Learning Through Massive Open Online Courses Platforms Based on Fuzzy Analytic Hierarchy Process

Abstract

The Massive Open Online Course (MOOC) concept has apprehended the interest of most of the actors in higher education. MOOC platforms are considered a crucial source of information for both learners and professors by offering hundreds of courses around the world. However, this technology has faced many challenges, particularly their low completion rates. The present article proposes the architecture of a framework using a Fuzzy Analytic Hierarchy Process algorithm (Fuzzy-AHP) to determine the triangular weight of the courses from the most widespread MOOCS in the literature. Weights of the courses are calculated by fuzzy numbers in line with the learning profile. The outcome of the proposed framework is to improve teaching effectiveness, facilitate learning among learners, encourage long life learning and maximize motivation as well as reducing the dropout rates.