DETERMINANTS OF INSTRUCTIONAL TECHNOLOGY ADOPTION IN HYBRID EDUCATIONAL SETTINGS: EXPLORING INDIVIDUAL AND INSTITUTIONAL FACTORS FOR INSTRUCTORS

Year 2025, Volume: 26 Issue: 4, 131 - 148, 01.10.2025

Ferhan Sahin , Hatice Guler , Mehmet Akif Hasiloglu

https://doi.org/10.17718/tojde.1581959

Abstract

The empirical evidence regarding the acceptance and use of hybrid education and online instructional technologies in mandatory educational contexts remains limited. Specifically, studies addressing instructors’ acceptance and usage of these technologies in the context of hybrid education are even scarcer. This study aims to fill this gap by investigating the factors influencing instructors’ intention to use online instructional technologies within the framework of an extended Technology Acceptance Model (TAM). The study includes 301 instructors from five different state universities who have experience in conducting both faceto- face and online courses within the hybrid education format. The research employs confirmatory factor analysis, structural equation modeling, and bootstrapping analysis for data analysis. The findings reveal that the proposed model explains 54.7% of ease of use, 53.5% of usefulness, and 65.4% of intention variance. Notably, self-efficacy and compatibility factors exhibit the most substantial influence on the outcomes. Furthermore, the findings suggest that the impact of institutional and individual factors, such as facilitating conditions, openness, and resistance to change, differ significantly in the context of mandatory hybrid education compared to conventional settings. The study discusses theoretical and practical implications and highlights potential avenues for future research.

Keywords

Instructional technologies , Online education , Hybrid education , Instructors , Technology acceptance model , Path modeling

References

• Al-alak, B. A., & Alnawas, I. A. (2011). Measuring the acceptance and adoption of e-learning by academic staff. Knowledge Management & E-Learning: An International Journal, 3(2), 201-221. https://doi.org/10.34105/j.kmel.2011.03.016
• Alharbi, S., & Drew, S. (2014). Using the technology acceptance model in understanding academics’ behavioural intention to use learning management systems. International Journal of Advanced Computer Science and Applications, 5(1).
• Ali, I. (2019). Personality traits, individual innovativeness and satisfaction with life. Journal of Innovation & Knowledge, 4(1), 38-46. https://doi.org/10.1016/j.jik.2017.11.002
• Al-Maroof, R., Al-Qaysi, N., Salloum, S. A., & Al-Emran, M. (2022). Blended learning acceptance: A systematic review of information systems models. Technology, Knowledge and Learning, 1-36. https://doi.org/10.1007/s10758-021-09519-0
• Anderson, S. E., Groulx, J. G., & Maninger, R. M. (2011). Relationships among preservice teachers’ technology-related abilities, beliefs, and intentions to use technology in their future classrooms. Journal of Educational Computing Research, 45(3), 321-338. https://doi.org/10.2190/EC.45.3.d