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Generative Artificial Intelligence in Teaching and Learning

Our page focuses on Generative Artificial Intelligence (Generative AI) as it relates to teaching and learning at McMaster. To see McMaster’s broader approach to Generative AI please see the Office of the Provost & Vice-President (Academic) website.

Generative AI is a type of artificial intelligence that uses machine learning to generate new content by analyzing and processing vast amounts of data from diverse sources. Generative AI tools can generate text, images, video, sound and code. 

Different tools are trained on different datasets and with different training methods. The generated responses of these tools are probabilistic, which can result in errors in responses.  

Large language models (LLMs), for instance, specialize in analyzing and processing text and generating new text. Different LLMs have distinct datasets and employ unique training methods. GPT 3 and GPT 4 are examples of LLMs. OpenAI’s ChatGPT is a chatbot created on GPT 3 or GPT 4.  

While generative AI is not new, OpenAI’s launch of ChatGPT in November 2022 marked the fastest recorded adoption of a technology tool 

Over the intervening months, the release of similar text-based generative AI tools from Microsoft’s Bing to Google’s Bard, in addition to improvements in tools have contributed to a perception of an explosion of AI 

Indeed, the rapid proliferation of tools and advancements in technology saw over 100 leaders in AI technology write an open letter urging a collective pause on AI developments more powerful than GPT 4 to give time for security and safety features to develop and for the creation of regulation and governance structures.  

The need for such regulation or governance extends to full nations, but also to specific sectors, such as post-secondary education, and in turn, McMaster University.   

Broader issues related to generative AI include privacy of personal data, risks of misinformation, existential risks, environmental costs, labour exploitation, and copyright. 

Expandable List

  • Create informative, well-written text: prose, poetry, dialogue, code  
  • Provide examples and references  *references may be ‘hallucinated’ 
  • Generate outlines, questions, tables, long form text  
  • Summarize inputted text  
  • Provide feedback on text – both form and structure  
  • Explain concepts at different levels of understanding   
  • Translate between languages  
  • Remember within a chat thread – follow-up prompts
  • Hallucinations: confident declarations that are factually inaccurate (e.g., references to articles that don’t exist)  
  • Uneven access material after 2021: the free version of ChatGPT cannot access the web, though the subscription model can, as can Microsoft’s Bing 
  • Biases in training data are replicated in generated responses  
  • There is variation in responses based on the wording and framing of the user’s prompt 
  • If using ChatGPT 3 (free version) there can be lag times or delays in access if demand is high; Bing and ChatGPT 4 do not experience these delays. 

McMaster Resources

Generative AI in Teaching and Learning at McMaster University – MI Guidebook

This Guidebook introduces educators to generative AI in teaching and learning at McMaster University, including relevant guidelines. It offers practical advice for using generative AI in teaching, including assessment, as well as opportunities and challenges for student learning.

Resources for students

These resources may be used by instructors to stimulate discussions with students about generative AI in their courses in keeping with the Provisional Guidelines on the Use of Generative AI at McMaster.

Compiled Resource Lists 

This list “AI Text Generators: Sources to Stimulate Discussions Among Teachers” is curated by Anna Mills for the Writing Across the Curriculum Clearninghouse. It is a continually updated, well organized list of resources relevant to post-secondary educators.  

Santa Fe University’s Library developed this repository of resources for post-secondary educators organized by frequently asked questions and includes resources on how educators can make use of generative AI in their teaching, as well as free courses on using generative AI.  

Contact North has both compiled relevant resources on generative AI and produced several good webinars on applications of generative AI to teaching and assessment.  

Compiled resources under “a critical lens” are pieces that critique or challenge generative AI hype.  

Overview of Generative AI 

This “back to basics” article for educators explains what AI is, what a large language model is and what ChatGPT is and then explains some potential implications for educators.  

This interactive New York Times feature demonstrates how a large language model (LLM) like ChatGPT is trained while also explaining some of the core concepts behind LLMs. 

For a more technical read, this article explains in an accessible way what a large language model is and how they work.  

An article from Vice explains what ChatGPT – a specific generative AI tool – is for a non-technical audience. 

Ethical Use 

These guidelines from the European Network for Academic Integrity explore the ethical use of generative artificial intelligence in the post-secondary context.  

UNESCO issued guidelines on the use of generative AI with a broader scope on education.  

This video recorded webinar features guests speaking about the ethical use of generative AI in relation to academic integrity, accessibility and equity.  

This MIT technology review series looks at the risks of exploitation that generative AI poses.  

Assignment Design 

This webinar from Anna Mills covers an introduction to generative AI, as well as suggestions for distinguishing human and AI writing, and designing assignments to discourage AI use.  

This series of webinars from Deakin University offers an overview of generative AI, with a focus on assessment and future possibilities.  

Considerations for assessment design as well as examples are available here from Monash University.  

Find Out More 

This newsletter, One Useful Thing, by Ethan Mollick offers a near-weekly article on applications and issues of generative AI in post-secondary, with a specific focus on how educators can make use of generative AI in teaching and learning.  

The New York Times podcast, Hardfork, gives weekly hour-long podcast coverage of major issues in technology, with a significant focus around AI.  

There’s An AI For That aggregates generative AI tools which may be helpful for understanding the range of possible generative AI tools available.  

Practical Instructions and Applications of Generative AI for Teaching and Learning

Practical AI for Instructors and Students: Five-part video series by the Wharton School

This excellent introduction to generative AI for post-secondary educators offers an overview of the capabilities and limitations of generative AI tools, how to prompt well, and concrete examples of how to use tools in teaching and learning.

OpenAI Teaching with AI

This guide from OpenAI includes example prompts that may be useful for instructors, as well as possible ways to incorporate generative AI meaningfully into classes.