Generative Artificial Intelligence Techniques in Improving the Quality of Higher Education and Scientific Research: A Critical Analytical Study with a Field-Based Applied Model (Al-Farooq Journal of Sciences, 2026)
This study moves beyond conventional descriptive approaches to critically examine the controversial dimensions of employing generative artificial intelligence technologies in academic contexts. Adopting a mixed-methods framework integrating critical literature analysis with a field-administered questionnaire targeting faculty members across three Libyan universities, alongside an experimental implementation employing large language models in a graduate research course.The study finds that the core challenge lies in the required cultural and institutional transformation. Field results reveal statistically significant disparities (p < 0.05) in academic attitudes across generations and disciplines. Critical analysis confirms methodological contradictions in measuring effectiveness, necessitating a shift to executive mechanisms with quantifiable KPIs while considering economic feasibility and available infrastructure in Libya.The study highlights a critical risk: originality index declined from 71% to 42% in the experimental group (Cohen's d = 3.31, very large effect), posing a genuine threat to academic creativity. Regarding critical thinking, the study lacked sufficient statistical power (Power = 8%) to detect any potential effect; therefore, no conclusive evidence regarding its improvement or decline can be drawn. This underscores the need for future replication with larger samples. The study concludes that the optimal solution lies in restructuring assessment practices to focus on the "journey of thinking" rather than the "final product," presenting a three-phase implementation plan with low-cost alternatives suitable for Libya's limited infrastructure.
Keywords: Generative Artificial Intelligence, Critical Analysis, Large Language Models, Mixed Methods, Field Study, Key Performance Indicators, Economic Feasibility, Cohen's d Effect Size, Libyan Context, Open-Source Models