Artificial Intelligence & Education Research
This research project explores how artificial intelligence may change teaching evaluation, higher education assessment, and institutional decision-making. It examines algorithmic bias, scoring reliability, multimodal AI evaluation models, and the risks of using AI to judge instructional performance.
AI as an Evaluator:
Algorithmic Bias in Teaching Assessment
AMCIS 2026 Research Presentation
Co-authored research accepted for presentation at AMCIS 2026 examining AI-assisted teaching assessment, algorithmic bias, rubric reliability, and decision-making in higher education. This project demonstrates research communication, evidence evaluation, and the ability to explain technical issues for academic and professional audiences.
AI as an Evaluator:
Algorithmic Bias in Teaching Assessment
Presented original research on AI-assisted evaluation systems, algorithmic bias, scoring reliability, and decision-making implications in higher education assessment.
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