Students in AI‑Rich Learning Environments – Profiles, Practices, and Needs
Do we really understand students’ learning journeys in an AI-rich learning environment? How do cognitive, emotional, and behavioral factors interact with students’ use of AI tools, and how might this shape their progress?
Course details
The workshop focuses on analyzing student characteristics and needs in a course context where AI tools may play a role in everyday study practices.
You learn to develop realistic learning profiles that consider a student’s domain knowledge, how they might engage with AI, when it genuinely supports their learning, and where it may obscure or reduce meaningful effort. Together, we examine different functions of student AI use – why they turn to AI, and for which types of tasks – as well as situations where AI is hardly used at all.
From there, we explore how to uncover underlying learning needs and how to redesign guidance, tasks, and feedback so that courses remain both AI-informed and learning-rich: making sure that, whether students use AI extensively, selectively, or rarely, the core learning processes are still activated and supported.
Intended learning outcome
- Analyze the characteristics and needs of students in a specific course context to develop a realistic understanding of their learning profiles.
- Analyze and diagnose areas and causes of student struggles in the learning process, including cognitive, affective, and behavioral challenges.
- Evaluate student use of AI to identify and interpret underlying learning needs and opportunities for enhancing the learning process.
Good to know
| Target audience | UvA teaching staff | |
| Preparation | If you do not have your BKO then completing the Basic Didactics elearning (with particular attention to Module 1) will be helpful but not required. | |
| Prior knowledge | For this workshop, we assume participants have a basic understanding of what generative AI is and how it works in broad terms; if you are new to the topic, we recommend completing the AI e‑learning or attending an introductory AI session beforehand. | |
| Language | English | |
| Trainer | Jacqui Edwards (TLC Central, GenAI Living Lab) | |
| Participants | Minimum of 8, maximum of 20 participants | |
| Location | At one of our UvA locations (see Registration). | |
| Dates |
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| Organised by | TLC Central, GenAI Living Lab |
Frequently asked questions
Not primarily. We look at student AI use neutrally: when it supports learning, when it undermines it, and when AI is barely used at all. The goal is to design courses and tasks that remain learning-rich across these different patterns of use.
No. We treat AI use as a signal: sometimes it reveals productive strategies, sometimes gaps in skills or motivation, and sometimes design issues in our courses. We explore all of these possibilities.
You will work with examples from your own teaching (where possible) to identify student struggles and AI use patterns, and you will draft concrete ideas for redesigning tasks, instructions, or feedback in your course.
This workshop is for teachers and educational professionals who want to better understand how their students learn in an AI-rich context and who are curious about the impact of AI on study behaviour, not just the tools themselves.
No. Basic familiarity with tools like UvA AI Chat, ChatGPT, Copilot, or other AI assistants is helpful, but not required. The focus is on interpreting student behaviour and learning needs, not on technical AI skills.
Registration
The course is funded from central funds. Signing up is not non-committal, we will count on your participation.
- Registration buttons for employees with an @UvA.nl email address:
- For AUC, ACTA or FdG (AMC) employees: send an email with your name, faculty and date for which you want to register to tlc-centraal@uva.nl
After registering, you will receive an automated invitation for your Outlook calendar (please don’t forget to accept). If the location is not yet known at that time, an update will follow later.
A proof of participation is available upon request. Please send an email to tlc-centraal@uva.nl after the course.
More information?