AI Academy: Building Generative AI Literacy in Higher Ed Instructors
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arXiv
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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866911170996207616 |
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| author | Chen, Si Tang, Xiuxiu Cheng, Alison Chawla, Nitesh Ambrose, G. Alex Metoyer, Ronald |
| author_facet | Chen, Si Tang, Xiuxiu Cheng, Alison Chawla, Nitesh Ambrose, G. Alex Metoyer, Ronald |
| contents | Generative AI is reshaping higher education, yet research has focused largely on students, while instructors remain understudied despite their central role in mediating adoption and modeling responsible use. We present the \textit{AI Academy}, a faculty development program that combined AI exploration with pedagogical reflection and peer learning. Rather than a course evaluated for outcomes, the Academy provided a setting to study how instructors build AI literacies in relation to tools, policies, peer practices, and institutional supports. We studied 25 instructors through pre/post surveys, learning logs, and facilitator interviews. Findings show AI literacy gains alongside new insights. We position instructors as designers of responsible AI practices and contribute a replicable program model, a co-constructed survey instrument, and design insights for professional development that adapts to evolving tools and fosters ethical discussion. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_11999 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AI Academy: Building Generative AI Literacy in Higher Ed Instructors Chen, Si Tang, Xiuxiu Cheng, Alison Chawla, Nitesh Ambrose, G. Alex Metoyer, Ronald Human-Computer Interaction Generative AI is reshaping higher education, yet research has focused largely on students, while instructors remain understudied despite their central role in mediating adoption and modeling responsible use. We present the \textit{AI Academy}, a faculty development program that combined AI exploration with pedagogical reflection and peer learning. Rather than a course evaluated for outcomes, the Academy provided a setting to study how instructors build AI literacies in relation to tools, policies, peer practices, and institutional supports. We studied 25 instructors through pre/post surveys, learning logs, and facilitator interviews. Findings show AI literacy gains alongside new insights. We position instructors as designers of responsible AI practices and contribute a replicable program model, a co-constructed survey instrument, and design insights for professional development that adapts to evolving tools and fosters ethical discussion. |
| title | AI Academy: Building Generative AI Literacy in Higher Ed Instructors |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.11999 |