Computational thinking through programming: a meta-analysis of collaborative versus solo problem solving
Access status:
Open Access
Type
ThesisThesis type
Masters by ResearchAuthor/s
Ju, ZeyuAbstract
In the current era is characterized by rapid advancements in artificial intelligence. Defined as the ability to approach problem-solving through a computational lens—much like computer programming and algorithm design—computational thinking is increasingly valued in computer ...
See moreIn the current era is characterized by rapid advancements in artificial intelligence. Defined as the ability to approach problem-solving through a computational lens—much like computer programming and algorithm design—computational thinking is increasingly valued in computer education. Researchers and educators alike have recognized the importance of integrating computational thinking with collaborative practices within educational settings, however, there exists a gap in the literature concerning the impact and effectiveness of collaboration for the development of computational thinking skills. To address this void, the present study conducted a meta-analysis focused on comparing the outcomes of collaborative problem-solving through programming with solo problem-solving. By aggregating data from 40 distinct studies, this research encompasses a broad spectrum of learners with which to compare effect sizes across multiple contexts. Utilizing a random effects model, the study found significant differences between collaborative and individual problem-solving methods. Specifically, moderate effects were observed in cognitive learning outcomes and a smaller effect was also noted in the affective domain. The study also included other factors—such as educational level, programming environments used, duration of study, grouping method, and group size—related to when and how collaboration becomes most effective. The competency model created through this meta-analysis is built upon existing pedagogical theories and learning design literature. It synthesizes a diverse array of knowledge to present a cohesive framework for understanding and evaluating collaborative problem-solving in the realm of computing. The insights derived from this review contribute to our understanding of collaborative practices in computational thinking education and the findings may also be useful for educators, curriculum designers, and researchers.
See less
See moreIn the current era is characterized by rapid advancements in artificial intelligence. Defined as the ability to approach problem-solving through a computational lens—much like computer programming and algorithm design—computational thinking is increasingly valued in computer education. Researchers and educators alike have recognized the importance of integrating computational thinking with collaborative practices within educational settings, however, there exists a gap in the literature concerning the impact and effectiveness of collaboration for the development of computational thinking skills. To address this void, the present study conducted a meta-analysis focused on comparing the outcomes of collaborative problem-solving through programming with solo problem-solving. By aggregating data from 40 distinct studies, this research encompasses a broad spectrum of learners with which to compare effect sizes across multiple contexts. Utilizing a random effects model, the study found significant differences between collaborative and individual problem-solving methods. Specifically, moderate effects were observed in cognitive learning outcomes and a smaller effect was also noted in the affective domain. The study also included other factors—such as educational level, programming environments used, duration of study, grouping method, and group size—related to when and how collaboration becomes most effective. The competency model created through this meta-analysis is built upon existing pedagogical theories and learning design literature. It synthesizes a diverse array of knowledge to present a cohesive framework for understanding and evaluating collaborative problem-solving in the realm of computing. The insights derived from this review contribute to our understanding of collaborative practices in computational thinking education and the findings may also be useful for educators, curriculum designers, and researchers.
See less
Date
2024Rights statement
The author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.Faculty/School
Faculty of Arts and Social SciencesSydney School of Education and Social Work
Awarding institution
The University of SydneyShare