Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-learning Content Personalization
Adaptive Educational Hypermedia Systems (AEHS) play a crucial role in supporting adaptive learning and immensely outperform learner-control based systems. AEHS’ page indexing and hyperspace rely mostly on navigation supports which provide the learners with a user-friendly interactive learn...
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doaj-0d271ea399cb461cb346c30be75341892020-11-25T01:40:00ZengMDPI AGEducation Sciences2227-71022020-02-011024210.3390/educsci10020042educsci10020042Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-learning Content PersonalizationOthmar Othmar Mwambe0Phan Xuan Tan1Eiji Kamioka2Graduate School of Engineering and Science, Shibaura Institute of Technology, 3 Chome-7-5 Toyosu, Koto-ku, Tokyo 135-8548, JapanSIT Research Laboratories, Shibaura Institute of Technology, 3 Chome-7-5 Toyosu, Koto-ku, Tokyo 135-8548, JapanGraduate School of Engineering and Science, Shibaura Institute of Technology, 3 Chome-7-5 Toyosu, Koto-ku, Tokyo 135-8548, JapanAdaptive Educational Hypermedia Systems (AEHS) play a crucial role in supporting adaptive learning and immensely outperform learner-control based systems. AEHS’ page indexing and hyperspace rely mostly on navigation supports which provide the learners with a user-friendly interactive learning environment. Such AEHS features provide the systems with a unique ability to adapt learners’ preferences. However, obtaining timely and accurate information for their adaptive decision-making process is still a challenge due to the dynamic understanding of individual learner. This causes a spontaneous changing of learners’ learning styles that makes hard for system developers to integrate learning objects with learning styles on real-time basis. Thus, in previous research studies, multiple levels navigation supports have been applied to solve this problem. However, this approach destroys their learning motivation because of imposing time and work overload on learners. To address such a challenge, this study proposes a bioinformatics-based adaptive navigation support that was initiated by the alternation of learners’ motivation states on a real-time basis. EyeTracking sensor and adaptive time-locked Learning Objects (LOs) were used. Hence, learners’ pupil size dilation and reading and reaction time were used for the adaption process and evaluation. The results show that the proposed approach improved the AEHS adaptive process and increased learners’ performance up to 78%.https://www.mdpi.com/2227-7102/10/2/42adaptive educational hypermedia systemsbioinformatics-based adaptive hypermedia systemsadaptive real-time systemsadaptive hypermedia systemsmultimedia content personalization |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Othmar Othmar Mwambe Phan Xuan Tan Eiji Kamioka |
spellingShingle |
Othmar Othmar Mwambe Phan Xuan Tan Eiji Kamioka Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-learning Content Personalization Education Sciences adaptive educational hypermedia systems bioinformatics-based adaptive hypermedia systems adaptive real-time systems adaptive hypermedia systems multimedia content personalization |
author_facet |
Othmar Othmar Mwambe Phan Xuan Tan Eiji Kamioka |
author_sort |
Othmar Othmar Mwambe |
title |
Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-learning Content Personalization |
title_short |
Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-learning Content Personalization |
title_full |
Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-learning Content Personalization |
title_fullStr |
Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-learning Content Personalization |
title_full_unstemmed |
Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-learning Content Personalization |
title_sort |
bioinformatics-based adaptive system towards real-time dynamic e-learning content personalization |
publisher |
MDPI AG |
series |
Education Sciences |
issn |
2227-7102 |
publishDate |
2020-02-01 |
description |
Adaptive Educational Hypermedia Systems (AEHS) play a crucial role in supporting adaptive learning and immensely outperform learner-control based systems. AEHS’ page indexing and hyperspace rely mostly on navigation supports which provide the learners with a user-friendly interactive learning environment. Such AEHS features provide the systems with a unique ability to adapt learners’ preferences. However, obtaining timely and accurate information for their adaptive decision-making process is still a challenge due to the dynamic understanding of individual learner. This causes a spontaneous changing of learners’ learning styles that makes hard for system developers to integrate learning objects with learning styles on real-time basis. Thus, in previous research studies, multiple levels navigation supports have been applied to solve this problem. However, this approach destroys their learning motivation because of imposing time and work overload on learners. To address such a challenge, this study proposes a bioinformatics-based adaptive navigation support that was initiated by the alternation of learners’ motivation states on a real-time basis. EyeTracking sensor and adaptive time-locked Learning Objects (LOs) were used. Hence, learners’ pupil size dilation and reading and reaction time were used for the adaption process and evaluation. The results show that the proposed approach improved the AEHS adaptive process and increased learners’ performance up to 78%. |
topic |
adaptive educational hypermedia systems bioinformatics-based adaptive hypermedia systems adaptive real-time systems adaptive hypermedia systems multimedia content personalization |
url |
https://www.mdpi.com/2227-7102/10/2/42 |
work_keys_str_mv |
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