Emerging Practices in Game-Based Assessment

  • Vipin VermaEmail author
  • Tyler Baron
  • Ajay Bansal
  • Ashish Amresh
Part of the Advances in Game-Based Learning book series (AGBL)


Educational assessment has evolved over the past several years from traditional pen and paper-based tests to the use of technology (such as games) and continues to evolve. The assessments must provide feedback to learners and diagnostic information to teachers. Game-based learning offers an interactive environment for the students to learn in a fun and challenging way while keeping them engaged in the learning process. Game-based assessment (GBA) offers a way to assess them in this setting while they are interacting with a game. GBA may be composed of built-in quizzes and surveys to assess the student learning while they are playing. However, such methods tend to distract their attention from learning to complete the assessment. Stealth assessment is a way to assess the learners while they are playing an educational video game without breaking their flow. The future of GBA will be made up of a content-agnostic stealth assessment with a model of student’s knowledge built into it. The student model will help to adapt the game-play and accommodate the game to an individual learner. Content-agnostic game engineering (CAGE) is a framework that helps provide multiple learning contents within a single game to achieve content-agnostic assessment. Finally, adding a student model which makes the game and learning adapt to an individual student driven by their pace and performance while learning in the game is the need of the hour.


Game-based assessment Stealth assessment Content-agnostic assessment Student model Mouse-tracking 


  1. Baron, T. (2017). An Architecture for Designing Content Agnostic Game Mechanics for Educational Burst Games (Doctoral dissertation, Arizona State University).Google Scholar
  2. Baron, T., & Amresh, A. (2015). Word towers: Assessing domain knowledge with non-traditional genres. In European Conference on Games Based Learning (p. 638). Academic Conferences International Limited.Google Scholar
  3. Bellotti, F., Kapralos, B., Lee, K., Moreno-Ger, P., & Berta, R. (2013). Assessment in and of serious games: An overview. Advances in Human-Computer Interaction, 2013, 1.Google Scholar
  4. Birk, M. V., Mandryk, R. L., & Atkins, C. (2016, October). The motivational push of games: The interplay of intrinsic motivation and external rewards in games for training. In Proceedings of the 2016 Annual Symposium on Computer-Human Interaction in Play (pp. 291–303). New York, NY: ACM.CrossRefGoogle Scholar
  5. Brawl Stars. (2017). Supercell.Google Scholar
  6. Chatzisarantis, N. L., Biddle, S. J., & Meek, G. A. (1997). A self-determination theory approach to the study of intentions and the intention–behaviour relationship in children’s physical activity. British Journal of Health Psychology, 2(4), 343–360.CrossRefGoogle Scholar
  7. Cheng, M.-T., Rosenheck, L., Lin, C.-Y., & Klopfer, E. (2017). Analyzing gameplay data to inform feedback loops in the radix endeavor. Computers & Education, 111, 60–73.CrossRefGoogle Scholar
  8. Chin, J., Dukes, R., & Gamson, W. (2009). Assessment in simulation and gaming: A review of the last 40 years. Simulation & Gaming, 40(4), 553–568.CrossRefGoogle Scholar
  9. Conrad, S., Clarke-Midura, J., & Klopfer, E. (2014). A framework for structuring learning assessment in a massively multiplayer online educational game: Experiment centered design. International Journal of Game-Based Learning (IJGBL), 4(1), 37–59.CrossRefGoogle Scholar
  10. Corbett, A. T., & Anderson, J. R. (1994). Knowledge tracing: Modeling the acquisition of procedural knowledge. User Modeling and User-Adapted Interaction, 4(4), 253–278.CrossRefGoogle Scholar
  11. Csikszentmihalyi, M. (1975). Play and intrinsic rewards. Journal of Humanistic Psychology, 75, 41.Google Scholar
  12. Baker, R. S., Gowda, S. M., Wixon, M., Kalka, J., Wagner, A. Z., Salvi, A., ... & Rossi, L. (2012). Towards sensor-free affect detection in cognitive tutor algebra. International Educational Data Mining Society.Google Scholar
  13. D’Mello, S., & Graesser, A. (2010, June). Mining bodily patterns of affective experience during learning. In Educational data mining 2010.Google Scholar
  14. Deci, E. L., & Ryan, R. M. (2008). Self-determination theory: A macrotheory of human motivation, development, and health. Canadian Psychology/Psychologie Canadienne, 49(3), 182.CrossRefGoogle Scholar
  15. Deci, E. L., & Vansteenkiste, M. (2004). Self-determination theory and basic need satisfaction: Understanding human development in positive psychology. Ricerche di psicologia.Google Scholar
  16. Dragon Age: Origins. (2009). BioWare.Google Scholar
  17. Ekman, P., & Friesen, W. V. (1978). Facial action coding system: Investigator’s guide. Palo Alto, CA: Consulting Psychologists Press.Google Scholar
  18. Faulkenberry, T. J. (2016). Testing a direct mapping versus competition account of response dynamics in number comparison. Journal of Cognitive Psychology, 28(7), 825–842.CrossRefGoogle Scholar
  19. Fletcher, J., & Tobias, S. (2011). Computer games and instruction. Charlotte, NC: Information Age Publishing.Google Scholar
  20. Freeman, B., & Higgins, K. (2016). A randomised controlled trial of a digital learning game in the context of a design-based research project. International Journal of Technology Enhanced Learning, 8(3–4), 297–317.CrossRefGoogle Scholar
  21. Freeman, J. B., & Ambady, N. (2009). Motions of the hand expose the partial and parallel activation of stereotypes. Psychological Science, 20(10), 1183–1188.CrossRefGoogle Scholar
  22. Freire, M., Serrano-Laguna, Á., Iglesias, B. M., Martínez-Ortiz, I., Moreno-Ger, P., & Fernández-Manjón, B. (2016). Game learning analytics: Learning analytics for serious games. In Learning, design, and technology (pp. 1–29). Cham, Switzerland: Springer.Google Scholar
  23. Friedman, N., Geiger, D., & Goldszmidt, M. (1997). Bayesian network classifiers. Machine Learning, 29(2–3), 131–163.CrossRefGoogle Scholar
  24. García, P., Amandi, A., Schiaffino, S., & Campo, M. (2007). Evaluating Bayesian networks’ precision for detecting students’ learning styles. Computers & Education, 49(3), 794–808.CrossRefGoogle Scholar
  25. Gee, J. P. (2003). What video games have to teach us about learning and literacy. Computers in Entertainment (CIE), 1(1), 20–20.CrossRefGoogle Scholar
  26. Järvinen, A. (2008). Games without frontiers: Theories and methods for game studies and design. Tampere, Finland: Tampere University Press.Google Scholar
  27. Kibler, J. (2011). Cognitive disequilibrium. Encyclopedia of child behavior and development, 380–380.Google Scholar
  28. League of Legends. (2009). Riot Games.Google Scholar
  29. Lepora, N. F., & Pezzulo, G. (2015). Embodied choice: How action influences perceptual decision making. PLoS Computational Biology, 11(4), e1004110.CrossRefGoogle Scholar
  30. Malone, T. W. (1981). Toward a theory of intrinsically motivating instruction. Cognitive Science, 5(4), 333–369.CrossRefGoogle Scholar
  31. Metrics. (2019). Retrieved from
  32. Mislevy, R. J., Almond, R. G., & Lukas, J. F. (2003). A brief introduction to evidence-centered design. ETS Research Report Series, 2003(1), i–29.CrossRefGoogle Scholar
  33. Mislevy, R. J., Behrens, J. T., Dicerbo, K. E., & Levy, R. (2012). Design and discovery in educational assessment: Evidence-centered design, psychometrics, and educational data mining. Journal of Educational Data Mining, 4(1), 11–48.Google Scholar
  34. Moreno-Ger, P., Martinez-Ortiz, I., Freire, M., Manero, B., & Fernandez-Manjon, B. (2014). Serious games: A journey from research to application. In 2014 IEEE Frontiers in Education Conference (FIE) Proceedings (pp. 1–4). IEEE.Google Scholar
  35. Papesh, M. H., & Goldinger, S. D. (2012). Memory in motion: Movement dynamics reveal memory strength. Psychonomic Bulletin & Review, 19(5), 906–913.CrossRefGoogle Scholar
  36. Pardos, Z. A., & Heffernan, N. T. (2010). Modeling individualization in a Bayesian networks implementation of knowledge tracing. In International Conference on User Modeling, Adaptation, and Personalization (pp. 255–266). Berlin, Germany: Springer.CrossRefGoogle Scholar
  37. Plass, J. L., Homer, B. D., Kinzer, C. K., Chang, Y. K., Frye, J., Kaczetow, W., … Perlin, K. (2013). Metrics in simulations and games for learning. In Game analytics (pp. 697–729). London, UK: Springer.CrossRefGoogle Scholar
  38. Renard, L. (2016a). The ABC of a school without grades. An interview with Christel moors. Retrieved from
  39. Renard, L. (2016b). What is formative assessment? The 6 building blocks. Retrieved from
  40. Rheem, H., Verma, V., & Becker, V. (2017). Give and take in a moustracking choice paradigm. Poster presented at Proceedings of the 58th Annual Meeting of Psychonomic Society, Vancouver, BC.Google Scholar
  41. Rheem, H., Verma, V., & Becker, V. (2018). Use of mouse-tracking method to measure cognitive load. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 62, pp. 1982–1986). Los Angeles, CA: SAGE Publications.Google Scholar
  42. Ritterfeld, U., Cody, M., & Vorderer, P. (2009). Serious games: Mechanisms and effects. New York, NY: Routledge.CrossRefGoogle Scholar
  43. Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary Educational Psychology, 25(1), 54–67.CrossRefGoogle Scholar
  44. Ryan, R. M., LaGuardia, J. G., & Rawsthorne, L. J. (2005). Self-complexity and the authenticity of self-aspects: Effects on well being and resilience to stressful events. North American Journal of Psychology, 7(3), 431.Google Scholar
  45. Ryan, R. M., Rigby, C. S., & Przybylski, A. (2006). The motivational pull of video games: A self-determination theory approach. Motivation and Emotion, 30(4), 344–360.CrossRefGoogle Scholar
  46. Scheuer, O., & McLaren, B. M. (2012). Educational data mining. In Encyclopedia of the sciences of learning (pp. 1075–1079). Berlin, Germany: Springer.CrossRefGoogle Scholar
  47. Second Life. (2003). Linden Labs.Google Scholar
  48. Shute, V. J. (2011). Stealth assessment in computer-based games to support learning. Computer Games and Instruction, 55(2), 503–524. Google Scholar
  49. Shute, V. J., & Spector, J. M. (2008). Scorm 2.0 white paper: Stealth assessment in virtual worlds. Unpublished manuscript. Tallahassee, FL: Florida State UniversityGoogle Scholar
  50. Shute, V. J., & Ventura, M. (2013). Stealth assessment: Measuring and supporting learning in video games. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
  51. Sicart, M. (2008). Defining game mechanics. Game Studies, 8(2). Retrieved from:
  52. Snow, E., Jacovina, M., Varner, L., Dai, J., & McNamara, D. (2014, July). Entropy: A stealth measure of agency in learning environments. In Educational Data Mining 2014.Google Scholar
  53. Sørebø, Ø., & Hæhre, R. (2012). Investigating students’ perceived discipline relevance subsequent to playing educational computer games: A personal interest and self-determination theory approach. Scandinavian Journal of Educational Research, 56(4), 345–362.CrossRefGoogle Scholar
  54. Team Ico. (2005). Shadow of the Colossus (PlayStation 2).Google Scholar
  55. Van Eck, R. (2006). Digital game-based learning: It’s not just the digital natives who are restless. Educause Review, 41(2), 16.Google Scholar
  56. Vygotsky, L. (1978). Interaction between learning and development. Readings on the Development of Children, 23(3), 34–41.Google Scholar
  57. Wang, L., Shute, V. J., & Moore, G. (2015). Best practices and lessons learned of stealth assessment. Retrieved December, 9, 2015.Google Scholar
  58. West, D. M., & Bleiberg, J. (2013). Education technology success stories. Issues in Governance Studies.Google Scholar
  59. Yamauchi, T., & Xiao, K. (2018). Reading emotion from mouse cursor motions: Affective computing approach. Cognitive Science, 42(3), 771–819.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Vipin Verma
    • 1
    Email author
  • Tyler Baron
    • 1
  • Ajay Bansal
    • 1
  • Ashish Amresh
    • 1
  1. 1.Arizona State UniversityChandlerUSA

Personalised recommendations