Open AccessMalaysian Learners’ Preferences-Based Profile Model Towards Adaptive Massive Open Online Courses
Author(s) -
Mohammed Gharawi,
Azman Bidin,
Ah Choo Koo
Publication year - 2020
Publication title -
xi'nan jiaotong daxue xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 21
ISSN - 0258-2724
DOI - 10.35741/issn.0258-2724.55.1.51
Subject(s) - popularity , massive open online course , open educational resources , presentation (obstetrics) , open education , computer science , mathematics education , online course , psychology , knowledge management , world wide web , medicine , social psychology , radiology
Massive open online courses’ technology is becoming the most recent innovations in online education and academia. Recently, it has been widely adopted in educational sectors and gained popularity among both students and instructors. Massive open online courses have rapidly become a trend in the field of higher education and received much recognition from scholars and non-profit educational organizations. Therefore, there has been a growing interest in investigating its limitations, challenges, and impact on education. Some issues and problems have been reported in the research and practice, such as problems related to massive open online course learners’ motivation and engagement during the courses, and course contents’ presentations have a significant impact on learner’s motivation. However, there have been few contributions to the literature in discerning the varying motivational drivers for choosing to consume the different presentation styles of massive open online courses. Therefore, the main goal of this work is to propose an innovative framework for adaptive massive open online course based on learners’ preferences. As such, the courses’ presentations are adapted to the preferred learning style of each learner. In this regard, this paper was conducted based on quantitative research methods.