I am Jewoong Moon, Assistant Professor of Instructional Technology in the Department of Educational Leadership, Policy, and Technology Studies at the University of Alabama. My research focuses on game-based learning, immersive learning environments, learning analytics, and AI-augmented simulations for education.
1. What current project or professional work are you most excited about?
I am most excited about a line of work I call glass-box stealth assessment for adaptive learning system design: embedding evidence-centered assessment inside VR and game environments so that learning is measured through authentic actions, while keeping the assessment logic transparent and auditable instead of hidden in a black box. A current example is a VR safety-training simulation that infers trainees' hazard-recognition skills from their in-world behavior and adapts feedback in real time. In parallel, I am building LLM-driven simulations for teacher education, where preservice teachers practice responding to virtual students with social-emotional and behavioral needs and receive analytics-based feedback on their interactions. What excites me is the convergence: generative AI now lets us build rich, responsive practice environments quickly, and learning analytics lets us make what happens inside them visible and defensible as evidence of learning.
2. What motivated you to enter your field, and how has your research or professional focus evolved over time?
I entered the field through a fascination with what game play reveals about how people learn. Games generate rich behavioral traces, and I wanted to understand whether those traces could tell us something trustworthy about thinking, not just engagement. That question led me to doctoral study in instructional systems and learning technologies at Florida State University, where I worked on game-based and virtual-world learning for neurodiverse learners, designing environments where autistic children could practice social skills safely.
My focus has evolved in three phases. I began with game-based and immersive learning experience design, asking how mechanics and narratives support learning. I then moved deeper into learning analytics and educational data mining, developing methods to turn telemetry from games and VR into assessment evidence. Most recently, generative AI has reshaped my agenda: I now design AI-driven simulations, from teacher-training chatbots to VR clients for counselor education, and study how to keep such systems pedagogically grounded and psychometrically honest. Across these shifts, the through line has stayed the same: building playful, immersive environments where learning can be both experienced and measured.
3. How has KAERA contributed to your professional network, scholarship, or sense of community?
KAERA has been my professional venue within the larger AERA community. As a Korean scholar working in the U.S., I have often navigated two academic cultures at once, and KAERA is the space where that dual identity is an asset instead of a complication. My deepest involvement has been with the Mentoring Committee, where I have served for three years, first as a member, then as vice chair last year, and now as chair this year. Supporting graduate students and early-career scholars through this committee has been one of the most rewarding parts of my professional life. It has connected me with mentors and mentees across institutions, sharpened how I advise my own students, and given me a concrete way to pay forward the generosity I received when I was starting out. KAERA turned service into genuine community.
4. What advice would you give to graduate students or early-career scholars in the field?
Build a habit of finishing. Ideas are abundant in graduate school; completed manuscripts are rare. A modest study that is written, revised, and submitted teaches you more than a brilliant project that stays in your head. Second, treat evidence as a discipline: verify your claims, document your pipelines, and make your work reproducible, because your credibility compounds over time. Third, learn your tools deeply. Methodological and technical skills, whether analytics, design, or now AI, are what make you useful to collaborators and independent as a scholar. Finally, find your community early. Mentors will not appear on their own; ask questions, attend the small gatherings, and offer help before you need it. I wish I had known earlier that rejection is the normal texture of this career, not a verdict on your worth. Persistence, more than talent, is what separates those who thrive.
5. Outside of your professional work, tell us some interesting facts about yourself.
Outside work, I enjoy building indie games and simulators as a creative hobby. To unwind, I visit museums to see Impressionist and German Expressionist paintings, two styles I never tire of. I am also an avid pin collector, always hunting for one more piece.