An Assessment of the Familiarity of Undergraduates with the Application of Artificial Intelligence Programs in Project Writing and Development in Polytechnics in Nigeria

Artificial Intelligence (AI) programs have progressively permeated the academic ecosystem, altering the manner in which students conceive, research, write, and defend project reports. This study assessed the familiarity of undergraduates with the application of artificial intelligence programs in project writing and development in polytechnics in Nigeria. The study was anchored on the Technology Acceptance Model (Davis, 1989) and the Diffusion of Innovation Theory (Rogers, 2003), both of which provided a theoretical lens for interpreting how perceived usefulness, perceived ease of use, and innovation attributes shape students' adoption of AI-driven tools such as ChatGPT, Grammarly, QuillBot, the Turnitin AI detector, and Google Gemini. A descriptive survey design was adopted, and a multi-stage random sampling technique was used to select six federal and state polytechnics spanning the six geopolitical zones of Nigeria, namely Federal Polytechnic Nasarawa, Yaba College of Technology, Kaduna Polytechnic, Akanu Ibiam Federal Polytechnic Unwana, Rivers State Polytechnic, and Federal Polytechnic Bauchi. A structured questionnaire was administered to 300 final-year and penultimate-year Higher National Diploma (HND) and National Diploma (ND) students, out of which 268 copies (89.3%) were validly completed and returned. Data were analysed using frequency counts, simple percentages, mean scores, and chi-square statistics at the 0.05 level of significance. Findings revealed that undergraduates in Nigerian polytechnics possess a moderately high level of familiarity with generic AI programs such as ChatGPT (86%) and Grammarly (71%), but comparatively low familiarity with more specialised tools such as Jasper/Copy.ai (11%) and Perplexity AI (22%). AI programs were most frequently applied at the proofreading, grammar checking, and literature-search stages of project writing, while application at the data-analysis stage remained the least explored. Unstable electricity and internet connectivity, inadequate digital literacy training, the cost of premium subscriptions, and the fear of being accused of academic malpractice emerged as the most prominent challenges limiting deeper engagement with these tools. The chi-square analysis indicated a statistically significant relationship between students' level of familiarity and their institutional location (urban versus semi-urban campuses). The study concluded that although AI literacy is gradually taking root among polytechnic undergraduates, its application remains uneven, superficial in places, and insufficiently guided by institutional policy. It was recommended, among other things, that polytechnic management should integrate AI literacy modules into general studies curricula, provide subsidised access to premium AI tools, and develop clear ethical guidelines that distinguish permissible assistive use of AI from outright academic misconduct.