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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 91Թand its context of an international liberal arts education. Please send to aiataup.edu any suggestions for this list.

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)
  • surveys of AI use
Practical overviews for AI in teaching/learning
  • (Anna Mills)
Generative AI tutorials for faculty

(metaLAB (at) Harvard)

Communicating with students about AI & AI use

Syllabus statements & 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)
  • – tool for generating clear AI use guidelines according to the nature of an assignment (Ryan Watkins)
  • Engaging With AI Isn't Adopting AI (Marc Watkins) – "normalizing AI disclosure as a means of curbing the uncritical adoption of AI and restoring the trust between professors and students"
  • (Torrey Trust) – and see her detailed (the specificity and the "why is this allowed" may get students' attention in ways that more general language might not)
Discussing AI with students

Academic integrity & AI use
  • AI detection & its issues
    • (Chris Ostro) – "any discussion about AI detection has to be paired with additional training"
    • : "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%)."
    • (Sarah Eaton) – “If you insist on using tools to detect AI-generated text in student work at least do so in an open and transparent way”
    • (Liang et al.) – “GPT detectors frequently misclassify non-native English writing as AI generated”
    • | Computers and Education: Artificial Intelligence (Fleckenstein et al.) – “Generative AI can simulate student essay writing in a way that is undetectable for teachers”
  • Constructive approaches to academic integrity & assessment validity
    • (Camosun College Library)
    • – and see his detailed explanation and examples for
  • Examples of tools used to fool AI detectors

Perspectives & discussion material on AI in learning/teaching

  • (Cognitive Resonance)

Teaching with and about AI

AI & ethics
  • – AI & Bias (UCLA Institute for Technology, Law & Policy)
  • AI Ethics & Policy News - Examples of AI ethics issues covered in the news, categorized by issue area
  • – description and examples of application of Hugging Face’s framework for ethical AI (Rigorous; Consentful; Socially Conscious; Sustainable; Inclusive; Inquisitive)
Critical source evaluation
Teaching writing
  • (MLA-CCCC Joint Task Force on Writing and AI)
  • (MLA-CCCC Joint Task Force on Writing and AI)
Technical guidance for using AI in teaching
Other teaching resources
  • (metaLAB (at) Harvard)
  • (Ethan R. Mollick, Lilach Mollick)
  • (University of Maine) - partially crowdsourced but curated collection of links (with brief descriptions) to teaching resources and strategies
  • (MLA-CCCC Joint Task Force on Writing and AI)
  • – discussion thread with example prompts for using genAI to assist in different learning scenarios (requires joining POD AI in Education discussion group)
Books on teaching & AI
  • (Troy Heaps)
  • (José Antonio Bowen and C. Edward Watson – AAC&U)

Guides for students

  • (Elon University & AAC&U)

AI in libraries & research

  • Research tools
    • AI-Based Literature Review Tools (Texas A&M University Libraries)
Citation
  • (U Calgary Libraries) – summaries of APA, Chicago and MLA styles + other sources of citation guidance
  • (MLA Style)
  • (Chicago Manual of Style)
  • (APA Style)
Transparency & disclosure

Clearinghouses of information/resources

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

Discussion & keeping up

Discussion with global peers
  • (requires EDUCAUSE account – 91Թfaculty & staff can create accounts)
  • AI & Libraries
    • (meeting notes and recordings)
Blogs & newsletters
  • (Lance Eaton)
  • (Ethan Mollick)
  • newsletter (Amherst College)
  • (Jeremy Caplan)

Training opportunities

  • – free self-paced course

Campus-level AI initiatives & policy development

We’ve found the resources listed here useful in shaping the AI@91Թinitiative. 91Թcolleagues 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)
Environment, frameworks & examples for policy development
  • Governmental policy frameworks & recommendations
    • Europe
      • EU AI Act
    • France
    • United States
  • Higher ed frameworks & recommendations for policy development
    • – based on this study:
  • Commentary & analysis on higher ed AI policy
    • (IHE)
  • Library & publishing organizations’ guidance on AI
    • (ARL)
  • Examples of existing policies
    • Lists of existing policies
    • Specific examples of note
      • (proposed) (metaLAB (at) Harvard)
      • (College Unbound / Lance Eaton)
      • See “AUP-relevant examples of campus-level initiatives” below
  • Templates for developing your own policy
    • (Joe Sabado)
Academic integrity policies

(See also the section above “Communicating with students about AI & AI use - Academic integrity & AI use”)

  • Using human rights principles to guide academic integrity policies
    • : future-proofing human rights protection in the era of AI (Council of Europe Commissioner for Human Rights)
    • (Sarah Eaton)
  • ” (Sarah Eaton)
  • (Josh Brake)
AI literacy & curricular integration

  • 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)

AUP-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)
    • (AU Kuwait Center for Teaching Excellence)
Staff guidelines on AI use – examples