Factors Predicting Career Choices among Fourth-Year Students in the Faculty of Humanities and Social Sciences, Burapha University: A Multilevel Multiple Regression Analysis
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Abstract
The purposes of this research were to study multilevel predictive factors and to create multilevel predictive equations affecting factors predicting career choices of fourth-year students at the Faculty of Humanities and Social Sciences, Burapha University. The sample consisted of 420 fourth-year undergraduate students from 14 courses by simple random sampling. A 5-point rating scale questionnaire was utilized, with content validity ranging from .67 to 1.00, item discrimination from .20 to .65, and reliability of .91. The statistical method employed was multilevel multiple regression analysis using the Mplus 8.10 program for analysis.
The results indicated that, at the student level, factors predicting career choices, which accounted for 53.60% of the variance, included average monthly family income (.05) with a statistical significance level of .05, while career type (.16) and motivation (.72) were significant at the .01 level, respectively. At the course level, which could predict 89.20% of the variance, factors included the type of career (-.43) with a statistical significance level of .05, and motivation (1.00) significant at the .01 level, respectively.
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