Generative AI for Collaborative Learning: Fostering Critical Thinking in Teacher Education

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Title: Generative AI for Collaborative Learning: Fostering Critical Thinking in Teacher Education
Language: English
Authors: Auli Lehtinen (ORCID 0000-0002-4027-8723), Faisal Channa, Piia Näykki, Emilia Ahlström, Mikko Hiljanen
Source: Journal of Computer Assisted Learning. 2026 42(3).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 16
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Cooperative Learning, Critical Thinking, Technology Uses in Education, Preservice Teachers, Lesson Plans, Sustainable Development, Preservice Teacher Education
DOI: 10.1002/jcal.70256
ISSN: 0266-4909
1365-2729
Abstract: 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.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1506755
Database: ERIC
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  Data: Generative AI for Collaborative Learning: Fostering Critical Thinking in Teacher Education
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  Data: <searchLink fieldCode="AR" term="%22Auli+Lehtinen%22">Auli Lehtinen</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-4027-8723">0000-0002-4027-8723</externalLink>)<br /><searchLink fieldCode="AR" term="%22Faisal+Channa%22">Faisal Channa</searchLink><br /><searchLink fieldCode="AR" term="%22Piia+Näykki%22">Piia Näykki</searchLink><br /><searchLink fieldCode="AR" term="%22Emilia+Ahlström%22">Emilia Ahlström</searchLink><br /><searchLink fieldCode="AR" term="%22Mikko+Hiljanen%22">Mikko Hiljanen</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Computer+Assisted+Learning%22"><i>Journal of Computer Assisted Learning</i></searchLink>. 2026 42(3).
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: 16
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Cooperative+Learning%22">Cooperative Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Critical+Thinking%22">Critical Thinking</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Preservice+Teachers%22">Preservice Teachers</searchLink><br /><searchLink fieldCode="DE" term="%22Lesson+Plans%22">Lesson Plans</searchLink><br /><searchLink fieldCode="DE" term="%22Sustainable+Development%22">Sustainable Development</searchLink><br /><searchLink fieldCode="DE" term="%22Preservice+Teacher+Education%22">Preservice Teacher Education</searchLink>
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  Data: 10.1002/jcal.70256
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  Data: 0266-4909<br />1365-2729
– Name: Abstract
  Label: Abstract
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  Data: 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.
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        Value: 10.1002/jcal.70256
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        PageCount: 16
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Cooperative Learning
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      – SubjectFull: Critical Thinking
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      – SubjectFull: Technology Uses in Education
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      – SubjectFull: Preservice Teachers
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      – SubjectFull: Sustainable Development
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      – SubjectFull: Preservice Teacher Education
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      – TitleFull: Generative AI for Collaborative Learning: Fostering Critical Thinking in Teacher Education
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