Abstract-To achieve the adaptability required in ALS, adaptive learning system (ALS) takes advantage of granular and reusable content. The main goal of this paper is to examine the learning object granularity issue which is directly related with Learning Object (LO) reusability and the adaptability process required in ALS. For that purpose, we present the learning objects approach and the related technologies. Then, we discuss the fine-grained as a fundamental characteristic to reach the adaptability and individualization required in ALS. After that, we present some learning object granularity approaches in the literature before presenting our granularity approach. Finally, we propose an example of implementation of our approach to test its ability to meet the properties associated with fine-grained and adaptability.

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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.