Integrating AI Technologies into Academic Writing and Research Workflows in Science and Technology: A Productivity Enhancing Approach
Agaku Raymond Msughter
Department of Physics, Faculty of Science, Rev. Fr. Moses Orshio Adasu University P.M.B. 102119, Makurdi, Nigeria.
Otor Daniel Abi *
Department of Physics, Joseph Sarwuan Tarka University P.M.B. 2373, Makurdi, Benue State, Nigeria.
P. I. Adoga
ICT Directorate, National Open University of Nigeria Headquarters, Abuja, Nigeria.
P. R. Jubu
Department of Industrial Physics, Joseph Sarwuan Tarka University Makurdi (Federal University of Agriculture Makurdi) P.M.B. 2373, Makurdi, Benue State, Nigeria.
D. O. Sunday
Department of Physics, Joseph Sarwuan Tarka University P.M.B. 2373, Makurdi, Benue State, Nigeria.
J. C. Akwaka
Department of Chemistry Education, Joseph Sarwuan Tarka University Makurdi (Federal University of Agriculture Makurdi) P.M.B. 2373, Makurdi, Benue State, Nigeria.
D. Ajaga
Department of Chemistry Education, Joseph Sarwuan Tarka University Makurdi (Federal University of Agriculture Makurdi) P.M.B. 2373, Makurdi, Benue State, Nigeria.
G. U. Onoja
Department of Computer Science, Joseph Sarwuan Tarka University Makurdi (Federal University of Agriculture Makurdi) P.M.B. 2373, Makurdi, Benue State, Nigeria.
E. E. Etunke
Radio Nigeria Harvest FM, Makurdi, Benue State, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Academic writing in science and technology demands structured expression, evidence-based reasoning, and the ability to manage complex ideas and large volumes of information. However, these processes are often time-consuming and challenging. This study examined the integration of Artificial Intelligence (AI) technologies into academic writing and research workflows in science and technology as a productivity-enhancing approach. Specifically, it explored the awareness of AI tools among scholars and their perceived usefulness in improving research output. Guided by the Technology Acceptance Model (TAM), a sample of 364 respondents was selected using the Taro Yamane formula. Data were collected through structured questionnaires and analyzed using descriptive statistics, mean scores, and standard deviations. Findings revealed high awareness and frequent use of AI tools such as ChatGPT, Grammarly, Grammarly Plagiarism Checker, EndNote, Turnitin, Excel Plugins, Python Libraries, and SciBERT/Semantic Scholar. Respondents reported that AI tools significantly improve the quality of academic writing, reduce grammar and referencing errors, accelerate task completion, and allow greater focus on creative and experimental work. The results also indicated that AI tools are generally easy to learn and integrate into existing research workflows. The study concludes that AI has become a valuable ally in enhancing the efficiency, accuracy, and creativity of academic writing and research in science and technology. It recommends targeted training, institutional investment in AI resources, and the establishment of clear ethical guidelines to ensure responsible adoption.
Keywords: Artificial Intelligence (AI), academic writing, research workflows, science and technology, productivity enhancement, Technology Acceptance Model (TAM)