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Exploring Factors That Support Pre-Service Teachers' Engagement in Learning Artificial Intelligence

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Title: Exploring Factors That Support Pre-Service Teachers' Engagement in Learning Artificial Intelligence
Language: English
Authors: Musa Adekunle Ayanwale (ORCID 0000-0001-7640-9898), Emmanuel Kwabena Frimpong, Oluwaseyi Aina Gbolade Opesemowo (ORCID 0000-0003-0242-7027), Ismaila Temitayo Sanusi (ORCID 0000-0002-5705-6684)
Source: Journal for STEM Education Research. 2025 8(2):199-229.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 31
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Preservice Teachers, Teacher Competencies, Learner Engagement, Student Attitudes, Critical Thinking, Creativity, Student Behavior, Social Influences, Anxiety, Readiness, Goal Orientation, Self Efficacy
DOI: 10.1007/s41979-024-00121-4
ISSN: 2520-8705
2520-8713
Abstract: Artificial intelligence (AI) is becoming increasingly relevant, and students need to understand the concept. To design an effective AI program for schools, we need to find ways to expose students to AI knowledge, provide AI learning opportunities, and create engaging AI experiences. However, there is a lack of trained teachers who can facilitate students' AI learning, so we need to focus on developing the capacity of pre-service teachers to teach AI. Since engagement is known to enhance learning, it is necessary to explore how pre-service teachers engage in learning AI. This study aimed to investigate pre-service teachers' engagement with learning AI after a 4-week AI program at a university. Thirty-five participants took part in the study and reported their perception of engagement with learning AI on a 7-factor scale. The factors assessed in the survey included engagement (cognitive--critical thinking and creativity, behavioral, and social), attitude towards AI, anxiety towards AI, AI readiness, self-transcendent goals, and confidence in learning AI. We used a structural equation modeling approach to test the relationships in our hypothesized model using SmartPLS 4.0. The results of our study supported all our hypotheses, with attitude, anxiety, readiness, self-transcendent goals, and confidence being found to influence engagement. We discuss our findings and consider their implications for practice and policy.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1467868
Database: ERIC
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  Data: Exploring Factors That Support Pre-Service Teachers' Engagement in Learning Artificial Intelligence
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  Data: <searchLink fieldCode="AR" term="%22Musa+Adekunle+Ayanwale%22">Musa Adekunle Ayanwale</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0001-7640-9898">0000-0001-7640-9898</externalLink>)<br /><searchLink fieldCode="AR" term="%22Emmanuel+Kwabena+Frimpong%22">Emmanuel Kwabena Frimpong</searchLink><br /><searchLink fieldCode="AR" term="%22Oluwaseyi+Aina+Gbolade+Opesemowo%22">Oluwaseyi Aina Gbolade Opesemowo</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0003-0242-7027">0000-0003-0242-7027</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ismaila+Temitayo+Sanusi%22">Ismaila Temitayo Sanusi</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-5705-6684">0000-0002-5705-6684</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+for+STEM+Education+Research%22"><i>Journal for STEM Education Research</i></searchLink>. 2025 8(2):199-229.
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: 10.1007/s41979-024-00121-4
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  Data: 2520-8705<br />2520-8713
– Name: Abstract
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  Data: Artificial intelligence (AI) is becoming increasingly relevant, and students need to understand the concept. To design an effective AI program for schools, we need to find ways to expose students to AI knowledge, provide AI learning opportunities, and create engaging AI experiences. However, there is a lack of trained teachers who can facilitate students' AI learning, so we need to focus on developing the capacity of pre-service teachers to teach AI. Since engagement is known to enhance learning, it is necessary to explore how pre-service teachers engage in learning AI. This study aimed to investigate pre-service teachers' engagement with learning AI after a 4-week AI program at a university. Thirty-five participants took part in the study and reported their perception of engagement with learning AI on a 7-factor scale. The factors assessed in the survey included engagement (cognitive--critical thinking and creativity, behavioral, and social), attitude towards AI, anxiety towards AI, AI readiness, self-transcendent goals, and confidence in learning AI. We used a structural equation modeling approach to test the relationships in our hypothesized model using SmartPLS 4.0. The results of our study supported all our hypotheses, with attitude, anxiety, readiness, self-transcendent goals, and confidence being found to influence engagement. We discuss our findings and consider their implications for practice and policy.
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  Data: 2025
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        Value: 10.1007/s41979-024-00121-4
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 31
        StartPage: 199
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Preservice Teachers
        Type: general
      – SubjectFull: Teacher Competencies
        Type: general
      – SubjectFull: Learner Engagement
        Type: general
      – SubjectFull: Student Attitudes
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      – SubjectFull: Critical Thinking
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      – SubjectFull: Creativity
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      – SubjectFull: Student Behavior
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      – SubjectFull: Social Influences
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      – SubjectFull: Anxiety
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      – SubjectFull: Readiness
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      – SubjectFull: Goal Orientation
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      – SubjectFull: Self Efficacy
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      – TitleFull: Exploring Factors That Support Pre-Service Teachers' Engagement in Learning Artificial Intelligence
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            NameFull: Emmanuel Kwabena Frimpong
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            NameFull: Oluwaseyi Aina Gbolade Opesemowo
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