Talent and behavioral learning dashboards as a bridge between leariniganalytics and educational interventions.

The overall objective of the doctoral project is to bridge the gap between learning analytics and specific educational interventions.

Learning analytics is defined as "measuring, collecting, analysing and reporting data about students and their context, with the purpose of better understanding and optimising learning and the environment in which this happens. Learning dashboards, platforms that offer and visualise the learning data are instrumental in the implementation of learning analytics. They try to understand the learning process, provoke self-reflection and improve the learning process. Research in the field of learning analytics has shown that "engagement", measured through learning-platform activity, access to university libraries, etc relates to study success. In addition, there are many background factors such as education background (number of hours of mathematics, advice of school council, gender, socioeconomic factors) that help predict study success. Educational research shows the importance of learning and study skills, which are often measured by questionnaires. Although all of these factors are related to study success, it is not always feasible or desirable to directly address students through learning dashboards (e.g. gender-related questions). In addition, an additional factor is essential: the feedback must be "actionable". This means that students should be able to adjust their behavior based on feedback. Dispositional learning analytics, a recent research area of learning analytics, aims to combine all of the above-mentioned data sources and deploy educational interventions using learning dashboards.

The new project fits in with this new research area and aims to bridge the gap between learning analytics and education practice using talent and behavioral learning dashboards. The project will investigate which data sources are available and whether the new interactive technology, based on "micro-interactions", can open up a more continuous communication line with students. Based on these data sources, a student-based dashboard will provide more continuous feedback during the learning process. Next, the project will examine the effectiveness and impact of the student-based dashboard. Finally, we want to explore whether the measured interactions with the learning dashboard can contribute as a data source.

This project can only succeed thanks to the research already carried out and the resulting pilot dashboards. In addition, the multidisciplinary team (Human Computer Interaction of the Department of Computer Science, LESEC, and educational science) and the contact with concrete study career guidance centres (study advice, student counselling and tutorial services) and education practice play a major role.

The project offers a unique opportunity for the SciEngTech Group and KU Leuven to be a forerunner within the hot topic of learning analytics and learning dashboards at both national and international levels.