An adaptive HMM based approach for improving e-Learning methods
The evolution of web based interaction and information processing has provided an important platform to conduct e-learning activities. However, most of the current e-learning platforms provide static content without considering learning requirements of all its users. These users may have varying Vis...
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Institute of Electrical and Electronics Engineers Inc.
2023
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| _version_ | 1833351268380180480 |
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| author | Deeb B. Hassan Z. Beseiso M. |
| author2 | 56406345300 |
| author_facet | 56406345300 Deeb B. Hassan Z. Beseiso M. |
| author_sort | Deeb B. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | The evolution of web based interaction and information processing has provided an important platform to conduct e-learning activities. However, most of the current e-learning platforms provide static content without considering learning requirements of all its users. These users may have varying Visual, Auditory and Kinesthetic (VAK) oriented learning curves based on their mental abilities and these individual curves may also change during the course of education. Maladaptive e-Learning systems cannot impart quality content for each student as the users observe the information based on their exclusive learning traits. To address this problem and to enhance the e-learning experience, adaptive methods to impart e-learning contents are of prime interest. This research presents a novel approach to design an e-learning platform with adaptive content delivery. The model proposed in this research is based on clustering of students using K-means algorithm and the course of content delivery is adaptively characterized for each student using Hidden Markov Models. Both techniques are used to devise an adaptive algorithm which efficiently manages the clustering of students based on their VAK aptitudes and predicts the future e-learning framework for these students. This adaptive algorithm can thus be applied to any e-learning platform for optimal content delivery to its users in real-time. © 2014 IEEE. |
| format | Conference Paper |
| id | my.uniten.dspace-21859 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2023 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | my.uniten.dspace-218592023-05-16T10:45:45Z An adaptive HMM based approach for improving e-Learning methods Deeb B. Hassan Z. Beseiso M. 56406345300 13607947600 57215677011 The evolution of web based interaction and information processing has provided an important platform to conduct e-learning activities. However, most of the current e-learning platforms provide static content without considering learning requirements of all its users. These users may have varying Visual, Auditory and Kinesthetic (VAK) oriented learning curves based on their mental abilities and these individual curves may also change during the course of education. Maladaptive e-Learning systems cannot impart quality content for each student as the users observe the information based on their exclusive learning traits. To address this problem and to enhance the e-learning experience, adaptive methods to impart e-learning contents are of prime interest. This research presents a novel approach to design an e-learning platform with adaptive content delivery. The model proposed in this research is based on clustering of students using K-means algorithm and the course of content delivery is adaptively characterized for each student using Hidden Markov Models. Both techniques are used to devise an adaptive algorithm which efficiently manages the clustering of students based on their VAK aptitudes and predicts the future e-learning framework for these students. This adaptive algorithm can thus be applied to any e-learning platform for optimal content delivery to its users in real-time. © 2014 IEEE. Final 2023-05-16T02:45:45Z 2023-05-16T02:45:45Z 2014 Conference Paper 10.1109/WCCAIS.2014.6916638 2-s2.0-84908675989 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908675989&doi=10.1109%2fWCCAIS.2014.6916638&partnerID=40&md5=d0e6f46a7c94c01d4bd5276cfa597e85 https://irepository.uniten.edu.my/handle/123456789/21859 6916638 Institute of Electrical and Electronics Engineers Inc. Scopus |
| spellingShingle | Deeb B. Hassan Z. Beseiso M. An adaptive HMM based approach for improving e-Learning methods |
| title | An adaptive HMM based approach for improving e-Learning methods |
| title_full | An adaptive HMM based approach for improving e-Learning methods |
| title_fullStr | An adaptive HMM based approach for improving e-Learning methods |
| title_full_unstemmed | An adaptive HMM based approach for improving e-Learning methods |
| title_short | An adaptive HMM based approach for improving e-Learning methods |
| title_sort | adaptive hmm based approach for improving e-learning methods |
| url_provider | http://dspace.uniten.edu.my/ |