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About

Michael Horn is a researcher whose work sits at the intersection of human-computer interaction, tangible computing, and informal science education. Best known for his investigations into how children learn through physical, hands-on computing experiences, Horn has made significant contributions to understanding the educational value of tangible programming languages — systems that allow learners to interact with code through physical objects rather than screens or keyboards. His most influential work, "Comparing the use of tangible and graphical programming languages for informal science education" (2009), has garnered 280 citations and stands as a landmark study in the field, directly addressing a gap in research by rigorously evaluating whether tangible interfaces genuinely offer learning advantages over conventional graphical approaches. This kind of evidence-based inquiry has been central to his scholarly identity, pushing the field beyond assumption toward empirical grounding. Horn's research spans both formal classrooms and science museum environments, reflecting a commitment to understanding learning across diverse, real-world contexts. His more recent work, such as his 2021 study on parent-child collaborative coding with robots, demonstrates an evolving interest in social dimensions of computational learning — exploring how families make meaning together through symbolic reasoning. His body of work remains a valuable resource for educators, designers, and researchers shaping the future of child-centered computing.