Visible Learning Trajectories Programme AI track
AI literacy at the curriculum level
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Generative AI (GenAI) is a permanent part of education and professional practice. Degree programmes therefore need to make explicit choices: what should students be able to do themselves, where do we use GenAI purposefully, and how do we safeguard validity and academic integrity?
The AI track within the Visible Learning Trajectories Programme supports degree programmes in systematically designing an AI learning trajectory or learning trajectory objectives, tailored to their needs. We start with shared vision-building: what does the future profile of our graduates require?
Bachelor’s and Master’s programmes that have participated in the Visible Learning Trajectories Programme and want to embed GenAI at curriculum level can apply for the AI track within the Visible Learning Trajectories Programme.
Would you and your teacher team like to develop a shared vision of the role of AI in a single 2-hour session, without taking part in the full AI track? Or would you like to make well-founded assessment choices at the course and learning trajectory level, with and without GenAI, in one 3-hour session? That is also possible; please get in touch. |
What does the AI track involve?
During the first session, the team develops a shared vision for the role of GenAI in the programme. The following interconnected questions are central:
- Do we want to include GenAI-specific learning trajectory objectives?
This concerns whether, and where, GenAI-related knowledge and skills are explicitly embedded in the programme’s exit qualifications, learning trajectory objectives and course learning objectives (e.g. understanding, using and critically evaluating AI-generated output). - Do we want to alter the assessment structure in response to GenAI?
We adopt a two-lane approach: some learning objectives are assessed through AI-robust assessment formats without GenAI support, while others deliberately integrate GenAI and assess students on their responsible, critical, and transparent use of it. This ensures that core competencies are demonstrated independently, while AI-related competencies are embedded explicitly and coherently throughout the programme. - Do we want to employ GenAI as a means to enhance learning?
This concerns whether, and how, GenAI can support learning activities. The team identifies its didactical added value, defines the conditions for its use, and determines how to organise consistent, responsible, and purposeful integration of GenAI in teaching and learning.
During the remaining three four-hour sessions, these strategic choices are translated into concrete adjustments to the curriculum, assessment and teaching practices. This ensures that AI literacy and responsible GenAI use are integrated coherently at the programme level. The sessions are facilitated by two expert trainers with complementary expertise in pedagogy and AI: one trainer from the Visible Learning Trajectories Programme and one trainer from the faculty’s Teaching and Learning Centre (TLC).
AI as both tool and learning goal, for students and teachers
The AI learning trajectory is designed around four quadrants. This helps us consider GenAI as an end (or as learning goal) and as a means (as a tool to support learning), for both students and lecturers.
This framework conceptualises responsible AI integration as a reciprocal relationship between learning about AI and learning with AI. It positions these two dimensions —AI as end and AI as means— against the roles of students and lecturers, resulting in four interdependent quadrants. Treating GenAI both as an end and as a means, the framework aligns pedagogy, assessment, and infrastructure to ensure coherence between classroom practices and evaluation methods and defines progression pathways for both students and lecturers.
More information
Do you have any questions or are you interested in participating in the Visible Learning Trajectories Programme and/or the AI track? Contact us
Would you and your teacher team like to develop a shared vision of the role of AI in a single 2-hour session, without taking part in the full AI track? Or would you like to make well-founded assessment choices at the course and learning trajectory level, with and without GenAI, in one 3-hour session? That is also possible; please get in touch.
Read more about the Visible Learning Trajectories Programme
Personal experience of the AI track: Moss Shukla
What should a Bachelor’s thesis assess in a world where artificial intelligence can generate literature reviews, suggest hypotheses, analyse data and even draft academic text? For Moss Shukla, Thesis Coordinator within the Bachelor’s programme in Psychology, this question became the starting point for a fundamental redesign proposal of thesis assessment during the AI track.