A Meta-Analysis Examining the Effects of STEM+CT Interventions on Computational Thinking

• In Event: Integrating Computer Science and Technological, Pedagogical, and Content Knowledge in Teaching and Learning

Abstract

The purpose of this meta-analysis is to examine the effects of computational thinking integration in STEM learning on students’ computational thinking in K-12 education. Following systematic procedures, we identified 19 qualified studies in which we extracted effect sizes on students’ computational in one-group pre-test to post-test designs. We also examined moderating variables, including student level, STEM content type, intervention duration, type of intervention (e.g., simulation), and computational thinking dimensions. Overall, we found a statistically significant large effect size (g = 0. 86 [95% CI of 0.498 to 1.227]; p < .001). The moderating variables were not statistically significant. We provide a discussion of the findings and present implications for future research and practice.

Authors

• Li Cheng, Worcester Polytechnic Institute
  Presenting Author

• Xiaoman Wang, University of Florida
  Presenting Author

• Albert Dieter Ritzhaupt, University of Florida
  Presenting Author