ARTIFICIAL INTELLIGENCE DEPENDENCY, ACADEMIC PROCRASTINATION, DECISION MAKING AND ACADEMIC STRESS IN UNIVERSITY STUDENTS.

Abstract

In the past few years, AI has become an integral element of students' academic routines, generating concerns about its impact on learning behavior’s, stress levels, and decision-making skills. A quantitative correlational research design was employed to explore the relationship with artificial intelligence dependency, academic procrastination, decision-making, and academic stress in university students The sample consisted of 500 out of which 46 % were male and 54 % were female students, aged 18 to 24 years with the M= 21.0, SD=1.91 enrolled in private sector universities of Lahore. Data were collected through self-administered survey forms including informed consent, a demographic information sheet, and Dependence on Artificial Intelligence (DAI), the Academic Procrastination Scale (APST), the Decision-Making Questionnaire (DMQ), and the Academic Stress Scale (ASS). Data analysis was conducted using Pearson’s product-moment correlation and multiple regression in SPSS 27th version. The findings of the Pearson’s correlation analysis revealed that artificial intelligence dependency had a strong positive relationship with academic procrastination and a negative relationship with academic stress, but a poor relationship with decision-making. Academic procrastination has a positive relationship with academic stress and decision-making subscales, while decision making have partially negative relationship with academic stress. The regression analysis examined that gender and academic procrastination predict academic stress in university students. The study emphasizes the need to address maladaptive technology use, procrastination tendencies, and inefficient decision-making methods in order to reduce academic stress and enhance well-being in higher education settings