Clustering University Teaching Staff through UTAUT: Implications for the Acceptance of a New Learning Management System

Autor/inn/en	Garone, Anja; Pynoo, Bram; Tondeur, Jo; Cocquyt, Celine; Vanslambrouck, Silke; Bruggeman, Bram; Struyven, Katrien
Titel	Clustering University Teaching Staff through UTAUT: Implications for the Acceptance of a New Learning Management System
Quelle	In: British Journal of Educational Technology, 50 (2019) 5, S.2466-2483 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Garone, Anja)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0007-1013
DOI	10.1111/bjet.12867
Schlagwörter	College Faculty; Integrated Learning Systems; Technology Integration; Intention; Teacher Behavior; Teacher Surveys; Foreign Countries; Multivariate Analysis; Belgium + Suchen Sie Ihr Suchwort? Fakultät; Teacher behaviour; Lehrerverhalten; Ausland; Multivariate Analyse; Belgien
Abstract	The unified theory of acceptance and use of technology (UTAUT) is a survey instrument used to determine technology usage intention and behaviour. UTAUT consists of four predictor variables; performance expectance, effort expectancy, social influence and facilitating conditions. This study investigates the technology acceptance profiles of university teaching staff, by using the UTAUT predictor variables as clustering variables, in the context of the implementation of a new learning management system (LMS). While students are mostly the focus of research on technology acceptance in higher education, university teaching staff are predominantly overlooked. Using a modified UTAUT questionnaire, 244 university teaching staff from a Belgian university took part in a survey focusing on their acceptance and use of the new LMS. Most studies on LMS acceptance in higher education are variable centred, whereas this research takes a person-centred approach. This approach will shed new light on how UTAUT can provide information which can be used to interpret the professional development needs during an institution-wide educational technology implementation. A cluster analysis with the predictor variables of UTAUT as input variables resulted in three distinct groups: a high, moderate and a low scoring cluster. These differences between the clusters were also reflected in the acceptance of the LMS. The results of this study will therefore facilitate decision making and guidelines for the design of institution-wide professional development initiatives that are targeted towards the needs of specific groups of university teaching staff. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01