Equal opportunities in tracking advice using dashboard supportIn Progress
Dutch education system, both at the national level and within schools. Traditionally, the selection moment takes place at the end of primary school (6th grade), where a tracking advice is formulated based on the teacher’s recommendation, supported by the results of the final primary education test. However, the transition from primary to secondary education is a vulnerable phase for many students. Research shows that this transition can have negative effects on students’ academic performance, well-being, and motivation, and can increase educational inequality. Therefore, accurate determination — ensuring that each student is placed at the level best suited to their abilities — is crucial for every learner.
In this project, the Limburg Secondary Education Foundation (LVO), Maastricht University, and the Radboud Teachers Academy are jointly exploring how AI can assist in determining the most appropriate educational placement for students. The main goal of the project is to develop an AI-supported dashboard that helps teachers combine, structure, and analyse various relevant data sources in order to provide suitable preliminary and final school recommendations. The dashboard will first be developed in collaboration with Raayland College and later tested and validated at other schools.
The development of the dashboard follows a design-based research approach, consisting of a conceptual phase, a development phase, and a validation phase. An important component of the project focuses on exploring the ethical factors involved in each stage of developing the AI model and dashboard. This way, we explore not only what is technically possible, but also what is desirable from an ethical perspective.
In the first phase, the problem definition is further clarified, and the initial design of the dashboard is developed. During this phase, educational professionals and researchers will refine the research question and map out teachers’ needs regarding the dashboard. Elements such as learning development, student behaviour, and background characteristics that contribute to appropriate school advice will be identified. Available data sources will also be inventoried and assessed for quality, and consideration will be given to how they can be combined safely. These insights will be used to create an initial version of the dashboard and the underlying algorithm. In addition, this phase includes exploring, together with teachers, what knowledge and skills they need to use the dashboard effectively.
The second phase, the development phase, involves the technical creation of a prototype of the dashboard, consisting of two parts: a front-end interface for teachers to view relevant information, and a back-end where AI performs analyses and provides recommendations. The dashboard will be developed and tested iteratively with teachers to ensure that it is user-friendly and practical.
In the third phase, the prototype dashboard and accompanying professional development program will be validated in a broader setting by implementing the dashboard in various schools. Both qualitative and quantitative methods will be used in this process. The outcomes will result in a version of the dashboard that can be effectively used by teachers in practice.
Funded by: NOLAI
Duration: 1 November 2023 – 1 September 2026
Project website: www.ru.nl/onderzoek/onderzoeksprojecten/maichart-vo