A Proposed Framework for the Governance of Generative Artificial Intelligence (GenAI) Tools in Scientific Research Writing at Yemeni Universities

Abstract

This study aimed to develop a proposed framework for governing the use of Generative Artificial Intelligence (GenAI) tools in scientific research writing within Yemeni universities. A descriptive-survey methodology was employed, utilizing a 30-item questionnaire administered to a purposive sample of (180) academic leaders and faculty members, alongside (11) experts to validate the proposed framework. Descriptive and inferential statistical methods (T-test and One-Way ANOVA) were used for hypothesis testing. Findings revealed that the current reality of governance practices was "Weak" (M=2.60), while opportunities were rated "High" (M=3.95), and challenges recorded the highest rating (M=4.06). Regarding hypotheses: The results showed no statistically significant differences attributable to the job position variable across all dimensions. However, significant differences were found at (0.05) attributable to the university variable in the "Reality" and "Challenges" dimensions, while no significant differences were observed in the "Opportunities" dimension. The research concluded with a comprehensive operational governance framework featuring an executive matrix and flexible Key Performance Indicators (KPIs) that account for technical disparities among Yemeni universities while safeguarding academic integrity.​