Deterding, Christoph Sebastian

Gow, Jeremy

Hesketh, Joseph

German

White Rose Research Online

How Players Learn Team-versus-Team Esports : First Results from A Grounded Theory Study

This is a repository copy of How Players Learn Team-versus-Team Esports : First Results from A Grounded Theory Study.White Rose Research Online URL for this paper:https://eprints.whiterose.ac.uk/156463/Version: Accepted VersionProceedings Paper:Hesketh, Joseph, Deterding, Christoph Sebastian orcid.org/0000-0003-0033-2104 and Gow, Jeremy (2020) How Players Learn Team-versus-Team Esports : First Results from A Grounded Theory Study. In: DiGRA'20 Abstract - Proceedings of the 2020 DiGRA International Conference. DIGRA 2020, 02-06 Jun 2020 DiGRA conference proceedings . ,FIN . eprints@whiterose.ac.ukhttps://eprints.whiterose.ac.uk/Reuse Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of the full text version. This is indicated by the licence information on the White Rose Research Online record for the item. Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. How Players Learn Team-versus-Team Esports: First Results from A Grounded Theory Study Anonymous First Author  Institutional Affiliation Address line 1 Address line 2 Telephone firstauthor@institution.com   Anonymous Second Author, Third Author  Institutional Affiliation Address line 1 Address line 2 Telephone secondauthor@institution.com​, ​thirdauthor@institution.com Keywords Esports, game learning, grounded theory, Dota 2, CS:GO INTRODUCTION Esports games are competitive multiplayer digital games that are commonly played in            organised competitions between professional teams or players (Hamari & Sjöblom          2017). An essential part of Esports practices is learning the games and how to play               them competitively, be it to play better or to better appreciate spectated matches, as              evidenced by numerous online tools, knowledge platforms, discussions, and video on           platforms like ​Twitch dedicated to teaching gameplay tactics and strategy (Taylor           2012, 2018; Hamari & Sjöblom 2017). Yet, with few exceptions, research on learning             in games has focused on game​-based learning: serious games and gamification that            facilitate learning with relevance outside of gameplay (Whitton 2014, Boyle et al.            2016, Sailer & Homner, 2019). Where researchers have studied ​game ​learning, they            have chiefly explored distributed expertise, collaborative knowledge construction, and         the acquisition of scientific habits of mind in massively multiplayer online           role-playing games (MMORPGs), with field data from the mid-2000s (Steinkuehler          & Duncan, 2008; Oliver & Carr, 2009; Chen, 2012; Ask, 2016). By comparison, we              know little about individual and peer learning of Esports games, especially in their             contemporary online media environment, saturated with streaming, training bots, and          the like. To address this knowledge gap, we have been conducting a grounded theory study             (Charmaz, 2014), mixing qualitative semi-structured interviews and contextual        inquiry to develop a model of ​how amateur and semi-professional players learn            team-vs-team Esports games ​. We here report our preliminary findings on learning           processes, tools, and outcomes, comparing them with current literature around game           learning. This study is part of a larger project aimed to inform designers how players               Proceedings of DiGRA 2020 © 2020 Authors & Digital Games Research Association DiGRA. Personal and educational classroom             use of this paper is allowed, commercial use requires specific permission from the author.   utilise existing tools to learn to play, and thus, how they might better support players               in learning. DATA AND METHOD The present preliminary findings are based on interviews with 12 adult players (all             male and UK-based), 4 of ​Dota 2 (Valve 2013) and 8 of ​Counter Strike: Global               Offensive ​(​CS:GO ​, Valve 2012), recruited through online forums and personal          connections. For comparison, we intentionally recruited players from two different          games with varying degrees of expertise in a game, ranging from 8 hours recorded              playtime to over 5,000 hours. Each interview was transcribed for analysis. Following           grounded theory, we iteratively cycled between data collection, coding, and          theorizing, continuously re-viewing and re-coding previous transcripts in constant         comparison. The following reported codes have reached theoretical saturation,         meaning even new data intentionally sampled to challenge them is easily           accommodated by our codes. PRELIMINARY FINDINGS Player reports on learning ​Dota 2 and ​CS:GO highlighted three different analytic            aspects: ​learning processes (​how players engaged with information and tools to           learn), ​learning tools (what tools players used to find and disseminate information),            and ​learning goals ​ (the particular knowledge and skills players sought to learn). Interviews showed several different yet interconnected kinds of learning processes,          where players distinguished quite clearly between them, while also reporting          sometimes fluid switching from one to the other. These four are ​identifying            knowledge and skill gaps; ​consuming ​and internalising information; ​applying existing          knowledge and skills in new contexts or combinations; and active ​practicing of            existing knowledge and skills to improve and internalise them. Participants also           highlighted the importance of ​deliberation as a meta-process or meta-quality: whether           or what one learns in each process was reported to depend on the amount of               connected deliberation. Across these processes, participants reported using a variety of tools created by            developers, the player community, or even themselves. ‘In-built’ or in-game tools           used for learning were different ​game modes (e.g. competitive, casual, training           environments) and various ​add-ons and extensions (like spectator mode, replays, ping           systems, chat). Out-of-game, the primary tools used were ​streaming services (e.g.           Twitch.tv, YouTube), ​forums (e.g. Reddit, Steam forums), ​statistics services (e.g.          OpenDota), and out-of-game communication tools like TeamSpeak or Discord. In terms of learning goals, these different tools and processes are variously (and as              stated, often quite deliberately) used to learn about ​basic controls (mappings of            buttons and keys to in-game actions) and ​game mechanics ​(​goals, rules, and systems),             train up ​motor skills used by actions in-game that involve quick muscle movements             and low cognitive load, but also to identify, develop, test, and refine ever-changing             strategies (high-level planning of player and team actions) and the so-called ​meta (the             ongoing evolution of ‘best’ strategies globally or within particular team setups).           Interestingly, players also reported actively learning ​non-game-specific knowledge        and skills (e.g. prioritisation, teamwork) as well as meta- ​learning skills ​:          understanding how one best learns and teaches. -- 2  --   DISCUSSION AND OUTLOOK Many of the learning processes, tools, and goals we observed resonate with findings             in existing research on game learning in MMORPGs (Steinkuehler & Duncan, 2008;            Oliver & Carr, 2009; Chen, 2012; Ask, 2016). Two things that stand apart are the               meta as a moving learning target, and the evolution of part- or fully-professional and              commercial learning-focused offerings in streaming and statistics services, which         previously were found to be chiefly fan-made. Another difference is the importance            participants gave to meta-cognitive and meta-learning processes and skills like          identifying knowledge gaps, deliberation, or learning to learn. This matches          literatures in professional education and sport expertise on the importance of           reflection and deliberate practice (Macnamara et al., 2014; Mann, Gordon, &           MacLeod, 2009), suggesting Esports as a potentially fruitful focal object for           knowledge travel between these fields and game learning.  We readily acknowledge that our sample is small and very homogeneous and our             findings to date quite abstract for the purposes of informing learning support. In             planned future work, we will engage a more diverse sample of players in contextual              inquiry on one particular area of learning needs that also emerged from the data,              namely the transition of single-player human-vs-bot to multiplayer human-vs-human         play. BIBLIOGRAPHY Ask, K. (2016). The Value of Calculations: The Coproduction of Theorycraft and            Player Practices. ​Bulletin of Science, Technology & Society, 36​(3), 190-200.          https://doi.org/10.1177/0270467617690058 Boyle, E. A., Hainey, T., Connolly, T. M., Gray, G., Earp, J., Ott, M., … Pereira, J.                 (2016). An update to the systematic literature review of empirical evidence of the             impacts and outcomes of computer games and serious games. ​Computers and           Education​, ​94​, 178–192. ​https://doi.org/10.1016/j.compedu.2015.11.003  Charmaz, K. (2014). ​Constructing Grounded Theory​. Thousand Oaks, CA: Sage. Chen, M. (2012). ​Leet Noobs: The Life and Death of an Expert Player Group in World                of Warcraft​. New York, NY: Peter Lang Publishing. Connolly, T. M., Boyle, E. A., MacArthur, E., Hainey, T., & Boyle, J. M. (2012). A                systematic literature review of empirical evidence on computer games and          serious games. ​Computers and Education​, ​59​(2), 661–686.       https://doi.org/10.1016/j.compedu.2012.03.004  Gee, J. P. (2007). ​What Video Games Have To Teach Us About Learning And              Literacy. ​New York, NY: St. Martin’s Press. Hamari, J., & Sjöblom, M. (2017). What is eSports and why do people watch it?               Internet Research​, ​27​(2), 211–232. ​https://doi.org/10.1108/IntR-04-2016-0085 Macnamara, B. N., Hambrick, D. Z., & Oswald, F. L. (2014). Deliberate practice and              performance in music, games, sports, education, and professions: A         meta-analysis. P ​sychological science, 25​(8), 1608-1618. -- 3  --   Mann, K., Gordon, J., & MacLeod, A. (2009). Reflection and reflective practice in             health professions education: A systematic review. ​Advances in Health Sciences          Education, 14​(4), 595–621. https://doi.org/10.1007/s10459-007-9090-2 Oliver, M., & Carr, D. (2009). Learning in virtual worlds: Using communities of             practice to explain how people learn from play. ​British Journal of Educational            Technology​, ​40​(3), 444–457. ​https://doi.org/10.1111/j.1467-8535.2009.00948.x  Sailer, M., & Homner, L. (2019). The Gamification of Learning: a Meta-analysis.            Educational Psychology Review​, 1–36.    https://doi.org/10.1007/s10648-019-09498-w  Steinkuehler, C., & Duncan, S. (2008). Scientific habits of mind in virtual worlds.             Journal of Science Education and Technology, 17​(6), 530–543.        https://doi.org/10.1007/s10956-008-9120-8 Taylor, T. L. (2012). ​Raising the Stakes: E-Sports and the Professionalization of            Computer Gaming​. Cambridge, MA: MIT Press. Taylor, T. L. (2018). ​Watch Me Play: Twitch and the Rise of Game Live Streaming​.               Princeton, NJ: Princeton University Press. Valve Corporation. 2013. ​Dota 2.​ Online Game. Valve Corporation. Valve Corporation, Hidden Path Entertainment. 2012. ​Counter Strike: Global         Offensive.​ Online Game. Valve Corporation. Whitton, N. (2014). ​Digital Games and Learning: Research and Theory​. Oxford:           Taylor & Francis.     -- 4  --  

How Players Learn Team-versus-Team Esports:First Results from A Grounded Theory Study

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How Players Learn Team-versus-Team Esports : First Results from A Grounded Theory Study

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