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Assessment of Artificial Intelligence in Students' Research

Edelresa S Juachon Honorata Yaneza Arthur Cabradilla Azael May Jomadiao Bonipart Salinas
Oct 2026 · JPAIR Institutional Research · 0 citations

TL;DR

This study examines the growing influence of artificial intelligence (AI) tools on student research in higher education, focusing on both their opportunities and challenges, and recommends comprehensive institutional guidelines, targeted training programs, and ethical frameworks to ensure responsible integration of AI.

Abstract

This study examines the growing influence of artificial intelligence (AI) tools on student research in higher education, focusing on both their opportunities and challenges. AI-powered writing assistants, literature review platforms, citation generators, and data analysis tools are increasingly integrated into academic workflows. Findings show that these tools enhance efficiency and quality by automating repetitive tasks such as grammar checking, citation management, and data organization. Students reported positive impacts, with weighted mean scores indicating agreement that AI improves clarity in writing (3.81), supports data analysis (3.71), and strengthens overall research quality (3.85). These opportunities allow learners to devote more time to higher-order skills such as critical analysis, argumentation, and creative idea generation. However, the study also highlights significant challenges. Students expressed concerns about limited training (3.65), difficulties in trusting AI-generated results (3.68), and the need for greater institutional support (3.70). Neutral responses regarding access barriers (3.28) and effective tool usage (2.97) suggest uneven readiness across the academic community. Ethical issues such as academic integrity, over-reliance on technology, and risks of unintentional plagiarism further complicate AI’s role in research. The finding shows the underscore of the dual nature of AI in higher education: it offers powerful opportunities to enhance research productivity and learning outcomes, yet it also presents risks that must be carefully managed. The study concludes by recommending comprehensive institutional guidelines, targeted training programs, and ethical frameworks to ensure responsible integration of AI. 

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