Artificial Intelligence (AI) in Academic Writing
Discover how artificial intelligence (AI) is revolutionizing academic writing and research. Explore the benefits of using AI tools for enhancing your writing process and improving research outcomes.
QUANTITATIVE RESEARCH
Realyn Manalo
5/16/20253 min read
The rise of generative AI tools, such as ChatGPT, has redefined how academic writing is conceptualized, produced, and evaluated. These technologies offer students new ways to draft, edit, and organize written work—blurring the line between assistance and authorship. As AI becomes more embedded in educational environments, institutions face critical questions about integrity, learning development, and the evolving role of educators. While students increasingly rely on AI for efficiency, concerns persist around overreliance, originality, and diminished critical thinking. The challenge now lies in understanding not just how students use AI tools, but how their sustained integration into curricula affects long-term academic growth, ethical reasoning, and the future of writing instruction.
Who Can Use These Topics
This research is ideal for students and professionals pursuing the following courses or strands:
College Programs:
BA/BS in English Language Studies or Creative Writing
BA/BS in Communication
BS in Information Technology
BS in Psychology
BSEd/BEEd (Major in English or Educational Technology)
Senior High School Strands:
Humanities and Social Sciences (HUMSS)
Science, Technology, Engineering, and Mathematics (STEM)
Accountancy, Business, and Management (ABM)
General Academic Strand (GAS)
Why This Topic Needs Research
AI in academic writing is a fast-evolving field, but multiple research gaps remain:
Limited analysis of long-term academic impact: While students view AI positively, research has yet to evaluate how sustained AI use across disciplines influences academic integrity and independent writing (Kim et al., 2024).
Insufficient scope of intervention studies: Active learning methods reduce AI misuse, but their effectiveness across educational levels and subjects needs further testing (van Niekerk et al., 2025).
Neglect of learner diversity and cultural context: AI literacy shapes writing quality, yet factors like discipline, background, and prior tech exposure are rarely considered in performance analyses (Kim et al., 2025).
Lack of institutional policy research: Ethical frameworks exist in theory, but how journal policies and academic protocols affect responsible AI use in practice remains understudied (Cohen & Moher, 2025).
Missing longitudinal data on writing development: Tools improve ease of use and performance, but their influence on critical thinking, ethical reflection, and writing autonomy over time is unknown (Bantoto et al., 2024).
Underexplored faculty development approaches: Few studies examine how teacher training can help guide ethical and creative AI use while maintaining writing standards (Fontanilla et al., 2023).
Socioeconomic and institutional differences overlooked: Students’ access, use, and understanding of AI tools vary significantly by income, discipline, and school policies, yet these factors are rarely analyzed (Clorion et al., 2024).
Feasibility & Challenges by Target Group
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References
Bantoto, F. M. O., Rillo, R., Abequibel, B., Mangila, B. B., & Alieto, E. O. (2024, May). Is AI an Effective “Learning Tool” in Academic Writing? Investigating the Perceptions of Third-Year University Students on the Use of Artificial Intelligence in Classroom Instruction. In International Conference on Digital Technologies and Applications (pp. 72-81). Cham: Springer Nature Switzerland.
Clorion, F. D. D., Alieto, E. O., Fuentes, J. O., Suicano, D. J. B., Natividad, E. R., Miñoza, M. V., ... & Vallejo, R. G. (2024). Artificial Intelligence in Academic Writing in Higher Education in a Country of Emerging Economy: An Analysis of Knowledge, Perceived Influence, Extent of Use and Perception. In General Aspects of Applying Generative AI in Higher Education: Opportunities and Challenges (pp. 301-326). Cham: Springer Nature Switzerland.
Cohen, J. F., & Moher, D. (2025). Generative artificial intelligence and academic writing: friend or foe?. Journal of Clinical Epidemiology, 179, 111646.
Fontanilla, J. B., Bautista, K. H., Lactao Jr, M., Villacorte, M. A., & Santos, R. (2023). Educators' Perspectives on the Impact of Artificial Intelligence on Writing Competence. International Journal of Multidisciplinary Research and Publications, 6(6), 29-34.
Kim, J., Yu, S., Detrick, R., & Li, N. (2025). Exploring students’ perspectives on generative AI-assisted academic writing. Education and Information Technologies, 30(1), 1265-1300.
Kim, J., Yu, S., Lee, S. S., & Detrick, R. (2025). Students’ prompt patterns and its effects in AI-assisted academic writing: Focusing on students’ level of AI literacy. Journal of Research on Technology in Education, 1-18.
van Niekerk, J., Delport, P. M., & Sutherland, I. (2025). Addressing the use of generative AI in academic writing. Computers and Education: Artificial Intelligence, 8, 100342.