Research Article

Integrating AI tools into preservice mathematics teacher education: A qualitative study of lesson planning practices

Nadeyah J. Alreiahi 1 * , Noha Alrwaished 2
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1 Department of Educational Technology, College of Education, Kuwait University, KUWAIT2 Department of Curriculum and Instruction, College of Education, Kuwait University, KUWAIT* Corresponding Author
Contemporary Educational Technology, 17(4), October 2025, ep617, https://doi.org/10.30935/cedtech/17549
Published: 15 December 2025
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ABSTRACT

This study examined the participation of preservice teachers (PSTs) in artificial intelligence (AI)-generated lesson-plan training sessions, primarily within a mathematics instruction course in a teacher training program. Although earlier research has explored AI in education, few studies have specifically looked at how AI-generated lesson plans affect PSTs’ lesson-planning skills. This study addresses this gap by exploring math PSTs’ views on the use of AI-generated tools in lesson planning. Data were collected from focus group interviews with fifty students and were analyzed thematically using a coding framework after targeted training sessions. The findings revealed key themes, including the time-saving benefits of AI, its ability to produce innovative activities, and the support these tools provide to PSTs. While AI tools served as scaffolds, the importance of teacher agency, pedagogical knowledge, and content alignment remained vital. These results highlight the potential of AI support in teacher training programs, while also recognizing that it does not replace essential skills such as critical thinking and professional judgment. The study offers implications and recommendations for integrating AI while maintaining pedagogical rigor and curriculum integrity.

CITATION (APA)

Alreiahi, N. J., & Alrwaished, N. (2025). Integrating AI tools into preservice mathematics teacher education: A qualitative study of lesson planning practices. Contemporary Educational Technology, 17(4), ep617. https://doi.org/10.30935/cedtech/17549

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