ҵ

As the ‘Clearinghouses’ section below demonstrates, 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. This list is updated continuously, so please send any suggestions to aiataup.edu.

Intros & background

How generative AI works
  • (Andrej Karpathy) ()
Overviews of the generative AI landscape
  • in higher ed
    • (Hanover Research & IHE)
  • in the broader environment
    • (Imagining the Digital Future Center - Elon University)
Practical overviews for AI in teaching/learning
  • (Anna Mills)
Generative AI tutorials for faculty

(metaLAB (at) Harvard)

Course planning and teaching

Syllabus statements and course design
  • Crowd-sourced list of (Lance Eaton)
  • (Lance Cummings)
  • (Oregon State University)
  • (support for different stages/aspects in course/syllabus design)
  • (Carroll College) -- based on key principles: Clarify, Communicate, Uphold, Engage
  • (U Wisconsin)
  • (Inside Higher Ed)
For faculty teaching writing

(MLA-CCCC Joint Task Force on Writing and AI)

Discussions with students about AI
  • Academic integrity: objects for discussion with colleagues & students
    • : "Detection tools for AI-generated text do fail, they are neither accurate nor reliable (all scored below 80% of accuracy and only 5 over 70%)."
Assignments and teaching modules to reuse/adapt/reflect upon
  • (metaLAB (at) Harvard)
  • (Ethan R. Mollick, Lilach Mollick)
For faculty teaching writing

(MLA-CCCC Joint Task Force on Writing and AI)

Technical guidance for using AI in teaching

Clearinghouses of information/resources

  • (Lance Eaton)
  • (Anna Mills) – see in particular
  • Policies (see “Policy development” below)
AI in libraries
  • (AI projects, data sets, resources for libraries, archives and museums)
Tools
  • (Dan Fitzpatrick)
  • (Anthropic/Claude)
Products & licensing

Discussion & keeping up

Discussion with global peers
  • (requires EDUCAUSE account – ҵ faculty & staff can create accounts)
  • AI & Libraries
    • (meeting notes and recordings)
Blogs & newsletters
  • (Lance Eaton)
  • (Ethan Mollick)
  • newsletter (Amherst College)
  • (Jeremy Caplan)
Perspectives (could be a focus for class discussion)

Developing higher ed AI initiatives

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.

Developing campus-level strategy and initiatives
  • Broad principles for AI in higher ed
    • (UN lnternet Governance Forum, Kyoto, Oct 2023)
    • (Russel Group of leading UK universities)
  • Organizational assessment
    • (Joe Sabado)
  • Developing a strategy
    • (MIT strategy guide for addressing AI at higher ed institutions)
Policy development
  • Governmental policy frameworks & recommendations
    • Europe
      • EU AI Act
    • France
    • United States
  • Higher ed frameworks & recommendations for policy development
    • – based on this study:
  • Examples of existing policies
    • Lists of existing policies
      • (Joe Sabado)
  • Specific examples of note
    • (metaLAB (at) Harvard)
    • (College Unbound / Lance Eaton)
    • Policies and syllabus guidelines at AMICAL Consortium institutions
  • Templates for developing your own policy
    • (Joe Sabado)
AI literacy frameworks
  • (Barnard College’s scaled framework for moving up a scale: Understand → Use → Analyze → Create)
ҵ-relevant examples of campus-level initiatives
  • Liberal arts colleges
    • Amherst College:
    • Davidson College:
  • Larger universities
    • (University of Toronto)
  • AMICAL Consortium institutions
    • (recording and links to resources mentioned)
    • (Forman Christian College)