• Journal of Practical Engineering Education
• /
• v.16 no.2
• /
• pp.227-239
• /
• 2024

This study aims to analyze the impact of vocational training received by learning workers through the degree-linked work-study program on their learning outcomes. Specifically, we explore the causal relationship between various factors considered during university degree program admission and selection, and the average GPA (Grade Point Average) after admission. To achieve this, we conducted regression analysis and variance analysis using historical admission data and GPA records of 976 students from three undergraduate programs at a domestic K university that implements the degree-linked work-study model. Additionally, we included company information from publicly available databases that could potentially influence the academic performance of learning workers. Our analysis revealed significant causal relationships across various factors, including the classification of the high school attended, gender, family background, subject-specific grades in high school, duration of employment at the company, and age at the time of admission. Based on these findings, we anticipate that universities operating similar degree programs can enhance their selection procedures for learning workers. Furthermore, the results of this study can serve as foundational data for future policy recommendations related to degree-linked work-study programs.

• Journal of Engineering Education Research
• /
• v.27 no.1
• /
• pp.3-12
• /
• 2024

The degree-linked programs for employees, operated by joint training centers in specialized universities that have implemented work-study integrated programs, are educational programs that require an annual government budget of around 80 billion KRW. However, the 70+ universities running these programs face issues such as a decline in academic achievement and an increase in dropout rates among students. In this paper, I conducted multiple regression analysis based on observed and measured information to examine whether the participating students in these programs are achieving an appropriate level of academic performance and to identify the factors that universities need to invest in to achieve that level. To do this, I hypothesized a causal relationship between the university's input factors and students' academic achievement, and used the SPSS program to analyze the statistical data, confirming the validity of the hypothesis. The collected data for the study were obtained through a survey developed using a Likert 4-point scale, which quantified the distribution of grades among students enrolled in IT-related departments offering the degree-linked programs for employees and the emotional contact efforts made by the universities to motivate them for academic success. Particularly, through the results of multiple regression analysis, it was confirmed that these input factors, unlike those for students in general education programs, require more personalized and frequent interactions.