Artificial Intelligence (AI) in teaching and learning

Are you wondering how generative AIs like ChatGPT are affecting teaching and learning in higher education? Looking for support in learning more or making changes to your teaching practices? On this page you will find information about our Certificates in AI Pedagogy as well as a curated collection of resources, in a variety of formats.

We also invite you to visit York's Vice-Provost of Teaching and Learning's support page. Generative AI in Teaching and Learning includes a wealth of real-world examples, practical advice, and up-to date resources for students and faculty, with a separate section for graduate studies. You will also find a page to support our community in ethical discussions around AI, and a page on the basics of AI, GenAI 101.

If you are looking for professional development opportunities related to artificial intelligence (AI) in teaching and learning, check out a list of events from our website calendar.

Teaching Commons Certificates in AI Pedagogy

AI is changing higher education—are you ready to lead, question, and teach with confidence?

The Certificates in AI Pedagogy are a flexible program designed for all who teach at York and are looking to build a thoughtful, informed, and balanced approach to teaching and learning in the age of generative AI. Whether you’re eager to explore new tools or cautiously considering the implications, this program provides space for both critical reflection and practical experimentation.

In these certificates, you will:

Explore how AI is reshaping higher ed pedagogy—ethically, culturally, and technologically
Choose your path: dive into critical conversations or experiment with practical teaching strategies (or both!)
Apply what you learn by creating or revising teaching materials for your own context
Connect with a growing community of colleagues at York navigating AI in education

Choose between the Essentials and the Leadership certificates (below). Visit this list of events from our website calendar to find current offerings that can count towards the certificates.

Questions? Email Robin Sutherland-Harris.

Certificate in AI Pedagogy Essentials

The Certificate in AI Pedagogy Essentials represents roughly 20 hours of participant time. It can be completed within a one-year span, and should be completed within a two-year span.

Completion requirements:

Two core components:
- AI & Education Course (offered in Fall Semester)
- AI Intensive (offered in Winter Semester)
Three workshops from our AI workshop series
- Workshops fall into the Critical Lens theme and Practical Pedagogy theme. Take all three workshops from the same theme to receive a Specialist’s Badge on your certificate, or mix and match.
Capstone
- Update your Statement of Teaching Philosophy to address the role of AI in education.
Community Engagement
- Attend a York-hosted, AI-related showcase, hack-a-thon, panel, conference or other event and submit proof of registration and a brief written or oral reflection.
Keep a record of your participation and contact us when you have completed all the certificate requirements.

Certificate in AI Pedagogy Leadership

The Certificate in AI Pedagogy Leadership represents an additional 15 hours of participant time, for a total of roughly 35 hours. This certificate can be completed within a one-year span, and should be completed within a four-year span.

Completion requirements:

The Certificate in AI Pedagogy Essentials (see above)
Three additional workshops from our AI workshop series
- Workshops fall into the Critical Lens theme and Practical Pedagogy themes. Take five out six workshops, in total, from the same theme to receive a Specialist’s Badge on your certificate, or mix and match.
Capstone
- Create and share a teaching resource in our TC website repository (e.g., syllabus statement, assignment redesign, AI course policy) (Your Capstone resource should align broadly with either the Critical Lens theme or the Practical Pedagogy theme to receive the Specialist’s Badge).
- The submission process involves one round of feedback and revision, provided either by Teaching Commons staff or by a peer also participating in the Leadership Certificate.
Community Contribution
- Present or speak at the AI Institute, the GenAI Pedagogies Community of Practice, or at a York-hosted, AI-related showcase, hack-a-thon, panel, conference or other event. Submit proof of participation and a brief written or oral reflection. (Your contribution should align broadly with either the Critical Lens theme or the Practical Pedagogy theme to receive the Specialist’s Badge).
- Should such an opportunity not be available, participants may alternatively provide meaningful feedback on a Leadership Certificate peer’s Capstone resource.
Keep a record of your participation and contact us when you have completed all the certificate requirements.

The Certificate in AI Pedagogy Leadership positions you ideally to take on formal or informal leadership roles regarding AI in your departmental or unit context, and the Teaching Commons will support you in this with co-facilitation of one department-level session and prepared materials for you to adapt and use in two follow-up sessions.

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

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.

Heighten

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.

Arrange

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.

Ratify

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.

Evidence

Objective: Incorporate evidence, citations, and other elements to build credibility and trust.

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

Using SHARE in Your Teaching

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.

SHARE Framework in Practice: 5 Teaching Use-Cases

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 o3.

Featured resource

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/

Read the article!

Further resources

Generative Artificial Intelligence (AI) - A 3-page document, part of the Teaching Commons food for thought series, that gives an overview of generative AI, and links to a variety of resources.

Sabzalieva, E., & Valentini, A. (2023). ChatGPT and artificial intelligence in higher education: Quick start guide. UNESCO International Institute for Higher Education in Latin America and the Caribbean. https://unesdoc.unesco.org/ark:/48223/pf0000385146.locale=en

Syed, Imran. (2023, September). Embracing AI in the Classroom (Part One) and (Part Two). Teaching Commons Blog. https://www.yorku.ca/teachingcommons/2023/09/14/blog-240/

Totten, T. (2023, September). From Obstacle to Opportunity: Reinventing Assignments in the Age of Generative AI. Teaching Commons Blog. https://www.yorku.ca/teachingcommons/2023/09/14/blog-239/

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/

Recordings of events & workshops

Access 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.

Practical AI series:

York University Summit on Generative AI in Higher Education: Faculty Showcase

Session: Artificial intelligence and academic integrity

Current research on GenAI & T&L @York

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.

Community of Practice: Generative AI Pedagogies at York

This community of practice is dedicated to uniting York University educators who share an interest in generative AI. Together, we connect, collaborate, and share resources, exploring best practices and addressing the challenges and opportunities we face in responding to this technology into postsecondary education. Our community of practice accepts new members at any time, and all who teach at York are welcome.

Learn more and join!