AI-Supported STEM Learning
STEM learning and science and engineering practices, including inquiry, modeling, argumentation, and classroom-based research.
PhD Student | Science Education | University of Georgia
Zhaoji Wang
Hi, I am Zhaoji Wang, a Ph.D. student in Science Education at the University of Georgia. Before beginning my doctoral study, I was mentored by Dr. Chen Chen at The University of Hong Kong and Professor Siu-sze Yeung at The Education University of Hong Kong. My current research focuses on AI-enhanced science learning, learning analytics, and educational data science.
Outside the lab, I am a photographer; you may find me and my camera, and sometimes a fishing rod, in the Appalachian Mountains or along the coastline near Savannah.
Academic Profile
My work brings together science education, AI4Education, learning analytics, and technology-supported STEM teaching and learning. I study how AI-enhanced tools can support scientific argumentation, modeling, assessment, and classroom decision making.
Methodologically, I work with educational data mining, natural language processing, automated assessment, and quantitative modeling to better understand learners' progress in STEM contexts.
Main Areas
Research Interests
Learning Analytics
Educational data mining, student modeling, and machine learning for learning progressions.
AI4Education
Text analysis, natural language processing, LLM-assisted assessment, and multi-agent systems for STEM education.
Educational Technology
Technology-supported teaching, AI chatbots, human-computer interaction, and learner behavior in digital environments.
Methods
Methods and Technical Skills
I use quantitative, computational, and AI-enabled methods to study learning processes, classroom interaction, and educational assessment.
NLP and text mining
Educational data mining
Knowledge tracing
HLM and SEM
IRT and CAT
SNA and ENA
LLM-assisted assessment
Multi-agent AI systems