Research Data Repository for Learner Model Publication
Description
This repository contains the code and resources for the research publication "Learner Models: Design, Components, Structure, and Modelling". The goal of this project is to explore learner models in adaptive e-learning environments, with a focus on modelling learner models. We will look at learner models from the perspective of computer science and pedagogy to answer the major question: What do learner models look like and how are they filled, kept up-to-date, and used?
This repository serves to ensure the reproducibility of the results and to create transparency. The repository includes the following components:
- Data: Raw and processed datasets used in the research.
- Tools: An interactive visualization tool to visualize the data and the visualization scripts for the UpSetPlots used in the article.
- Results: Preprocessed results, charts, figures, and analysis outputs.
- Documentation: A detailed description of the methodology, experiments, and findings.
- Experimental: Possible ideas and next steps from the results of the systematic literature review (e.g., a classifier that assigns the components of the new created taxonomy).
Files
data.zip
Files
(79.7 MB)
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md5:917ba2996d3fcb99a47d878279c6e12a
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79.7 MB | Preview Download |
Additional details
References
- F. Böck et al. 2025. Learner Models: Design, Components, Structure, and Modelling - A Systematic Literature Review, User Modeling and User-Adapted Interaction - The Journal of Personalization Research, Springer Nature