Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2970
Title: Know More: Social Media based Student Centric E-learning platform with Machine Learning Approaches
Authors: Malavige, O
Nasome, V
Costa, M
Jayasinghe, B
Karunasena, A
Samarakoon, U
Keywords: KnowMore
Social Media
E-learning platform
Machine Learning
Approaches
Student Centric
based Student
Issue Date: 18-Jul-2022
Publisher: IEEE
Citation: V. Nasome, O. Malavige, M. Costa, B. Jayasinghe, A. Karunasena and U. Samarakoon, "KnowMore: Social Media based Student Centric E-learning platform with Machine Learning Approaches," 2022 IEEE 7th International conference for Convergence in Technology (I2CT), 2022, pp. 1-7, doi: 10.1109/I2CT54291.2022.9824235.
Series/Report no.: 2022 IEEE 7th International conference for Convergence in Technology (I2CT);
Abstract: Social media has become increasingly popular among the younger generation in the last decade. Students engage with social media on daily basis, and it affects their interests, lifestyle, and attitude. There are many existing e-learning applications used by higher educational institutes, but such applications are mainly focused on delivering teaching content rather than facilitating active and interactive learning. This paper proposes a novel e-learning platform to create an active and interactive learning environment for students leveraging social media strategies, especially those of “Facebook.” The objective of this platform is to promote self-motivation, self-learning, and interaction. The platform features were built on considering three aspects important for learning, which are personal knowledge management, learning management, and collaborative learning. Features of the proposed platform that it comprises are Newsfeed, Classmates, Profile, Cluster, Repository, Knowledgebase, Bookmark, Topic Map, Search Engine, Test Mark Prediction, and Slide Show Summary generator. Machine Learning techniques and Natural Language Processing were used to build some of the platform features. The feedback collected on the proposed system, “KnowMore,” shows that the satisfaction of the students has increased with the system.
URI: http://rda.sliit.lk/handle/123456789/2970
ISSN: 978-1-6654-2168-3
Appears in Collections:Department of Information Technology
Research Papers - IEEE
Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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