HOW AI AND CREATIVITY ENCOURAGE UNIVERSITY STUDENTS TO BE MORE PREPARED TO ENTER THE WORKFORCE

Abstract

This study aims to determine how AI mastery (X1), creativity (X2), and learning motivation (X3) influence the job-seeking interest (Y) of university students. A quantitative methodology was used, involving a survey of 104 participants. Data were collected through questionnaires and analyzed using SPSS. The reliability of the instruments was confirmed with high Cronbach’s Alpha values: 0.909 for AI Mastery, 0.930 for Creativity, 0.933 for Learning Motivation, and 0.937 for Job-Seeking Interest. Multiple regression analysis showed that these three factors together significantly affect job-seeking interest. The model explained 85.9% of the variation in job-seeking interest, with an F-value of 203.510 (sig. 0.000). Individually, AI Mastery (β 0.258; sig. 0.022), Creativity (β 0.306; sig. 0.017), and Learning Motivation (β 0.633; sig. 0.000) all had significant effects. Learning Motivation was the most influential factor. Therefore, higher levels of AI mastery, creativity, and learning motivation are related to greater interest in seeking employment among students.