Exploring College Students’ Satisfaction in Cloud-Based Electronic Learning in Chengdu, China

Guo Li

Authors

Guo Li

Keywords:

Cloud-based e-learning, College students, Perceived usefulness, Cognitive absorption, Satisfaction

Abstract

Purpose: This study aims to explore the factors impacting college students’ perceived usefulness, cognitive absorption, and satisfaction in cloud-based electronic learning in Chengdu, China. Research design, data, and methodology: Purposive, quota, and convenience Sampling were adopted. The quantitative method was used to collect sample data through a questionnaire survey. The sample consisted of students from four universities in Chengdu. Before data collection, Item-Objective Congruence (IOC) and a pilot test of Cronbach's Alpha were adopted to test the content validity and reliability. After data collection, Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were used to analyze the data to verify the reliability, validity, and goodness of fit of the data and to test the hypothesis. Results: Perceived usefulness was significantly impacted by interactivity, and cognitive absorption was significantly impacted by confirmation. Perceived usefulness was the strongest predictor of satisfaction, followed by perceived usefulness, cognitive absorption, and system quality. Conclusions: Six of the eight hypotheses proposed were supported and proved to be able to achieve the research objectives. Therefore, it is recommended that developers and universities ensure the interactivity, confirmation, and information quality of cloud-based e-learning systems so that students have a positive experience, thereby improving perceived usefulness, cognitive absorption, and satisfaction.

Author Biography

Guo Li

School of Automation, Chengdu University of Information Technology, Chengdu, Sichuan, China.

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