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Authors: Adson Marques Esteves ; Aluizio Haendchen Filho ; André Luiz Alice Raabe ; Angélica Karize Viecelli ; Jeferson Miguel Thalheimer and Lucas Debatin

Affiliation: Laboratory of Technological Innovation in Education (LITE), University of the Itajai Valley (UNIVALI), Itajai, Brazil

Keyword(s): Adaptive Computer Learning, Educational Technology, Learning Technology, Recommendation System.

Abstract: Nowadays there are many research using the LDA (Latent Dirichlet Allocation) algorithm to find preferences and characteristics for recommendation systems. In some of the most relevant studies, the recommendation is based on the student's level of evolution within the discipline. This work presents a new recommendation approach with the LDA algorithm. The approach differs from previous LDA studies since the recommendation technique is based on the experiences and preferences from a group of students and not just an individual student. The main objective is to verify, through simulation, whether the methods used, and the algorithm can generate recommendations close to those considered ideal. The obtained results indicate that the application of the LDA for creating groups to generate recommendations provides a good result in delivering content and practices in accordance with the student's interests. It’s empirical research, as the conclusions are drawn from concrete and verifiable evi dence used in the simulations. (More)

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Paper citation in several formats:
Esteves, A.; Filho, A.; Raabe, A.; Viecelli, A.; Thalheimer, J. and Debatin, L. (2022). Adaptive Learning Content Recommendation using a Probabilistic Cluster Algorithm. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-569-2; ISSN 2184-4992, SciTePress, pages 724-731. DOI: 10.5220/0011056200003179

@conference{iceis22,
author={Adson Marques Esteves. and Aluizio Haendchen Filho. and André Luiz Alice Raabe. and Angélica Karize Viecelli. and Jeferson Miguel Thalheimer. and Lucas Debatin.},
title={Adaptive Learning Content Recommendation using a Probabilistic Cluster Algorithm},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2022},
pages={724-731},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011056200003179},
isbn={978-989-758-569-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Adaptive Learning Content Recommendation using a Probabilistic Cluster Algorithm
SN - 978-989-758-569-2
IS - 2184-4992
AU - Esteves, A.
AU - Filho, A.
AU - Raabe, A.
AU - Viecelli, A.
AU - Thalheimer, J.
AU - Debatin, L.
PY - 2022
SP - 724
EP - 731
DO - 10.5220/0011056200003179
PB - SciTePress

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