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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/21485

Title: MOOCs in universities: intelligent model for delivering online learning content
Authors: Sammour, George
Al-Zoubi, Abdallah
Gladun, Anatoly
Khala, Katerina
Schreurs, Jeanne
Issue Date: 2016
Publisher: IEEE
Citation: MOOCs in universities: intelligent model for delivering online learning content, p. 167-171
Abstract: - A massive open online course (MOOC) is a model for delivering learning content online to any person who wants to take a course, with no conditions on attendance. Unlike traditional courses, MOOCs require additional skills, provided by videographers, instructional designers, IT specialists and platform specialists. Over the past few years several Universities facilitated partnership with MOOCs providers and are building MOOC courses, to serve as e-Iearning versions of their courses. Despite all the advantages offered by the MOOC courses, the current statistics show that only a very limited number of registered learners are completing the course. And the vast majority are stopping learning at an early stage. The main reason can be found in the lack of motivation of the students to pass the exams to become a eertifieate, because universities do not accept the certifieates for credits. The aim of this paper is to study the readiness of students to take MOOC courses on one hand and the acceptance of MOOC courses in Universities. A study is conducted on two Universities, Hasselt University, Belgium and Princess Sumaya University for Technology, Jordan. The results of the study are promising, as they suggest that such virtual study programs are accepted in both Universities. However, professors in both Universities elucidate coneerns on accepting the equivalence of the MOOC courses to their own courses.
Notes: Sammour, G (reprint author), PSUT, Amman, Jordan. george.sammour@psut.edu.jo; zoubi@psut.edu.jo; glanat@yahoo.com; cecerongreat@ukr.net; jeanne.schreurs@uhasselt.be
URI: http://hdl.handle.net/1942/21485
DOI: 10.1109/IntelCIS.2015.7397216
ISI #: 000380470400025
ISBN: 9781509019496
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2017
Appears in Collections: Research publications

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