Overview
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In the previous week, you completed and shared your Technology Integration Activity assignment. This week, we will take time to explore the activities created and shared by your classmates. We will also take some time to explore what’s on the horizon in terms of digital technology developments that could be integrated into education. We will look at Artificial Intelligence (AI) and its impact on education. You will have a chance to learn about AI, and to share your thoughts on how you might be able to respond to the challenges and opportunities presented by it.
By the end of Week 13, you should also have completed all of the requirements for Assignment 1: Community Engagement. This should include a final reflective post, looking back on what you have accomplished with your Technology Integration Activity project, what strengths you have developed in the use of digital technologies in education, and what skills and technologies you would like to continue to explore and develop.
Topics
Week 13 is divided into four topics:
- Topic 1: Technology Integration
- Future Trends: Artificial Intelligence in Education
- Topic 2: Community Engagement
- Topic 3: Assignment 1 Submission
Learning Outcomes
When you have completed this week’s activities, you should be able to:
- Describe what Artifical Intelligence is and the challenges and opportunities it presents.
- Discuss your initial experiences using agentic and generative Artificial Intelligence.
Resources
Learn more about Artificial Intelligence
Databricks. (2025). Retrieval Augmented Generation.
https://www.databricks.com/glossary/retrieval-augmented-generation-rag
Finn, T. & Downie, A. (2025). Agentic AI vs. generative AI.
https://www.ibm.com/think/topics/agentic-ai-vs-generative-ai
Gadesha, V. (September 14, 2025). What is prompt engineering?
https://www.ibm.com/think/topics/prompt-engineering
Heaps, T. (2024). Generative Artificial Intelligence: Practical Uses in Education. Open Education Manitoba. https://pressbooks.openedmb.ca/aiineducation/
Heaps, T. (2024). Writing and refining prompts, In Generative Artificial Intelligence: Practical Uses in Education. Open Education Manitoba. https://pressbooks.openedmb.ca/aiineducation/chapter/writing-and-refining-prompts/
Keen, M. IBM. (April 21, 2025). Generative vs Agentic AI: Shaping the Future of AI Collaboration. https://www.youtube.com/watch?v=EDb37y_MhRw
Keen, M. IBM. (July 28, 2023). How Large Language Models Work. https://youtu.be/5sLYAQS9sWQ?si=WaHsZ1-MzWYY3zKE
Massachusetts Institute of Technology, Sloan School of Management. (2021). Machine Learning, Explained. https://mitsloan.mit.edu/ideas-made-to-matter/machine-learning-explained
Stanford University, Human-Centered Artificial Intelligence. (2020). Artificial Intelligence Definitions.
https://hai.stanford.edu/sites/default/files/2020-09/AI-Definitions-HAI.pdf
Stryker, D. & Kavlakoglu, E. (August 9, 2024). What is artificial intelligence (AI)?
https://www.ibm.com/think/topics/artificial-intelligence
Artificial Intelligence and education
British Columbia. (2024). Considerations for Using AI Tools in K-12 Schools.
https://www2.gov.bc.ca/assets/gov/education/administration/kindergarten-to-grade-12/ai-in-education/considerations-for-using-ai-tools-in-k-12-schools.pdf
British Columbia. (2024). Curriculum Connections: Digital Literacy and the Use of AI. https://www2.gov.bc.ca/assets/gov/education/administration/kindergarten-to-grade-12/ai-in-education/curriculum-connections-digital-literacy-and-the-use-of-ai.pdf
British Columbia. (2024). Digital Literacy and Use of AI in Education: Supports for British Collumbia schools.
https://www2.gov.bc.ca/gov/content/education-training/k-12/administration/program-management/ai-in-education
Chiu, T. K., Ahmad, Z., Ismailov, M., & Sanusi, I. T. (2024). What are artificial intelligence literacy and competency? A comprehensive framework to support them. Computers and Education Open, 6, 100171. https://www.sciencedirect.com/science/article/pii/S2666557324000120
Klopfer, E., Reich, J., Abelson, H., & Breazeal, C. (2024). Generative AI and K-12 Education: An MIT Perspective. An MIT Exploration of Generative AI.
https://mit-genai.pubpub.org/pub/4k9msp17/release/1
Park, J. (2025). A systematic literature review of generative artificial intelligence (GenAI) literacy in schools. Computers and Education: Artificial Intelligence, 9.
https://www.sciencedirect.com/science/article/pii/S2666920X25001274
Park, Y., & Doo, M. Y. (2024). Role of AI in Blended Learning: A Systematic Literature Review. The International Review of Research in Open and Distributed Learning, 25(1), 164–196. https://www.irrodl.org/index.php/irrodl/article/view/7566
Perkins, M., Furze, L., Roe, J., & MacVaugh, J. (2024). Navigating the generative AI era: Introducing the AI assessment scale for ethical GenAI assessment. Journal of University Teaching and Learning Practice, 21(6).
https://open-publishing.org/journals/index.php/jutlp/article/view/810
Royce, C.A. & Bennet, V. (May 12, 2025). Agentic AI: Developing the Benefits for Classroom Learning – Part 1.
https://www.nsta.org/blog/agentic-ai-developing-benefits-classroom-learning-part-i
Royce, C.A. & Bennet, V. (June 5, 2025). Agentic AI: Developing the Benefits for Classroom Learning – Part 2.
https://www.nsta.org/blog/agentic-ai-developing-benefits-classroom-learning-part-ii
Thompson Rivers University. (2024). Artificial Intelligence in Education. https://aieducation.trubox.ca/
Artificial Intelligence controversies
Collin, S., Lepage, A. & Nebel, L. (2024). Ethical and Critical Issues of Artificial Intelligence in Education: A Systematic review of the literature. Canadian Journal of Learning and Technology, 49(4). (Use Google Translate to get English version)
https://cjlt.ca/index.php/cjlt/article/view/28448/20767
Kosmyna, N., Hauptmann, E., Yuan, Y.T., Situ, J., Liao, X.H., Beresnitzky, A., Braunstein, I. & Maes P. (2025). Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. arXiv:2506.08872.
https://arxiv.org/abs/2506.08872
Nicoletti, L. & Bass, D. (June 9, 2023). Humans are Biased. Generative AI is Even Worse. Bloomberg.
https://www.bloomberg.com/graphics/2023-generative-ai-bias/
Zewe, A. (January 17, 2025). Explained: Generative AI’s environmental impact. MIT News: On campus and around the world.
https://news.mit.edu/2025/explained-generative-ai-environmental-impact-0117
Read this if AI is getting you down
Burgess, K. (June 25, 2024). ChatGPT Now has PhD-Level Intelligence, and the poor personal choices to prove it. McSweeney’s Internet Tendency.
https://www.mcsweeneys.net/articles/chatgpt-now-has-phd-level-intelligence-and-the-poor-personal-choices-to-prove-it
Try out some Artificial Intelligence
Contact North. (2024). Free, Personalized AI Powered Apps. https://apps.contactnorth.ca/
Topic 1: Technology Integration
Future Trends: Artificial Intelligence in Education
A few definitions
- Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy. https://www.ibm.com/topics/artificial-intelligence
- Generative Artificial Intelligence (Gen AI) is a type of artificial intelligence that learns patterns from vast amounts of existing data and uses that knowledge to create new, novel content, such as text, images, audio, video, or code, in response to user prompts. (from the Google AI Overview for the search: What is generative AI?).
- Agentic Artificial Intelligence (Agentic AI) refers to artificial intelligence systems designed to act autonomously to achieve goals, setting objectives, planning, and executing actions with minimal human intervention. (from the Google AI Overview for search: What is agentic AI?).
Artificial intelligence burst into the foreground of the worlds of education and content creation, among others with the release of ChatGPT 3 in November of 2022. It was the first instance of generative AI that was widely recognized as useful by those that were not already engaged in the field of AI. The text content it could produce was substantially better than other versions and platforms developed previously but it was in line with progress that had been made over many years.
It took some time for post-secondary educators in Canada to approach generative AI and agentic AI in a constructive way, and this process has been even slower for K-12 education.
The implications for education that were presented immediately, and in the following years can be expressed as several difficult issues summarized below.
AI Implications in Education Today
AI as a challenge to academic integrity
The first issue to confront educators was the potential for breaches of academic integrity by students that might ask an AI platform to complete a written assignment for them. Even with the capabilities of updated versions of ChatGPT and other platforms, generating a decent essay can take several iterations of initial prompt and refining questions. Post-secondary researchers found AI could produce a paper in the ‘B’ grade range on most topics, but each version has improved since.
In response, many instructors have adopted strategies such as in-class writing assignments; using iterative writing projects where progress is reviewed at several stages; or using ‘Track changes’ in MS Word to enable a view of the development of written work. Short one-on-one discussions of student writing have also become popular, where class size permits.
AI as a tool for student writing/creating
In some cases, instructors have included (typically limited) permission to use AI in an assignment. This often is limited to an ideation phase, but with the requirement that students indicate how it was used, which tool was used, and how they reflected on and decided what AI output to use. In a communications example the student would use a graphic creation tool like Dalle to generate an image for specific use. They would record the prompts used and the number of iterations before a usable product was produced. This process can then be examined and reflected upon.
Ethical issues of AI
Privacy – Most AI tools require a user to sign up for an account. Tools based outside of Canada (the vast majority) may use information used to create an account, along with any prompts or conversations used with the tool in ways the user may not have intended.
Cost – The most effective versions of Generative AI tools, as text or image producers, require a monthly subscription. This creates a divide in student abilities to take advantage of assignments or activities where AI is permitted or encouraged.
Bias – Generative AI tools are trained using the internet. Most platforms employ staff to try to remove or suppress the biases that this training produces in the content it generates.
Hallucinations – Many Generative AI platforms will create content that is false, including references in response to specific requests. This has been reduced in later versions but there remains a risk to blindly trusting AI content.
Environmental impact – AI data centres use large amounts of electricity to drive large language models and manage agentic AI queries. In addition to consuming power that adds to the carbon footprint, water is a key resource in cooling these data centres.
AI as a tool for instructors
Curriculum development – AI can be a starting point for the brainstorming stage of developing a course or program. It can also be used to check that an obvious topic hasn’t been missed.
Marking – We already have the automated marking of multiple choice and short answer questions within most learning management systems. Systems that give automated feedback on writing can be a great self-check for students starting or returning to post-secondary learning. They can also be an important impetus to take the next step of getting help from the institutional writing centre. The use of AI to actually award grades for students is much more controversial.
AI use as a skill for learners and researchers
AI tools have for some time assisted learners in writing. There is a strong argument that students need to develop an AI literacy that includes being able to use these tools as a partner in the writing process and in various forms of research.
Agentic AI as a support for learning
One promising agentic AI tool for learning are chat bots that support student learning in a specific discipline. There are many examples of these agents, with a large language model that supports a conversational approach, using a more discrete selection of materials on a topic to create an ‘expert’ tutor for a specific subject.
AI use as a skill required in the workplace
The use of AI for both text and graphics in environments with the need for quick turnaround and massive quantities of content has been accepted in the fields of communications and marketing. A tension exists between teaching the generation of content from scratch and preparing students for their eventual workplace.
Topic 2: Community Engagement
Activity 1: Discussion Questions
Your instructor will post questions in the course discussion forum related to this week’s topics. Respond to these questions, and check out (and reply to) some of the responses posted by your classmates. Feel free to use the course forum to post any thoughts or questions you may have related to this week’s readings and activities.
Activity 2: Try Out Some AI
Check out the AI agents set up by Contact North or us an AI platform that you are comfortable with (CoPilot, Google AI etc.). Adopt the role of a student, an instructor or a curriculum developer (as listed above). Set out a goal for your use of AI, experiment with one or more AI tools, and write a short blog post describing your experience.
In your post include:
- The role you assumed
- Your goal for the AI use
- The tool(s) you tried out
- The results you had with each tool
- Any issues you see with your AI use in a real-world setting
Topic 3: Assignment 1 Submission
Throughout this course, you have been working on Assignment 1: Community Engagement. You have created your own portfolio for sharing your thoughts, and the assignments that you have completed throughout the course. This week, make sure that you have met all of the Community Engagement requirements as set out in the Assignment 1: Community Engagement assignment guide. Wrap up your course portfolio activities with a final reflective post. Consider:
- What do you feel you have accomplished in this course, in particular, with your Technology Integration Activity?
- Where do you see your strengths with the integration of digital technologies in education now, at the end of this course?
- What skills and tools would you like to continue to explore and develop now that the course is wrapping up?
Refer to the Assignment 1: Community Engagement assignment guide for further details about specific assignment completion requirements.
Due Date: End of Week 13.
Week 13 Summary
In this week, we have explored some emerging technologies that have the potential to significantly impact education. We have looked at artificial intelligence, its impact on K-12 and post-secondary education, and the challenges and opportunities it presents. As this week—and this course—come to a close, you have put the final touches on your course portfolio and wrapped up your Community Engagement activities as part of Assignment 1. But, hopefully, that is not the end of your Community Engagement activities! Hopefully, the connections you have made in this course will become a part of the personal learning network (PLN) that you have begun to create, and that PLN will continue to be a resource for you to draw upon to learn more about and support each other in the effective and meaningful integration of digital technologies in teaching and learning.
References
Simon Fraser University. (2024). Artificial Intelligence at SFU. https://www.sfu.ca/big-data/using-data/artificial-intelligence-at-sfu.html
University of British Columbia. (2024). Generative AI. https://genai.ubc.ca/
University of Toronto. (2024). Use Artificial Intelligence Intelligently. https://security.utoronto.ca/framework/guidelines/use-ai-intelligently/
