Natalie Lao

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About

Natalie Lao is a leading researcher at the intersection of artificial intelligence education and human-computer interaction, with a primary focus on making AI accessible to young learners. Her most influential work, "Behavioral-pattern exploration and development of an instructional tool for young children to learn AI" (48 citations), represents a pioneering contribution to K-12 AI literacy. In this study, Lao developed a novel instructional tool designed specifically for young students and employed sophisticated learning analytics to map the sequential behavioral patterns children exhibit while engaging with AI concepts. This research is notable not only for its innovative pedagogical approach but also for its empirical rigor in understanding how children naturally construct AI knowledge through hands-on interaction. Lao's work addresses a critical gap in AI education: the need for developmentally appropriate tools that scaffold complex computational thinking for elementary-age students. By systematically analyzing learning behaviors, she provides educators and designers with evidence-based insights into effective AI teaching strategies. Her research has significant implications for curriculum design, educational technology development, and the broader goal of democratizing AI literacy from an early age, positioning her as a key voice in shaping how the next generation learns about and interacts with intelligent systems.