Block-based versus text-based programming environments on novice student learning outcomes: a meta-analysis study - Xu, Zhen; Ritzhaupt, Albert D.; Tian, Fengchun; Umapathy, Karthikeyan (Computer science education, 2019)
Background and Context: The use of block-based programming environments is purported to be a good way to gently introduce novice computer programmers to computer programming. A small, but growing body of research examines the differences between block-based and text-based programming environments. Objective: Thus, the purpose of this study was to examine the overall effect of block-based versus text-based programming environments on both cognitive and affective student learning outcomes. Method: Five academic databases were searched to identify literature meeting our inclusion criteria and resulted in 13 publications with 52 effect size comparisons on both cognitive and affective outcomes. Findings: We found small effect size (g = 0.245; p = .137; with a 95% confidence interval of −0.078 to 0.567) in favor of block-based programming environments on cognitive outcomes, and a trivial effect size (g = 0.195, p = .429; with a 95% confidence interval of −0.289 to 0.678) on affective outcomes. Both effect size calculations were statistically insignificant using random effects models. The effect sizes were examined for moderating effects by education level, learning environment, and study duration. Some evidence of publication bias was detected in these data. Implications: More research is needed to examine the utility and efficacy of block-based programming environments for novice programmers. Future studies should account for hybrid programming environments using novel research methods.