Determinants for the Attitude for Rain Class for University Chinese Language and Literature Education Students in Kunming Region of China
Abstract
The aim of this study is to explore the online learning attitude of Chinese language and literature majors in a Kunming-based university toward the Rain Class platform, as well as the core factors affecting these attitudes, measuring System Quality (SYQ), Information Quality (INQ), Interactivity (INT), Perceived Usefulness (PU), Confirmation (CONF), Satisfaction (SAT), and Attitude (ATT) to clarify whether and how these factors shape the attitudes of the target student group. A quantitative survey was conducted among Chinese language and literature students at the target university, yielding 500 valid samples through quota sampling. Structural Equation Modeling (SEM) and Confirmatory Factor Analysis (CFA) were applied to examine the causal relationships between the studied factors. Statistical findings confirmed all proposed hypotheses, with Information Quality showing the strongest direct influence on students' attitudes. All hypotheses have been validated, and the research objectives have been accomplished, thus recommending that university academic affairs and student affairs departments analyze the key contributions of existing online learning implementation strategies to further enhance the learning attitudes of Chinese language and literature majors
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