A Multi-Criteria Decision-Making (MCDM) Approach for Data-Driven Distance Learning Recommendations

Autor/inn/en	Alshamsi, Aysha Meshaal; El-Kassabi, Hadeel; Serhani, Mohamed Adel; Bouhaddioui, Chafik
Titel	A Multi-Criteria Decision-Making (MCDM) Approach for Data-Driven Distance Learning Recommendations
Quelle	In: Education and Information Technologies, 28 (2023) 8, S.10421-10458 (38 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Alshamsi, Aysha Meshaal) ORCID (El-Kassabi, Hadeel) ORCID (Serhani, Mohamed Adel) ORCID (Bouhaddioui, Chafik)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-023-11589-9
Schlagwörter	Evaluation Criteria; Decision Making; Distance Education; Academic Achievement; School Holding Power; Weighted Scores; Information Systems; Course Selection (Students); Data Analysis; COVID-19; Pandemics + Suchen Sie Ihr Suchwort? Decision-making; Entscheidungsfindung; Distance study; Distance learning; Fernunterricht; Schulleistung; Course selection; Student; Students; Kurswahl; Auswertung
Abstract	Distance learning has been adopted as an alternative learning strategy to the face-to-face teaching methodology. It has been largely implemented by many governments worldwide due to the spread of the COVID-19 pandemic and the implication in enforcing lockdown and social distancing. In emergency situations distance learning is referred to as Emergency Remote Teaching (ERT). Due to this dynamic, sudden shift, and scaling demand in distance learning, many challenges have been accentuated. These include technological adoption, student commitments, parent involvement, and teacher extra burden management, changes in the organization methodology, in addition to government development of new guidelines and regulations to assess, manage, and control the outcomes of distance learning. The objective of this paper is to analyze the alternatives of distance learning and discuss how these alternatives reflect on student academic performance and retention in distance learning education. We first, examine how different stakeholders make use of distance learning to achieve the learning objectives. Then, we evaluate various alternatives and criteria that influence distance learning, we study the correlation between them and extract the best alternatives. The model we propose is a multi-criteria decision-making model that assigns various scores of weights to alternatives, then the best-scored alternative is passed through a recommendation model. Finally, our system proposes customized recommendations to students, and teachers which will lead to enhancing student academic performance. We believe that this study will serve the education system and provides valuable insights and understanding of the use of distance learning and its effectiveness. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01