Project Activities
Focused program of research
The initial intervention to be developed was a 2-dimentional (2D) game so researchers can better understand how variables such as reasoning, practice, and feedback affect outcomes. A commercial game design partner, Tabula Digita, then created a 3-dimensional (3D) game based on the 2D efficacy findings. To succeed in the game, students used math skills to maneuver through various levels, whose difficulty varied online via an embedded self-assessment component.
In addition to designing "serious games" for student use, the Center team also examined the teachers' views of the games and their content strengths and gaps, and then provided the teachers with professional development and other supports to increase their knowledge and receptivity to games, which will be studied experimentally. The Center team conducted an in-depth investigation of students' interests, knowledge, and expectations through focus groups, cognitive task analyses, and other qualitative protocols and tests of their background knowledge. The Center team also produced guidelines for researchers and practitioners at key points in the program of research, culminating in a set of comprehensive guidelines.
Structured Abstract
Research design and methods
The efficacy study included 45 classrooms from 15 schools, whereby classrooms were randomly assigned to one of three groups: (1) students used the game in the classroom; (2) students used the game in the classroom and practice homework using the game at home; and (3) students received the standard curriculum (control group). A variety of standardized measures assessed the impact of the intervention on students' math learning. Supplemental measures assessed students' self-concept and teachers' attitudes. Hierarchical linear models were employed to examine the effect of the intervention on students' achievement.
People and institutions involved
IES program contact(s)
Project contributors
Products and publications
ERIC Citations: Find available citations in ERIC for this award here.
Book chapter
Baker, E.L. (2014). Learning and Assessment: Twenty-First Century Skills and Cognitive Readiness. In H.F. O'Neil, and R.S. Perez (Eds.), Teaching and Measuring Cognitive Readiness(pp. 53-70). New York: Springer.
Chung, G.K., and Delacruz, G.C. (2014). Cognitive Readiness for Solving Equations. In H.F. O'Neil, and R.S. Perez (Eds.), Teaching and Measuring Cognitive Readiness(pp. 135-148). New York: Springer.
Holyoak, K.J. (2012). Analogy and Relational Reasoning. The Oxford Handbook of Thinking and Reasoning (pp. 234-259). New York: Oxford Press.
Mislevy, R.J., Behrens, J.T., Dicerbo, K.E., Frezzo, D.C., and West, P. (2012). Three Things Game Designers Need to Know About Assessment. Assessment in Game-Based Learning (pp. 59-81). New York: Springer.
Stripling, R., and Chang, G. (2013). Brain Activity Based Assessment (BABA). Foundations of Augmented Cognition, Volume 8027 (pp. 390-398). Berlin Heidelberg: Springer.
Journal article, monograph, or newsletter
Kerr, D., and Chung, G.K. (2012). Identifying Key Features of Student Performance in Educational Video Games and Simulations Through Cluster Analysis. Journal of Educational Data Mining, 4(1): 144-182.
Mislevy, R., Behrens, J.T., Dicerbo, K.E., and Levy, R. (2012). Design and Discovery in Educational Assessment: Evidence-Centred Design, Psychometrics, and Educational Data Mining. Journal of Educational Data Mining, 4(1): 11-48.
O'Neil, H.F., Chung, G.K., Kerr, D., Vendlinski, T.P., Buschang, R. E., and Mayer, R.E. (2014). Adding Self-Explanation Prompts to an Educational Computer Game. Computers in Human Behavior, 30: 23-28. doi:10.1016/j.chb.2013.07.025
Richland, L.E., Stigler, J.W., and Holyoak, K.J. (2012). Teaching the Conceptual Structure of Mathematics. Educational Psychologist, 47(3): 189-203.
Rupp, A.A., Levy, R., DiCerbo, K., Sweet, S., Crawford, A.V., Calico, T., Benson, Martin; Fay, D., Kunze, K.L., Mislevy, R.J., and Behrens, J.T. (2012). Putting ECD Into Practice: The Interplay of Theory and Data in Evidence Models Within a Digital Learning Environment. Journal of Educational Data Mining, 4(1): 49-110.
Proceeding
Kerr, D., and Chung, G.K. (2013). Identifying Learning Trajectories in an Educational Video Game. In Proceedings of the 2013 Uncertainty in Artificial Intelligence Application Workshops, Volume 1024 (pp. 20-28). Seattle, WA: UAI.
Lee, H.S., Thompson, B.J., Holyoak, K.J., and Stigler, J.W. (2010). Learning Inter-Related Concepts in Mathematics From Videogames. In Proceedings of the 9th International Conference of the Learning Sciences, Volume 2 (pp. 445-446). online: International Society of the Learning Sciences.
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