sis 22(6): e10

Research Article

E-Learning through an Adaptive cMOOC: Is it Worthy of Further Research?

Download230 downloads
  • @ARTICLE{10.4108/eetsis.v9i6.2713,
        author={Soumaya El Emrani and Manuel Palomo-Duarte and Jos\^{e} Miguel Mota and Juan Manuel Dodero},
        title={E-Learning through an Adaptive cMOOC: Is it Worthy of Further Research?},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={9},
        number={6},
        publisher={EAI},
        journal_a={SIS},
        year={2022},
        month={9},
        keywords={cMOOC, adaptive MOOC, machine learning, intelligent system, systematic literature review, covid-19},
        doi={10.4108/eetsis.v9i6.2713}
    }
    
  • Soumaya El Emrani
    Manuel Palomo-Duarte
    José Miguel Mota
    Juan Manuel Dodero
    Year: 2022
    E-Learning through an Adaptive cMOOC: Is it Worthy of Further Research?
    SIS
    EAI
    DOI: 10.4108/eetsis.v9i6.2713
Soumaya El Emrani1,*, Manuel Palomo-Duarte2, José Miguel Mota2, Juan Manuel Dodero2
  • 1: Abdelmalek Essaâdi University
  • 2: University of Cádiz
*Contact email: soumaya.emrani@gmail.com

Abstract

This paper describes the types of MOOC considered by researchers, and highlights the latter’s focus on Connectivist MOOC. In addition, it analyses MOOC methodologies, and learners’ interest in MOOC based on the concepts of adaptability, connectivism, and socio-constructivism. This is to address the high dropout rate issue on MOOC platforms. The main objective of this work is to review the empirical results reported in these studies. To reach this goal, a Systematic Literature Review of 798 papers was carried out from 2013 until April 2021, where 446 papers were selected as primary studies. The results obtained from the classification and the analysis of the collected data confirmed the importance of continuing research in the field. Based on the concepts of socio-constructivism and adaptability, the objective is to provide an adaptive cMOOC for the profile and the needs of each learner; blending learning styles and pedagogical models with machine learning technologies.