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dc.contributor.authorJu, Zeyu
dc.date.accessioned2024-06-11T23:15:53Z
dc.date.available2024-06-11T23:15:53Z
dc.date.issued2024en_AU
dc.identifier.urihttps://hdl.handle.net/2123/32647
dc.description.abstractIn 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.en_AU
dc.language.isoenen_AU
dc.subjectcollaborationen_AU
dc.subjectcollaborative problem solvingen_AU
dc.subjectcomputational thinkingen_AU
dc.subjectmeta-analysisen_AU
dc.subjectprogrammingen_AU
dc.titleComputational thinking through programming: a meta-analysis of collaborative versus solo problem solvingen_AU
dc.typeThesis
dc.type.thesisMasters by Researchen_AU
dc.rights.otherThe 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.en_AU
usyd.facultyFaculty of Arts and Social Sciencesen_AU
usyd.facultySydney School of Education and Social Worken_AU
usyd.degreeMaster of Arts (Research) M.A.(Res.)en_AU
usyd.awardinginstThe University of Sydneyen_AU
usyd.advisorReimann, Peter
usyd.advisorJacobson, Michael


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