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Playing out diplomacy: gamified realization of future skills and discipline-specific theory

Published online by Cambridge University Press:  01 January 2026

Milla Kruskopf Open the ORCID record for Milla Kruskopf [Opens in a new window] ,
Elina E. Ketonen Open the ORCID record for Elina E. Ketonen [Opens in a new window]  and
Mikael Mattlin Open the ORCID record for Mikael Mattlin [Opens in a new window]
Milla Kruskopf*
Affiliation:
Faculty of Educational Sciences, University of Helsinki, Siltavuorenpenger 5 A, 00014 Helsinki, Finland
Elina E. Ketonen*
Affiliation:
Faculty of Educational Sciences, University of Helsinki, Siltavuorenpenger 5 A, 00014 Helsinki, Finland
Mikael Mattlin*
Affiliation:
Department of Philosophy, Contemporary History and Political Science, University of Turku, Assistentinkatu 7, 20014 Turku, Finland
*
E-mail: milla.kruskopf@helsinki.fi
E-mail: elina.e.ketonen@helsinki.fi
E-mail: mikael.mattlin@utu.fi
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Abstract

Future horizons, shaped by unpredictable ecosystems and exponential automation, require discipline-specific as well as transdisciplinary skills to navigate. In the context of political science education, negotiation simulations, for example in the form of board games, can aid in developing both. As a plausibility probe for wider investigations, we set out to research whether an International Relations course concept utilizing the classical board game Diplomacy with pedagogically altered rules and gaming conditions enhances students’ (n = 23) understanding of discipline-specific knowledge and future skills. We utilized a conceptual pre-post measure as well as free-form learning diaries to investigate development in participants’ conceptual understanding and future skills along the course. The results tentatively suggest quantifiable and qualitatively observable changes in the discipline-specific conceptual, as well as more broad-based competence level. The gamified learning environment provided students with an activating and engaging learning environment that better acquainted them not only with discipline-specific theory, but more importantly, also with skills regarded important for their future.

Keywords

Active learningDiplomacyFuture skillsGamificationIRLearning environments

Information

Type
Teaching and Learning
Information
European Political Science , Volume 20 , Issue 4 , December 2021 , pp. 698 - 722
Copyright
Copyright © 2021 European Consortium for Political Research

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References

Asal, V. 2005. Playing games with international relations. International Studies Perspectives 6(3): 359-373. CrossRefGoogle Scholar
Asal, V., Miller, I., and Willis, C.N.. 2019. System, state or individual: Gaming levels of analysis in international relations. International Studies Perspectives 21(1): 1-11. https://doi.org/10.1093/isp/ekz018. Google Scholar
Bandura, A., Freeman, W.H., and Lightsey, R.. 1997. Self-efficacy: The exercise of control. New York: W. H. Freeman.Google Scholar
Barrows, H.S. 1996. 1996 Problem-based learning in medicine and beyond: A brief overview. New Directions for Teaching and Learning 1996(68): 3-12. https://doi.org/10.1002/tl.37219966804. CrossRefGoogle Scholar
Bereiter, C., and Scardamalia, M. 2003. Learning to work creatively with knowledge. Powerful learning environments In Unravelling basic components and dimensions of powerful learning environments, De Corte, E., Verschaffel, L., Entwistle, N., and van Merriënboer, J.. Oxford: Elsevier Science. Google Scholar
Bridge, D., and Radford, S.. 2014. Teaching diplomacy by other means: Using an outside-of-class simulation to teach international relations theory. International Studies Perspectives 15(4): 423-437. CrossRefGoogle Scholar
Brown, V.A., Harris, J.A., and Russell, J.Y., eds. 2010. Tackling wicked problems through the transdisciplinary imagination. London: Earthscan. Google Scholar
Csikszentmihalyi, M. 1996. Creativity, flow and the psychology of discovery and invention. New York: Harper Collins Publishers.Google Scholar
Drake, P., and K. Sung. 2011. Teaching introductory programming with popular board games. In Proceedings of the 42nd ACM technical symposium on computer science education, pp. 619–624. https://doi.org/10.1145/1953163.1953338.CrossRefGoogle Scholar
Eckstein, H. 1975. Case study and theory in political science In Handbook of political science, ed. Greenstein, F.I. and Polsby, N.W.. Reading, Mass: Addison-Wesley Pub.. Google Scholar
Eckstein, H. 2000. Case study and theory in political science. In Case study method: Key issues, Key texts, ed. R. Gomm, M. Hammersley and P. Foster, 119–164. London: SAGE.Google Scholar
Eskin, B. 2004. World domination: The game. Washington: Washington Post.Google Scholar
Frank, A. 2012. Gaming the game: A study of the gamer mode in educational wargaming. Simulation and Gaming 43(1): 118-132. CrossRefGoogle Scholar
Frey, C.B., and Osborne, M.A.. 2017. The future of employment: How susceptible are jobs to computerisation?. Technological Forecasting and Social Change 114: 254-280. CrossRefGoogle Scholar
Gick, M.L., and Holyoak, K.J.. 1983. Schema induction and analogical transfer. Cognitive Psychology 15(1): 1-38. CrossRefGoogle Scholar
Hämäläinen, M., and T. Honkela. 2019. Co-operation as an asymmetric form of human-computer creativity. Case: Peace machine. In Proceedings of the first workshop on NLP for conversational AI, pp. 42–50.Google Scholar
Head, B.W. 2008. Wicked problems in public policy. Public Policy 3(2): 101-118. Google Scholar
Heuer, F., and Reisberg, D.. 1992. Emotion, arousal, and memory for detail. In The handbook of emotion and memory: Research and theory, ed. Christianson, Sven-Åke, 151-180. New York: Psychology Press. Google Scholar
Hidi, S., and Anderson, V.. 1986. Producing written summaries: Task demands, cognitive operations, and implications for instruction. Review of Educational Research 56(4): 473-493. CrossRefGoogle Scholar
Hidi, S., Renninger, K.A., Krapp, A. 2004. Interest, a motivational variable that combines affective and cognitive functioning. In Motivation, emotion, and cognition, ed. Yun, D. and Sternberg, R., 103-130. New York: Routledge. Google Scholar
Honkela, T. 2017. Rauhankone: Tekoälytutkijan testamentti [Peace machine: A testament of an AI researcher]. Helsinki: Gaudeamus.Google Scholar
Howard, P.N. 2020. Lie machines: How to save democracy from troll armies, deceitful robots, junk news operations, and political operatives. New Haven: Yale University Press.Google Scholar
Hudson, V.M., and Day, B.S.. 2019. Foreign policy analysis: Classic and contemporary theory. Lanham: Rowman & Littlefield.Google Scholar
Ito, M., Gutiérrez, K., Livingstone, S., Penuel, B., Rhodes, J., Salen, K., Schor, J., Sefton-Green, J., and Watkins, S.C.. 2013. Connected learning: An agenda for research and design. Irvine: Digital Media and Learning Research Hub.Google Scholar
Jackson, R., Sørensen, G., and Møller, J.. 2019. Introduction to international relations: Theories and approaches. Oxford: Oxford University Press.Google Scholar
Ketonen, E. 2017. The role of motivation and academic emotions in university studies: The short- and long-term effects on situational experiences and academic achievement. Helsinki: Faculty of Educational Sciences.Google Scholar
Krippendorff, K. 2004. Content analysis: An introduction to its methodology. Thousand Oaks: Sage.Google Scholar
Kruskopf, M., Hakkarainen, K., Li, S., and Lonka, K. 2020. Lessons learned on student engagement from the nature of pervasive socio-digital interests and related network participation of adolescents. Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.12506 Google Scholar
Levy, J.S. 2008. Case studies: Types, designs, and logics of inference. Conflict Management and Peace Science 25(1): 1-18. CrossRefGoogle Scholar
Loggins, J.A. 2009. Simulating the foreign policy decision-making process in the undergraduate classroom. PS: Political Science and Politics 42(2): 401-407. Google Scholar
Lonka, K., Ketonen, E. 2012. How to make a lecture course an engaging learning experience?. Studies for the Learning Society 2(2–3): 63-74. https://doi.org/10.2478/v10240-012-0006-1 CrossRefGoogle Scholar
Lonka, K. 2018. Phenomenal learning from Finland. Helsinki: Edita.Google Scholar
Lonka, K., and Ahola, K.. 1995. Activating instruction: How to foster study and thinking skills in higher education. In European Journal of Psychology of Education 10 (4): 351. CrossRefGoogle Scholar
Marton, F., and Säljö, R.. 1976. On qualitative differences in learning: I—Outcome and process. British Journal of Educational Psychology 46(1): 4-11. CrossRefGoogle Scholar
Mattlin, M. 2018. Adapting the DIPLOMACY board game for 21st century international relations teaching. Simulation and Gaming 49(6): 735-750. https://doi.org/10.1177/1046878118788905. CrossRefGoogle Scholar
Mattlin, M. 2021. Anarchy is what students make of it: Playing out Wendt’s three cultures of anarchy. Journal of Political Science Education. https://doi.org/10.1080/15512169.2020.1861457 CrossRefGoogle Scholar
Messerli, P., Murniningtyas, E., Eloundou-Enyegue, P., Foli, E.G., Furman, E., Glassman, A., Hernández Licona, G., Kim, E.M., Lutz, W., Moatti, J.-P., Richardson, K., Saidam, M., Smith, D., Kazimieras Staniškis, J., and van Ypersele, J.-P.. 2019. Global sustainable development report 2019: The future is now—science for achieving sustainable development. Department of Economic and Social Affairs: United Nations.Google Scholar
Messner, D., S. Schlacke, M. Fromhold-Eisebith, U. Grote, E. Matthies, K. Pittel, and R. Blake-Rath. 2019. Towards our common digital future. Flagship report. German Advisory Council on Global Change (WBGU).Google Scholar
Muis, K.R., Pekrun, R., Sinatra, G.M., Azevedo, R., Trevors, G., Meier, E. and Heddy, B.C.. 2015. The curious case of climate change: Testing a theoretical model of epistemic beliefs, epistemic emotions, and complex learning. Learning and Instruction 39: 168-183. CrossRefGoogle Scholar
Nedelkoska, L., and Quintini, G.. 2018. Automation, skills use and training (No. 202). Paris: OECD Publishing.Google Scholar
OECD (The Organisation for Economic Co-operation and Development). 2018. Putting faces to the jobs at risk of automation, policy brief on the future of work. Paris: OECD Publishing.Google Scholar
OECD (The Organisation for Economic Co-operation and Development). 2019. Future of education and skills 2030: OECD learning compass 2030—A series of concept notes. Retrieved from http://www.oecd.org/education/2030-project/.Google Scholar
Patton, M.Q. 1990. Qualitative evaluation and research methods. Thousand Oaks: Sage.Google Scholar
Pekrun, R. 2014. Emotions and learning. Educational Practices Series-24, UNESCO International Bureau of Education.Google Scholar
Rajaraman, A., and J.D. Ullman. 2011. Data mining. In Mining of massive datasets, pp. 1–17. Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781139058452.002.CrossRefGoogle Scholar
Raymond, C., Tawa, J., Tonini, G., and Gomaa, S.. 2018. Using experimental research to test instructional effectiveness: A case study. Journal of Political Science Education 14(2): 167-176. CrossRefGoogle Scholar
Rittinger, E.R. 2020. Inspiring students to think theoretically about international relations through the game of diplomacy. Journal of Political Science Education 16(1): 41-56. CrossRefGoogle Scholar
Rosario, R.A., and Widmeyer, G.R.. 2009. An exploratory review of design principles in constructivist gaming learning environments. Journal of Information Systems Education 20(3): 289-300. Google Scholar
Sawyer, R.K. 2011. Explaining creativity: The science of human innovation. New York: Oxford University Press.Google Scholar
Scardamalia, M., and C. Bereiter. 2014. Knowledge building and knowledge creation: Theory, pedagogy and technology. In The Cambridge handbook of the learning sciences, pp. 397–417.Google Scholar
Schrodt, P.A. 2011. Forecasting political conflict in Asia using latent Dirichlet allocation models. Dublin: In Annual Meeting of the European Political Science Association.Google Scholar
Silge, J., and Robinson, D.. 2017. Text mining with R: A tidy approach. Sebastopol: O'Reilly Media Inc..Google Scholar
Sundararajan, N., and Adesope, O. 2020. Keep it coherent: A meta-analysis of the seductive details effect. Educational Psychology Review. https://doi.org/10.1007/s10648-020-09522-4 CrossRefGoogle Scholar
Voros, J. 2003. A generic foresight process framework. Foresight 5(3): 10-21. CrossRefGoogle Scholar
Vosniadou, S. ed. 2009. International handbook of research on conceptual change. London: Routledge. CrossRefGoogle Scholar
Webb, E.J., Campbell, D.T., Schwartz, R.D., and Sechrest, L.. 1966. Unobtrusive measures; nonreactive research in the social sciences. Chicago: Rand McNally.Google Scholar
Wing, J.M. 2006. Computational thinking. Communications of the ACM 49(3): 33-35. CrossRefGoogle Scholar