TECHNOLOGICAL SELF-EFFICACY AND ONLINE DATABASE ACCESS AS PREDICTORS OF AI USABILITY FOR RESEARCH AMONG SOCIAL SCIENCES LECTURERS IN OYO STATE COLLEGES OF EDUCATION

The integration of artificial intelligence (AI) in academic research has transformed knowledge production, yet its adoption among social sciences lecturers in colleges of education remains underexplored. While existing studies on AI usability in academia predominantly focus on science and technology disciplines, limited attention has been given to social sciences educators, who play a crucial role in shaping pedagogical and policy frameworks. Moreover, prior research has examined technological self-efficacy and access to online research databases as independent factors influencing digital engagement, but few studies have investigated their combined impact on AI usability for research. This study bridges these gaps by analysing how technological self-efficacy and access to online research databases jointly predict AI usability among social sciences lecturers in colleges of education in Oyo State, Nigeria. Using a correlational research design, data were collected from 110 lecturers through a structured questionnaire. Pearson Product Moment Correlation and multiple regression analyses revealed that both technological self-efficacy and access to online research databases significantly influence AI usability, jointly explaining 65% of its variance. The study provides empirical evidence that institutional access to digital resources moderates the effect of individual technological self-efficacy on AI adoption in research. Unlike previous studies that primarily focused on digital literacy training, this study highlights the necessity of addressing infrastructural constraints alongside individual competency development. The findings offer valuable insights for policymakers and institutional administrators seeking to enhance AI adoption in research, ensuring equitable access to digital resources, and fostering a technologically competent academic workforce.