Integrating Generative AI in Teacher Education: Pre-Service Teachers’ Perspectives, Attitudes, and Design Challenges
Aman Yadav, Michael Lachney, Amber Hu, Lyle Tavernier
Michigan State University
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As generative AI (GenAI) becomes an integral component of the socio-technical landscape in teaching and learning, it is crucial for teacher education programs to prepare pre-service teachers to assess its affordances and limitations. However, research on pre-service teachers’ attitudes toward GenAI is still emerging. Understanding these perspectives is essential for informing teacher education programs about where pre-service teachers stand and how to advance their AI literacy. This article explores pre-service teachers’ understanding and application of GenAI for their envisioned future classrooms. We collected data from pre-service teachers at a Midwestern United States public university, analyzing 17 survey responses quantitatively and conducting qualitative analyses of eight interviews and two lesson design challenge case studies. Our findings indicate that pre-service teachers generally held positive views about GenAI, particularly in terms of its potential for lesson planning, resource creation, and reducing workload. However, they expressed concerns about students’ over-reliance on AI, which they thought could potentially undermine teacher-student interactions. Furthermore, the study found that pre-service teachers identified limitations while using ChatGPT for lesson design and recognized its shortcomings, especially when they had strong content knowledge.
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计算机 / AIIntelligent Tutoring Systems and Adaptive Learning
Online Learning and Analytics · Artificial Intelligence in Education
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