(untitled) (Comprehensive Journal of Science, 2025)
: This research paper examines the effects of curriculum quality, faculty expertise, and infrastructure quality on academic results among 278 non-graduated IT students at the Higher Institute of Engineering and Technology and the Higher Institute of Science and Technology in Zliten, Libya. This represents a sample drawn from a population of 1000 (Ministry of Technical Education). The cross-sectional quantitative study relied on a 5-point Likert-scale questionnaire to test the hypothesis that these specified factors are positively predictive. Descriptive statistics indicated that perceptions of curriculum quality and faculty expertise were moderate to high, whereas perceptions of infrastructure quality were neutral. Multiple linear regression revealed a significant predictability of academic outcomes (R² = 0.382, p < 0.001), with faculty expertise as the strongest predictor. The sample, which consists of mostly young people, is mostly male, and reflects a local trend. It is based on the Input-Process-Output model and Social Learning Theory , which help fill knowledge gaps in Libyan IT education research. The cross-sectional design and potential bias in responses are key limitations. Recommendations include training faculty, upgrading infrastructure, and revising curriculum to support sustainable development goals.