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UX based adaptive e-learning hypermedia system (U-AEHS): an integrative user model approach

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Abstract

Adaptive E-Learning Hypermedia System (AEHS) has been known as a method to provide the optimized learning for each learner’s unique characteristics. To this end, learning system developers configure the general characteristic elements of learners in AEHS and analyze learning functions customized for each feature. After then, they develop system to provide learning contents suitable for each learner through the analyzed data thereof. However, there are various learning functions in learning system. Moreover, each individual learner has a different set of characteristic elements. Therefore, it is very difficult to establish application criteria. In particular, it is imperative to have all profile data of learners in e-learning system in order to provide customized learning for each individual learner. Also, it is required to select and provide adequate learning contents by analyzing accurately necessary elements for learning. However, it is very difficult to analyze and determine what learning is necessary for learners and also which learning process is adequate for learners. In this regard, this study proposed Adaptive E-Learning Hypermedia System (AEHS) that leveraged UX (user experience) to provide optimal learning process customized for learners in e-learning system. The basic data model of UX leveraged user profile based on learning style. Learning style for learning has a large number of elements. Thus, this system defined those elements that could reflect learner characteristics from human factors. After then, this study profiled based on the actual data of learners for each characteristic. In this way, this system analyzed accurately which learning would be necessary for learners. In the end, this system proposed required learning contents for learners when learners selected learning based thereon.

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Jeong, HY. UX based adaptive e-learning hypermedia system (U-AEHS): an integrative user model approach. Multimed Tools Appl 75, 13193–13209 (2016). https://doi.org/10.1007/s11042-016-3292-7

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  • DOI: https://doi.org/10.1007/s11042-016-3292-7

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