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Unpacking the Effects of GenAI on Cultivating Students' Computational Thinking: A Meta-Analysis

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Title: Unpacking the Effects of GenAI on Cultivating Students' Computational Thinking: A Meta-Analysis
Language: English
Authors: Jie Xu (ORCID 0000-0003-3345-4116), Zexi Chen (ORCID 0009-0003-4406-1390), Mengyao Chen, Yan Li, Xianlong Xu (ORCID 0000-0003-0736-7932)
Source: Journal of Educational Computing Research. 2026 64(4):1024-1067.
Availability: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
Peer Reviewed: Y
Page Count: 44
Publication Date: 2026
Document Type: Journal Articles
Information Analyses
Education Level: Elementary Secondary Education
Postsecondary Education
Descriptors: Computation, Thinking Skills, Problem Solving, Artificial Intelligence, Technology Uses in Education, Effect Size, Instructional Program Divisions, Elementary Secondary Education, Postsecondary Education, Geographic Regions, Intervention, Incidence, Teaching Methods, Interaction, Role, Feedback (Response)
DOI: 10.1177/07356331261419586
ISSN: 0735-6331
1541-4140
Abstract: Computational thinking (CT) is crucial for enhancing students' complex problem-solving abilities in the intelligent era. The emergence of generative artificial intelligence (GenAI) is profoundly transforming the global educational landscape and demonstrating significant potential for promoting personalized learning. However, the literature offers varied results on the effectiveness of using GenAI to cultivate students' CT. This study comprehensively investigated the effects of GenAI on students' CT and the role of moderating factors, integrating 45 effect sizes from 25 empirical studies published between 2022 and 2025. A theoretical framework of factors influencing students' CT was proposed based on activity theory, and the moderating factors included educational level, region, intervention duration, teaching mode, interaction mode, role setting, and feedback type. The results indicated that GenAI had a significant overall positive effect on students' CT development. Specifically, the largest effect size was computational practice, followed by computational concept and computational perspective. Furthermore, the analysis revealed that region, teaching mode, and interaction mode had significant moderating effects. Based on these results, this study offers targeted implications across the dimensions of theoretical foundation, educational practice, and technological development, providing empirical evidence for implementing GenAI teaching and developing GenAI tools to cultivate students' CT.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1502166
Database: ERIC
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  Data: Unpacking the Effects of GenAI on Cultivating Students' Computational Thinking: A Meta-Analysis
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  Data: <searchLink fieldCode="AR" term="%22Jie+Xu%22">Jie Xu</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-3345-4116">0000-0003-3345-4116</externalLink>)<br /><searchLink fieldCode="AR" term="%22Zexi+Chen%22">Zexi Chen</searchLink> (ORCID <externalLink term="https://orcid.org/0009-0003-4406-1390">0009-0003-4406-1390</externalLink>)<br /><searchLink fieldCode="AR" term="%22Mengyao+Chen%22">Mengyao Chen</searchLink><br /><searchLink fieldCode="AR" term="%22Yan+Li%22">Yan Li</searchLink><br /><searchLink fieldCode="AR" term="%22Xianlong+Xu%22">Xianlong Xu</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-0736-7932">0000-0003-0736-7932</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Educational+Computing+Research%22"><i>Journal of Educational Computing Research</i></searchLink>. 2026 64(4):1024-1067.
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  Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com
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  Data: 44
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  Data: <searchLink fieldCode="DE" term="%22Computation%22">Computation</searchLink><br /><searchLink fieldCode="DE" term="%22Thinking+Skills%22">Thinking Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+Solving%22">Problem Solving</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Effect+Size%22">Effect Size</searchLink><br /><searchLink fieldCode="DE" term="%22Instructional+Program+Divisions%22">Instructional Program Divisions</searchLink><br /><searchLink fieldCode="DE" term="%22Elementary+Secondary+Education%22">Elementary Secondary Education</searchLink><br /><searchLink fieldCode="DE" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink><br /><searchLink fieldCode="DE" term="%22Geographic+Regions%22">Geographic Regions</searchLink><br /><searchLink fieldCode="DE" term="%22Intervention%22">Intervention</searchLink><br /><searchLink fieldCode="DE" term="%22Incidence%22">Incidence</searchLink><br /><searchLink fieldCode="DE" term="%22Teaching+Methods%22">Teaching Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Interaction%22">Interaction</searchLink><br /><searchLink fieldCode="DE" term="%22Role%22">Role</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+%28Response%29%22">Feedback (Response)</searchLink>
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  Data: 10.1177/07356331261419586
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  Data: 0735-6331<br />1541-4140
– Name: Abstract
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  Data: Computational thinking (CT) is crucial for enhancing students' complex problem-solving abilities in the intelligent era. The emergence of generative artificial intelligence (GenAI) is profoundly transforming the global educational landscape and demonstrating significant potential for promoting personalized learning. However, the literature offers varied results on the effectiveness of using GenAI to cultivate students' CT. This study comprehensively investigated the effects of GenAI on students' CT and the role of moderating factors, integrating 45 effect sizes from 25 empirical studies published between 2022 and 2025. A theoretical framework of factors influencing students' CT was proposed based on activity theory, and the moderating factors included educational level, region, intervention duration, teaching mode, interaction mode, role setting, and feedback type. The results indicated that GenAI had a significant overall positive effect on students' CT development. Specifically, the largest effect size was computational practice, followed by computational concept and computational perspective. Furthermore, the analysis revealed that region, teaching mode, and interaction mode had significant moderating effects. Based on these results, this study offers targeted implications across the dimensions of theoretical foundation, educational practice, and technological development, providing empirical evidence for implementing GenAI teaching and developing GenAI tools to cultivate students' CT.
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  Data: 2026
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  Data: EJ1502166
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        Value: 10.1177/07356331261419586
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      – Text: English
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        PageCount: 44
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    Subjects:
      – SubjectFull: Computation
        Type: general
      – SubjectFull: Thinking Skills
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