Digital Player Typologies in Gamification and Game-Based Learning: A Meta-Synthesis

Year 2020, Volume: 9 Issue: 1, 49 - 68, 05.02.2020

Sezan Sezgin

https://doi.org/10.14686/buefad.610524

Abstract

Educational practices based on individual differences have become more significant as a result of technological advances. Learners today, demand learning processes which contain visual stimuli, ease of use, fast thinking and movement and playful activities. The two of such learning approaches are gamification and game-based learning. This research is a concept-centric meta-synthesis study examining player types as an individual difference in playful learning environments. In this research, the studies which analysed the typology of players, are examined in terms of methods used, game environments and contextual aspects The definitions and classifications given in 11 researches were reviewed in detail and analysed in terms of their findings and conclusions. Content analysis revealed the common points and 9 different thematic components in relation to general player typology were identified. According to study, it is concluded that, player typologies can be used as an individual difference criterion in the game-based educational processes. However, it is also recognized that player typologies identified by different researchers may not be eligible for all settings and practices. Given that game-based approaches are highly affected from cultural context, cultural characteristics of community of learners should be taken into consideration if these approaches to be employed in learning environments.

Keywords

Gamification, Player types, Individual differences, Gamer typology, Meta-synthesis

References

• Annetta, L. A., Folta, E., & Klesath, M. (2010). V-Learning: Distance education in the 21st century through 3D virtual learning environments. Springer Science & Business Media.
• Balcı, A. (2011). Sosyal bilimlerde araştırma: Yöntem, teknik ve ilkeler. Ankara: Pegem A Yayıncılık.
• Bartle, R. (1996). Hearts, clubs, diamonds, spades: players who suit MUDs. J. MUD Res. 1(1), 19
• Bartle, R. (2003). A self of sense. Retrieved from http://www.mud.co.uk/richard/selfware.htm / Last Accessed 01 December 2018.
• Buckley, P., & Doyle, E. (2016). Gamification and student motivation. Interactive learning environments, 24(6), 1162-1175.
• Cowley, B., Charles, D., Black, M., & Hickey, R. (2013). Real-time rule-based classification of player types in computer games. User Modeling and User-Adapted Interaction, 23(5), 489-526. de la Peña Esteban, F. D., Torralbo, J. A. L., Casas, D. L., & García, M. C. B. (2019). Web gamification with problem simulators for teaching engineering. Journal of Computing in Higher Education, 1-27.
• dos Santos, W. O., Bittencourt, I. I., & Vassileva, J. (2018). Design of tailored gamified educational systems based on gamer types. In Anais dos Workshops do Congresso Brasileiro de Informática na Educação (Vol. 7, No. 1, p. 42).
• Drachen, A., Canossa, A., & Yannakakis, G. N. (2009). Player modeling using self-organization in Tomb Raider: Underworld. In Computational Intelligence and Games, 2009. CIG 2009. IEEE Symposium on (pp. 1-8). IEEE.
• Erkuş, A. (2011). Davranış bilimleri için bilimsel araştırma süreci. Ankara: Seçkin Yayıncılık.
• Ferro, L. S., Walz, S. P., & Greuter, S. (2013). Towards personalised, gamified systems: an investigation into game design, personality and player typologies. In Proceedings of The 9th Australasian Conference on Interactive Entertainment: Matters of Life and Death (p. 7). ACM.
• Fullerton, T. (2008). Working with Dramatic Elements. In Game Design Workshop. A playcentric approach to creating innovative games. Morgan Kaufmann, Burlington, MA
• Gelder, A., & Kovenock, D. (2017). Dynamic behavior and player types in majoritarian multi-battle contests. Games and Economic Behavior, 104, 444-455.
• Gil, B., Cantador, I., & Marczewski, A. (2015). Validating gamification mechanics and player types in an e-learning environment. In Design for Teaching and Learning in a Networked World (pp. 568-572). Springer, Cham.
• Götzenbrucker, G., & Köhl, M. (2009). Ten years later. Eludamos. Journal for Computer Game Culture, 3(2), 309-324.
• Hamari, J., & Tuunanen, J. (2014). Player types: A meta-synthesis. Retrieved from https://tampub.uta.fi/bitstream/handle/10024/99064/player_types_a_meta_synthesis.pdf?sequence=1 /Last Accessed 15 November 2018.
• Hanlon, M. (2006). Survey reveals U.S. gamer market is diversifying. Retrieved from https://newatlas.com/go/6097/ /Last Accessed 09 November 2018.
• Huizinga, J. (1955) Homo Ludens: A Study of the Play Element in Culture. Boston: The Beacon Press.
• Kapp, K. M. (2012). The gamification of learning and instruction: game-based methods and strategies for training and education. John Wiley & Sons.
• Kingsley, T. L., & Grabner‐Hagen, M. M. (2015). Gamification: Questing to Integrate Content Knowledge, Literacy, and 21st‐Century Learning. Journal of adolescent & adult literacy, 59(1), 51-61.
• Kirriemuir, J., & McFarlane, A. (2004). Literature review in games and learning. A NESTA Futurelab Research report - report 8. 2004. Retrieved from http://www.savie.ca/SAGE/Articles/1236-KIRRIEMUR-2004.pdf /Last Accessed 02 December 2018.
• Klopfer, E., Osterweil, S., & Salen, K. (2009). Moving learning games forward. Cambridge, MA: The Education Arcade.
• Koivisto, J., & Hamari, J. (2014). Demographic differences in perceived benefits from gamification. Computers in Human Behavior, 35, 179-188.
• Kuo, C. M., & Chen, H. J. (2019). The Gamer Types of Seniors and Gamification Strategies Toward Physical Activity. In International Conference on Human-Computer Interaction (pp. 177-188). Springer, Cham.
• Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 159-174.
• Looyestyn, J., Kernot, J., Boshoff, K., Ryan, J., Edney, S., & Maher, C. (2017). Does gamification increase engagement with online programs? A systematic review. PloS one, 12(3), e0173403.
• Marczewski, A. (2015). User Types. In Even Ninja Monkeys Like to Play: Gamification, Game Thinking and Motivational Design (1st ed., pp. 65-80). CreateSpace Independent Publishing Platform.
• McMillan, J. H., & Schumacher, S. (1984). Research in education: A conceptual introduction. Little, Brown.
• Moller, L., & Huett, J. B. (2012). The Next Generation of distance education. Springer.
• Monterrat, B., Desmarais, M., Lavoué, E., & George, S. (2015). A player model for adaptive gamification in learning environments. In International conference on artificial intelligence in education (pp. 297-306). Springer, Cham.
• Nacke, L. E., Bateman, C., & Mandryk, R. L. (2011). BrainHex: preliminary results from a neurobiological gamer typology survey. In International Conference on Entertainment Computing (pp. 288-293). Springer, Berlin, Heidelberg.
• Park, S., & Kim, S. (2017). A Validation of Differences in Academical Achievement among Bartle's Player Types in Educational Gamification Environments. Journal of Korea Game Society, 17(4), 25-36.
• Schuurman, D., De Moor, K., De Marez, L., & Van Looy, J. (2008). Fanboys, competers, escapists and time-killers: a typology based on gamers' motivations for playing video games. In Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (pp. 46-50). ACM.
• Sezgin, S., Bozkurt, A., Yılmaz, E. A., & van der Linden, N. (2018). Oyunlaştırma, Eğitim ve Kuramsal Yaklaşımlar: Öğrenme Süreçlerinde Motivasyon, Adanmışlık ve Sürdürebilirlik. Mehmet Akif Ersoy Üniversitesi Eğitim Fakültesi Dergisi, (45), 169-189.
• Sezgin, S., & Yuzer, T. V. (2017). Games As Futuristic Tools: Looking For An Advanced Definition. In Conference Proceedings of the 10th International Conference of Education, Research and Innovation ICERI (pp. 8512-8521).
• Stemler, S. (2001). An overview of content analysis. Practical Assessment, Research & Evaluation, 7(17), 137-146.
• Stewart, B. (2011). “Personality And Play Styles: A Unified Model.” Accessed from: http://www.gamasutra.com/view/feature/6474/personality_and_play_styles_a_.php. / Last Accessed 02 December 2018.
• Tondello, G. F., Wehbe, R. R., Diamond, L., Busch, M., Marczewski, A., & Nacke, L. E. (2016). The gamification user types hexad scale. In Proceedings of the 2016 annual symposium on computer-human interaction in play (pp. 229-243). ACM.
• Vahlo, J., Kaakinen, J. K., Holm, S. K., & Koponen, A. (2017). Digital game dynamics preferences and player types. Journal of Computer-Mediated Communication, 22(2), 88-103.
• Walsh, D., & Downe, S. (2005). Meta‐synthesis method for qualitative research: a literature review. Journal of Advanced Nursing, 50(2), 204-211.
• Whang, L. S., & Chang, G. (2004).“Lifestyles of virtual world residents: Living in the on-line game ‘lineage’”. In CyberPsychology & Behavior, 7(5). 592-600.
• Xu, Y., Poole, E. S., Miller, A. D., Eiriksdottir, E., Kestranek, D., Catrambone, R., & Mynatt, E. D. (2012). This is not a one-horse race: understanding player types in multiplayer pervasive health games for youth. In Proceedings of the ACM 2012 conference on computer supported cooperative work (pp. 843-852). ACM.
• Yee, N. (2006). Motivations for play in online games. CyberPsychology & Behavior, 9(6), 772-775.