COMPARATIVE ANALYSIS OF STUDENT ENGAGEMENT IN TRADITIONAL VS AI-ASSISTED LEARNING USING UWES-9S

Abstract

In this study, we empirically investigate the impact of AI--assisted learning environments versus traditional teaching methods on student engagement at the University of Montenegro. Using the Utrecht Work Engagement Scale for Students (UWES-9S) and a qualitative survey, we assessed three core dimensions of engagement: vigour, dedication, and absorption. A total of 82 undergraduate students (age range 19–27; 59% female, 41% male) participated in a semester-long comparative analysis using a pre-and-post intervention design. Sixty students from the Faculty of Science and Mathematics were assigned to the AI-assisted group due to logistical and course scheduling constraints, while twenty-two students from the Faculty of Metallurgy continued with traditional instruction, forming the control group. Our analysis employed a mixed ANOVA to explore interactions between time and instructional type, revealing significant improvements when the group switched to AI-assisted instruction for vigour (F(1,80) = 22.35, p < 0.001, ηp2 = 0.218), dedication (F(1,80) = 24.48, p < 0.001, ηp2 = 0.234), and absorption (F(1,80) = 20.11, p < 0.001, ηp2 = 0.201). Elevated Cohen's d values indicated large effect sizes, demonstrating both statistical and practical significance in these enhancements.