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Conference Paper: Collaborative and Individual Problem Solving in Computational Thinking Through Programming: A Meta-Analysis

TitleCollaborative and Individual Problem Solving in Computational Thinking Through Programming: A Meta-Analysis
Authors
Issue Date2020
PublisherAll Academic, Inc.
Citation
The American Educational Research Association (AERA) Annual Meeting, San Francisco, USA, 17-21 April 2020 (Conference Canceled due to COVID-19 Pandemic) How to Cite?
AbstractThis meta-analysis aims at examining overall effects of collaborative versus individual problem-solving in programming on cognitive and affective learning outcomes. We searched four databases systematically and identified 12 publications accounted for 40 effect size comparisons on cognitive learning outcomes. We found medium effect size (g = 0.537; p = .006) in favor of collaborative programming on cognitive learning outcomes, which is statistically significant using random effects model. We also examined the moderating effects of education level, programming environment and study duration, of which education level and study duration are statistically significant. Inconsistent results were found on affective learning outcomes. More research focusing social aspects is needed to study the collaborative problem solving in visual programming and robotics programming.
DescriptionRoundtable Session: Computational Thinking and Computer Science in Elementary School Contexts
Persistent Identifierhttp://hdl.handle.net/10722/308416

 

DC FieldValueLanguage
dc.contributor.authorLAI, X-
dc.contributor.authorYE, J-
dc.contributor.authorWong, KWG-
dc.date.accessioned2021-12-01T07:53:03Z-
dc.date.available2021-12-01T07:53:03Z-
dc.date.issued2020-
dc.identifier.citationThe American Educational Research Association (AERA) Annual Meeting, San Francisco, USA, 17-21 April 2020 (Conference Canceled due to COVID-19 Pandemic)-
dc.identifier.urihttp://hdl.handle.net/10722/308416-
dc.descriptionRoundtable Session: Computational Thinking and Computer Science in Elementary School Contexts-
dc.description.abstractThis meta-analysis aims at examining overall effects of collaborative versus individual problem-solving in programming on cognitive and affective learning outcomes. We searched four databases systematically and identified 12 publications accounted for 40 effect size comparisons on cognitive learning outcomes. We found medium effect size (g = 0.537; p = .006) in favor of collaborative programming on cognitive learning outcomes, which is statistically significant using random effects model. We also examined the moderating effects of education level, programming environment and study duration, of which education level and study duration are statistically significant. Inconsistent results were found on affective learning outcomes. More research focusing social aspects is needed to study the collaborative problem solving in visual programming and robotics programming.-
dc.languageeng-
dc.publisherAll Academic, Inc. -
dc.relation.ispartofAERA (American Educational Research Association) Annual Meeting, 2020 (Conference Canceled)-
dc.titleCollaborative and Individual Problem Solving in Computational Thinking Through Programming: A Meta-Analysis-
dc.typeConference_Paper-
dc.identifier.emailWong, KWG: wongkwg@hku.hk-
dc.identifier.authorityWong, KWG=rp02193-
dc.identifier.hkuros330582-
dc.publisher.placeUnited States-

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