Abstract: Massive open online courses (MOOCs) are a variety of courses offered through the online mode, paid or unpaid and has evolved as an excellent learning resource for students. The structure of the course design is mainly linear where there are a few video lectures provided by either professors of several universities, or people with expertise in the particular subject. They are usually graded on a weekly basis through quizzes or peer-graded assignments. The objective of this paper is to extract the concepts taught in the videos from the subtitles, which could later be used to enhance recommendations of the learners using their clickstream data. The teachers could also use this to see the demand for their courses. Evaluate two keyword extraction methods, which are BERT and LDA using different Coursera courses. The experimental results show that BERT outperforms LDA in terms of Coherence.

Aarika Kawtar, Habib Benlahmar, Mohamed Amine Naji, Elfilali Sanaa and Zouheir Banou, “Extract Concept using Subtitles in MOOC” International Journal of Advanced Computer Science and Applications(IJACSA), 13(1), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130176

@article{Kawtar2022,
title = {Extract Concept using Subtitles in MOOC},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130176},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130176},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {1},
author = {Aarika Kawtar and Habib Benlahmar and Mohamed Amine Naji and Elfilali Sanaa and Zouheir Banou}
}