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ThinkMind // DATA ANALYTICS 2020, The Ninth International Conference on Data Analytics // View article data_analytics_2020_2_120_60067


An Intelligent Recommender System for E-learning Process Personalization: A Case Study in Maritime Education

Authors:
Stefanos Karnavas
Alexandros Bousdekis
Stavroula Barbounaki
Dimitris Kardaras

Keywords: learning profiles; learning styles; higher education; k-means clustering, Bayesian network; classification

Abstract:
The lockdown due to the pandemic of COVID-19 led to an unprecedented impact on education. Higher education institutions were forced to shift rapidly to distance and online learning. On the one hand, this fact revealed the weaknesses of adoption and utilization of e-learning strategies and technologies, but, on the other hand, it resulted in a digital revolution in education. However, the wide adoption of e-learning strategies and technologies and the complete transformation of the physical learning process to a virtual one pose the challenge of personalization of the learning process. This paper proposes a recommender system for supporting the professors in higher education in understanding their students’ needs so that he/she adapts the e-learning process accordingly. To do this, it utilizes learning profile theory and it implements k-means clustering and Bayesian Networks (BN) The proposed approach was applied to a maritime educational institution.

Pages: 84 to 89

Copyright: Copyright (c) IARIA, 2020

Publication date: October 25, 2020

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-816-7

Location: Nice, France

Dates: from October 25, 2020 to October 29, 2020

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