Identifying determinants of student learning effects in intensive online environments: an empirical investigation in civil engineering education

ABSTRACT

The COVID-19 pandemic forced a dramatic change from face-to-face learning environments to intensive learning environments. This study aimed to identify and quantify the determinants of student learning effects and their conduction mechanism in intensive online environments. Using a structural equation model and a questionnaire survey, this study proposed and validated the relationships among six constructs including student engagement, perceived learning, satisfaction, instructor behaviours, student characteristics, and the state of health, well-being, and sense of community-related (HWC) issues. 306 valid responses from civil engineering students in 19 universities in China were used to validate the proposed relationships. The measurement and structural model evaluation indicated that the model fit of the fitted model is acceptable with x(2)/df = 2.548, RMSEA = 0.071, AGFI =0.78, and CFI = 0.93. The results first showed the key factors for student learning effects from the instructor, the student, and the HWC issues with a factor loading greater than 0.8. This study further inferred from the different path coefficients in the fitted model and the mediating model that instructor behaviours greatly influence student perceived learning and satisfaction through student engagement with a contribution of 100% and 58%, respectively;student characteristics have a decisive impact on student perceived learning with a path coefficient of 0.59;HWC issues negatively impact student satisfaction with a path coefficient of -0.11. The findings enrich online education theories in an intensive online environment by clarifying and quantifying the influencing mechanism of the determinants. The findings also advance education practices for students, instructors, and educational administrators by helping them find out their contribution to learning effectiveness and the key factors to improve future online teaching levels.