EFFECT OF ARTIFICIAL INTELLIGENCE TOOLS ON LITERATURE REVIEW EFFECTIVENESS AMONG MASTER'S STUDENTS AT NDEJJE UNIVERSITY

This review explores how artificial intelligence (AI) tools may affect the way Master's students at Ndejje University conduct literature reviews. It considers four aspects of an effective review: finding a sufficiently broad range of relevant studies, critically comparing and combining their findings, completing review tasks efficiently, and ensuring that sources and interpretations are accurate and relevant. The discussion is guided by the Technology Acceptance Model (TAM) and Task–Technology Fit (TTF), which help explain why students choose to use AI and whether a particular tool is suitable for the task at hand. The tools considered include AI-assisted academic search platforms, conversational AI systems, and writing-support applications. Existing literature points to possible benefits, such as helping students discover publications, organise information, and prepare preliminary summaries. At the same time, AI outputs may contain errors, omit important studies, present unreliable references, or encourage students to rely too heavily on automated answers. For this reason, the review emphasises checking AIgenerated information against original publications and retaining independent scholarly judgement. The manuscript is currently a developed draft, not a completed systematic review: database searches, screening, formal quality appraisal, and final PRISMA reporting still need to be completed. Until those steps are finished, it is not possible to draw firm conclusions about the extent to which AI tools affect literature review effectiveness among Master's students at Ndejje University.