This year, the biannual EARLI conference took place between 21-26 August 2023 in Thessaloniki, Greece and EduTec member Ioana Jivet represented DIPF with two contributions.

The 1.5-hour ICT demo Closing the Feedback Loop – A Moodle Plugin for (Semi-)automated Feedback introduced participants to the work of PhD student Tornike Giorgashvili, supervised by Hendrik Drachsler and Ioana Jivet, and the outcomes of the HIKOF project: LearnDashPlus, a Moodle plugin which helps teachers provide written feedback in large courses. This tool also prompts students to reflect on the feedback they received and allows teachers to explore if such feedback helps students to understand their learning behavior and improve their learning performance. Our tool is intended to work as an educational intervention and an instrument of dialogue between teachers and students and thus closing the feedback loop. At the same time, the plugin can be a relevant research tool as it allows us to understand better how students perceive the feedback and self-reflect. During the demonstration, participants will have access to a Moodle installation with various learning activities and will be able to configure and examine the feedback plugin.

Citation: Giorgashvili, T., Jivet, I. & Drachsler, H. (2023) Closing the Feedback Loop – A Moodle Plugin for (Semi-)automated Feedback. Accepted demonstration at EARLI 2023, Thessaloniki, Greece.


Ioana Jivet co-authored an additional submission as part of the symposium of the SeReLiDiS Expert Group titled Using digital tools and analytics to promote regulation in individual and collaborative learning. The submission presented the outcomes of an ongoing research project that explores learners’ perspectives on what information they use and what information they are missing, in the expectation that these needs can be covered with learning analytics. Through eleven semi-guided interviews based on Zimmerman’s SRL model, we gathered qualitative data on what information learners currently use and would like to have when studying. The outcome is a list of indicators (i.e., information that could be displayed on dashboards) categorized as task-, process-, and SRL-level feedback. Potential data sources (e.g., trace logs, self-report, sensors) are identified for each indicator.

Citation: Wong, J., Jivet, I., Valle Torre, M., Martins Van Jaarsveld, G., Soleymani, A., Baars, M. & Specht, M. (2023) Designing feedback interventions with learning analytics: Identifying students’ information needs. Accepted at EARLI 2023, Thessaloniki, Greece.