Research
Research Interests
With over seven years immersed in educational research, I have cultivated an abiding fascination with the intersection of education and technology. Even as technology becomes deeply embedded in modern society, its potential educational applications remain largely unexplored. My research interests focus on using technology to improve teaching methods and learning outcomes. Based on my current research, I am primarily interested in the following topics and look forward to any collaboration:
Learning Analytics and Educational Data Mining
Machine Learning
Natural Language Processing (NLP) and Large Language Models (LLMs)
Explainable and Human-centered Artificial Intelligence (XAI / HAI)
Human-computer Interaction
Equity and Fairness in Education
Instructional Design / Educational Gamification and Media / Digital Learning Ecology and Online Learning
I aim to conduct pioneering studies that help shape the future of AI-enabled education, improve digital literacy and skills development, and expand access to personalized, high-quality learning experiences. Through rigorous research and imaginative thinking, I hope to open new frontiers in education that cultivate empowered, knowledgeable learners ready to make their mark. I am excited to connect with fellow scholars and practitioners who share my passion for education, technology, and entrepreneurship. If you are interested in discussing any of these topics, please do not hesitate to contact me. I have provided multiple means of contact below and would be most appreciative of your kind consideration.
FUNDING, FELLOWSHIPS AND OTHER RESEARCH AWARDS
OpenAI Researcher Access Program
April 2024 - April 2025
API Subsidy: $5,000 (OpenAI # 0000001997)
Investigating the use of large language models (LLMs) in the educational context to address challenges of fairness and representativeness, focusing on developing explainable AI (XAI) for personalized student feedback.
Aiming to enhance AI-based feedback systems by analyzing differences between human-written and AI-generated content and creating a taxonomy of effective feedback types.
Creating AI tools that offer safe, reliable, and educationally sound feedback, fostering improved learning outcomes for students.