Abstract
Collaborative-problem solving (CPS) is an important 21st century skill and it continues to be a complex skill to model and assess. We approached this challenge by first looking at the individual level primary cognitive and social aspects of CPS. This paper demonstrates ongoing work of designing and developing game-based models of three CPS components: cooperation, problem-solving, and persistence. A study was conducted collecting data from the game-play of 11 groups (three middle school students in each group) tasked with solving challenges in Physics Playground. We employed evidence-centered design principles to develop behavioral indicators of cooperation, problem-solving and persistence. These were used to code each student’s behavior during three hours of video-recorded gameplay. For each CPS component, we applied hierarchical clustering on this video-coded data and qualitatively evaluated two generated clusters of students across groups. For cooperation, there was more communication with other students in working towards a solution for one group. For problem-solving, one group had more instances of talking about possible solutions. For persistence, one group had more attempts in a challenge and was more on-task. Implications of results, limitations and future work were discussed.
Keywords
T. L. McKinniss—Independent Scholar.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Griffin, P., Care, E. (eds.): Assessment and Teaching of 21st Century Skills: Methods and Approach. EAIA. Springer, Dordrecht (2015). https://doi.org/10.1007/978-94-017-9395-7
Organization for Economic Co-operation and Development (OECD): PISA 2015 collaborative problem solving frameworks (2013). http://www.oecd.org/pisa/pisaproducts/pisa2015draftframeworks.htm
Hesse, F., Care, E., Buder, J., Sassenberg, K., Griffin, P.: A framework for teachable collaborative problem solving skills. In: Griffin, P., Care, E. (eds.) Assessment and Teaching of 21st Century Skills. EAIA, pp. 37–56. Springer, Dordrecht (2015). https://doi.org/10.1007/978-94-017-9395-7_2
Liu, L., Hao, J., von Davier, A.A., Kyllonen, P., Zapata-Rivera, J.D.: A tough nut to crack: measuring collaborative problem solving. In: Handbook of Research on Technology Tools for Real-World Skill Development, pp. 344–359. IGI Global (2016)
Chang, C.J., et al.: An analysis of collaborative problem-solving activities mediated by individual-based and collaborative computer simulations. J. Comput. Assist. Learn. 33(6), 649–662 (2017)
Mislevy, R.J., Riconscente, M.M.: Evidence-centered assessment design: layers, concepts, and terminology. In: Downing, S., Haladyna, T. (eds.) Handbook of Test Development, pp. 61–90. Erlbaum, Mahwah (2006)
Shute, V.J., Ventura, M.: Stealth Assessment: Measuring and Supporting Learning in Video Games. MIT Press, Cambridge (2013)
Leighton, J.P.: Avoiding misconception, misuse, and missed opportunities: the collection of verbal reports in educational achievement testing. Educ. Measur. Issues Pract. 23(4), 6–15 (2004)
Saldaña, J.: The Coding Manual for Qualitative Researchers. Sage, London (2015)
Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction. SSS. Springer, New York (2009). https://doi.org/10.1007/978-0-387-84858-7
Camara, W., O’Connor, R., Mattern, K., Hanson, M.A.: Beyond Academics: A Holistic Framework for Enhancing Education and Workplace Success. ACT Research Report Series 2015 (4). ACT, Inc. (2015)
Acknowledgments
We are grateful to Prof. Valerie Shute and Dr. Lubin Wang from Florida State University for their support in this study.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
San Pedro, M.O.Z., Liu, R., McKinniss, T.L. (2019). Developing Game-Based Models of Cooperation, Persistence and Problem Solving from Collaborative Gameplay. In: Isotani, S., Millán, E., Ogan, A., Hastings, P., McLaren, B., Luckin, R. (eds) Artificial Intelligence in Education. AIED 2019. Lecture Notes in Computer Science(), vol 11626. Springer, Cham. https://doi.org/10.1007/978-3-030-23207-8_46
Download citation
DOI: https://doi.org/10.1007/978-3-030-23207-8_46
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-23206-1
Online ISBN: 978-3-030-23207-8
eBook Packages: Computer ScienceComputer Science (R0)