Pre-Service Teachers’ Intention to Use MUVEs as Practitioners – A Structural Equation Modeling Approach
Journal of Information Technology Education: Research
• Volume 16
• 2017
• pp. 047-068
Aim/Purpose: The study examines the effectiveness of university courses in shaping pre-service teachers’ intention to use 3D multi-user virtual environments (MUVEs) when they become practicing teachers.
Background: Four variables (perceived usefulness, perceived ease of use, self-efficacy, and attitude toward use), as well as behavioral intention to use MUVEs, were used to build a research model that extended the Technology Acceptance Model, and structural equation modeling was used for parameter estimation and model testing.
Methodology: Self-reported data was gathered from 325 pre-service teachers studying at the Department of Primary School Education at the University of the Aegean in Greece.
Contribution: The study demonstrated the applicability of the TAM as a model that can adequately explain pre-service teachers’ intention to use MUVEs as practicing teachers.
Findings: Results analyses revealed a good model fit and, overall, 64% of the variance in behavioral intention was explained. Perceived usefulness and perceived ease of use were the most influential factors.
Recommendations for Practitioners: In order to increase the odds of a successful use of MUVEs in educational settings, institutions need to address specific organizational factors that will positively influence pre-service teachers’ intentions to use them and provide experiences relevant to that technology. Also, more emphasis is needed on the usability of MUVEs.
Background: Four variables (perceived usefulness, perceived ease of use, self-efficacy, and attitude toward use), as well as behavioral intention to use MUVEs, were used to build a research model that extended the Technology Acceptance Model, and structural equation modeling was used for parameter estimation and model testing.
Methodology: Self-reported data was gathered from 325 pre-service teachers studying at the Department of Primary School Education at the University of the Aegean in Greece.
Contribution: The study demonstrated the applicability of the TAM as a model that can adequately explain pre-service teachers’ intention to use MUVEs as practicing teachers.
Findings: Results analyses revealed a good model fit and, overall, 64% of the variance in behavioral intention was explained. Perceived usefulness and perceived ease of use were the most influential factors.
Recommendations for Practitioners: In order to increase the odds of a successful use of MUVEs in educational settings, institutions need to address specific organizational factors that will positively influence pre-service teachers’ intentions to use them and provide experiences relevant to that technology. Also, more emphasis is needed on the usability of MUVEs.
MUVEs, pre-service teachers, structural equation modeling, Technology Ac-ceptance Model
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