iMath OptLearn ConceptMap based question recommender system (University of Ljubljana)
This recommender system
1. Takes a list of questions with keywords as an input (.csv or .xlsx file), and generates a concept map. At this stage of development, the concept map is fixed and independent of student history;
2. Takes concept map and student history (may be empty) and sequentially generates recommended questions
During phase 2 (recommender), the algorithm estimates selected learning indicators and maximizes selected ones. The student history is updated for every next question generation.
1. Takes a list of questions with keywords as an input (.csv or .xlsx file), and generates a concept map. At this stage of development, the concept map is fixed and independent of student history;
2. Takes concept map and student history (may be empty) and sequentially generates recommended questions
During phase 2 (recommender), the algorithm estimates selected learning indicators and maximizes selected ones. The student history is updated for every next question generation.
Scientific Area:
Python
Language/Environments:
Learning, Optimization
Target Group:
Advanced
Cite as:
A Košir, U Burnik, G Strle A Košir. ''Learning content Concept map editor (University of Ljubljana)'', available at https://github.com/aipereira/iMath_Public/tree/main/Applet/LJUBLJANA.
Author of the review:
Andrej Košir
University of Ljubljana
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