Understanding University Teachers’ Acceptance of Online Teaching Platforms: A Technology Acceptance Model Study

Abstract

Online teaching platforms are now everyday infrastructure in Chinese higher education, yet their value ultimately depends on whether teachers are willing to keep using them. Guided by the technology acceptance model (TAM), this study examined university teachers’ acceptance of online teaching platforms in the post-pandemic period. A cross-sectional survey was completed by 236 full-time university teachers in Yunnan Province, China. The instrument measured perceived usefulness (PU), perceived ease of use (PEOU) and behavioral intention (BI) alongside usage patterns, and the data were analyzed with descriptive statistics, t tests, analyses of variance and multiple regression. Teachers reported generally high acceptance, and Chaoxing Xuexitong dominated platform use while most functions served content delivery rather than interaction. PU and PEOU together explained 54.9% of the variance in BI, with PEOU the stronger predictor (β = .646) compared with PU (β = .162). PEOU also predicted PU. Acceptance varied with age, teaching experience, professional title and subject area, with the largest gaps in PEOU, whereas gender differences appeared only in BI. The findings suggest that usability support and differentiated training, especially for senior and older teachers, matter more than further persuasion about platform benefits. Implications for institutions, platform developers and teacher development programs are discussed.