Computational thinking (CT), which is a cognitive skill used to solve problems with computational solutions, has drawn increasing attention among researchers and practitioners due to the growing recognition of CT competence as a 21st century skill. Collaboration is commonly integrated into CT education to facilitate novice learning, but there is inadequate knowledge regarding the influences of collaboration in CT education. This meta-analysis examined the overall effects on the cognitive, social and affective competencies of collaborative versus individual problem solving in CT through programming. We identified 33 publications involving 4717 learners, which allowed for 220 effect size comparisons. We found a medium effect size (Hedges' g = 0.562; p < 0.001) in favour of collaborative problem solving on cognitive learning outcomes and a small effect size (Hedges' g = 0.316; p < 0.01) on affective learning outcomes using a randomeffects model. Categorical moderator analysis revealed the moderating effects of educational level, programming environment, study duration, grouping method and group size. The competency model that was generated from the synthesized literature on
Background: Computational thinking (CT) is regarded as an essential 21st-century skill, and attempts have been made to integrate it into other subjects. Instructional approaches to CT development and assessment in the field of computer science have attracted global attention, but the influence of CT skills on other subject areas is under-researched.Objective: Our goal is to investigate the transfer effects of CT in different subject areas and examine the educational characteristics of CT intervention approaches that promote the transfer of learning.Method: We carefully selected and reviewed 55 empirical studies from leading bibliographic databases and examined the transfer of CT using a meta-analysis and a qualitative synthesis. Results and Conclusions:We identified and summarized these effects in the fields of mathematics, science, engineering and the humanities. A meta-analysis of these studies identified a generally significant effect of the transfer of CT skills to other subject areas. We also explored the characteristics of CT interventions that aid the transfer of learning by qualitatively assessing the identified studies. The results of the review offer a holistic view of the trends in CT transfer research that can be used as a reference for both researchers and instructors. K E Y W O R D S computational thinking, meta-analysis, qualitative synthesis, transfer of learning 1 | INTRODUCTION Computational thinking (CT) has become a key motivator for bringing computer science back into K-12 schools (Tikva & Tambouris, 2021).CT is initially defined as a set of cognitive problem-solving skills originating from computer science (Wing, 2006), and gradually the notion of CT has been developed into a new cross-disciplinary literacy, which can be a vehicle for personal expression and can connect with other literacy practices (Kafai & Proctor, 2021). Grover and Pea (2013)
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