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The manuscript shares findings from a study engaging secondary mathematics preservice teachers using Artificial Intelligence (AI) chatbots to design mathematics lesson plans. Phenomenology was employed to investigate how six secondary preservice teachers used AI chatbots and navigated this new resource compared to their knowledge and experience in developing culturally responsive mathematics lesson plans that included mathematics and social justice goals. Our data analysis revealed that PSTs’ confidence in their Mathematical Content Knowledge and Pedagogical Content Knowledge allowed them to be critical of using AI-generated lesson plans. This finding contrasted with previous research on elementary education preservice teachers who gave away their decision-making agency to AI chatbots, especially about mathematics. The data suggests that the secondary PSTs had confidence in their Mathematical and Pedagogical Content Knowledge, making them more critical of the AI-generated lesson plans. The findings also indicate that AI tools can help teachers learn about Technological Pedagogical Knowledge (TPK). Overall, the data stressed the need to support PSTs in using AI chatbots critically. The implications of this study provide possible ways to help PSTs overcome their overconfidence in AI chatbots and imply that more professional development tools and programs must be constructed to help inservice teachers use AI tools.
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Understanding Preservice Elementary Teachers as Mathematical Modelers and Their Perceptions of the Process
A growing consensus holds that preservice K–8 teachers (PSTs) need to experience the modeling process as learners to understand it and envision teaching modeling in their future classrooms. We examine this recommendation by exploring how PSTs construct models and how collaborative learning practices influence them in revising and refining their models. We also explore their reflections on modeling as a pedagogical experience. We introduce Modeling Decision Maps as a tool to examine how PSTs construct and refine mathematical models, and we draw on reflective journal entries to capture PSTs’ perspectives on the process. Our findings indicate that realistic modeling tasks provide opportunities to foster PSTs’ understanding of modeling, grow their mathematical modeling skills, and attune them to important pedagogical practices.
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- PAR ID:
- 10544814
- Publisher / Repository:
- Journal for Research in Mathematics Education
- Date Published:
- Journal Name:
- Journal for Research in Mathematics Education
- Volume:
- 55
- Issue:
- 4
- ISSN:
- 0021-8251
- Page Range / eLocation ID:
- 182 to 209
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5951/jresematheduc-2022-0127
