Exploring Determinants of University Students' Adoption of Learnmaster E-Learning in Wuhu, China
Abstract
This research examines the key factors that shape vocational college students' continued use of Learnmaster E-Learning Technology (LELT) in Wuhu, Anhui Province, China. Drawing upon an integrated framework that merges the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and Social Cognitive Theory (SCT), this study incorporates self-efficacy, effort expectancy, facilitating conditions，and performance expectancy as additional constructs to strengthen its explanatory capacity. This approach effectively addresses domain-specific challenges within vocational education contexts, including technological instability and limited interactive capabilities in digital learning platforms. A structured survey was distributed to 500 students across eight departments of Anhui Mechanical and Electrical Vocational College, all of whom had previous exposure to LELT. This investigation is particularly necessary for the focal institution, as it is currently seeking to modernize its teaching models, enhance digital learning engagement, and improve student outcomes by leveraging e-learning platforms. Confirmatory Factor Analysis (CFA) was utilized to verify both convergent and discriminant validity, after which Structural Equation Modeling (SEM) was conducted to assess the overall model fit and examine seven proposed paths. The findings provided support for all proposed hypotheses, highlighting self-efficacy as the strongest determinant of behavioral intention, while facilitating conditions and performance expectancy also exhibited significant positive impacts. Based on these findings, the study proposes three strategic recommendations: integrating LELT performance metrics into institutional evaluation and scholarship systems; enhancing technical support infrastructure through micro-service architecture optimization; and implementing phased training programs designed to build user confidence and reduce cognitive load. The proposed recommendations are intended to promote a more comprehensive incorporation of e-learning tools within vocational education contexts. Moreover, the study confirms the applicability of the extended TAM-UTAUT-SCT framework in interpreting technology adoption behaviors in Chinese vocational colleges, thereby offering both conceptual contributions and actionable implications for educators, system designers, and policymakers working toward digital education advancement.
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