Background
In today's digital world, a lot of data is collected and stored in databases, also about students and their learning environment. With learning analytics (LA), this data is analysed and reported on with the aim to better understand students' learning processes and to optimise their learning environment. Insights from LA can help higher education institutions respond to challenges, such as identifying and supervising high-risk students or implementing (blended) learning more effectively.
Research objective
The use of LA at the Artesis Plantijn University of Applied Sciences (AP) is still in its infancy. A necessary first step for the use of LA is to develop a qualitative dashboard for different user groups (i.e. students, teachers/tutors and heads of programs). The LAP! project tries to develop LA dashboards for different user groups in an evidence-informed manner. Thereby, the project tries to answer research questions about the added value of self-report questionnaires in LA, the advantages of user research and the possibilities of artificial intelligence (AI). This requires a multidisciplinary approach.
Methodology
The project follows the set-up of a design study. Research activities include literature reviews, user research through focus groups and eye-tracking, secondary database analysis and experiments with machine learning. The research results are not only relevant for AP, but give other educational institutions insights in e.g. digital predictors of study success and do's and don'ts in the development of an LA dashboard. The source code of the dashboards will be made publicly available (Open source approach).