Comparative Analysis of Student Engagement in Traditional vs AI-Assisted Learning Using UWS-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.