There is a large and growing number of resources available on the web for AI in higher education. The list below has been curated for relevance to ҵ and its context of an international liberal arts education. Please send to aiaup.edu any suggestions for this list.
(metaLAB (at) Harvard)
(Elon University & AAC&U)
We’ve found the resources listed here useful in shaping the AI@ҵ initiative. ҵ colleagues may find these useful as well in thinking about how they can contribute to the initiative or its goals.
(See also the section above “Communicating with students about AI & AI use - Academic integrity & AI use”)
AI literacy frameworks
(Barnard College’s scaled framework for moving up a scale: Understand → Use → Analyze → Create)
(MLA & CCCC)
AI Literacy Model - Practitioner-Scholar Approach Template (Joe Sabado)
(EDUCAUSE AI Literacy Programs for Faculty, Staff, and Students Working Group)
- Updates to their gen ed learning outcomes are highlighted in : info lit learning outcomes now mention evaluating *origins* of information and understanding ethical dimensions of information work using AI
rs (UNESCO) - both frameworks emphasize a human-centered mindset and AI ethics, as well as understanding of AI in order to use it in learning or teaching contexts
AI across the curriculum
(Southworth et al.) – includes U Florida’s AI literacy framework
(IHE) (Kathleen Landy)