Kees Hoogland

Papers

Total Citations

H-Index

About

Kees Hoogland is a leading researcher at the intersection of mathematics education and human-robot interaction, with a primary focus on how social robots can transform primary mathematics learning. His most influential work, "Design Specifications for a Social Robot Math Tutor" (2023, 20 citations), presents a groundbreaking framework for integrating a robot's social capabilities with mathematical tasks—addressing the critical challenge of ensuring children benefit from social interaction rather than being distracted by it. This paper offers concrete design specifications for creating personal, engaging math tutoring experiences through conversational robots. His earlier foundational study, "Exploring requirements and opportunities for social robots in primary mathematics education" (2022, 5 citations), identified key needs and opportunities in Dutch primary schools, particularly in the wake of COVID-19 disruptions that left students behind and overburdened teachers. Hoogland's work is notable for its practical, design-oriented approach that bridges educational theory with cutting-edge robotics, offering tangible solutions for post-pandemic learning recovery. His research has significant implications for personalized, socially-aware educational technology.