{"title":"STEM教育中整合计算思维对学生认知和非认知技能的影响：一项荟萃分析","authors":"Hanzhu Yang, Linlin Hu, Hao Wang, Yunfei Xin","doi":"10.1111/jcal.70079","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Computational thinking (CT) is a cognitive approach intricately linked with core competencies in Science, Technology, Engineering, and Mathematics (STEM). Numerous studies have explored strategies to effectively integrate CT into STEM education and systematically evaluated the multidimensional impact on student learning outcomes.</p>\n </section>\n \n <section>\n \n <h3> Objectives and Methods</h3>\n \n <p>This meta-analysis synthesises findings from 46 high-quality empirical studies to verify the effectiveness of integrating CT into STEM on the development of students' cognitive and non-cognitive skills and to analyse the moderating effects of various potential factors on skill acquisition.</p>\n </section>\n \n <section>\n \n <h3> Results and Conclusions</h3>\n \n <p>The results demonstrate that the integration of CT in STEM education has a significant effect on enhancing students' cognitive skills (Hedges's <i>g</i> = 0.651, 95% CI [0.527, 0.776], <i>p</i> < 0.001), with this effect significantly moderated by the intervention duration and the instructional tools. Additionally, the implementation of CT in STEM positively impacts the development of students' non-cognitive skills (Hedges's <i>g</i> = 0.538, 95% CI [0.345, 0.730], <i>p</i> < 0.001), with educational level, sample size, intervention duration, and instructional tools identified as important moderator variables influencing the acquisition of non-cognitive skills. Based on the findings, this study recommends systematic CT interventions lasting 3 months to 1 year, utilising interactive and practice-oriented instructional tools such as block-based programming, maker, and unplugged activities. Furthermore, it suggests tailoring instructional strategies to different educational stages. These recommendations deepen the understanding of the role of CT in STEM education, providing practical guidance for educators and policymakers.</p>\n </section>\n </div>","PeriodicalId":48071,"journal":{"name":"Journal of Computer Assisted Learning","volume":"41 4","pages":""},"PeriodicalIF":5.1000,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Impact of Integrating Computational Thinking in STEM Education on Students' Cognitive and Non-Cognitive Skills: A Meta-Analysis\",\"authors\":\"Hanzhu Yang, Linlin Hu, Hao Wang, Yunfei Xin\",\"doi\":\"10.1111/jcal.70079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Computational thinking (CT) is a cognitive approach intricately linked with core competencies in Science, Technology, Engineering, and Mathematics (STEM). 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Additionally, the implementation of CT in STEM positively impacts the development of students' non-cognitive skills (Hedges's <i>g</i> = 0.538, 95% CI [0.345, 0.730], <i>p</i> < 0.001), with educational level, sample size, intervention duration, and instructional tools identified as important moderator variables influencing the acquisition of non-cognitive skills. Based on the findings, this study recommends systematic CT interventions lasting 3 months to 1 year, utilising interactive and practice-oriented instructional tools such as block-based programming, maker, and unplugged activities. Furthermore, it suggests tailoring instructional strategies to different educational stages. 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引用次数: 0
摘要
计算思维（CT）是一种认知方法，与科学、技术、工程和数学（STEM）的核心能力有着复杂的联系。许多研究探索了将CT有效地融入STEM教育的策略，并系统地评估了对学生学习成果的多维影响。本荟萃分析综合了46项高质量的实证研究结果，以验证将CT融入STEM对学生认知和非认知技能发展的有效性，并分析各种潜在因素对技能习得的调节作用。结果与结论：STEM教育中整合CT对学生认知技能的提高有显著影响（Hedges’s g = 0.651, 95% CI [0.527, 0.776], p < 0.001），干预时间和教学工具显著调节了这种影响。此外，在STEM中实施CT对学生非认知技能的发展有积极影响（Hedges's g = 0.538, 95% CI [0.345, 0.730], p < 0.001），教育水平、样本量、干预时间和教学工具被认为是影响非认知技能习得的重要调节变量。基于研究结果，本研究推荐持续3个月至1年的系统CT干预，利用交互式和以实践为导向的教学工具，如基于块的编程、maker和不插电活动。在此基础上，提出了针对不同阶段的教学策略。这些建议加深了对CT在STEM教育中的作用的理解，为教育工作者和政策制定者提供了实践指导。
Impact of Integrating Computational Thinking in STEM Education on Students' Cognitive and Non-Cognitive Skills: A Meta-Analysis
Background
Computational thinking (CT) is a cognitive approach intricately linked with core competencies in Science, Technology, Engineering, and Mathematics (STEM). Numerous studies have explored strategies to effectively integrate CT into STEM education and systematically evaluated the multidimensional impact on student learning outcomes.
Objectives and Methods
This meta-analysis synthesises findings from 46 high-quality empirical studies to verify the effectiveness of integrating CT into STEM on the development of students' cognitive and non-cognitive skills and to analyse the moderating effects of various potential factors on skill acquisition.
Results and Conclusions
The results demonstrate that the integration of CT in STEM education has a significant effect on enhancing students' cognitive skills (Hedges's g = 0.651, 95% CI [0.527, 0.776], p < 0.001), with this effect significantly moderated by the intervention duration and the instructional tools. Additionally, the implementation of CT in STEM positively impacts the development of students' non-cognitive skills (Hedges's g = 0.538, 95% CI [0.345, 0.730], p < 0.001), with educational level, sample size, intervention duration, and instructional tools identified as important moderator variables influencing the acquisition of non-cognitive skills. Based on the findings, this study recommends systematic CT interventions lasting 3 months to 1 year, utilising interactive and practice-oriented instructional tools such as block-based programming, maker, and unplugged activities. Furthermore, it suggests tailoring instructional strategies to different educational stages. These recommendations deepen the understanding of the role of CT in STEM education, providing practical guidance for educators and policymakers.
期刊介绍：
The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope
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