Michael S. Horn

Michael S. Horn is a Professor in the Department of Computer Science and the Learning Sciences at Northwestern University's School of Education and Social Policy, with additional affiliation at Tufts University's Computer Science department. His interdisciplinary work bridges Human-Computer Interaction, Learning Sciences, and Educational Technology, focusing on creating innovative learning experiences across formal classrooms, museums, and informal settings.

His research encompasses:

• Design of tangible and embodied learning interfaces
• Computational thinking and programming education
• Museum and informal learning environments
• Integration of music and coding in educational contexts
• Application of artificial intelligence in educational settings
• Children's understanding of complex scientific concepts

Horn's recent work demonstrates a significant shift toward exploring the intersection of artificial intelligence and education, particularly how Large Language Models can support learning processes and research methodologies. His publications reveal consistent attention to making abstract computational concepts accessible through concrete, embodied interactions that connect learners with meaningful content.

His notable scientific contributions include:

• Development of the NetLogo programming environment for agent-based modeling in education
• Creation of museum exhibits like DeepTree and FloTree for visualizing evolutionary concepts
• Innovation in music+code learning environments such as TunePad
• Research on children's understanding of electricity through augmented circuit exhibits
• Pioneering work on room-scale augmented reality for computational modeling

Horn has mentored numerous graduate students who have become productive researchers in learning sciences and educational technology. His collaborative network is extensive, with particularly strong ties to Uri Wilensky (31 joint publications), Chia Shen, and other leaders in the field. His work consistently demonstrates how well-designed technological interventions can transform how learners engage with complex concepts across multiple domains.