Artificial Intelligence (AI) pedagogies resources

Artificial Intelligence (AI) pedagogies encompass critical considerations and practical approaches. The resources below include tools for teaching with AI, a self-paced course at York, resources including articles, free external courses, and recordings of critical conversations about AI in teaching and learning, as well as current research.

The SHARE framework for scholarly co-writing with AI aims to integrate generative AI into the academic writing process. This approach is designed to help students and educators navigate the complexities of authorship, cognitive offloading, and the ethical use of AI in scholarly work. SHARE provides a step-by-step strategy for scholarly co-writing with AI, adaptable to various levels of AI involvement and different assessments. For more information about key concepts and scholarship that inform this framework, as well as a list of references, you can download this .pdf.

Following the creation of a draft text, either by the human author(s) alone or by having AI respond to a prompt or prompts, SHARE proposes a series of writing/editing stages that preserve human authorial integrity. Each stage can be conducted by the human author alone or in conversation with AI.

Streamline
Heighten
Arrange
Ratify
Evidence

Objective: Remove redundancies, repetitions, and unnecessary words or phrases to make the text more concise and clear.

Application: Identify and eliminate any superfluous content that does not add value to the argument or narrative.

Objective: Identify and fill gaps in the content, such as missing scope, content, or counterarguments.

Application: Enhance the text by adding necessary information, expanding on key points, and addressing any overlooked aspects.

Objective: Revise the order of paragraphs and sections to ensure logical flow and coherence.

Application: Reorganize the text to improve the structure and ensure that the argumentation progresses naturally and effectively.

Objective: Fact-check and ensure the AI-generated content aligns with the author’s intentions and claims.

Application: Verify the accuracy of the information, correct any errors, and ensure that the content reflects the author’s perspective and objectives.

Objective: Remove redundancies, repetitions, and unnecessary words or phrases to make the text more concise and clear.

Application: Add relevant data, references, and citations to support the claims made in the text and enhance its scholarly value.

Flexibility: The framework can be adapted for individual or group work, short or long assignments, and varying levels of AI involvement.

Scaffolding: Steps can be integrated into multiple class sessions, focusing on different aspects of the framework, and various elements of academic writing, revising, and editing.

Critical Framework: SHARE can be used to critically analyze AI-generated texts, fostering deeper discussions about content and writing practices.

Quick Tips:

Start small: pilot just one stage in a low-stakes task.
Log everything: saving prompt transcripts makes Ratify easier and can help ease academic integrity concerns.
Rotate labor: alternate human-first and AI-first versions to show contrasts.
Leverage discipline-specific tools (e.g., CAD plug-ins, Zotero, chemical-structure generators) to embed SHARE naturally.

First-Year Writing “Micro-Draft Clinics”

First-year composition / gen‑ed writing • 100‑student lecture + tutorials • Blended • AI attitude: cautious but curious

SHARE Stage	Concrete Activity	Pedagogical Pay-off
Streamline	TA live-demos ChatGPT trimming a student volunteer’s paragraph; everyone tests on one sentence of their own draft.	Immediate model of concision without outsourcing whole text.
Heighten	Homework: students prompt AI for missing counter-arguments or stronger transitions.	Teaches rhetorical completeness.
Arrange	In tutorial, peer pairs drag-and-drop paragraphs in Padlet to check logical flow.	Visualizes structure; prevents AI-generated disorder.
Ratify	Students highlight two AI-suggested facts & post a source-check note in LMS.	Builds fact-checking habits.
Evidence	Librarian mini-workshop on Zotero; final draft must include AI-disclosure footnote.	Normalizes transparent citation and AI use.

Biology Lab‑Report “Evidence Stations”

2nd‑year biology lab • 32‑seat in‑person lab • AI attitude: skeptical

SHARE Stage	Concrete Activity	Pedagogical Pay‑off
Streamline	Station 1: AI suggests concise wording for Results.	Shows editing without altering data integrity.
Heighten	Station 2: prompt AI for overlooked controls or statistical qualifiers.	Strengthens experimental rigour.
Arrange	Station 3: teams reorder Methods–Results–Discussion for narrative clarity.	Reinforces scientific storytelling.
Ratify	Station 4: benchmates cross‑check AI claims against raw data sheets.	Embeds data‑first verification.
Evidence	Final station auto‑imports verified citations (e.g., ISO enzyme standards).	Ensures traceable, discipline‑specific referencing.

Business Capstone “Client Memo Sprint”

Final‑year consulting project • 6 groups of 5 • Hybrid • AI attitude: enthusiastic

SHARE Stage	Concrete Activity	Pedagogical Pay‑off
Streamline	AI condenses memo draft into a one‑page executive summary.	Mirrors real client expectations.
Heighten	Teams prompt AI for missing cost‑benefit angles or stakeholder impacts.	Broadens analytical scope.
Arrange	Reorder content to match client template in Google Docs.	Teaches professional formatting.
Ratify	15‑min “hallucination hunt”: locate & correct at least one AI error.	Instils critical AI literacy.
Evidence	Embed spreadsheets & market data; memo ends with AI‑assistance disclosure.	Demonstrates transparent, data‑driven recommendations.

Humanities Seminar “Dialogic Close‑Reading Essay”

Upper‑level literature • 12‑student seminar • Face‑to‑face • AI attitude: highly skeptical

SHARE Stage	Concrete Activity	Pedagogical Pay‑off
Streamline	Students present AI‑compressed vs. original paragraph; discuss nuance loss.	Reveals when AI oversimplifies literary analysis.
Heighten	Manually add deeper textual evidence and secondary‑source dialogue.	Centers human interpretation.
Arrange	Instructor‑guided exercise reorders body paragraphs into a thematic arc.	Strengthens argumentative coherence.
Ratify	Quote‑check each AI paraphrase against primary text; annotate discrepancies.	Safeguards against misquotation.
Evidence	MLA citations plus brief AI‑usage note in end‑matter.	Retains scholarly rigour and transparency.

Online Graduate Research‑Methods “Annotated Lit‑Review Pathway”

Master’s • 25‑student asynchronous online • AI attitude: mixed

SHARE Stage	Concrete Activity	Pedagogical Pay‑off
Streamline	Week 1: AI trims a bloated summary; students critique what was lost/gained.	Develops precision and reflection.
Heighten	Week 2: prompt AI for missing theoretical lenses or under‑represented populations.	Promotes inclusive scholarship.
Arrange	Week 3: reorder sources in Miro to create thematic clusters.	Visualises literature architecture.
Ratify	Week 4: peers verify two citations each, marking errors in Hypothes.is.	Cultivates communal fact‑checking culture.
Evidence	Week 5: Zotero builds bibliography; appendix uploads AI prompt log.	Reinforces citation accuracy & AI disclosure.

These use-cases were created with the partial assistance of ChatGPT o

Generative AI in teaching: Self-paced learning

This fully online, self-paced course is designed to help you explore the practical pedagogy of teaching in the age of artificial intelligence. This course will guide you through a range of topics and resources to understand the implications of this new technology for your course policies, assessments, and teaching strategies.

Learn more

illustration of individual with graduate cap and diploma in a red circle

Resources

Important Websites:

AI@York: The central hub for AI at York University. https://www.yorku.ca/ai-at-york/
AI Technology and Academic Integrity for Instructors. https://www.yorku.ca/unit/vpacad/academic-integrity/ai-technology-and-academic-integrity/

Editable Slide Deck:

GenAI for YorkU Students: An adaptable resource for discussing AI in the classroom. https://www.yorku.ca/teachingcommons/wp-content/uploads/sites/38/2024/11/GenAI-and-Academic-Integrity-slide-deck.pptx

Getting Started with GenAI Video Series:

Part 1: AI 101 - How GenAI works and some tool demos
Part 2: The Academic Integrity Landscape and Defining Expectations
Part 3: Course Policies and Detection
Part 4: Teaching and Assessment
PDF of slides with embedded links to resources

Articles and Blogs:

Aschaiek, S. (2023, Summer). A bot aced my homework: How ChatGPT is impacting the academic experience. The York University Magazine. https://magazine.yorku.ca/issues/summer-2023/a-bot-aced-my-homework/
Syed, Imran. (2023, September). Embracing AI in the Classroom (Part One) and (Part Two). Teaching Commons Blog.
Totten, T. (2023, September). From Obstacle to Opportunity: Reinventing Assignments in the Age of Generative AI. Teaching Commons Blog.
Ward, A. (2023, January 26). How will AI tools such as ChatGPT shape teaching and learning? YFile. https://yfile.news.yorku.ca/2023/01/26/how-will-ai-tools-such-as-chatgpt-shape-teaching-and-learning/

Panels and Showcases:

Artificial intelligence and academic integrity (February 2023)
Critical Perspectives on Generative AI (October 2023)
York University Summit on Generative AI in Higher Education: Faculty Showcase (October 2024)
AI Teaching Showcase (January 2025)

Workshops and Webinars:

Practical AI series (2024):
Surveillance Pedagogies (July 2025)
- PDF of slides with embedded links to resources
The Essay is Dead... Now What? Alternative Assessment in a Post-AI Landscape (August 2025)
- Crowdsourced repository of alternative assessment strategies
- Alternative Assessment Brainstorm: In-Class Activities to Inspire Critical Thinking. Led by Dr. Eliana El Khoury (Assistant Professor, Humanities & Social Sciences, Athabasca University)
- Human and Artful Writing Assessment in the Age of AI: A Meditation Session on Why We Teach. Led by Dr. Elisabeth Rodriguez Fielder (Associate Professor, English, University of Iowa)
- The SHARE Framework for Scholarly Co-Writing with AI. Led by Dr. Robin Sutherland-Harris (Educational Developer, York University)
- New Final Exams: Alternatives to the End of Year Assessments. Led by Dr. Elisha Lim (Assistant Professor, Humanities, York University)
Building AI Literacy (September 2025)
- PDF of slides with embedded links to resources
- AI Literacy Handout: Frameworks and definitions
- Crowdsourced repository of AI literacy strategies

Access to some recordings may be restricted to the York community, so if you are prompted to sign in, select "Sign in with SSO". Enter “yorku” in the company domain, then you will then be able to access the recording by using your PPY username and password.

SHARE Framework

Are you interested in using or adapting the SHARE framework in your teaching? We would love to hear from you! We are currently launching a SoTL project that explores faculty use of this framework across a variety of teaching contexts. Contact Robin Sutherland-Harris for more information.

General introductions
AI Literacy Frameworks

Courses

Teaching with AI Micro-Credential from eCampus Ontario, free for York faculty and staff.
Destination AI by CIFAR (Canadian Institute for Advanced Research)
Indigenous Perspectives on AI commissioned by CIFAR and developed by Ridge Road Training & Consulting, Inc., co-authored and co-constructed by a team of Indigenous and non-Indigenous educators.
Artificial Intelligence (AI) Education for Teachers: Coursera course offered by Dr. Anne Forbes and Dr. Markus Powling from Macquarie University.
Care About AI: Introducing Artificial Intelligence from CARE-AI at the University of Guelph. Use the code TWAI2025 to the relevant field on the registration form.

Readings

Aspenlieder, E., & Fulmer, S. (2025). AI Playbook for Teaching and Learning Leaders: A Community Guide. University of Guelph.
Bertram Gallant, T., & Rettinger, D. A. (2025). The opposite of cheating: Teaching for integrity in the age of AI. University of Oklahoma Press.
Mollick, E. (2024). Co-intelligence: Living and Working with AI. Portfolio/Penguin.
Sabzalieva, E., & Valentini, A. (2023). ChatGPT and artificial intelligence in higher education: Quick start guide (UNESCO Digital Library). UNESCO.

These three recommended frameworks offer a starting place for faculty looking to strategically approach AI literacy. For concrete classroom strategies to build and support AI literacy, visit our crowdsourced Google spreadsheet here.

Digital Education Council. (2025). DEC AI Literacy Framework
- Includes human-centricity, competency levels, need for separate treatment of domain expertise and faculty vs student competencies
- Potentially overwhelming!
University of Toronto Libraries Framework for AI Literacy
- Approachable and easy to use: Understand, Use, Evaluate
- Offers practical classroom suggestions for building AI literacy
- Might miss some elements (human centredness, disciplinary nuance)
Also consider: UWO’s Domains of AI Awareness for Education
- Avoids assumption that AI literacy = AI adoption
- Begins with questions “What implications does using Generative AI have for myself and society? And what uses (if any) align with my values and beliefs?”