Asian Journal of Research in Nursing and Health

Aims: This study aimed to analyze the effects of Artificial Intelligence utilization on the study habits of nursing students in a private college.

Study Design: A descriptive-correlational quantitative research design was employed.

Place and Duration of Study: The study was conducted in a private college in Iloilo City among nursing students enrolled during the second semester of Academic Year 2025–2026.

Methodology: The study involved 325 nursing students from different year levels selected through stratified random sampling. Data were collected using a validated survey instrument composed of three parts: demographic profile, Artificial Intelligence Utilization questionnaire, and Study Habits Inventory. The Artificial Intelligence Utilization instrument measured six domains: self-efficacy, technological readiness, perceived usefulness, perceived ease of use, attitude, and AI tools usage. Study habits were measured using a 20-item inventory assessing students’ learning behaviors and routines. Data were analyzed using descriptive statistics including frequency, percentage, mean, and standard deviation. Inferential analysis was conducted using Spearman’s rho to determine the relationship between Artificial Intelligence utilization and study habits.

Results: Among 325 nursing students, AI utilization was generally positive (M = 3.70, SD = 0.57), with high self-efficacy (M = 3.68, SD = 0.66) and technological readiness (M = 3.90, SD = 0.62), and study habits were moderately strong (M = 2.70, SD = 0.60), highest in using digital tools (M = 3.34, SD = 0.86) and organizing materials (M = 3.21, SD = 0.89), but lowest in maintaining focus (M = 1.80, SD = 1.00). Data were non-normal (Kolmogorov–Smirnov, p < 0.05), and Spearman’s rho showed positive correlations between AI subdomains and study habits, with technological readiness highest (rs = .238, p = .000) and actual AI usage negligible (rs = .046, p = .405), indicating AI supports learning but habits depend more on personal motivation and self-discipline.

Conclusion: The assessment revealed that AI is widely used by nursing students as a complementary tool to enhance efficiency in academic tasks, supported by their positive attitudes, confidence, and readiness to use technology. Despite this, students maintained strong and disciplined study habits, suggesting that self-discipline, motivation, and self-regulation are more influential on academic engagement than AI. Although correlations between AI use and study habits were statistically significant, their strength indicates that AI has only a limited effect on students’ study practices.