Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1672
Title: MOOCs Recommender based on User Preference and Video Quality
Authors: Sankalpa, R
Sankalpani, T
Sandeepani, T
Ransika, N
Kodagoda, N
Suriyawansa, K
Keywords: MOOCs Recommender based
User Preference
Video Quality
Issue Date: 10-Dec-2020
Publisher: IEEE
Citation: R. Sankalpa, T. Sankalpani, T. Sandeepani, N. Ransika, N. Kodagoda and K. Suriyawansa, "MOOCs Recommender based on User Preference and Video Quality," 2020 2nd International Conference on Advancements in Computing (ICAC), 2020, pp. 79-84, doi: 10.1109/ICAC51239.2020.9357278.
Series/Report no.: 2020 2nd International Conference on Advancements in Computing (ICAC);Vol 1 Pages 79-84
Abstract: MOOCs (Massive Open Online Courses) are a new revolution in the field of e-learning. MOOCs are capable of providing several thousands of learners with access to courses over the internet. MOOCs are produced in many different video production styles and these styles play an important role in helping the consumer stay engaged and interested in the courses. MOOCs provide a large number of courses in different domains to a wide range of learners. It has become difficult and a time-consuming task for a user to find the most suitable courses that suit a learner's personal preferences. This paper describes how to recommend a course based on the preferred video style of the learner and the basic learning style of the learner which determines the learner's preferences on other materials in a course. In the course recommendation process, this paper also describes how to classify the course in order to recommend the most appropriate massive open online courses for users according to their most preferred video production style.
URI: http://rda.sliit.lk/handle/123456789/1672
ISBN: 978-1-7281-8412-8
Appears in Collections:Department of Information Technology-Scopes
Research Papers - SLIIT Staff Publications

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