Game-Based Learning for Students’ Computational Thinking: A Meta-Analysis

Abstract

Computational thinking (CT) education has drawn increasing attention from educators and researchers. This study conducted a meta-analysis of 27 empirical studies to examine the effectiveness of game-based learning (GBL) for fostering students’ CT. The effects of various factors on the learning process for acquiring CT were also examined. The results showed that (a) conducting GBL can foster students’ CT, and the overall effect was at the upper-middle level (Hedges’ g = .600, 95% CI [.465, .735], p < .001). (b) Furthermore, conducting GBL can improve students’ CT concepts (Hedges’ g = .916, 95% CI [.410, 1.423], p < .001), CT skills (Hedges’ g = .494, 95% CI [.389, .600], p < .001), and CT perspectives (Hedges’ g = .927, 95% CI [.039, 1.816], p < .05). (c) Additionally, game mode, teaching context, and participant characteristics have positive effects on CT. Based on the findings, it is suggested that using more unplugged games and video games, designing collaborative game activities, and tailoring approaches according to gender difference and programming experience can effectively promote CT. The results have significance for fostering students’ CT in GBL; it is further suggested that instruction processes be rationally designed.