An analytical model of college students' self-assessed satisfaction with the effectiveness of online learning: a structural equation model integrating LICE and S-O-R models.

Abstract

Nowadays, e-learning significantly affects college students' academic life. This study aims to examine the factors that influence college students' satisfaction with online learning outcomes. The study population consisted of undergraduate students from Dalian Medical University, with a total of 715 college students participating in the study. Out of these participants, 602 valid questionnaires were obtained. Demographic data was analyzed using SPSS.22, and the data was cleaned and prepared for testing the research hypotheses. The proposed research framework was examined using structural equation modeling (SEM) through Smart-PLS 3.0. The results of the study showed that student satisfaction with learning outcomes was positively correlated with several factors: quality of teacher instruction (β = 0.100, p < 0.0001), quality of e-learning platforms (β = 0.059, p < 0.0001), individual learner factors such as learning motivation (β = 0.112, p < 0.001), and e-learning environment (β = 0.469, p < 0.001). Additionally, self-learning efficacy (β = 0.081, p < 0.0001), learning strategies (β = 0.031, p < 0.001), and learning motivation (β = 0.039, p < 0.001) were found to have mediating effects. Understanding the satisfaction of college students with the effect of e-learning holds great significance in coping with teaching methods in unexpected situations. It enables adjustments to teaching strategies, improvements to learning platforms, and mobilization of students' motivation. Thus, it serves as a valuable reference in addressing unexpected teaching scenarios.