Multi-criteria decision analysis identifies key career planning drivers in university students, highlighting the need to align industry collaboration with skill building.
Key Points
To evaluate an applied higher education model at an industrial university by integrating student perceptions with academic and industry expert evaluations.
Gathered evaluation data from 76 students and 13 academic and industry experts.
Applied a hybrid framework using the Pythagorean Fuzzy Analytic Hierarchy Process to weight criteria, a decision tree algorithm to model predictive relationships, and correlation analysis to assess inter-criteria associations.
Identified foreign language development, professional networking, high academic average, and software/programming skills as significant determinants of students' five-year career planning.
Showed that academic guidance, industry collaboration, and practical skills development function as an interdependent, complementary structure.