While technological advancement drives much of the excitement around AI in education, the most profound and lasting improvements in learning outcomes will come from understanding how humans learn, think, and grow in relationship with intelligent systems. Technology alone cannot solve educational challenges; understanding the human dimensions of learning is equally vital and often more complex than the technical challenges themselves.
Our interdisciplinary research program integrates cutting-edge insights from cognitive science, educational psychology, neuroscience, and human-computer interaction to ensure that AI-driven educational innovations serve authentic human learning needs:
Human-AI Learning Interaction Studies: We conduct extensive empirical research to understand how students interact with AI-driven educational tools, examining not just learning outcomes but also motivation, self-efficacy, metacognitive development, and long-term learning transfer. Our studies employ both quantitative performance metrics and qualitative analysis of learning experiences to build comprehensive models of human-AI educational collaboration.
Pedagogical Framework Development: We develop evidence-based pedagogical frameworks that integrate AI capabilities with established learning theories—from constructivism and social learning theory to more recent insights from cognitive science about spaced repetition, retrieval practice, and desirable difficulties. These frameworks guide the design of AI systems that enhance rather than replace fundamental pedagogical principles.
Educational Equity and Inclusion Research: We conduct critical research on how AI systems can either perpetuate or help address educational inequalities, examining issues of algorithmic bias, digital divide impacts, and the differential effects of AI-driven education across diverse populations. This includes developing inclusive design principles and accessibility standards for AI educational tools.
Teacher Professional Development and AI Integration: We study how educators can most effectively integrate AI tools into their practice, examining questions of professional identity, pedagogical autonomy, and the evolving skill sets required for teaching in AI-augmented environments. Our research informs professional development programs that help teachers leverage AI while maintaining their essential human role in education.
By grounding our work in human science and maintaining focus on fundamental questions of human development, we strive to ensure that technological innovation serves the deeper goals of education—fostering critical thinking, creativity, empathy, and lifelong learning—rather than merely optimizing narrow performance metrics.