The Modern Developer’s Dilemma: The Impacts of Generative AI to Problem Solving Skills and Critical Thinking of 3rd year IT Students at Quezon City University
by Cris Jane Dejapa, Edrian James Montecalvo, Emmanuel Frias, Harold R. Lucero, Jacob Navarro, John Alfred Jauod
Published: June 13, 2026 • DOI: 10.51244/IJRSI.2026.1305000264
Abstract
The widespread adoption of Generative Artificial Intelligence (AI) in programming education has significantly transformed the way students approach academic tasks, coding activities, and technical problem-solving. This study investigated the impacts of Generative AI utilization on the problem-solving skills and critical thinking skills of 3rd year Information Technology students at Quezon City University. The primary objective of the study was to determine the level of Generative AI utilization among students and examine its significant relationship and predictive effect on students’ cognitive and technical skills. A quantitative descriptive-correlational research design was employed using a validated digital survey questionnaire distributed through Google Forms to 273 respondents selected through stratified random sampling. The collected data were analyzed using weighted mean, standard deviation, Pearson Product–Moment Correlation, Independent Samples t-test, regression analysis, and Cronbach’s alpha reliability testing. The findings revealed that 69.6% of the respondents were highly utilizing Generative AI, using AI tools often (37%) or very often (32.6%) on a weekly basis. Results further showed that respondents demonstrated a high level of Generative AI utilization across academic tasks, code generation, debugging, and technological reliance, with students frequently relying on AI tools for programming assistance, error explanation, and task completion. Respondents also exhibited positive levels of problem-solving and critical thinking skills, particularly in evaluating AI-generated outputs, understanding programming logic, and resolving coding errors. Reliability analysis showed excellent internal consistency for the overall instrument (α = .973), while the Critical Thinking Skills scale achieved good reliability after reverse coding (α = .890). Pearson correlation analysis revealed a very strong positive relationship between Generative AI utilization and problem-solving skills (r = .896, p < .001) and a moderate positive relationship between AI utilization and critical thinking skills (r = .407, p < .001). Furthermore, Independent Samples t-test results showed a statistically significant difference between students with high and low AI utilization in terms of problem-solving skills (t = 10.85, p < .001). Regression analysis further confirmed that Generative AI utilization significantly predicts students’ problem-solving skills (R² = .803, β = .896, p < .001). Overall, the study concludes that Generative AI can serve as an effective educational support tool that enhances programming efficiency, technical learning, and cognitive development when used responsibly and balanced with independent reasoning and critical evaluation.