How Can Video Generative AI Transform K-12 Education? Examining Teachers' Perspectives through TPACK and TAM
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arXiv
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| Auteurs principaux: | , , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866912269693091840 |
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| author | Lee, Unggi Jeong, Yeil Kim, Seungha Son, Yoorim Byun, Gyuri Kim, Hyeoncheol Lim, Cheolil |
| author_facet | Lee, Unggi Jeong, Yeil Kim, Seungha Son, Yoorim Byun, Gyuri Kim, Hyeoncheol Lim, Cheolil |
| contents | The rapid advancement of generative AI technology, particularly video generative AI (Video GenAI), has opened new possibilities for K-12 education by enabling the creation of dynamic, customized, and high-quality visual content. Despite its potential, there is limited research on how this emerging technology can be effectively integrated into educational practices. This study explores the perspectives of leading K-12 teachers on the educational applications of Video GenAI, using the TPACK (Technological Pedagogical Content Knowledge) and TAM (Technology Acceptance Model) frameworks as analytical lenses. Through interviews and hands-on experimentation with video generation tools, the research identifies opportunities for enhancing teaching strategies, fostering student engagement, and supporting authentic task design. It also highlights challenges such as technical limitations, ethical considerations, and the need for institutional support. The findings provide actionable insights into how Video GenAI can transform teaching and learning, offering practical implications for policy, teacher training, and the future development of educational technology. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_08003 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | How Can Video Generative AI Transform K-12 Education? Examining Teachers' Perspectives through TPACK and TAM Lee, Unggi Jeong, Yeil Kim, Seungha Son, Yoorim Byun, Gyuri Kim, Hyeoncheol Lim, Cheolil Computers and Society The rapid advancement of generative AI technology, particularly video generative AI (Video GenAI), has opened new possibilities for K-12 education by enabling the creation of dynamic, customized, and high-quality visual content. Despite its potential, there is limited research on how this emerging technology can be effectively integrated into educational practices. This study explores the perspectives of leading K-12 teachers on the educational applications of Video GenAI, using the TPACK (Technological Pedagogical Content Knowledge) and TAM (Technology Acceptance Model) frameworks as analytical lenses. Through interviews and hands-on experimentation with video generation tools, the research identifies opportunities for enhancing teaching strategies, fostering student engagement, and supporting authentic task design. It also highlights challenges such as technical limitations, ethical considerations, and the need for institutional support. The findings provide actionable insights into how Video GenAI can transform teaching and learning, offering practical implications for policy, teacher training, and the future development of educational technology. |
| title | How Can Video Generative AI Transform K-12 Education? Examining Teachers' Perspectives through TPACK and TAM |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2503.08003 |