Testing a novel extended educational technology acceptance model using student attitudes towards virtual classrooms

Bibliographic Data

ID21297217
AuthorsAndrew Kemp (0000-0002-2135-6634, School of Education, Faculty of Arts, Business, Law and Economics The University of Adelaide Adelaide South Australia Australia, corresponding author), Edward Palmer (0000-0002-3343-9066, School of Education, Faculty of Arts, Business, Law and Economics The University of Adelaide Adelaide South Australia Australia), Peter Strelan (0000-0002-3796-1935, School of Psychology, Faculty of Health and Medical Sciences The University of Adelaide Adelaide South Australia Australia), Helen Thompson (0000-0001-5366-3172, School of Mathematical Sciences, Faculty of Science Queensland University of Technology Brisbane Queensland Australia)
Year2024
Volume55
Issue5
Pages2110-2131
Publication date2024-09-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBritish Journal of Educational Technology (JOURNAL)
Journal identifiersISSN: 0007-1013 • E-ISSN: 1467-8535
PublisherWiley (PUBLISHER • GB)
DOI10.1111/bjet.13440
OpenAlexW4391606055
LanguageEN
Citations received12
References cited90

Many technology acceptance models used in education were originally designed for general technologies and later adopted by education researchers. This study extends Davis' technology acceptance model to specifically evaluate educational technologies in higher education, focusing on virtual classrooms. Prior research informed the construction of the model, which contains perceived usefulness, perceived ease of use, behavioural intent, access and convenience, system attributes and self‐efficacy. Education‐specific constructs include cognitive engagement, feedback, instructor practice and class interaction and communication. Additionally, a new construct called comfort and well‐being is introduced. A total of 427 valid responses on a 5‐point Likert scale were received from university students. Exploratory factor analysis, confirmatory factor analysis and structural equation modelling were used to analyse the data. The model accounted for 78% of variance of behavioural intent, with comfort and well‐being demonstrating the strongest influence. Cognitive engagement, access and convenience influenced perceived usefulness, and system attributes and self‐efficacy influenced perceived ease of use. Feedback, instructor practice and class interaction and communication were not significant as educational constructs for this cohort. Based on this analysis, a final extended educational technology acceptance model (EETAM) is proposed for further use and testing. Practitioner notes

Class (philosophy) · Confirmatory factor analysis · Construct (python library) · Educational technology · Exploratory factor analysis · Human–computer interaction · Likert scale · Mathematics education · Structural equation modeling · Student engagement · Technology Acceptance Model · Usability · Applied Psychology · Computer Science · Online and Blended Learning · Psychology · Technology Adoption and User Behaviour · Technology-Enhanced Education Studies

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