Digital Games, Design, and Learning: A Systematic Review and Meta-Analysis

In the April 2015 edition of Review of Educational Research can be found:

Digital Games, Design, and Learning: A Systematic Review and Meta-Analysis.

Authors: Douglas B. Clark, Emily E. Tanner-Smith, and Stephen S. Killingsworth.

Abstract: In this meta-analysis, we systematically reviewed research on digital games and learning for K–16 students. We synthesized comparisons of game versus nongame conditions (i.e., media comparisons) and comparisons of augmented games versus standard game designs (i.e., value-added comparisons). We used random-effects meta-regression models with robust variance estimates to summarize overall effects and explore potential moderator effects. Results from media comparisons indicated that digital games significantly enhanced student learning relative to nongame conditions (g = 0.33, 95% confidence interval [0.19, 0.48], k = 57, n = 209). Results from value added comparisons indicated significant learning benefits associated with augmented game designs (g = 0.34, 95% confidence interval [0.17, 0.51], k = 20, n = 40). Moderator analyses demonstrated that effects varied across various game mechanics characteristics, visual and narrative characteristics, and research quality characteristics. Taken together, the results highlight the affordances of games for learning as well as the key role of design beyond medium.

My notes: One swallow doesn’t make a summer, and one paper doesn’t “prove” that digital games are jolly useful things to use in education, learning and teaching. However, every so often an article, paper or report of the thousands (yes, thousands) published on games in learning every year comes along that does show something significant, has some persuasive analysis in it, and is definitely worth a read. This recent paper is one. The work looks at research published between 2000 and 2012 and was funded by the Bill and Melinda Gates Foundation. There’s a brief, and far less technical, summary document which introduces the various hypotheses. It’s a long text; the statistics within are somewhat hardcore (and my first degree was in statistics), and it’s a good few hours of concentrated reading. The reference section is also pretty good.

More information at:

n.b. Thanks to Doug for a copy of a version of the paper.