7.2. Volunteer Reflections

Raisa Jivani, EdD in Post-Secondary Leadership (Candidate), Werklund School of Education, UCalgary

From Impossible to “I’m Possible”: A Preservice Teacher Educator’s Take on the AI Transformation

Forget the old playbook for the future of education. After attending the AI Innovation in Higher Education Exchange, I feel less like an architect with a fixed blueprint and more like a curator on the project, working alongside students to construct an understanding with powerful new tools. The entire event buzzed with incredible ideas, but the biggest takeaway was a feeling that what once seemed impossible is now proudly declaring, “I’m possible.”

One theme that truly stood out was the dawn of the “cyborg” student, a concept powerfully articulated by Dr. Mohammad Keyhani from the Haskayne School of Business. And don’t worry, this isn’t a sci-fi movie plot. He’s talking about students who will naturally use AI as a partner in their learning. Think of AI less as a crutch and more as a collaborator in their thinking. Instead of staring at a blank page, they can co-create a first draft with a tool, freeing up their mental energy for what truly matters: applying their uniquely human critical thinking and emotional intelligence to challenge, refine, and elevate the work. As his research at the University of Calgary shows, the goal isn’t to fear the machine, but to learn how to ask the right questions.

This forward-thinking approach reminds me of the incredible work happening right here at UCalgary, like the SMARTIE tool developed by Dr. Soroush Sabbaghan. His AI-powered tool is a brilliant example of using technology with heart, helping educators build more inclusive and diverse courses. It’s a powerful reminder that one of technology’s greatest promises lies in building more inclusive and equitable learning spaces for all students.

As a doctoral student and a teacher of future teachers, these ideas felt like a clear call to action. We’re at a “Ctrl+Alt+Del” moment for our teaching methods. Our role is changing. We are no longer the sole gatekeepers of information. Instead, we are becoming the architects of learning experiences that build the uniquely human skills that AI can’t copy. We must teach our students, and their students, to be the critical thinkers who can challenge an algorithm’s answer and the emotionally intelligent leaders who can navigate human connection.

I left the conference with a powerful sense of optimism. The future of education isn’t about being replaced by technology; it’s about being empowered by it. It’s about realizing that our ability to think, feel, and connect will be our most valuable skills. The future is knocking, and it’s asking us to rethink and readapt. And for this educator, the answer is a definite, “I’m ready.” It’s time to get with the program- the AI program, that is. After all, the future is what we make it, and it looks like we’re all about to get a major upgrade.

Adelee Penner, PHD in Educational Leadership, Werklund School of Education, UCalgary

Volunteering at the University of Calgary’s AI Innovation and Higher Education Exchange was an inspiring and thought-provoking experience. My biggest takeaway was the idea that AI shouldn’t just be an add-on to existing educational practices but should be leveraged to transform the way we think about teaching and learning in higher education. One of the most powerful insights I gained was the value of designing learning tasks that students cannot complete without the support of AI tools. This reframing challenges instructors to move beyond surface—level assignments and toward complex, real-world tasks that mirror the kinds of thinking, problem-solving, and collaboration students will need in a rapidly evolving world.

Rather than replacing critical thinking, AI—when used thoughtfully—can amplify it. For example, AI tools can help students analyze data more efficiently, visualize abstract concepts, and test multiple hypotheses quickly. This frees up cognitive space for learners to engage in higher-order thinking: asking better questions, evaluating sources, making nuanced arguments, and reflecting critically on the ethical implications of their work. Instead of memorizing content or performing procedural tasks, students are invited to work with the machine to co-create knowledge, refine their understanding, and explore complex, interdisciplinary problems.

I also appreciated the opportunity to participate in the creation of case studies during the exchange. This collaborative process grounded our conversations in practical application and allowed us to model what responsible and innovative use of AI can look like across different disciplines. It was clear that there is no one-size-fits-all approach, and that thoughtful, intentional design is key. Being part of a community of educators, researchers, and thought leaders who are willing to explore these questions openly and critically was energizing.

This experience has shifted my perspective on AI in education—from viewing it as a challenge to be managed, to recognizing it as a powerful catalyst for reimagining what deep, meaningful learning can be.

Author’s note:  In the spirit of the day, I have used ChatGPT to help author this reflection.  It took a few tries to prompt a response worth sharing.

Uju Nnubia, PhD in Learning Sciences, Werklund School of Education, UCalgary

Workshop Reflections

The most important aspects of the workshops that stood out for me were the “Flipping the Script: How AI Became a Grammar Coach in a Beginners’ French Course” and “Teaching Cyborg Students: Experiences from a Generative AI Class at the University of Calgary”. These topics offered thought-provoking insights into the evolving role of artificial intelligence in higher education. Both workshops challenged traditional paradigms of teaching and learning by illustrating how AI is not only a tool but also an active participant in the educational process.

In the French course workshop, I was particularly intrigued by how AI was reimagined as a “grammar coach,” helping beginner students gain confidence in real-time learning. This approach empowered learners to experiment with language and build fluency through immediate feedback. It emphasized AI’s potential to democratize language learning by personalizing instruction and offering continuous support, functions that are often difficult for a single instructor to provide.

The “cyborg students” workshop expanded the conversation to a broader philosophical level. By treating students as hybrid learners—humans augmented by generative AI—it questioned conventional ideas of authorship, originality, and intellectual labor. The instructor highlighted the importance of teaching students not just to use AI but also to critically reflect on its outputs, biases, and ethical implications.

The question and answer section also offered a more direct engagement with the workshop facilitators on specific issues of interest to me. Generally, these workshops underscored that integrating AI into the classroom is not about replacing educators but reconfiguring the learning environment to be more responsive, inclusive, and future-ready. These sessions affirmed my belief that AI, when thoughtfully integrated, can amplify both teaching and learning—making education more accessible, reflective, and empowering for diverse student populations.

Craig Delean, Master of Urban Planning, School of Architecture, Planning and Landscape, UCalgary

AI Exchange Reflections

My perspective on generative AI is rather bleak. I was involved in creating collages to accompany the discussion for the “AI, Design, and Homelessness” panel held in March, and I had to research and understand issues of AI in order to steer the discussion toward concerns on people’s minds. Many of these concerns were not properly addressed during the Exchange and ended up sounding much more like an advertisement for it. I felt like that there weren’t enough varying opinions to address many of the ethical questions about the technology and its limitations, which were more often than not categorized as either “illogical fear” or that things that I had to trust would be “fixed later” as long as I invested in the technology first. I think more contrasting opinions would have created a more complex discussion.

I found it especially interesting that the presenters didn’t meaningfully confront the threat of plagiarism as an issue in AI use despite plagiarism being academic misconduct. Massive datasets needed for Gen AI to work confuse “free use” data and “freely accessible” copyrighted material. As a result, AI takes the work/labour and decision-making of millions of online users without consent or compensation in order to market the idea that these AI algorithms “think”. AI cannot create anything new by definition; it only amalgamates what is currently available as a result of human labour- oftentimes without proper sources. Major companies like Disney and Universal Studios have launched lawsuits towards Midjourney as a “plagiarism machine” for their IP. Considering how language models lack the same legal guardrails as visual models, it would have been insightful to have someone with a legal or academic writing background to address whether AI is or is not in line with proper academic conduct before advocating for its use.

I heard presenters admit to knowing that most essays are now written by Chat GPT, while also admitting that they also use Chat GPT to grade those same essays without any in-depth discussion on what the point of grades are if both students and educators care so little about them. I also found the suggestion to “treat students like robots, not people” a bit out of touch with students who already perceive University as an insufferable checklist of busywork required to get a degree. I understand that the point of these statements was to point out how classwork should be restructured to better use AI’s capabilities, but it only makes me wonder why educators had to wait for AI to come along before restructuring the classwork paradigms that weren’t giving students a fulfilling education. Why is AI the catalyst to change the apathy in learning that has been happening for, from what I understand, a decade now? Will AI really solve what educators haven’t been able to for years now? I don’t think the novelty of working with a new tool will solve this issue long-term.

But, above all, I was not sold on why I would even need to use AI as a student. I see my peers use AI in graduate level classes and it’s very obvious by the lack of craftsmanship. This isn’t a case of students not knowing how to “use AI properly in their workflow” as the panelists suggested, but rather that the workflow was never learned at all.

I have a Fine Art background and I learned the value of inconvenience. Working through complex design problems is always going to be hard, and no fancy tool will help you fix it unless you know how to work through a problem without them first. For example, a calculator won’t help you solve a complex math equation if you don’t know the order of the operations. I have always recognised inconvenience as how I learned the most. Reading the throw-away lines of a boring paper (that would have been deemed “unnecessary” by AI summaries) often sparked an idea for a design. Having to draw a thumbnail again and again until I got it just right (something I’ve been told I could make a hundred of in a second with ChatGPT) has often been the starting point of my favourite drawings.

I’ve noticed that many of my peers don’t have the ability to solve complex design issues and are trying to use AI to replace the inconvenient steps of working through problems. It’s convenient to ask ChatGPT to suggest some ideas for your Master Plan of a site in Calgary, but it’s inconvenient to make sure that they actually work in practice by going to the site, observing what happens there, talking to those who live in that community, and reading through handpicked pages in policy documents to understand what can and cannot be done. AI models can pluck data from a dataset of existing ideas but cannot make sophisticated or contextual design outcomes unless the student already knows how to do so without it.

Bypassing this inconvenience to make, from what I’ve observed in my classes, worse projects faster is not appealing to me. Learning takes time and inconvenience, and that’s what stuck with me the most during school.

I would have liked to see more variety in the panelists to show a complete story of AI and how it should or shouldn’t be applied. I think the fact I was told I would be “left behind” and “out of a job” if I didn’t bypass the part of learning I find most valuable rather upsetting. I personally find the notion that I must surrender my data and labour to mega-corporations so their product can, supposedly, “do work better and faster than me” rather insulting. I found it a bit odd that biases found in datasets and the issue of who creates and owns them were just seen as a “kink” in the algorithm rather than a major ethical flaw. AI was equated to “encountering aliens for the first time” yet I was told that many of the fears about it were illogical. I wish that there had been a more diverse cast of presenters so that the ethical concerns of this technology weren’t treated as an unfortunate blockade to inevitable progress.

Emmanuel Amaechi, Sustainable Development Solutions Network (SDSN) Canada Program Specialist, Office of Institutional Commitments, UCalgary

Participating in this session was both thought-provoking and energizing. The conversations around the evolving role of Generative AI in education particularly stood out to me. One of the most impactful moments was the presentation discussing how AI can enhance feedback mechanisms in large classrooms—an increasingly relevant challenge as class sizes increase. The speaker highlighted how personalized, timely feedback fosters deeper student engagement and learning, and how AI tools may help bridge the gap where human resources are limited.

Another insightful discussion revolved around the distinction between unstructured use and principled use of AI. This reminded me of how easily these tools can be adopted without intentionality, but that true value comes when educators thoughtfully integrate them into pedagogy to strengthen learning outcomes while safeguarding academic integrity.

I was also struck by the diversity of perspectives in the room—instructors, researchers, and students openly shared both excitement and caution. The hands-on group discussions fostered rich exchanges, allowing us to explore not only the promises of AI but also the ethical and practical challenges that come with its implementation. For me, the workshop raised important questions I’m still thinking about: How do we ensure equity in access to these tools? How can faculty be best supported in adopting new technologies? And how do we build frameworks that prioritize student learning while adapting to this rapidly shifting landscape?

Overall, this session sparked meaningful reflection on the future of higher education and how we, as scholars and practitioners, can thoughtfully engage with emerging technologies to enrich student learning experiences.