Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1664
Title: MOOCRec 2 for Humanities-Learning Style Based MOOC Recommender and Search Engine
Authors: Fazuludeen, F
Vijayakumaran, G
Mahroof, Z. A
Kodagoda, N
Suriyawansa, K
Keywords: MOOCRec 2
Humanities
Learning Style Based
MOOC Recommender
Search Engine
Issue Date: 5-Dec-2019
Publisher: IEEE
Citation: F. Fazuludeen, G. Vijayakumaran, Z. A. Mahroof, N. Kodagoda and K. Suriyawansa, "MOOCRec 2 for Humanities - Learning Style Based MOOC Recommender and Search Engine," 2019 International Conference on Advancements in Computing (ICAC), 2019, pp. 470-475, doi: 10.1109/ICAC49085.2019.9103397.
Series/Report no.: 2019 International Conference on Advancements in Computing (ICAC);Pages 470-475
Abstract: Introduction of Massive Open Online Courses (MOOC) has a great impact on the e-learning sector. Further, MOOC platforms like Coursera, EdX, and Future Learn have made learning accessible to millions of people for free. Also, availability of such platforms has become a blessing and a burden to people since users cannot find the right courses that suits them due to the availability of similar topic of courses in different platforms. Moreover, MOOCRec Humanities is a curated search platform for these courses. Further, MOOCRec tries to address this problem by considering the learning style of user and matching them with the right courses. Additionally, the courses are mapped using VARK learning model. For the mapping purpose, course video styles and course practical content such as quizzes and reading materials are considered. In addition, users can search individual topics that can be covered in a course.
URI: http://rda.sliit.lk/handle/123456789/1664
ISBN: 978-1-7281-4170-1
Appears in Collections:1st International Conference on Advancements in Computing (ICAC) | 2019
Department of Computer Science and Software Engineering -Scopes
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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