Mampy Hajong
St. Joseph University, Nagaland
Pages:118-124
The present research study examined the association and predictive relationship of
academic AI usage with procrastination and academic engagement among university
students in Chumoukedima. The study was carried out using a cross-sectional design,
and the sample consisted of 203 university students (aged between 18-26 years).
Participants were selected using convenience sampling. The data were collected using
three standardized scales – Academic AI Usage Scale, Tuckman Procrastination Scale,
and Utrecht Work Engagement Scale-9. Data analysis was conducted using SPSS,
where correlation and regression analyses were employed to study the relationship.
The findings revealed positive associations between academic AI usage and
procrastination, while academic AI usage and academic engagement demonstrated a
negative relationship. Moreover, academic AI usage was found to be a stronger predictor
of procrastination (R2=.320, F=94.447, p<0.01) than academic engagement (R2=.079,
F=17.229, p<0.01). These findings stress the need to implement interventions that
promote enhanced cognitive abilities and self-regulated learning, rather than allowing
students to become overly dependent on AI tools to complete their academic tasks
and acquire knowledge.