Collaborative and Individual Problem Solving in Computational Thinking Through Programming: A Meta-Analysis

• In Event: Moscone Center North Roundtable Session 14
  In Roundtable Session: Computational Thinking and Computer Science in Elementary School Contexts

Abstract

This meta-analysis aims at examining overall effects of collaborative versus individual problem-solving in programming on cognitive and affective learning outcomes. We searched four databases systematically and identified 12 publications accounted for 40 effect size comparisons on cognitive learning outcomes. We found medium effect size (g = 0.537; p = .006) in favor of collaborative programming on cognitive learning outcomes, which is statistically significant using random effects model. We also examined the moderating effects of education level, programming environment and study duration, of which education level and study duration are statistically significant. Inconsistent results were found on affective learning outcomes. More research focusing social aspects is needed to study the collaborative problem solving in visual programming and robotics programming.

Authors

• Xiaoyan LAI, The University of Hong Kong

• Jiachu Ye, The University of Hong Kong

• Ka Wai Gary Wong, The University of Hong Kong