Intelligent System Using Deep Learning for Answering Learner Questions in a MOOC

Authors

DOI:

https://doi.org/10.3991/ijet.v17i02.26605

Keywords:

(Intelligent System, MOOCs, deep learning, NLP, learner, improve learning, Question answering)

Abstract


Despite the great success of Massive Open Online Courses (MOOCs), the success rate of learners remains very low. Therefore, a lot of research has been done to understand and solve this abandonment problem. This work is part of the same effort which aims to improve learning in MOOCs. We offer an intelligent system capable of assisting the learner by providing answers to all his questions on the subjects covered in the MOOC. The architecture of our system is based on new advances in artificial intelligence, in particular the applications of deep learning in the field of natural language processing (NLP). The results obtained are quite interesting and demonstrate the relevance of our solution.

Author Biographies

Oussama Hamal, Mohammadia School of Engineers (EMI), Mohammed V University of Rabat, Morocco

I'm a researcher as a Ph.D candidate in using Artificial Intelligence AI in Education at "Computer Network; Modeling & E-learning" (RIME) Team at Mohammadia school of engineers (EMI) of Mohammed V University (UM5) - Rabat, Morocco. I am also pedagogical and didactic engineering. I had master of educational technology. My interests lie in the fields of Online Learning Tools,MOOCs, Machine Learning, Neural Networks and Artificial Intelligence, Natural Language Processing and Educational engineering.

Nour-eddine El Faddouli, Mohammadia School of Engineers (EMI), Mohammed V University of Rabat, Morocco

Full Professor at Mohammadia School of Engineers (EMI), Mohammed V University in Rabat, Morocco.

Cover ijET Vol. 17 No. 02 (2022)

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Published

2022-01-31

How to Cite

Hamal, O., & El Faddouli, N.- eddine. (2022). Intelligent System Using Deep Learning for Answering Learner Questions in a MOOC. International Journal of Emerging Technologies in Learning (iJET), 17(02), pp. 32–42. https://doi.org/10.3991/ijet.v17i02.26605

Issue

Vol. 17 No. 02 (2022)

Section

Papers

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Copyright (c) 2021 HAMAL Oussama, El Faddouli Nour-eddine

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