PREDICTIVE ACADEMIC ACHIEVEMENT IN CHINESE LANGUAGE SUBJECTS OF LAMPANG INTER-TECH COLLEGE
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Abstract
This study aimed to 1) compare students’ opinions regarding the factors affecting Chinese language learning achievement, both overall and by individual dimensions; 2) predict students’ Chinese language learning achievement; and 3) develop a logistic regression model to predict the Chinese language learning achievement of students at Lampang Inter-Tech College. The research employed a quantitative approach using a questionnaire as the research instrument. The sample consisted of 61 students enrolled in the Chinese language course during the first semester of the 2025 academic year, selected through purposive sampling. The data were analyzed using the independent samples t-test, one-way analysis of variance (ANOVA), and multiple logistic regression.
The findings revealed that: 1) students’ overall opinions regarding the factors affecting Chinese language learning achievement were at a high level. Among the dimensions, attitudes toward learning received the highest mean score, followed by motivation to learn, teacher-related factors, and the learning environment. Male and female students differed significantly in their opinions regarding the factors affecting Chinese language learning achievement (p < .05). In addition, students with different upper secondary educational backgrounds showed significantly different opinions at the .10 level. 2) The logistic regression model correctly classified 82.2% of the cases and accurately predicted 65.6% of the students who achieved a passing grade. 3) The logistic regression model identified cumulative grade point average (GPAX), motivation to learn, and teacher-related factors as significant predictors of Chinese language learning achievement, with regression coefficients of 3.21, 1.01, and 0.67, respectively.
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