A Recommendation System Framework for Educational Content Reinforcement in Virtual Learning Environments

Adson Damasceno, Lucas Carneiro, João T. De Sampaio, Allberson Dantas, Eudenia Magalhães, Paulo Maia, Francisco Oliveira

2022

Abstract

In Virtual Learning Environments, tutors play a vital role by supporting students and improving their learning through the courses. One important task is to identify content with which the students struggle and give them suggestions for educational resources to reinforce their learning and overcome difficulties. However, providing individualized suggestions for each student may be infeasible, especially for courses with many enrolled students. In this work, we propose and validate a framework for building recommendation systems of educational content for Virtual Learning Environments. Our proposed system identifies the content that a student needs to reinforce based on the results of his assessments and recommends resources that best relate to the questions that he answered incorrectly, using Information Retrieval, Machine Learning, and Natural Language Processing techniques. We validate our proposed solution by taking as a case study data collected from DAL - Dell Accessible Learning, an distance learning platform. We built a dataset with content from 8 courses to compare the performance of different methods and text representations in our framework. Our best result achieved an accuracy of 0.89 using a Nearest Neighbor method with TF-IDF representation.

Paper Citation

in Harvard Style

Damasceno A., Carneiro L., T. De Sampaio J., Dantas A., Magalhães E., Maia P. and Oliveira F. (2022). A Recommendation System Framework for Educational Content Reinforcement in Virtual Learning Environments. In Proceedings of the 14th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-562-3, pages 228-235. DOI: 10.5220/0011032000003182

in Bibtex Style

@conference{csedu22,
author={Adson Damasceno and Lucas Carneiro and João T. De Sampaio and Allberson Dantas and Eudenia Magalhães and Paulo Maia and Francisco Oliveira},
title={A Recommendation System Framework for Educational Content Reinforcement in Virtual Learning Environments},
booktitle={Proceedings of the 14th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2022},
pages={228-235},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011032000003182},
isbn={978-989-758-562-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - A Recommendation System Framework for Educational Content Reinforcement in Virtual Learning Environments
SN - 978-989-758-562-3
AU - Damasceno A.
AU - Carneiro L.
AU - T. De Sampaio J.
AU - Dantas A.
AU - Magalhães E.
AU - Maia P.
AU - Oliveira F.
PY - 2022
SP - 228
EP - 235
DO - 10.5220/0011032000003182