| dc.description.abstract | The purpose of this study is to investigate the relationship between student background, learning styles, and employment performance. The data sample consists of graduates of Nat-ional Central University in 2019. This study utilizes empirical data obtained from the univer-sity′s administrative data repository, including student’s background information, UCAN vo-cational interest diagnosis, and a post-graduation survey conducted one year after graduation. The study controls the impact of employment environment and salary level of that year. After data preprocessing, a total of 217 records with no missing data were included.
The research methodology involves first using causal odds ratio mining to identify pote-ntial quasi-causal rules within the data. Descriptive statistics are then employed to describe th-e distribute-on of the sample, followed by chi-square analysis for validating the statistical cor-relation of the quasi-causal rules. Finally, path analysis is used to verify whether causal relati-onships may exist among the identified quasi-causal rules. The study found that certain quasi-causal rules obtained through statistical methods can be validated to potentially indicate caus-al relationships.
In analyzing the issue, there are inherent differences between causal odds ratio mining and statistical methods, which may account for the divergent results obtained. If causal odds ratio mining is regarded as the first step in exploring possible relationships and causality bet-ween the data, rather than as final conclusions, and if statistical validation or other methods are subsequently employed for further investigation, this approach offers a means to explore unanswered questions or the possibility of unconsidered factors in existing problems. | en_US |