The 8th annual International Scholarship of Teaching and Learning (SoTL) conference brought together faculty members and researchers interested in conducting research on teaching and learning, with a particular emphasis on how technology is being used or should be used in higher education. The theme for this event was motivated by current events in Higher Education Institutions (HEIs) and the debate surrounding the use of Generative Artificial Intelligence (Gen AI) in and outside of the classroom.
While Gen AI is touted as a means of saving time on academic tasks, it is not speed (alone) that we should be seeking. In what we refer to as the ‘best day of the year’, 35 participants spent the day sharing ideas and best practices.
Mr. Jean-Michel Jullien and Dr. Henrietta Carbonel from UniDistance Suisse began the first session with a series of provocative questions about the use of Gen AI for specific tasks in the classroom, immediately setting the tone for the day! We were ready to reflect and discuss. Should Gen AI be used to create mind maps? No! Should students ask Gen AI to structure their work? No! Structuring your ideas is the point of learning. Okay, but what about asking Gen AI to create cooky and fun images for our presentations? No! Instead, you should source images from actual designers/photographers even if you don’t pay them. By citing them, you’re giving them visibility.
What is most important is to engage in conversations with students regarding their Gen AI use. To do so, they presented a practical tool that UniDistance has made available to the greater public. The tool helps faculty members to define what is and what isn’t allowed on a per-assignment basis, i.e., what is permitted/forbidden when drafting guidelines. In groups of three, participants tried the drag and drop menu to create their own versions of acceptable Gen AI use for specific academic tasks. The tool was so easy to use and the output can be downloaded for future reference.
The next session about learning without AI was presented by Dr. Omar Ballester Gonzalez and Mr. Quentin Besson. They shared the results of a funded HES-SO project that addressed two key questions: How do you teach to make judgments about a framework that keeps changing? - or in other words: How do you teach someone to swim in a fast-moving river?? The project led to the creation of a serious game to practice in a controlled and safe environment, i.e., direct instruction vs. productive failure.
In the first week of their course, students struggle to complete a task without AI tools. This helps them to realize what is missing and what they need to have to address the situation. Then, from weeks 2-7, they build on the theory with constant callbacks. Lectures build knowledge; Games build judgement. Students need both. In each class, students play a card game they created and use a scorecard to assess four elements of an open-ended problem: value, risk, trust and budget. Student groups use no technology; rather, they write their responses on pen and paper and surprise…they love it!
Dr. Tatyana Tsukanova’s presented the early stages of a project for faculty members with researchers in two other HES-SO schools, Dr. Davide Calvaresi (HES-SO Valais-Wallis, Haute Ecole d'Ingénierie) and Ms. Natalie Sarrasin (HES-SO Valais-Wallis, Haute Ecole de Gestion) on the challenges that are being faced in this age of Gen AI. While many projects focus on several HEI stakeholders, particularly students, in their project, they intend to create a toolbox of resources for faculty members.
During the session, participants were asked to consider a learning task that they do in the classroom and reflect on ways of AI-proofing the assessment of learning. Increasingly, faculty members must cope with potential AI-related cheating on assessments. A few recommendations to combat this nefarious use of technology included adding an oral component to the exam or writing the exam using pen and paper instead of laptops. Dr. Tsukanova concluded optimistically, saying that more options to assess learning will emerge in the future, with or without technology.
Dr. Thomas Davoine presented his teaching reflections on AI use in and outside the classroom. As a relatively inexperienced economics professor (currently in his fifth year), his observations were eye-opening. For example, fewer students are asking questions (office hour visits halved in one year). Students are only concerned about the hardest questions and then asking: “Why is ChatGPT giving me the wrong answer?” Students are becoming overconfident. They’re unable to answer Question 3 (the hardest) because they don’t know how to answer questions 1 and 2 (easier). They don’t realize that Q1 is embedded in Q3. He asks such students: “Are you sure you know how to answer Q1?” GenAI doesn’t have office hours. It’s open 24/7. Students who don’t attend class sometimes never interact with their teacher, which erodes trust. This lack of rapport, combined with overconfidence, leads to worse performance, which leads to poorer evaluations of their professor. It’s a vicious circle.
Dr. Davoine advocated for moving beyond policing students’ AI use, echoing the event’s focus on adapting evaluations to the AI era. He proffers a case-based approach where the process takes precedence over the answer. We should focus on how decisions are made and how we interpret evidence (and not the evidence itself). He asks students to weigh the pros and cons (that AI has drawn up), and justify the rationale/tradeoffs of choices. He suggests asking students to draft a portfolio, not a report (which ChatGPT can generate in seconds), or asking AI to extract insights from AI-generated work and asking students to reflect: Do you agree? Did you get the same takeaways?
In conclusion, Dr. Davoine stated that students are impatient and unwilling to go through the steps. “The answer is in the slides” but students haven’t watched the presentation in the first place. Understanding the solution isn’t the same thing as finding the solution yourself. First, your students don’t know HOW to learn. “Learning is about struggling.” Students, as one participant said, are more receptive to case-based learning that uses real-life situations. He concluded with a few suggestions to combat AI disengagement, including: the flipped classroom, ongoing evaluations instead of papers, and bonus points for identifying why AI failed.
The afternoon workshop, led by Dr. Laura Zizka, got participants brainstorming on the SoTL project that she will complete in the next year. The purpose of this project is to examine how students attain, assess, hone or sharpen critical thinking skills in this AI age. Only two rules for the project apply: it has to focus on Gen AI and critical thinking skills (applicable to all HES-SO HEIs), and the project must be completed (or at least the first phase of the project) within the year. Then, at the annual SoTL conference in February 2027, she will disseminate the research findings.
Four groups were formed to discuss, draft and present a SoTL project in one afternoon that will actually be completed. This project will be carried forward with the help of SoTL participants who would like to contribute or by Dr. Zizka herself.
They began by asking the questions “What do our students need/want? What can we as teachers learn to do differently?” Here is an overview of their discussions and project ideas:
Group 1 acknowledged the lack of student effort to acquire problem-solving skills. They discussed student resistance to anything difficult, i.e., engaging with the learning process itself. They are mostly interested in ‘Did I get the right answer on LMS?’ Many students want quick and immediate responses from Gen AI, rather than an exchange of right/wrong answers in a coaching environment. This led to a series of questions: What distinguishes students who genuinely want to use Gen AI to improve their learning from others seeking a shortcut? What motivates them to engage in the process and be less obsessed with outcomes? Is it personal competencies? Dispositional traits, the typology of the students. Values and their drivers? Prior education experience? Learning styles? Predictors? Incentives - intrinsic or external (i.e., “My parents promised me a car if I pass the exams”)?
Project title: Profiling the optimal AI user
Goal: We can help you get to where you need to be.
Create a strong list of questions to define the students’ learning culture (from the literature).
Include HEI students from all years and their good/bad use of Gen AI.
Look for common traits of the ‘good practice’ users.
Interview a sample of students: How do they use Gen AI? Come up with a list of best practices.
Group 2 began with the problem “Is critical thinking the same for students and teachers?” With Gen AI, it is hard for students to self-assess their current level of knowledge, i.e., what they know and what they don’t know. It is also difficult for students and teachers to keep up with the rapid changes in technology. Who is dictating the rhythm of what tools are being used? Further, students struggle to define the skills they will need for the future, “Can I critically assess what is expected of me in the future?” Group 2 thus decided to focus on understanding ‘who’ students need to be when they graduate: assess the world and themselves in the world. What is their sense of agency?
Project title: I think, therefore AI
The aim: To assess if overuse of Gen AI might affect/skew students’ confidence level, i.e., thinking that they ‘know’ a lot.
Confidential (not anonymous) questionnaire with some key Qs:
After exams: what do you think your grades are?
Do you trust AI as much as your teacher (or even more?!)
How much does AI feed your knowledge base?
Group 3 began with the problem of measuring critical thinking and defined the research question “Would a framework help students develop a more critical approach to Gen AI use?”. Their angle was to develop and validate a framework to evaluate the critical thinking and AI use via a new conceptual framework. They realized that the first step is to understand how Gen AI is being used in HEIs. What is ‘good’ or ‘bad’ use of Gen AI? Then, the term ‘critical thinking’ must be defined. How is critical thinking promoted/used/assessed in HEIs? Thus, before a framework can be created, the literature must be combed to answer the initial questions.
Project title: Fostering critical thinking in the use of Gen AI by students
Develop the framework to evaluate levels of critical thinking in a specific domain (applied each time).
Create a graph with different levels – beginner to advanced.
Conduct a pre-interview (face-to-face) to evaluate how Gen AI is used today.
Develop a series of activities (interventions/training) for critical thinking use of Gen AI for learning.
Group 4 identified a different problem: “How do students learn in this age of AI? Are they autonomous when unguided?”. Like Group 1, they confirmed that many students simply want to avoid failure and get straight to the point, seeking the fastest route to success. They have witnessed a decrease in student patience in the classroom and a low tolerance for uncertainty. Like Dr. Davoine’s observation, Group 4, found that students have become (falsely) overconfident; but, when faced with a complex project, they become stressed and feel lost. Thus far in their studies, the focus has been on being successful rather than learning. Group 4 concluded with an idea to weave in productive failure with the help of Gen AI into the learner journey to develop learning autonomy.
Project title: Productive failure for critical thinking
Create a set of questions to assess to what extent students have problem-solving skills.
Create a classroom experiment for two groups:
One class is a control group (no productive failure).
Another group gets a task designed for failure.
Each group presented their ideas and participants voted on the project they would most like to see in next year’s conference. Dr. Zizka acknowledged that all projects would be feasible and exciting to work on; however, the winner was (drum roll, please): Group 1! Congratulations to all of the groups and participants for contributing to the positive vibe of SoTL 2026. See you next year, when the results of this ambitious project will be shared!
“If you can impact just a few students, this is already a successful project!”
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Dr. Laura Zizka
Written by
Dr. Laura ZizkaAssociate Professor at EHL Hospitality Business School |