Sai Gattupalli, Ph.D.

Research Domains: AI Education, Learning Technologies, Intelligent Tutoring Systems, Computing and Mathematics Education, Modeling Translation, Teacher Education, and Curriculum Studies

Welcome — Namaste | నమస్తే | नमस्ते

I study how educational technology, including AI-enabled tools, is designed, adapted, and used by real teachers and learners in real classrooms, and whether it actually serves them.

My work sits at the intersection of education, computing, and human-centered systems design. A central thread running through all of it is what I call modeling translation: turning theoretical and computational ideas into learning tools that teachers and students can genuinely use and learn from. Through system prototyping, mixed-methods research, and human-in-the-loop evaluation, I study how adaptive learning technologies perform under real classroom and instructional constraints. This includes intelligent tutoring systems, AI-enabled learning tools, computational literacies curricula, and culturally responsive computing.

Education is my primary domain and enduring commitment. The deeper question driving my research is simple: who does this technology actually work for in the classroom, and who does it leave out?

My group's work at the Advanced Learning Technologies Lab spans a wide range of educational technology for K-12 and higher education. We focus on intelligent tutoring systems for mathematics and computing education, including AI-generated math hints and affective computing that helps these systems recognize and respond to students' motivational and emotional states as they learn. We are also committed to ethical and responsible computing, thinking carefully about transparency, fairness, and accountability as these tools reach real classrooms. Our current projects explore embodied, game-based approaches to teaching and learning computing education, AI-powered pedagogical agents that act as realistic learning companions, and the use of open-weight models for teaching and learning.