In IguideME, learning data from various learning activities and assessments will be collected and visualised for each student. In addition, learning data is linked to the learning outcomes and is also used to calculate the final course grade. The lecturer can also use this dashboard as an early warning system and detect students who may drop out. The project team compared the usefulness of various feedback tools in the learning process. For example, it determines which tool suits the chosen didactics best and how the functionalities of feedback tools can be properly integrated into the educational design and teaching practice.
In June 2023, the project team published a paper about the results of the dashboard in the Journal of Learning Analytics: ‘IguideME: Supporting Self-Regulated Learning and Academic Achievement with Personalized Peer-Comparison Feedback in Higher Education’.
The results showed that the treatment group outperformed the control group in Motivated Strategies for Learning Questionnaire (MSLQ) components, like "metacognitive self-regulation" and "peer learning,", as well as in the Achievement Goal Questionnaire (AGQ) component "other-approach" (striving to do better than others). The treatment group also excelled in reading assignments and achieved higher grades in high-level Bloom exam questions.
IguideME was developed as part of the SURF project Feedback GO (Feedback Grootschalig Onderwijs), a joint effort of the University of Amsterdam, VU Amsterdam and the University of Groningen. The project started in June 2021 and was led by Erwin van Vliet, assistant professor at SILS. The dashboard was made available in the Canvas environment.