Predictive Factors of Student Participation in University Career and Entrepreneurship Programs

View at Publisher

Ask AI

Bookmark

Share

Key Points

This study aims to identify key predictive factors influencing student participation in university career and entrepreneurship programs.
Utilized data from the Korean Employment Information Center's KEEP II data
Applied machine learning techniques including XGBoost for prediction
Employed SHAP for interpreting the predictive model
Distinguished between curricular and extracurricular program participation
Identified factors such as PBL lecture experience and self-concept as significant for curricular participation
Found extracurricular participation linked to factors like number of clubs and scholarship amounts
Highlighted the importance of new teaching methods for enhancing program efficacy

Answers are grounded in this paper and cite their sources.

Research explores factors predicting student participation in career programs, suggesting improvements for engagement.

No abstract yet. The journal hasn't published one we can show.

No takes yet. Share an insight, caveat, or question.

Kang et al. (2025) studied this question.

View at Publisher

Ask AI

Bookmark

Share