Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-Learning Content Personalization

Autor/inn/en	Mwambe, Othmar Othmar; Tan, Phan Xuan; Kamioka, Eiji
Titel	Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-Learning Content Personalization
Quelle	In: Education Sciences, 10 (2020), Artikel 42 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Mwambe, Othmar Othmar) ORCID (Tan, Phan Xuan)
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2227-7102
Schlagwörter	Biology; Information Science; Technology Uses in Education; Hypermedia; Multimedia Instruction; Student Needs; Preferences; Cognitive Processes; Resource Units; Electronic Learning; Prior Learning; Synchronous Communication; Program Effectiveness; Foreign Countries; College Students; Computer Science Education; Japan; Thailand + Suchen Sie Ihr Suchwort? Biologie; Informationswissenschaft; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Multimediales Lernen; Cognitive process; Kognitiver Prozess; Vorkenntnisse; Ausland; Collegestudent; Computer science lessons; Informatikunterricht
Abstract	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%. (As Provided).
Anmerkungen	MDPI AG. Klybeckstrasse 64, 4057 Basel, Switzerland. Tel: e-mail: indexing@mdpi.com; Web site: http://www.mdpi.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01