Preservice teachers' perceptions of AI as a creative partner in lesson planning.
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| Title: | Preservice teachers' perceptions of AI as a creative partner in lesson planning. |
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| Authors: | Willcox, Libba1 (AUTHOR) swillcox@iu.edu, Williams, Rebecca Danielle2 (AUTHOR) rwilliams44@murraystate.edu |
| Source: | International Journal of Education through Art. Mar2026, Vol. 22 Issue 1, p85-101. 17p. |
| Subject Terms: | *Lesson planning, *Educational technology, *Art education, *Teacher burnout, *Student teachers, Artificial intelligence & ethics, Technology Acceptance Model |
| Abstract: | More than three-quarters of current teachers report experiencing burnout and intentions to exit the profession sooner than expected. Art teachers encounter unique complexities when designing curriculum since they often work independently without the district-provided resources available to colleagues. This qualitative study examines how preservice art teachers utilize AI-supported lesson planning and offers insight for teacher educators as they incorporate AI tools into teacher preparation curricula. Twenty-two preservice art educators participated in this study, using ChatGPT during their lesson planning process. Grounded in the Technological Pedagogical Content Knowledge (TPACK) framework and the Technology Acceptance Model (TAM), the study examines both cognitive and affective dimensions involved in AI integration. The results indicate three major roles of AI: creative partner for ideation and content development, technical assistant for efficiency and organization, and problematic collaborator with inherent limitations and risks. While AI enhanced pedagogical knowledge, content knowledge and idea generation for most participants, concerns emerged regarding dependency risks, communication barriers and ethical considerations. This study suggests the need to balance efficiency gains with critical engagement, emphasizing that AI should augment rather than replace teacher expertise. Teacher educators must proactively integrate AI literacy into methods courses, teaching preservice teachers to engage iteratively and critically with AI as a collaborative tool that can meaningfully reduce burnout while preserving the authenticity and professional judgment essential to quality teaching. [ABSTRACT FROM AUTHOR] |
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| Database: | Education Research Complete |
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| Abstract: | More than three-quarters of current teachers report experiencing burnout and intentions to exit the profession sooner than expected. Art teachers encounter unique complexities when designing curriculum since they often work independently without the district-provided resources available to colleagues. This qualitative study examines how preservice art teachers utilize AI-supported lesson planning and offers insight for teacher educators as they incorporate AI tools into teacher preparation curricula. Twenty-two preservice art educators participated in this study, using ChatGPT during their lesson planning process. Grounded in the Technological Pedagogical Content Knowledge (TPACK) framework and the Technology Acceptance Model (TAM), the study examines both cognitive and affective dimensions involved in AI integration. The results indicate three major roles of AI: creative partner for ideation and content development, technical assistant for efficiency and organization, and problematic collaborator with inherent limitations and risks. While AI enhanced pedagogical knowledge, content knowledge and idea generation for most participants, concerns emerged regarding dependency risks, communication barriers and ethical considerations. This study suggests the need to balance efficiency gains with critical engagement, emphasizing that AI should augment rather than replace teacher expertise. Teacher educators must proactively integrate AI literacy into methods courses, teaching preservice teachers to engage iteratively and critically with AI as a collaborative tool that can meaningfully reduce burnout while preserving the authenticity and professional judgment essential to quality teaching. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 17435234 |
| DOI: | 10.1386/eta_00223_1 |
