Skip to Main Content

Artificial Intelligence

Artificial Intelligence tools have recently grown in popularity. Learn more about AI, how it is being integrated into coursework, and the opportunities and challenges presented by this emerging technology.

The MRU Library, Academic Development Centre and Student Learning Services have collaborated to bring you the information on this living page. It will continue to be updated with new resources and information related to AI and higher education as they arise. The intent of this page is to provide information and resources about AI to the MRU community; for concerns related to academic misconduct and integrity, please contact the Office of Student Community Standards.

Last updated January 23, 2023

What is AI?

Artificial intelligence: ‘Machines that imitate some features of human intelligence, such as perception, learning, reasoning, problem-solving, language interaction and creative work’  UNESCO (2022).

 

Artificial intelligence based tools are widely used in academia and beyond, and new tools continue to be developed. AI tools can be implemented with positive purposes in education by supporting learners and helping to reduce the burden of routine or repetitive tasks, allowing for more focus on learning and research. Consider, for example, the benefits of automatic transcription of a lecture, grammar or spellcheck, or related reading suggestions in a library database. Conversely, there are also concerns associated with these tools, such as embedded bias, or the potential for misuse if students use them in un-authorised ways to complete an assignment.  

Eaton and Anselmo (2023) provide a succinct and practical overview of the use of AI apps in the classroom. They recommend instructors engage with these tools, explain them to students and explore possibilities for enhancing teaching and learning.

Artificial intelligence (AI) is a general term used to describe a number of different, specific systems. We encounter and use AI every day: from navigating maps on Google or Apple, to asking Siri or Alexa to set a timer, to searching a library catalogue. AI is a part of our lives. 

Terms like algorithm, machine learning, training data, neural networks and deep learning are often referenced in discussions related to AI.

Algorithm

The “brains” of an AI system, algorithms are a complex set of rules and decisions that determine which action the AI system takes. Machine learning algorithms can discover their own rules or be rule-based, in which case human programmers input the rules.

Machine Learning (ML)

A field of study with a range of approaches to developing the algorithms used in AI systems. Machine learning algorithms can discover rules and patterns in data without a human specifying them, which can sometimes lead to the system perpetuating biases.

Training Data

The data, generated by humans, used to train the algorithm or machine learning model. Training data is an essential component to the AI system, and may perpetuate the systemic biases of source data when implemented.

For these and related definitions, browse the Glossary of Artificial Intelligence Terms for Educators (CIRCLS, n.d.).

Functions of AI

AI systems are powerful enough to perform a wide variety of practical functions and tasks (examples retrieved from NVIDIA, n.d.; Upshall, 2022).

Function

Examples of Tools*
*Note: this list is not an exhaustive list.

Generate text from a prompt 

“Write a paper on the impact of fake news on education”
“Write a poem about existentialism in the style of Walt Whitman”
“Simplify the following radiology report”

ChatGPT

CopyAI

Jasper

Create summaries

(e.g., summarize a journal article, report or book chapter)

Scholarcy

ChatGPT

Quillbot

Create an image or digital illustration from a prompt

“A Cubist oil painting of a couple lounging next to a creek”
“A photorealistic image of a half-eaten pumpkin pie”

DALL·E 2

Midjourney

Craiyon 

Stable Diffusion 

Generate computer code

(e.g., generate new code from a comment, fix flawed code)

GitHub Copilot

ChatGPT

Translate text

“Translate the following text from Turkish to English”

Google Translate

ChatGPT

Enhance productivity in teaching and research by assisting with repetitive tasks such as writing, transcribing and suggesting related resources

Grammarly [writing support]

Web of Science Reviewer Locator [suggests peer reviewers]

Transkribus [handwriting transcription for archival documents]

Turnitin [text matching]

Opportunities and Challenges

While emerging AI technologies present a number of opportunities for learners and educators, there are also challenges to integrating these systems into curriculum and coursework.

Opportunities

  • New AI tools offer opportunities to introduce discussion and instruction centering on AI Literacy (Upshall, 2022). For example, instructors could use AI output for activities designed to help learners build skills in AI tool appraisal and practise critical thinking.
  • AI tools may help increase efficiency in learning environments. One instructor using ChatGPT describes it as a “learning companion” and a “multiplier of ability” (Wingard, 2023). For example:
    • AI systems may assist faculty or students in the initial stages of a project, such as brainstorming.
    • Students could use ChatGPT as a virtual study partner, using it to summarize content or generate test questions (Wingard, 2023).
  • AI may be an assistive tool for those with accessibility needs.
  • The rise of AI has prompted educators to rethink their assessment practices.
     

Challenges

  • AI technologies are advancing rapidly, making it difficult to keep up with tools that are available and what functions they can and cannot perform. For example, ChatGPT was trained on a mined set of data and not live on the internet, but this is likely to change in the future.
  • AI tools have no knowledge of the real world and may need to be paired with human verification. For example, text matching tools identify matching text, but only a human can determine if plagiarism has occurred.
  • AI tools may be used in situations where they lack validity, such as when journal impact factors are used to judge the value of individual research papers.
  • AI systems may be manipulated or used in unethical ways, such as when a student uses them to bypass learning.
  • Outputs can be difficult to detect; identifying when a learner has used AI generated text in their writing can be very difficult, posing a challenge to educators (Kumar et al., 2022).
  • AI systems perpetuate existing human biases, as they generate outputs based on patterns in the data they were trained on. For example, AI photo editing tools have expressed racial biases (Poisson, 2022), and large language software such as ChatGPT has perpetuated gender biases and stereotypes (Lucy & Bamman, 2021) in their outputs. 
  • Canadian copyright law implies AI cannot own the copyright to creative works. Determining the author of an AI-created work will require a legislative amendment and careful consideration of who (or what) can author AI-generated works. In 2021, the Government of Canada released A Consultation on a Modern Copyright Framework for Artificial Intelligence and the Internet of Things (Government of Canada, 2021), which aimed to gather public feedback on potential legislative amendments to the Copyright Act regarding AI. At this time, no amendments have been proposed (Craig, 2021).

Suggestions for Faculty & Students

Suggestions for Faculty

  • Have open conversations with students about AI and the implications of its use in their academic work. What do they know? What potential opportunities and challenges do they see?
  • Engage, explore and experiment (Eaton & Anselmo, 2023). Trying out AI tools yourself will help you understand what is possible.
  • Help students acquire a foundational understanding of academic integrity (e.g., have them complete MRU’s academic integrity online training module).
  • Mention AI tools explicitly in your course outline. Each time you introduce an assessment, clarify your expectations with respect to AI tool use.
  • Think more deeply than ever (D'Agostino, 2023) about the learning outcomes of your course and how your assignments align with those outcomes. Ask yourself: What are the cognitive tasks your students need to perform without assistance? 
  • Encourage productive struggle and learning from failure by allowing resubmissions/rewrites where feasible (see slide 28 of this resource) (Trust, n.d.). Fear of failure can be a factor in a student’s decision to engage in academic misconduct.
  • Design activities where students analyze, evaluate and revise AI output, or consider developing multimodal “performance task” assignments (Alby, n.d.).
  • Focus on designing assignments that enhance interactions students may already have with AI. While it may be tempting to increase the difficulty level of an assignment to make it harder for ChatGPT, consider how this might also impact student learning and present barriers to students with disabilities. 

Suggestions for Students

  • For every assignment and test, ask your instructor what their expectations are with respect to AI use. If you are unsure whether use of this tool (or what specific use) is allowed in your course, reach out to your instructor.
  • Experiment with AI tools to better understand what they can and cannot do. Take the time to critically analyze the output. (Sometimes it looks great on the surface, but not when you look more deeply at the content. These tools are great synthesizers, but the critical thinker is you.)
  • Learn more about academic integrity by completing MRU’s online training module.
  • Ask yourself these key questions:
    1. If I use this tool for a particular task, how will it affect my learning? Will it enhance or diminish my learning? Will it give me opportunities to think more deeply or less deeply? If I use AI to generate writing, will I lose my own voice?
    2. If I use this tool, will it be fair to other students?
    3. If I use this tool, what are the privacy considerations?
  • Encourage your peers to ask themselves the above questions, too.

Upcoming Events

Higher Education Podcast Lunch & Learns: How AI is Impacting Higher Education

Date: Tuesday, February 14, 2023
Time: 12:00pm - 1:00pm
Presenter: ADC
Where: Online

For our February Lunch and Learn podcast, we will engage with the Teaching in Higher Ed podcast's latest episode with Cynthia Alby, which looks at how artificial intelligence (like ChatGPT) is impacting higher education. Podcast available at https://teachinginhighered.com/podcast/how-artificial-intelligence-is-impacting-higher-education/

AI Squared: Artificial Intelligence and Academic Integrity

Date: Wednesday, February 15, 2023
Time: 10:00am - 11:15am
Presenter: Student Learning Services & MRU Library
Where: Ideas Lounge (EL1270)

Will artificial intelligence change the face of higher education (and has it already?) This panel discussion will highlight different perspectives on the impact of large language models like ChatGPT and DALL-E 2 on teaching and learning in higher education, including challenges and potential opportunities. Our student, faculty and staff panelists will share their thoughts and experiences with these emerging technologies, explore how they intersect with academic integrity, and reserve plenty of time for questions and comments from attendees.

Higher Education Podcast Lunch & Learns: How AI is Impacting Higher Education

Date: Tuesday, February 16, 2023
Time: 12:00pm - 1:00pm
Presenter: ADC
Where: Online

For our February Lunch and Learn podcast, we will engage with the Teaching in Higher Ed podcast's latest episode with Cynthia Alby, which looks at how artificial intelligence (like ChatGPT) is impacting higher education. Podcast available at https://teachinginhighered.com/podcast/how-artificial-intelligence-is-impacting-higher-education/

Recommended Readings and Resources

D’Agostino, S. (2023, January 12). ChatGPT advice academics can use now. Inside Higher Ed.
https://www.insidehighered.com/news/2023/01/12/academic-experts-offer-advice-chatgpt

  • D’Agostino solicits advice from eleven leading academics for their thoughts on ChatGPT and learning, both the risks posed and opportunities offered by the technology.

 

Eaton, S., & Anselmo, L. (2023, January). Teaching and learning with artificial intelligence apps.
Taylor Institute for Teaching and Learning.
https://taylorinstitute.ucalgary.ca/teaching-with-AI-apps

  • Advice on using AI apps in the classroom.  “If we think of artificial intelligence apps as another tool that students can use to ethically demonstrate their knowledge and learning, then we can emphasize learning as a process not a product.”  

 

Fyfe, P. (2022). How to cheat on your final paper: Assigning AI for student writing. AI & Society. https://librarysearch.mtroyal.ca/permalink/01MTROYAL_INST/1qa1aqk/cdi_crossref_primary_10_1007_s00146_022_01397_z 

  • “This paper shares results from a pedagogical experiment that assigns undergraduates to ‘cheat’ on a final class essay by requiring their use of text-generating AI software. For this assignment, students harvested content from an installation of GPT-2, then wove that content into their final essay. At the end, students offered a ‘revealed’ version of the essay as well as their own reflections on the experiment. In this assignment, students were specifically asked to confront the oncoming availability of AI as a writing tool.”

 

Johnson, S. (2022, April 15). A.I. is mastering language. Should we trust what it says? New York Times Magazine.
https://www.nytimes.com/2022/04/15/magazine/ai-language.html

  • This longform piece from the New York Times Magazine provides a useful overview of large language models (LLMs) and the history of OpenAI, the company behind GPT-3 and DALL·E 2.

 

Kendon, T. (2023, January 10.) Articles and Resources for ChatGPT. ELEARN @ UCALGARY.
https://elearn.ucalgary.ca/articles-and-resources-for-chatgpt/

  • A growing list of reading and other resources relating to ChatGPT.
     

Office for Faculty Excellence (n.d.). Practical responses to ChatGPT. Montclair State University.
https://www.montclair.edu/faculty-excellence/practical-responses-to-chat-gpt/

  • Tips and suggestions for classroom approach and assignment design with ChatGPT in mind.
     

Poisson, J. (Host). (2022, December 14). AI art and text is getting smarter, what comes next?
[Audio podcast episode]. In Front Burner. CBC.
https://www.cbc.ca/radio/frontburner/ai-art-and-text-is-getting-smarter-what-comes-next-1.6684148

  • A 25-minute podcast episode featuring Will Knight of the magazine WIRED discussing AI art generator DALL-E 2 and the chatbot ChatGPT.

 

Stachowiak, B. (Host). (2023, January 12). How artificial intelligence is impacting higher education [Audio podcast episode]. In Teaching in Higher Ed. Teaching in Higher Ed.
https://teachinginhighered.com/podcast/how-artificial-intelligence-is-impacting-higher-education/

  • This 43-minute podcast interview with Dr. Cynthia Alby overviews AI in higher education and the way that tools like ChatGPT may change instruction methods and assessment.

 

Trust, T. (n.d.). ChatGPT and education [Google slides].
https://docs.google.com/presentation/d/1Vo9w4ftPx-rizdWyaYoB-pQ3DzK1n325OgDgXsnt0X0/edit?usp=sharing 

  • This Google Slides deck provides an overview of what ChatGPT is, what it can and cannot do, and what educators can do about it. It also includes links to additional resources at its end. Screenshots of the ChatGPT interface are also provided as illustrations of tasks it can perform which can be useful to refer to or provide to others in cases when the Open AI ChatGPT website is at capacity.

 

Warner, J. (2023, January 4). How about we put learning at the center? Inside Higher Ed.
https://www.insidehighered.com/blogs/just-visiting/how-about-we-put-learning-center 

  • Writing instructor John Warner discusses ChatGPT, seeing it as an opportunity to reflect on writing tasks performed by students and the learning in higher education more broadly.
     

Additional Information

Office of Student Community Standards (OSCS)

The Office of Community Standards is responsible for promoting the rights and responsibilities of students through the administration of the Code of Student Community Standards and the Code of Student Academic Integrity. They also support the MRU campus community in navigating conflict using various resolution pathways.

If you have questions or concerns about the use of AI in an assignment, course or academic assessment at MRU, please contact the Office of Community Standards by emailing studentcommunitystandards@mtroyal.ca

Feedback

As new AI technologies emerge, this page will be routinely updated with additional information and resources to support the MRU community. Have a suggestion for what to include? Get in touch with us. 

References

CIRCLS. (n.d.). Glossary of artificial intelligence terms for educators – CIRCLS. Educator CIRCLS Blog. Retrieved January 18, 2023, from
https://circls.org/educatorcircls/ai-glossary 


Craig, C. J. (2021). AI and copyright. In F. Martin-Bariteau & T. Scassa (Eds.), Artificial intelligence and the law in Canada. LexisNexis Canada.
https://ssrn.com/abstract=3733958 


Eaton, S., & Anselmo, L. (2023, January). Teaching and learning with artificial intelligence apps. Taylor Institute for Teaching and Learning.
https://taylorinstitute.ucalgary.ca/teaching-with-AI-apps


Government of Canada. (2021). A consultation on a modern copyright framework for artificial intelligence and the Internet of Things.
https://ised-isde.canada.ca/site/strategic-policy-sector/en/marketplace-framework-policy/copyright-policy/consultation-modern-copyright-framework-artificial-intelligence-and-internet-things-0


Kumar, R., Mindzak, M., Eaton, S. E., & Morrison, R. (2022, May 17). AI & AI: Exploring the contemporary intersections of artificial intelligence and academic integrity [Conference presentation]. Canadian Society for the Study of Higher Education Annual Conference, Online.
http://hdl.handle.net/1880/114647


Lucy, L., & Bamman, D. (2021). Gender and representation bias in GPT-3 generated stories. Proceedings of the Third Workshop on Narrative Understanding, 48–55.
https://doi.org/10.18653/v1/2021.nuse-1.5 


NVIDIA. (n.d.). NVIDIA large language models (LLMs). Retrieved January 18, 2023, from
https://www.nvidia.com/en-us/deep-learning-ai/solutions/large-language-models/ 


UNESCO. (2022). K-12 AI curricula: A mapping of government-endorsed AI curricula. UNESCOC Digital Library.
https://unesdoc.unesco.org/ark:/48223/pf0000380602 


Poisson, J. (Host).  (2022, December 14). AI art and text is getting smarter, what comes next? [Audio podcast episode]. In Frontburner. CBC.
https://www.cbc.ca/radio/frontburner/ai-art-and-text-is-getting-smarter-what-comes-next-1.6684148


Trust, T. (n.d.). ChatGPT & education [Google slides].
https://docs.google.com/presentation/d/1Vo9w4ftPx-rizdWyaYoB-pQ3DzK1n325OgDgXsnt0X0


Upshall, M. (2022). An AI toolkit for libraries. Insights, 35(18).
https://doi.org/10.1629/uksg.592


Wingard, J. (2023, January 10). ChatGPT: A threat to higher education? Forbes.
https://www.forbes.com/sites/jasonwingard/2023/01/10/chatgpt-a-threat-to-higher-education/