Generative AI for Collaborative Learning: Fostering Critical Thinking in Teacher Education.
Background: Generative artificial intelligence (GenAI) tools, such as ChatGPT, present both opportunities and concerns in education. They can support collaborative knowledge construction by providing systematic problem‐solving support. However, a strong focus on critical thinking and validity judgem...
| Publicado en: | Journal of Computer Assisted Learning Vol. 42; no. 3; pp. 1 - 17 |
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| Autores principales: | , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Jun2026
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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=194050900&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 194050900 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02664909 6M1 jtl: Journal of Computer Assisted Learning issn: 02664909 maglogo: Y pubinfo: dt: Jun2026 vid: 42 iid: 3 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 194050900 194050900 194050900 10.1002/jcal.70256 194050900 ppf: 1 ppct: 16 formats: tig: atl: Generative AI for Collaborative Learning: Fostering Critical Thinking in Teacher Education. aug: au: Lehtinen, Auli Channa, Faisal Näykki, Piia Ahlström, Emilia Hiljanen, Mikko affil: Faculty of Education and Psychology, University of Jyväskylä, Jyväskylä, Finland sug: subj: Artificial Intelligence, Generative Utilization Collaboration Learning Methods Critical Thinking Evaluation Teachers Education Teaching Methods Sustainable Growth Cues Human Funding Source Male Female Adult Middle Age Finland Exploratory Research Nonexperimental Studies Colleges and Universities Curriculum Learning Environment Descriptive Statistics Comparative Studies Data Analysis Software Mann-Whitney U Test Judgment Problem Solving Adult: 19-44 years Middle Aged: 45-64 years Male Female ab: Background: Generative artificial intelligence (GenAI) tools, such as ChatGPT, present both opportunities and concerns in education. They can support collaborative knowledge construction by providing systematic problem‐solving support. However, a strong focus on critical thinking and validity judgement is needed. GenAI's role in collaborative learning remains underexplored, especially in fostering critical thinking. Objectives: This study examines GenAI's role in a collaborative task where 75 pre‐service teachers co‐create lesson plans on sustainable development. Methods: Process mining is used to identify sequential patterns that indicate critical thinking. These patterns draw on video analysis and on categorising collaborative groups into high and low performers based on lesson‐plan quality. We analyse different prompt types (conceptual, pedagogical, and refining prompts). We also analyse activities, such as writing, editing, searching for other online sources, and copy‐pasting information. The sequential interplay of these activities reveals important aspects of critical engagement with GenAI. Results and Conclusions: The results showed that participants frequently engaged in an iterative process of prompt refinement, indicating reflective use of AI. They also integrated conceptual and pedagogical aspects in their prompting. High‐performing groups demonstrated deeper engagement in activities such as iterative writing and corroborating GenAI content with other online resources. In contrast, low‐performing groups showed repetitive prompting and reliance on AI‐generated content. The results illustrate GenAI's role in collaborative and reflective learning and call for targeted interventions to support critical thinking. Educational interventions should focus, for example, on prompt refinement, guided reflection, and verification of GenAI information against other sources. Theoretically and methodologically, our analyses provide a foundation for further research. Lay Summary: What is currently known about this topic? ○GenAI can support collaborative knowledge construction on complex topics by providing problem‐solving support.○GenAI can be used to support teachers work, for example, in lesson planning.○Responsible use of GenAI requires pedagogical approaches that are based on critical thinking and validity checking.What does this paper add? ○The results shed light on the under‐researched topic of GenAI tools in collaborative learning contexts, with a focus on critical thinking.○By analysing critical aspects of collaborative learning with GenAI, we can better understand how to meaningfully engage with GenAI in educational contexts.○This study systematically analyses the role of corroborating GenAI with other online resources, which has not been sufficiently addressed with GenAI‐based inquiry.Implications for practice/or policy ○The findings inform instructional strategies that encourage critical thinking in relation to GenAI.○Educational interventions should focus, for example, on prompting strategies, guided reflection in a collaborative setting, and validation of GenAI information against other sources.○Such strategies can prevent overreliance on GenAI.○Teacher education should multifacetedly address the role of GenAI. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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