International Journal of
Information and Education Technology

Abstract

This research highlights the creation and assessment of an AI-powered system for thesis advisor consultations, aiming to enhance the academic advisory process for graduate students. The system delivers efficient, accessible, customized support in essential areas such as research design, literature review, research tool development, and statistical analysis. Evaluation results revealed that the system achieved a “Very Good” rating across key metrics, including functionality, accuracy, usability, performance, and security, with an overall average score of 4.76. Quantitative assessments of thesis progress among 42 graduate students demonstrated significant improvements, particularly in research tool development and quality assessment, with 88–95% achieving “Good” progress. Qualitative feedback highlighted the system’s strengths in clarifying research objectives, guiding hypothesis formulation, and facilitating data analysis. Furthermore, a strong positive correlation (r = 0.608, p < 0.001) between research knowledge and thesis progress underscores the system’s effectiveness in fostering academic growth. While no significant differences were observed in research knowledge among students with varying experience levels, the system showcased its ability to provide equitable support. These findings highlight the transformative potential of AI in academic advisory processes, offering reliable and accessible consultation services. Future development efforts will aim to enhance the system’s capabilities in statistical analysis to meet advanced research needs better.