Abstract
Well-designed digital games hold promise as effective learning environments. However, designing games that support both learning and engagement without disrupting flow [1] is quite tricky. In addition to including various game design features (e.g., interactive problem solving, adaptive challenges, and player control of gameplay) to engage players, the game needs ongoing assessment and support of players’ knowledge and skills. In this chapter, we (a) generally discuss various types of learning supports and their influence on learning in educational games, (b) describe stealth assessment in the context of the design and development of particular supports within a game called Physics Playground [2], (c) present the results from recent usability studies examining the effects of our new supports on learning, and (d) provide insights into the future of game-based learning analytics in the form of stealth assessment that will be used for adaptation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper and Row.
Shute, V. J., & Ventura, M. (2013). Stealth assessment: Measuring and supporting learning in video games. Cambridge, Massachusetts: The MIT Press.
Ravitch, D. (2000). Left back: A century of failed school reforms. New York: Simon & Schuster.
Shute, V.J. (2007). Tensions, trends, tools, and technologies: Time for an educational sea change. In: C. A. Dwyer. (Eds.), The future of assessment: Sha** teaching and learning. (pp. 139–187). Lawrence Erlbaum Associates, Taylor & Francis Group, New York, NY.
Kliebard, H. (1987). The struggle for the American curriculum, 1893–1958. New York: Routledge and Kegan Paul.
Bobbitt, J. F. (1912). The elimination of waste in education. The Elementary School Teacher., 12, 259–271.
Lemann, N. (1999). The IQ meritocracy: Our test-obsessed society has Binet and Terman to thank—or to blame [Electronic version]. Times, 153, 115–116.
Clark, D. B., Tanner-Smith, E. E., & Killingsworth, S. S. (2016). Digital games, design, and learning: A Systematic review and meta-analysis. Review of Educational Research., 86, 79–122.
Castell, S. D., Jenson, J. (2003). Serious play: Curriculum for a post-talk era. Journal of the Canadian Association for Curriculum Studies, 1.
Prensky, M. (2001). Digital game-based learning. New York: McGraw-Hill.
Habgood, M. P. J., Ainsworth, S. E., & Benford, S. (2005). Endogenous fantasy and learning in digital games. Simulation & Gaming., 36, 483–498.
Ritterfeld, U., Shen, C., Wang, H., Nocera, L., & Wong, W. L. (2009). Multimodality and interactivity: Connecting properties of serious games with educational outcomes. CyberPsychology & Behavior, 12, 691–697.
Black, A. E., & Deci, E. L. (2000). The effects of instructors’ autonomy support and students’ autonomous motivation on learning organic chemistry: A self-determination theory perspective. Science Education, 84, 740–756.
Wouters, P., & van Oostendorp, H. (2013). A meta-analytic review of the role of instructional support in game-based learning. Computers & Education, 60, 412–425.
Shute, V. J. (2011). Stealth assessment in computer-based games to support learning. In S. Tobias & J. D. Fletcher (Eds.), Computer games and instruction (pp. 503–524). Charlotte, NC: Information Age Publishers.
Mislevy, R. J., Steinberg, L. S., Almond, R. G.(2003). Focus article: On the structure of educational assessments. Measurement: Interdisciplinary Research & Perspective, 1, 3–62.
Shute, V., Ke, F., & Wang, L. (2017). Assessment and adaptation in games. In P. Wouters & H. van Oostendorp (Eds.), Instructional techniques to facilitate learning and motivation of serious games (pp. 59–78). Cham: Springer.
DiCerbo, K. E., & Behrens, J. T. (2012). Implications of the digital ocean on current and future assessment. In R. Lissitz & H. J. Jiao (Eds.), Computers and their impact on state assessment: Recent history and predictions for the future (pp. 273–306). Charlotte, NC: Information Age.
Shute, V. J., Hansen, E. G., & Almond, R. G. (2008). You can’t fatten a hog by weighing it—Or can you? Evaluating an assessment for learning system called ACED. International Journal of Artificial Intelligence in Education, 18, 289–316.
Sun, C., Shute, V. J., Stewart, A., Yonehiro, J., Duran, N., D’Mello, S. Toward a generalized competency model of collaborative problem solving. Computers & Education. (in press).
Barzilai, S., & Blau, I. (2014). Scaffolding game-based learning: Impact on learning achievements, perceived learning, and game experiences. Computers & Education, 70, 65–79.
Lang, J., O’Neil, H. (2008). The effect of presenting just-in-time worked examples for problem solving in a computer game. In Presented at the American Educational Research Association Conference, New York.
Pea, R. D. (2004). The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity. Journal of the Learning Sciences, 13, 423–451.
Leutner, D. (1993). Guided discovery learning with computer-based simulation games: Effects of adaptive and non-adaptive instructional support. Learning and Instruction, 3, 113–132.
O’Rourke, E., Ballweber, C., PopoviĂ, Z.(2014). Hint systems may negatively impact performance in educational games. In Presented at the Proceedings of the first ACM conference on Learning @ scale conference. Atlanta, GA, USA March 4.
Ginns, P. (2005). Meta-analysis of the modality effect. Learning and Instruction, 15, 313–331.
Moreno, R., & Mayer, R. E. (2002). Learning science in virtual reality multimedia environments: Role of methods and media. Journal of Educational Psychology, 94, 598–610.
Cowley, B., Charles, D., & Black, M. (2008). Toward an understanding of flow in video games. Computers in Entertainment, 6, 1–27.
Vygotsky, L. S. (1978). Mind in society: The development of higher mental processes. Cambridge, MA: Harvard University Press.
Shute, V. J., & Zapata-Rivera, D. (2012). Adaptive educational systems. In P. Durlach (Ed.), Adaptive technologies for training and education (pp. 7–27). New York, NY: Cambridge University Press.
Kickmeier-Rust, M. D., & Albert, D. (2010). Micro-adaptivity: Protecting immersion in didactically adaptive digital educational games: Micro-adaptivity in digital educational games. Journal of Computer Assisted learning, 26, 95–105.
Shute, V. J., Graf, E. A., Hansen, E. G.(2005). Designing adaptive, diagnostic math assessments for individuals with and without visual disabilities. In L. PytlikZillig, R. Bruning, M. Bodvarsson (Eds.), Technology-based education: Bringing researchers and practitioners together. pp. 169–202. Information Age Publishing, Greenwich, CT.
Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research., 78, 153–189.
Peirce, N., Conlan, O., Wade, V.(2008). Adaptive educational games: Providing non-invasive personalised learning experiences. In: 2008 Second IEEE International Conference on Digital Game and Intelligent Toy Enhanced Learning, pp. 28–35. IEEE, Banff, AB, Canada.
Hatano, G. (1982). Cognitive consequences of practice in culture specific procedural skills. Quarterly Newsletter of the Laboratory of Comparative Human Cognition., 4, 15–18.
Verschaffel, L., Luwel, K., Torbeyns, J., & Van Dooren, W. (2009). Conceptualizing, investigating, and enhancing adaptive expertise in elementary mathematics education. European Journal of Psychology of Education, 24, 335.
Shute, V., Ventura, M., Kim, Y. J., & Wang, L. (2014). Video games and learning. In W. G. Tierney, Z. Corwin, T. Fullerton, & G. Ragusa (Eds.), Postsecondary play: The role of games and social media in higher education (pp. 217–235). Baltimore, MD: John Hopkins University Press.
Shute, V. J., D’Mello, S., Baker, R., Cho, K., Bosch, N., Ocumpaugh, J., et al. (2015). Modeling how incoming knowledge, persistence, affective states, and in-game progress influence student learning from an educational game. Computers & Education, 86, 224–235.
Taylor, W. L. (1953). “Cloze procedure”: A new tool for measuring readability. Journalism Bulletin, 30, 415–433.
Shute, V. J., Ventura, M., & Kim, Y. J. (2013). Assessment and learning of qualitative physics in Newton’s playground. The Journal of Educational Research., 106, 423–430.
Lopes, R., & Bidarra, R. (2011). Adaptivity challenges in games and simulations: A survey. IEEE Transactions on Computational Intelligence and AI in Games., 3, 85–99.
Karumbaiah, S., Baker, R. S., Shute, V. (2018). Predicting quitting in students playing a learning game. In 11th International Conference on Educational Data Mining, pp. 1–10. Buffalo, NY.
Acknowledgements
We wish to express our gratitude to the funding by the US National Science Foundation (NSF #037988) and the US Department of Education (IES #039019) for generously supporting this research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Shute, V., Rahimi, S., Smith, G. (2019). Game-Based Learning Analytics in Physics Playground. In: Tlili, A., Chang, M. (eds) Data Analytics Approaches in Educational Games and Gamification Systems. Smart Computing and Intelligence. Springer, Singapore. https://doi.org/10.1007/978-981-32-9335-9_4
Download citation
DOI: https://doi.org/10.1007/978-981-32-9335-9_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-32-9334-2
Online ISBN: 978-981-32-9335-9
eBook Packages: Computer ScienceComputer Science (R0)