Exploring the Effects of the CER Model‐Based GenAI Learning System to Cultivate Elementary School Students' Computational Thinking Core Skills in Science Courses.
Background: Computational thinking (CT) is a fundamental ability required of individuals in the 21st‐century digital world. Past studies show that generative artificial intelligence (GenAI) can enhance students' CT skills. However, GenAI may produce inaccurate output, and students who rely too much...
| Publicado en: | Journal of Computer Assisted Learning Vol. 41; no. 5; pp. 1 - 25 |
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| Autores principales: | , , |
| Formato: | clinical trial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Oct2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=188234208&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 188234208 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Oct2025 vid: 41 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 188234208 188234208 188234208 10.1111/jcal.70110 188234208 ppf: 1 ppct: 24 formats: tig: atl: Exploring the Effects of the CER Model‐Based GenAI Learning System to Cultivate Elementary School Students' Computational Thinking Core Skills in Science Courses. aug: au: Zhao, Jia‐Hua Shangguan, Shu‐Tao Wang, Ying affil: College of Education, Fujian Normal University Cangshan Campus, Fuzhou Fujian, , China sug: subj: Artificial Intelligence, Generative Utilization Educational Technology China Students, Elementary Critical Thinking Science Education Teaching Methods Outcomes of Education Evaluation Learning Methods Human Descriptive Statistics Clinical Trials Pretest-Posttest Control Group Design Quasi-Experimental Studies Deep Learning China Questionnaires Semi-Structured Interview Summated Rating Scaling One-Way Analysis of Variance Coefficient alpha Analysis of Covariance Post Hoc Analysis Algorithms Data Analysis Software ab: Background: Computational thinking (CT) is a fundamental ability required of individuals in the 21st‐century digital world. Past studies show that generative artificial intelligence (GenAI) can enhance students' CT skills. However, GenAI may produce inaccurate output, and students who rely too much on AI may learn little and be unable to think independently. Besides, most research on CT mainly focused on Scratch or programming classes, but incorporating it into the K‐12 science curriculum is better for students' deep learning and CT core skills development. Objectives: This study proposed a causal explanation and reflection (CER) model‐based GenAI learning system in science courses to cultivate students' CT core skills. Sample: One hundred and eighteen elementary school students in three different classes participated in this study. Methods: A quasi‐experiment was conducted in Fujian, China. Students in the experimental group learned with the CER model‐based GenAI learning system; students learned with the CER model‐based learning system in control group 1; students in control group 2 used the causal‐explanation‐based GenAI learning system. Students' learning achievement and CT core skills were examined. Results: The results showed that the CER model‐based GenAI learning system significantly improved students' science learning and CT core skills. Interview results further showed some students complained that GenAI only provided answers without encouraging them to comprehend the material. Conclusions: CT should not exist only in computer courses. Instead, it is an approach to problem‐solving that applies to all disciplines. Also, over‐reliance on GenAI may hinder learning ability. The effectiveness of GenAI‐based learning depends on its judicious use. pubtype: Academic Journal doctype: clinical trial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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