An open laptop is on a desk in a school classroom. A feedback dashboard with diagrams and charts is depicted on the laptop screen.Learning Analytics Dashboards (LADs) are important and widely-used tools used to give feedback to students and to aid them in their self-regulating learning process. Much has been done to investigate the design of LADs, but there is still a lack of knowledge regarding how students interpret the information shown on LADs and how they actually use these tools while learning. In a newly published study, we try to fill this gap.

In an experimental study, we compared two groups of students. One group was given personalized self-regulared learning (SRL) feedback on their interactions and learning advances. The control group was only given minimal feedback calculated from the average class scores. After reviewing their feedback, students submitted written reflections on how they would adjust their study behavior. The researchers then analyzed 1,251 self-reflection texts from 417 students at three different points in time.

The findings reveal that students who received personalized feedback focused on different aspects of their studying behavior compared to those receiving minimal feedback. The results also show that the content of the dashboards higly influenced how students phrase the texts of their self-reflection. Our research results highlight the need for more support to enhance students’ capability to make sense of feedback from LADs and to better reflect on their learning behavior.

This insights from our research open new possibilities for the future to enhance the effectiveness of LADs in educational settings and to supporting students’ long-term self-regulatory skills.

Giorgashvili, T., Jivet, I., Artelt, C., Biedermann, D., Bengs, D., Goldhammer, F., Hahnel, C., Mendzheritskaya, J., Mordel, J., Onofrei, M., Winter, M., Wolter, I., Horz, H., Drachsler, H.. (2024). Exploring Learners’ Self-reflection and Intended Actions After Consulting Learning Analytics Dashboards in an Authentic Learning Setting. In: Ferreira Mello, R., Rummel, N., Jivet, I., Pishtari, G., Ruipérez Valiente, J.A. (eds) Technology Enhanced Learning for Inclusive and Equitable Quality Education. EC-TEL 2024. Lecture Notes in Computer Science, vol 15159. Springer, Cham. https://doi.org/10.1007/978-3-031-72315-5_10