Train Data and Test Data for Nestor

bayesNestor is a Bayesian Network implementation designed to dynamically generate personalized learning paths tailored to the unique psychological traits of each learner, aiming to optimize educational outcomes. It is available from the pypi repository. Follow this link: pypi repository: bayesNestor · PyPI In this Zenodo publication, the data used to train and test Nestor is included and the results are available at a conference publication. Below is the citation for the mentioned paper: @inproceedings{nadimpalli2025nestor, title={Nestor: A Personalized Learning Path Recommendation Algorithm for Adaptive Learning Environments}, author={Nadimpalli, Vamsi Krishna and Maier, Robert and Ezer, Timur and Staufer, Susanne and Röhrl, Simon and Hauser, Florian and Grabinger, Lisa and Mottok, J{\"u}rgen}, booktitle={Proceedings of the 6th European Conference on Software Engineering Education}, pages={t.b.p}, year={2025}}