Determinants of Learning Management Systems Adoption in Nigeria: A Hybrid SEM and Artificial Neural Network Approach

Autor/inn/en	Yakubu, Mohammed Nasiru; Dasuki, Salihu Ibrahim; Abubakar, A. Mohammed; Kah, Muhammadou M. O.
Titel	Determinants of Learning Management Systems Adoption in Nigeria: A Hybrid SEM and Artificial Neural Network Approach
Quelle	In: Education and Information Technologies, 25 (2020) 5, S.3515-3539 (25 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Yakubu, Mohammed Nasiru)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-020-10110-w
Schlagwörter	Management Systems; Instructional Improvement; Student Surveys; Intention; Predictor Variables; Usability; Foreign Countries; College Students; Structural Equation Models; Artificial Intelligence; Networks; Technology Uses in Education; Higher Education; Student Attitudes; Universities; Social Influences; Student Behavior; Nigeria + Suchen Sie Ihr Suchwort? Unterrichtsqualität; Schülerbefragung; Prädiktor; Ausland; Collegestudent; Künstliche Intelligenz; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Hochschulbildung; Hochschulsystem; Hochschulwesen; Schülerverhalten; University; Universität; Sozialer Einfluss; Student behaviour
Abstract	Research has shown that technology, when used prudently, has the potential to improve instruction and learning both in and out of the classroom. Only a handful of African tertiary institutions have fully deployed learning management systems (LMS) and the literature is devoid of research examining the factors that foster the adoption of LMS. To fill this void, the present research investigates the factors contributing to students' acceptance of LMS. Survey data were obtained from registered students in four Nigerian universities (n = 1116); the responses were analyzed using artificial neural network (ANN) and structural equation modeling (SEM) techniques. The results show that social influence, facilitating conditions, system quality, perceived ease of use, and perceived usefulness are important predictors for students' behavioral intention to use LMS. Students' behavioral intention to use LMS also functions as a predictor for actual usage of LMS. Implications for practice and theory are discussed. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01