Determinants of School Teachers' Acceptance of Online Teaching in the Post-COVID-19 Era: A Technology Acceptance Model Approach

Indu George, Dr. Bindusree A. R., Dr. Hari Sundar G.

Abstract: This study examines school teachers? acceptance of online teaching in the post-COVID-19 era using the Technology Acceptance Model framework. A quantitative survey was conducted among 229 in-service government school teachers. Data were analyzed using exploratory factor analysis, reliability testing, correlation analysis, multiple regression, and structural equation modeling. Two significant predictors of online teaching acceptance were identified: perceived usefulness (r = .49, p < .001) and computer self-efficacy (r = .16, p < .001). Regression analysis indicated that these variables explained 27.7% of the variance in acceptance, with perceived usefulness emerging as the stronger predictor. Gender differences were also observed (p = .008). The findings highlight the importance of enhancing teachers? perceptions of instructional value and digital competence to sustain technology integration in post-pandemic education.

Keywords: Technology Acceptance Model (TAM), Online Teaching Adoption, Computer Self-Efficacy, Perceived Usefulness, Structural Equation Modeling, Post-COVID Education