Louis Alfieri

University of Pittsburgh

Papers

1

Total Citations

37

H-Index

1

About

Louis Alfieri’s research lies at the intersection of educational psychology, human-robot interaction, and STEM learning, with a particular focus on how technology can foster engagement and deep conceptual understanding in mathematics. His most cited work, “Case studies of a robot-based game to shape interests and hone proportional reasoning skills” (2015, 37 citations), exemplifies his innovative approach to “robot-math”—a pedagogical framework that embeds mathematics instruction within engineering and robotics challenges. Alfieri’s key contribution is demonstrating how hands-on, robot-centered activities can first spark student interest in proportional reasoning and then support the transfer of those skills to new contexts. By designing interventions that make abstract math concepts tangible and goal-directed, he has advanced understanding of how to bridge the gap between playful, interest-driven learning and rigorous academic skill development. His work has influenced both curriculum design and the broader conversation about the role of embodied, interactive technologies in education. Alfieri’s research continues to shape how educators and technologists think about motivating learners through authentic, problem-solving experiences that connect computation, design, and mathematics.

Research Focus

Key Achievements

1
H-Index
1
Papers
37
Total Citations
37
Avg Citations/Paper
🏆 Most Cited Paper
Case studies of a robot-based game to shape interests and hone proportional reasoning skills
37 citations · 2015
📈 Most Prolific Year: 2015 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Pittsburgh

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago