AI Integration in Literature Review Writing Among Fyp Students: Enhancing Efficiency While Maintaining Academic Integrity

This qualitative study investigates how undergraduate students integrate artificial intelligence (AI) tools into their Final Year Project (FYP) literature review writing processes, addressing growing concerns about academic integrity and learning effectiveness in the age of AI. Through semi- structured interviews with students from Applied Linguistics and English Language programs, we conducted thematic analysis to examine AI integration practices, verification strategies, and ethical boundaries. Five major themes emerged: AI as organizational and discovery tool, cautious integration with human oversight, ethical boundaries and academic integrity, proportion and balance guidelines, and skills development concerns. Students demonstrated sophisticated understanding of AI limitations, employing rigorous verification strategies while using tools like Elicit, Claude, and ChatGPT primarily for structural organization, source discovery, and preliminary content support rather than direct writing. Participants established clear ethical guidelines, recommending 10-30% AI assistance with mandatory human synthesis and critical analysis. The study reveals that students recognize risks to research skill development from over- dependence while appreciating efficiency gains in organizational tasks. We propose a four-phase Human-AI Collaborative Model that balances technological efficiency with academic integrity, emphasizing transparency, verification, and human-controlled critical thinking. These findings inform best practices for ethical AI integration in academic writing and suggest that current students are developing healthy frameworks for responsible AI use that preserve educational value while enhancing research efficiency.