 ‘cheering’ 200 chemotherapy 63 Cheng, William 240 Cheung, G. 182 Chex Quest 45 chronemics 129

Clark, D. B. 7 Clifford, S. 116 co-presence 14, 131, 139 cognitive control network 166 cognitive control tasks see executive functions cognitive demand 5–7, 48–9, 52–6, 63, 75, 82–4, 210–11 cognitive energy 83 cognitive miser (Fiske and Taylor) 7 cognitive overload 84 cognitive resources 16, 85 cognitive skills 25–39, 40n1, 67 Cole, H. 188 commodification 202 competence-related rewards 172 computer simulations 1–2 computer-mediated communication (CMC) 98, 104 Connolly, T. M. 114 Consalvo, Mia 110–11, 183 ‘Couch co-op’ 149, 158n1 Counter-Strike: Global Offensive (2012) 179–80, 183 Cox, A. L. 51 CPM (component process model) 78, 80 Creative (non-gaming channel) 205 Csikszentmihalyi, Mihaly 47–50, 162, 165, 240 curse of specificity 27, 35–6 Dal Cin, S. 54–5 Dance Dance Revolution (DDR) (1998) 103 Dardis, F. E. 93 Darfur is Dying (2006) 45, 234 Darwin, Charles 67 data collection 119–20 Dead Space (2008) 9 Death Race (1976) 61–2, 108 Deci, E. L. 64 decision making 114–15 default mode network 167 Defense of the Ancients 2 (2013) 97 Depping, A. 133 Dill, J. C. 116 Dill, K. E. 116 Dogruel, L. 7, 112 Domahidi, E. 14 Donohue, S. E. 33

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Dota 2 2016 International Championships 178 Downs, J. 156 Dragon Age: Inquisition (2014) 149, 151–3, 156–7 dual-tasking/multi-tasking 35 Duck Hunt (1984) 94 dynamic coordination theory (DCT) 237 dynamic human centered communication systems theory (DHCCST) 95 dynamic systems theory 95 dynamism 95 dyslexia 36 Echo Fox 179 ecological perception theory (Gibson) 92, 95 Eden, Allison 7 Egli, E. A. 14 Ekman, P. 67–8 Elder Scrolls V: Skyrim (2011) 100 eLeague 180 Electronic Games Research Lab, Vancouver 102 Elson, M. 11, 112 emotion psychology 76 emotional demand 8–11, 60–70, 74, 211, 224–6 endo-game manipulations 65 engagement 44–56 ‘ergodic literature’ 44 escapism 77 ESL (eSports company) 180 eSports: anatomy of participants 185–7; behavior of watching 240; communities/gratifications of the future 187–9; competition 235; introduction 178–9; League of Legends Season Three World Championship 178; legitimization and development of 179–83; motivations of participation 183–5; new audiences to 132, 137; tournaments 199–200 eSports TV 180 E.T. game 164 evanescence 131 excitation transfer theory 63 executive functions 35 exo-game manipulations 65

experiential mode 80–81 exploratory factor analysis (EFA) 209, 216, 218 exploratory structural equation modeling (ESEM) 209, 213 Fable series (2004–2014) 115 Facebook 202 facial expressions 67, 130 Fallout 4 (2015) 100 Ferguson, C. J. 109 Fielder, F. E. 16 Final Fantasy (1987) 9 Fire Emblem series (1990) 45 first-person shooter games 29, 36 Fiske, S. T. 7 flight stick controls 12 flow theory 49–52, 54–5, 110, 169–73, 226 fMRI (functional magnetic resonance imaging) 67–8 Foglesong, Kira 234 Fox, Rick 178–9 Friendship 7 (Mercury Project) 2 Fuller, M. 152 functional magnetic resonance imaging (fMRI) 165–6 game ‘modding’ communities 103 game streaming 15, 179, 183, 196 Game of Thrones (GoT) (2014) 155–7 Games Done Quick (charity event) 199 games-based persuasion 44–56, 48 ‘garbage in leads to garbage out’ 39 Garcia, J. E. 16 Gatzidis, Christos 238 Gaver, W. W. 99–100, 102 Gears of War (2006) 29 Gee, James 5 Gentile, D. A. 116 geomin rotation 216 GEQ (Game Engagement Questionnaire) 121 Gibson, E. J. 99 Gibson, J. J. 92, 95, 98–9, 101–2 ‘golden hands’ rule 11 Gordon, A. M. 77, 80 Graetz, J. M. 2 Grand Theft Auto series (1997–2015) 29, 108 gratifications 181–2, 188

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interactivity-as-product 3, 227 intervention study design 30–31 intrinsic motivation inventory 68 IRL (non-gaming channel) 205 Ishutin, Danylo ‘Densi’ 97 IVEs (interactive virtual environments) 113, 117 Iyengar, V. 116

Gravity Gaming see Echo Fox Green, C. Shawn 6, 13, 224 Green, M. C. 47, 52–3 Greenberg, S. 158 Griffiths, M. D. 188 Grizzard, Matthew 10, 65, 111–12 Grodal, T. 8–9, 69 Gros, D. 183 GTA 118 Guinness World Records 118

James, William 163 Jansz, Jeoren 2, 93, 208, 226 Jedi Knight II: Jedi Outcast (2002) 128 Jenkins, H. 152, 195–6 Jerebko, Jonas 179 Jin, S.-A. A. 49–51 Joeckel, S. 7, 112–14 Johnson-Laird, P. N. 66–7 Jones, M. B. 6 JRPGs 53 Juul, J. 6, 44

‘hack-and-slash’ approaches 37 Hackenholt, A. 183 Haidt, J. 76, 78 Half-Life 2 (2004) 111 Hall, Stefan 241 Halo (2001) 94, 179 Hamilton, W. A. 198 hand-eye coordination 170 Haptics 129 Hardin, R. L. 185 Hartmann, T. 65, 68, 80, 111, 115 Heider, F. 167 Hemenover, S. 9 Hodge, Sarah 238 Hoffman, D. L. 49 HoloDeck 94 hot or cool 3 Howard, S. 156 HTC Vive 227 Huang, J. 182 Huh, S. 14 human brain 25–6, 38, 68, 161–5, 167, 168, 171–3, 235 Hunicke, R. 98 ‘hybrid’ genres 37 identification 81–2 Ijsselsteijn, W. A. 94 in-game advertising 46 in-game behaviours: agency/ interactivity 109–113; conclusions 121; introduction 108; theorydriven bespoke morality game 113–21, 117, 119–20 input-output loops 93 instantaneity 131 interactivity 2–3, 5, 93, 101, 104, 109, 121, 195, 208–10 interactivity-as-demand 3 interactivity-as-process 3

Kahn, A. S. 170 Kant, Immanuel 75 Katz, E. 182–3 Kaufman, G. F. 47 Kegerise, A. D. 93 Keltner, D. 76–7 killers 135 Kim, Y.-Y. 170 Kinder, Marsha 147 Kinect (Microsoft) 211 kishotenketsu approach 9 kinesics (body movements) 127, 129 Klimmt, Christopher 93, 236 Kluge Room, Massachusetts Institute of Technology 1–2, 17 Knautz, K. 183 Koban, Kevin 237 Kolko/Rickard-Figueroa study (1985) 64, 67 Kowert, R. 9, 14 Kryston, Kevin 13, 234 Lang, A. 7, 95–7, 101, 112 laparoscopic surgeons 36, 39 Lawry, J. 102 LC4MP 7, 83–4 League of Legends (2009) 169, 178 League of Legends (2016) 179–80, 183 ‘lean forward’ media 93 LeBlanc, M. 98

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Lee, Joomi 96, 242 Lee, P. 180 legitimate peripheral participation (LPP) 200 Levieux, G. 51 Lewis, Melvin 235 Lewis, N. 111 Li, R. W. 32 Liebold, B. 94 Limperos, A. M. 93 Lin, J.-H. 231 Linderoth, J. 100 ‘Lirik’ (streamer) 202 Lu, A. S. 54 ludology 44 Lynch, Teresa 9, 65, 239 McAlaney, John 238 McGonigal, J. 8, 211 McLuhan, M. 3 Mandryk, Regan 133, 236 mapping principle 128 Mario franchise 53 Martinez-Garza, M. M. 7 Martins, N. 9, 65 Mass Effect series (2007–2012) 118, 120 Mathiak, K. 96 Matthews, Nicholas 96, 237 Mau, G. 51 maximum likelihood (ML) 216–17 Medal of Honor 29 mediaspheres 194 Meier, Sid 4–5, 241 Melacca, Davide 238 Mendelson, A. L. 181 mental models 169 mental rotation 6 mentalizing 167, 169, 173 Metz, Christian 240 Meyers, L. S. 14 MFQ (2008) 112, 121 MFT foundations 112, 114–16, 119–20 MIME (Model of Intuitive Morality and Exemplars) 115 mindfulness 75 Mitchell, E. 147 MMOGs 147–8 MMOs 100 MOBA games 37

MOBA (multiplayer online battle arena) 180 Monopoly (1935) 62 mood management theory 63–4, 236 moral decisions 115–17 moral foundations theory (MFT) 237 moral intuitions 114–15 moral reasoning 118 morality effects 110–113 Mortal Kombat MOBA (1992) 180 Mplus syntax 214 MTVU 45 multi-tasking/dual-tasking 35 multiplayer games 170–2 Multiple-Object Tracking Task 34 ‘MyCareer’ modes 45 Myst (1993) 149–50 Nakamura, J. 48 narrative 52–6, 81 narratology 44, 47 NASA 2 NASA Task Load Index 215 Nass, C. 98 National Space and Aeronautics Agency see NASA Natkin, S. 51 natural mapping concept 12 NBA 2K series 45 needle and wedge avatars 13 neuroticism 136 Neverwinter Nights (2002) 112–13 Neverwinter Nights 2 (2006) 136 Nintendo 11–12, 94, 147 Nintendo Entertainment System (NES) 11,13, 94, 227 ‘No Russian’ level 17 non-action video game players see NVGPs non-player characters (NPCs) 237 non-verbal messages 129 Novak, T. P. 49 nowloading.co 200 NPCs (non-player characters) 112, 117–19 NVGPs 29–37 Oatley, K. 66–7 occulesics (eye movement/contact) 129 Oehlberg, L. 157 offline social support 181

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Oldmeadow, J. A. 14 olfactics 130 Oliver, M. B. 10, 16, 93, 109, 210, 216 online gaming 14, 193–4 online maze games 128 online social capital 181 Open Science Foundation project file 214 ‘open-world’ style 37 Operation Flashpoint (2001) 111 Östman, J. 199 Overwatch (2016) 179 PANAS (Positive and Negative Affective Schedule) 121 Papacharissi, Z. 181 Papers, Please (2013) 45 paralanguage 129 Parasite Eve (1997) 240 Parisi, D. 11 partial reinforcement 51 participation supply and demand 202–3 participatory cultures 193–4, 205 Paul, Christopher 148 PDP-1 2, 11, 13, 17 Peña, Jorge 55 Peng, W. 53 persuasion 48–55 persuasive games 45–8 physical demand 11–13, 18n1, 211–12, 224–7 Piaget, J. 76 Pietschmann, D. 94 ‘platformer’ 8 player avatar relationships (PAR) 237 Player’s Unknown Battlegrounds (2017) 197 PlayStation (Sony) 211 PlayStation VR 227 Pokemon Red (1996) 197 Pong (1972) 8, 61–2 Portal 98–9 Possler, Daniel 7, 10, 65, 68–70, 236 power gamers 147–48 Prabhu, S. 111 Professor Layton series 45 programmed data processor see PDP-1 proof-of-concepts studies 69 Przybylski, A. K. 64 Putnam, R. 198

Qualtrics 184 Quandt, T. 14, 65, 112 Quick Time Events (QTEs) 156 QWERTY keyboard layout 12 Rama, P. 195 Raney, Arthur A. 10, 93, 236 rational mode 81 Ravaja, N. 8, 216 recordability 131 Reddit 184 Reeves, B. 98 Renegades (eSports franchise) 179 Resident Evil (1996) 9 Restaurant Empire (2003) 31 reward 163–4 Richter, W. A. 116 Rigby, C. S. 64 Riot Games League of Legends 178 Rise of the Tomb Raider (2015) 28 Ritterfeld, U. 96 Rogers, R. 12, 93, 210 role-playing game genre see RPG genre RPG genre 9, 38, 53, 100, 118, 150 Rubin, A. M. 182, 188 Ruggiero, T. E. 182, 188 Ruihley, B. J. 184–5 ‘run-and-gun’ approach 37 Ryan, R. 64 ‘Sacriel’ (streamer) 197 Sakaguchi, Hironobu 9 Salen, K. 109 ‘sandbox’ style 37 Sangalang, A. 54 Scarantino, A. 66–7 Scharkow, M. 65 Schell, Jesse 9–10 Scherer, K. R. 78–9 Schmierbach, M. G. 49–51, 93 Schwabism 186–8 SEC-profile 79–80 Second Life (2003) 129, 194 Seder, P. 78 self-transcendent experience 77 Sellers, M. 93 Severin, W. J. 181, 187–8 Shannon, Claude 139 Shen, C. 135 Sherrick, Brett 238 Sherry, J. L. 48–9, 110–11, 172, 212 shooter games 103

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INDEX

Sicart, M. 97 Silent Hill (1999) 150, 240 Simmel, M. 167 Sims, The (2000) 31 simultaneity 131 single-player games 170–1 Sinnott-Armstrong, W. 125 Sjöblom, M. 183 Skalski, Paul 12, 81, 169, 210, 212 Skyrim (2011) 37, 96 Skyrim lore 100 Smurfs: Rescue in Gargamel’s Castle (1982) 64 ‘sniper-based’ approach 37 social commerce 196, 200–1 social community 196 social demand: conclusions 139–40, 225; context 131–5; explanation 13–16, 212–13; feedback 137–9; introduction 126, 127, 128, 161–2; medium 130–1; messages 128–30; noise 139; receivers 136–7; senders 135–6; social tasks 166–73 social entertainment 199 social media platforms 193–6, 200 social publishing 198–9 social sanctions 172 ‘social television’ 157 social-task demands 162 socializers 135 Solomon, M. R. 196, 198–9, 201, 204 Sopranos, The (tv series) 195 Space Invaders (1978) 61 SpaceWar! (1962) 2, 8, 11, 13, 16 spatial presence 12, 81 Spec Ops: The Line (2012) 44–5, 115, 118 Spielberg, Steven 62 Star Trek 94, 157 Star Wars Galaxies (2003) 128–9 state hostility scale 68 Steinkuehler, C. A. 14, 194 Steuer, J. 93, 209 Stewart, D. 180 stimulus 79, 82 streaming: conclusions 204–5; hybrid gaming cultures 203–4; introduction 193–5; and social demands 132; and tandem play 152–3; and Twitch 195–205, 197 Strobach, T. 35 Stromer-Galley, J. 3, 210

Sundar, S. S. 3, 209, 227 Super Mario Bros. (1985) 4, 171 Super Mario World (1990) 97 synchronization of attention and reward networks 164–5 synchronization theory of flow (STF): conclusions 172–3; introduction 161, 162–5; and social tasks 168–72; and Video Games 165–6 Tactical Ops: Assault on Terror (2002) 96 ‘tactical shooter’ approach 37 Tamborini, R. 5, 8, 84, 96, 110–13, 212, 215–16, 226–7 Tan, E. S. 8 tandem play: conclusions 157–8; initial investigation 148–9; introduction 14, 146; more emerging themes 155–7; replicating, refining and expanding 154–5; sociality and play 146–8; themes 149–54 Tangram help/hurt task 121 ‘tank shooter’ approach 37 Tankard, J. W. 181, 187–8 targeting ability 170 task-switching 6, 35 Taylor, Jacqui 238 Taylor, Laurie 240 Taylor, S. E. 7 Taylor, T. L. 147–8 ‘teabagging’ 129 Terlutter, R. 46 Tetris (1984) 31 theory-of-mind processing see mentalizing theorycrafting 148 Thomas, N. 109 Thomas theorem 11 Thompson, D. I. 46 3D games 49 Tomb Raider (1996) 69 top-down attention 32–4 transportation 52–5, 81 Turner Broadcasting System (TBS) 180 Tuten, T. L. 196, 198–9, 201, 204 Twitch 86, 137–8, 179–80, 183, 194–205, 197 Twitch.tv. 148–9, 194–5, 203 Twitter 243–44 Tyrannosaurus Rex 69

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INDEX

UE4 117–18 Unreal Engine (game engine) 118 Unreal Tournament series (1998–2007) 33, 118 Until Dawn (2015) 115, 118 Useful Field of View task 33–4 user-generated content (UGC) 199 validation measures 215–16 verbal messages 128–9 Vernier acuity task 26–7 Vetere, F. 156 Video Game Demand Scale (VGDS): conclusions 228; discussion 223–5; implications and utility 225–8; interactivity and demand 209–13; introduction 208–9; measures 214– 16; method 213–14; participants 214; research goals 213; results 216–18, 219–21, 221–3, 223 video game play 27–8, 40n2 violent content 108 violent gaming 110 visibility 131 visuo-motor tasks 162, 166–7, 171–3 voice chat 130–1 Voida, A. 158 Vorderer, Peter 111 Waiguny, M. K. J. 51 Walk, R. D. 99

Wang, L. 111 Wanner, B. 183 Wasserman, Joe 239 Weaver, A. J. 96, 111 Weber, R. 93, 96, 110–11, 162–5, 169, 212 Wentzel, D. 55 Wiimote controller 12 William Morris Endeavor/IMG 180 Williams, D. 14, 128, 135, 170, 194 Witcher, The 3 (2015) 99 working memory 6 World of Warcraft (2004) 15, 28, 136, 148, 180 Xbox controllers 94 Xbox Live 137 Xiao, Min 240 Yee, N. 188 Yoo, S. C. 55 Young, R. 100 YouTube 86, 138 YouTube Gaming 204 Yung, Y.-F. 49 Zalik, D. 180 Zawadzki, P. 183 Zhang, J. W. 77 Zimmerman, E. 109 Zubek, R. 98

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