4.7 Article

A case study to examine undergraduate students' intention to use internet of things (IoT) services in the smart classroom

Journal

EDUCATION AND INFORMATION TECHNOLOGIES
Volume 28, Issue 8, Pages 10459-10482

Publisher

SPRINGER
DOI: 10.1007/s10639-022-11537-z

Keywords

IoT; Education; Smart classrooms; Technology acceptance; Technology readiness

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Recently, there has been increased interest in the adoption of IoT services in the education sector. However, empirical studies on IoT services in the smart classroom are limited. This study proposes an integrated model to examine students' intention to use IoT services in the smart classroom. The findings show that compatibility, discomfort, enjoyment, and self-efficacy significantly influence students' perceived ease of use and perceived usefulness of IoT services. The study also highlights the impact of innovativeness and insecurity on students' intention to use IoT services.
Recently, the education sector has received increased interest in terms of the adoption of Internet of things (IoT) services for learning activities. However, despite this interest, empirical studies on the adoption of IoT services in the smart classroom are limited. Thus, the present study examines students' intention to use IoT services in the smart classroom. Towards this end, an integrated model based on the technology acceptance model (TAM), technology readiness index (TRI), and external factors (enjoyment, compatibility, and self-efficacy) is proposed. A quantitative research design was therefore used to determine the factors that affect students' intention to use IoT services in the smart classroom, using a sample of 230 participants. The findings showed that compatibility, discomfort, enjoyment, and self-efficacy had a significant influence on both perceived ease of use (PEoU) and perceived usefulness (PU). Furthermore, innovativeness had a significant effect on PEoU, and insecurity had a significant impact on PU. The results also revealed that PU had a significant influence on the students' behavioural intention to use. These findings extend the understanding of students' intention to use IoT services in the smart classroom. This study could be beneficial to researchers, educators, and IoT developers. However, it also presents a number of limitations, such as a lack of qualitative methods and the small number of theories applied.

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