Many students experience test preparation as challenging, exciting, and sometimes stressful. Although mock tests and other formative moments give some indication, these are often inadequate in determining whether preparation is adequate, what material a student has already mastered, and where they need to pay extra attention. Nor do students know whether their approach is effective and efficient for a specific test moment. 

An advisory system for students to improve learning

Lecturer-researchers Marcel van Vliet and Memon Boukiour of the Learning Technology & Analytics (LTA) lectorate tackle this issue under DASH: Data-Driven Support and Advice Hub (DASH). In this project, students receive feedback on their learning performance and recommendations that help optimize test preparation. DASH aims to develop a system that allows students to formulate learning goals in a more targeted way, steer them accordingly, and evaluate the extent to which they have been achieved. In the literature, this process is also called self-regulation. These goals align with THUAS' educational vision, in which education is about transferring knowledge and developing critical, independent thinkers ready for the challenges of the modern labor market. 

Pilot Nutrition and Dietetics

The project is still in its early stages. We are currently looking at the relationship between the information from Brightspace and students' final test results. We are using data analysis and machine learning techniques. Based on this, we are building a prediction model to gain more insight into whether the information from Brightspace has predictive value for students' results. Once the model is ready, we will work with students to develop a recommender system: a plug-in in Brightspace that gives students advice on their learning. By continuously testing and incorporating student feedback, we can enrich the recommender system and make it suitable for larger groups of students. 

The project started in October 2023 with an exploration; by now, we have followed all the formal procedures to launch the project, collected the data, built a network of partners inside and outside the college, and mapped the processes to work with data responsibly. The academic year 2024-2025 is dedicated to developing a model and the first early version of DASH. The first is in the propaedeutic year of the Nutrition and Dietetics program, as this curriculum lends itself well to understanding study behavior.

Ethical issues

Working with data comes with great responsibility regarding ethical use, privacy, and security. We pay a lot of attention to this within Learning Technology & Analytics. In collaboration with lector Chris Detweiler and the Philosophy and Professional Practice lectorate, we are developing a working method to give students an explicit voice in this and similar projects. In addition, we are working closely with THUAS Analytics (Institutional Research & Analytics of THUAS University of Applied Sciences) and the product owner of Brightspace and Osiris regarding sustainably obtaining and working with data. With the AI hub, we work on analyzing and modeling data. Finally, we involve privacy officers and the ethics committee to recognize and address possible pitfalls early on.

Possible outcomes

We have strong indications that by strengthening students' self-regulatory capacity, their study performance improves, and their overall satisfaction with the educational process improves. As a result, students become more involved in their studies and the college.


As experienced teachers, we know that input and feedback make a project better and stronger. For questions, input, or more information, contact Memon Boukiour at or Marcel van Vliet at