Towards Distributed Intelligent Tutoring Systems Based on User-owned Progress and Performance Data

Description

The use of recommendation engines to personalise students’ learning experiences can be beneficial by
providing them with exercises that are tailored to their knowledge. However, the use of these systems
often comes at a cost. Most learning or tutoring systems require the data to be stored locally within a
proprietary database, limiting the freedom of the learner as they move across different systems during
their learning journey. In addition, these systems might potentially cause additional stress, as the learner
might feel observed without knowing who has access to their learning progress and performance data.
We propose a solution to this problem by decentralising learning progress and performance data in
user-owned Solid Pods. We outline the proposed solution by describing how it might be applied to
an existing environment for programming education that already includes research on how to align
difficulty levels of exercises across different systems

Period	2 May 2024 → 3 May 2024
Event title	2nd Solid Symposium
Event type	Conference
Location	Leuven, BelgiumShow on map
Degree of Recognition	International