REGAL Lab
Where AI meets enactive play for transformative learning
Collaborate With Us
We’re always open to collaboration opportunities with researchers, organizations, and communities.
If you’re interested in working with us, please don’t hesitate to get in touch. You can reach us at: fke@umd.edu
Digital Game-Based Learning
Our research of digital game-based learning focuses on using an integrative approach to design and examine scalable game and participatory simulation based learning systems that comprise learning-oriented game mechanics, design-based pedagogy, data-driven knowledge tracing, and adaptive learner support.
- E-Rebuild - Mathematical Thinking and Learning via Architectural Design and Modeling (Ke as PI, Funded by National Science Foundation, Grant #1318784; Grant #1720533)
- Virtual-Reality-Based Social and Cognitive Skills Training for Children with High Functioning Autism (Ke as PI, Funded by Spencer Foundation, Grant #201400178; National Science Foundation, Grant #1837917)
- Game-based Assessment and Support of STEM-related Competencies and Interest (Ke as Co-PI, Funded by National Science Foundation, Grant #1628937)
AI-Infused Enactive Learning
We design and study inclusive and immersive e-learning environments that promote engaging and effective learning interactions for a diversified learner population. The project of MILE (“Mixed-Reality-Integrated Learning Environment”) (Ke as PI, Funded by National Science Foundation, Grant #1632965; Grant #2110777) aims to study the design model and effects of an AI-infused, virtual world-based training platform to provide responsive teaching practice to preservice teachers and STEM graduate teaching assistants.
Integrating 3D virtual reality, LLM-driven virtual human, and body sensory technology, this training platform for teaching enables student instructors to practice, observe, and reflect on teaching in a variety of instructional settings, and provides them with a deep understanding of learning and teaching strategies through active experimentation and problem solving.
This project builds on an earlier project of Web-based teaching and learning: Across culture and age (Ke as PI, Funded by Spencer Foundation, Grant #200800124) that utilizes qualitative and quantitative techniques to explore the impact on learning and success of online pedagogies and contexts for students living in rural and urban areas.
Building upon the MILE platform, Evelyn project extends this work into a real-time 3D classroom simulation for preservice teacher training. Preservice teachers navigate an immersive virtual classroom as embodied avatars, engaging with LLM-driven virtual student agents that generate dynamic, context-sensitive dialogue in response to teacher input.
At the core of this iteration is a formal cognitive-affective state dependency model, a bidirectional, weighted, directed graph of constructs including arousal, sense of mastery, self-efficacy, and metacognitive awareness, that governs how each virtual student’s cognitive and emotional states evolve across the interaction.
The platform supports administrator oversight and a structured lesson-and-task system, creating a scalable training environment where preservice teachers can practice responsive teaching and directly observe the downstream effects of their instructional decisions on student state.
Principal Investigator
Fengfeng Ke
Dr. Fengfeng Ke is Clark Leadership Chair Professor in the College of Education at University of Maryland, College Park. Her research focuses on the design and study of technology-driven personalized and enactive learning systems, with an emphasis on mathematics, science, and neurodiversity education. She is particularly interested in exploring the dynamics of human-AI collaboration in the development and implementation of innovative learning systems that prepare future professionals. Her work has received funding from the National Science Foundation, the Spencer Foundation, the Department of Education, and the MacArthur Foundation.
Current Team
Rosalyn Shin
Rosalyn is a first year PhD student in Technology, Learning, and Leadership (TLL) program at University of Maryland, College Park. Her main research interest is on how AI should be used to enhance personalized learning experiences and improve educational outcomes. She works on developing AI-integrated learning and teaching technology that provides equity-oriented STEM education for students of different backgrounds and abilities.
Xiaoxue Zhou
Xiaoxue Zhou is a doctoral candidate in the Technology, Learning, and Leadership (TLL) program at the University of Maryland, College Park. Her research focuses on the technology-enhanced learning environments design, leveraging data mining of collaborative learning behaviors and applying artificial intelligence to support personalized knowledge acquisition. Her broader interests include learning technology governance, AI-driven personalization, and immersive simulations as tools for human-AI–augmented learning.
Nuodi Zhang
Nuodi is a PhD candidate in Instructional Systems and Learning Technologies at Florida State University. Her research investigates the design and use of educational technologies, including artificial intelligence, games, and simulations, to foster accessible, responsive, and adaptive learning experiences. With an emphasis on ecological and process-oriented perspectives, her work seeks to advance understanding of how teachers and diverse learners engage in STEM education.
Chaewon Kim
Chaewon is a PhD candidate in Instructional Systems and Learning Technologies at Florida State University. Her research investigates the design, development, and evaluation of learning experiences at the intersection of emerging technologies and human well-being. Her work includes implementing educational escape rooms for nursing education, developing a digital game for promoting healthy eating habits among young adults, and leveraging artificial intelligence and virtual reality to support individuals with neurodiversity in rural areas.
Lab Alumni
- Alex Barrett Instructional designer and educational technology researcher @ Florida State University
- ChihPu Dai Assistant Professor @ Texas A&M University
- Luke West Post-Doc Associate @ University of Tübingen
- Jewoong Moon Assistant Professor @ University of Alabama
- Yanjun Pan Postdoctoral Fellow @ Southern Methodist University
- Zhaihuan Dai Learning Designer @ University of South Florida
- Xinhao Xu Associate Professor @ University of Missouri
- Sungwoong Lee Associate Professor @ University of West Georgia
Projects
Project A
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Project B
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Project C
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