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Citation

Kim T, Lee G, Seo D, Yun J & Kim S (2025) Educational Technology Adoption: An Integration of UTAUT2 and Technology Readiness among Secondary. the 30th Annual Congress of the European College of Sport Science, Rimini (Italy, IT), 01.07.2025-04.07.2025.

Abstract
Introduction This study examines the factors influencing the adoption of a new educational technology (using a LiDAR sensor) among secondary school students in the United States. The primary aim of this study is to investigate the formation of intention to use of the new educational technology product by empirically testing its key antecedents. Grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and the Technology Readiness Index (TRI) 2.0, the research investigates how constructs such as Performance Expectancy, Hedonic Motivation, Habit, and Technology Readiness predict students’ Intention to Use the product. Methods Data were collected from 200 secondary school students using a convenience sampling approach. Structural equation modelling with Partial Least Squares (PLS) was employed to test the proposed model, and the Importance–Performance Map Analysis (IPMA) provided additional insights into areas for improvement. Given that the product is still in its pre-market stage, carefully designed stimuli were employed to simulate a realistic user experience. These stimuli includes video demonstrations, brochures with detailed product information, and comprehensive usage instructions. Results Overall, the PLS-SEM results indicate that Performance Expectancy, Hedonic Motivation, Habit, and Technology Readiness significantly predict students’ Intention to Use the product, with Facilitating Conditions notably enhancing Technology Readiness. Specifically, the results reveal that Performance Expectancy (β = 0.20, p < .05), Hedonic Motivation (β = 0.18, p < .05), Habit (β = 0.42, p < .001), and Technology Readiness (β = 0.14, p < .05) significantly influence Intention to Use. Furthermore, Facilitating Conditions significantly predict Technology Readiness (β = 0.34, p < .001). These findings suggest that while performance and enjoyment drive adoption, habitual use and technological predispositions also play crucial roles. Discussion The study concludes by discussing practical implications, including the potential benefits of gamification and targeted marketing strategies for technology-ready segments. The IPMA results offer additional insights beyond the standard structural analysis by comparing each construct’s relative importance with its performance. Based on the results, we provided practical implications. For instance, both Performance Expectancy and Hedonic Motivation exhibit high importance yet only moderate performance, placing them in the “Keep Up the Good Work” category. This suggests that while users recognise the benefits of JUST ON STUDY in enhancing their study performance and enjoy its features, there remains potential to further refine these aspects. For instance, developers might enhance features that directly improve study outcomes or integrate additional gamification elements (e.g., point systems, progress badges, and leaderboards) to boost engagement and motivation.