Factors influencing teaching innovation at a university: an extension of the job demands-resources (JD-R) model in the digital age
Yifan Huang, Biyang Huang & Zi Yang
Abstract
This study aims to extend the job demands-resources (JD-R) model to the realm of higher education in China, seeking to provide valuable insights into teaching innovation in the digital era. Specifically, it explores how critical decisions related to teaching innovation are shaped by the intricate interplay between the digital resources available to university faculty members and the digital demands placed upon them. The data was collected from a survey of 1,612 faculty members from universities across China, and was analyzed using structural equation modeling (SEM) and moderated mediation effect model to investigate these complexities. Our findings highlight the significant mediating role played by teacher self-efficacy in the relationship between digital resources and teaching innovation. Notable differences are also observed in how organizational and personal digital resources influence innovative teaching. Furthermore, our findings support the moderating role of digital demands. Specifically, digital demands negatively impact the relationship between digital resources and teaching innovation. These demands are found to dampen the mediating effect of teacher self-efficacy on the association between digital resources and teaching innovation. Overall, the study depicts an intricate and dynamic interaction between digital resources and demands, emphasizing their importance in achieving an optimal balance to encourage faculty members’ adoption of innovative teaching practices.
Higher Education, Published: 30 August 2025
