A structural model of pre-service teachers' attitude, acceptance, and continuance intention towards mobile augmented reality

• Published in: CONTEMPORARY EDUCATIONAL TECHNOLOGY
• Main Authors: Nizar, Nur Nabihah Mohamad; Zulnaidi, Hutkemri; Basar, Annisaa; Maaruf, Siti Zuraida
• Format: Article
• Language: English
• Published: BASTAS PUBL LTD - UK 2024
• Subjects: Education & Educational Research
• Online Access: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-recordWOS:001363171300005

The increasing prevalence of mobile augmented reality (MAR) has garnered attention in contemporary times. However, its application within educational settings remains largely untapped, primarily due to its predominant utilization in entertainment domains. MAR presents opportunities for augmenting learning experiences, fostering enhanced adaptability in educational methodologies, and enriching students' academic endeavors. Therefore, this study aims to enhance the use of MAR and formulates a model of MAR usage for pre-service teachers. In the context of this study, MAR learning cardiovascular (MARLCardio) serves as an experimental tool for exemplifying the features of MAR. This study integrates the Unified Theory of Acceptance and Use of Technology (UTAUT), Technology Acceptance Model (TAM), and Expectation Confirmation Model (ECM) as underpinning theories. This study was undertaken to determine factors that influence pre-service teachers' attitude, acceptance, and their intention to continue using MAR in the learning process. Responses from 456 pre-service teachers through a survey were analyzed using structural equation modelling. Findings in this study found that pre-service teachers agree that facilitating condition play a crucial role in shaping pre-service teachers' positive attitude and influencing their intention to continue using MAR. Meanwhile, performance expectancy plays a major role in ensuring pre-service teachers' acceptance of using MAR in their learning process. It was anticipated that the formulated MAR structural model would offer insights and support forthcoming research endeavors aimed at fostering the sustainability of MAR utilization.