Celebrating Chip Li's Ph.D. Candidacy

We are thrilled to share another exciting milestone for the VIABLE Lab: Hongming (Chip) Li successfully passed his Ph.D. qualifying examination on March 13, 2026, and advanced to Ph.D. candidacy in Educational Technology at the University of Florida.

Research Direction

Chip's work sits at the intersection of learning analytics, educational data mining, large language models, human-computer interaction, and human-centered AI. The clearest thread running through it is a simple but difficult question: if AI is going to support learning, teaching, or research, how do we make sure its outputs are not only useful, but also interpretable and trustworthy?

That question now runs through several connected lines of work. In his newest research, Chip is examining whether LLM judgments can actually be trusted in educational workflows, including coding tasks where models report confidence but may still be wrong. At the same time, he is studying how AI can support learning more constructively, whether through assessment systems that align more closely with expert judgment or study tools that reduce preparation burden without taking away learner agency.

These newer directions build naturally on the foundation of his earlier work. From instructional design and collaborative learning to AI-assisted writing and learning analytics dashboards, Chip has consistently asked how AI can remain accountable to human goals rather than simply automate decisions. That same logic also explains his interest in AI safety and constraint-based design, including work connected to the VETTING framework, where the challenge is not just making AI capable, but making it educationally appropriate.

Selected Venues and Research Areas

• AIED - Reliability, confidence calibration, and trust in LLM-supported educational coding workflows; AI-augmented sense-making for collaborative problem solving; and generative AI support for productive failure teaching
• ISLS - AI support for self-regulated learning, multimodal assessment of collaboration, modeling collaborative dialogue in mathematics learning, and LLM-based data augmentation for online learning communities
• EDM - Real-time collaborative learning analytics, a critical examination of AI-assisted academic writing, teacher perception analysis in computing education, and explainable recommendation for work-integrated learning
• AAAI - Transparent and collaborative AI-assisted instructional design
• AECT - Human-AI instructional design, AI-supported critical thinking, constrained chatbot use, explainable recommendation, and broader translation of research into usable human-AI learning tools
• JEDM - Data-driven feedback taxonomy development for mathematics learning
• L@S - Automated aesthetic assessment of mathematical story images
• Creativity Research Journal - Rubric-guided multimodal AI assessment aligned with expert judgment in learning games
• AERA and APA Division 10 - Generative AI for productive failure teaching and AI-supported creativity assessment

Systems, Safety, and Service

A defining feature of Chip's work is that he does not treat system-building as separate from scholarship. Across projects such as LOGEN AI, VETTING Chat, ProductiveMath, GM Dashboard, and SmartFlash, he has helped turn research ideas into tools that can actually be used, studied, and improved in real settings. This has made him an important part of the lab's ability to move from concepts to functioning educational technologies.

That same orientation also appears in his interest in AI safety and constraint-based design, especially in work connected to the VETTING framework, where the challenge is not only to make AI capable, but to make it educationally appropriate.

Recognition and Leadership

Chip's work has also been recognized through multiple awards, funding opportunities, and forms of professional trust, including the Emerging Learning Technology Award at AECT, a Best Paper Nominee recognition at AIED, the iRAISE Travel Scholarship at AAAI, the School of Teaching and Learning Travel Award, Doctoral Consortium travel support at EDM, and OpenAI-supported research funding. These recognitions reflect not only strong scholarship, but also the practical relevance of the tools and research directions he is helping shape.

Beyond publications and platform development, Chip has also taken on sustained leadership and service roles. He has contributed to the UF College of Education Research Symposium for three consecutive years, serving as Technology Chair and later Co-Director; he serves as Web Chair for EDM 2026; and he has supported ISLS as a Session Host. Alongside this, he has also contributed through conference and journal reviewing, student mentoring, and other technical and organizational service.

Mentorship and Dissertation Committee

Chip is chaired by Dr. Anthony Botelho. His dissertation committee includes Dr. Avery Closser, Dr. Rui (Tammy) Huang, and Dr. Jinnie Shin from Research, Evaluation, and Methodology (REM).

Looking Ahead

Advancing to candidacy marks the beginning of the dissertation phase, where Chip will have more room to deepen this agenda around explainable, reliable, and practically deployable AI for education. His recent work suggests a strong direction ahead: not just building AI systems for learning, but clarifying when they should be trusted, how they should be constrained, and how they can support human judgment without displacing it.

We are proud to celebrate this achievement and grateful for all that Chip contributes to the lab. Congratulations, Chip!

To learn more about Chip's research and publications, visit his team profile page.