Integrating Generative AI in Contemporary Research Writing: Exploring Postgraduates’ Knowledge and Willingness to Use GenAI in the Upper East Region of Ghana

Aim: In the 21st century era where academic research boundaries are increasingly blurred by technological innovations, it is critical to understand postgraduate students' willingness to embrace Generative AI as a research ally to reshape their scholarly work and lift their academic writing experience to newer heights. This study assessed postgraduate students' knowledge and willingness to use Generative AI (GenAI) as a research tool. Methods: This study was quantitative and a cross-sectional survey research design was employed to collect primary data from a sample of 238 selected from an accessible population of 588. The sample members were considered using a convenient sampling method. Data were collected through structured closed-ended questionnaire instruments which were self-designed and piloted. The questionnaires' Cronbach's reliability coefficient was 0. 913: This value reflects a good internal consistency, as well as serves to show the robustness of the instrument to measure the objectives of this study. The study used a period of 3 weeks to collect, clean, and analyze the study data using descriptive statistics and simple linear regression analysis (SPSS 20.0). Results: The study showed that postgraduates have a moderate to high level of knowledge (M 3.189 - 3.706) and willingness to use GenAI (M 2.966 - 3.349). A simple linear regression analysis showed that knowledge level significantly predicted willingness to use Generative AI for research purposes, (r² =. 023, B = 0.12, p = 0.021). Recommendation: Educational institutions should implement targeted training programs on GenAI tools to enhance postgraduate students’ competency and confidence in using these tools for research.