Ximeng Chen

Papers

Total Citations

H-Index

About

Ximeng Chen is a leading researcher at the intersection of educational technology and human-robot interaction, with a primary focus on how students perceive and adopt AI-driven tools in learning environments. Their most-cited work, "Impact of perceived ease of use and perceived usefulness of humanoid robots on students' intention to use" (2025, 18 citations), extends the Technology Acceptance Model (TAM) to explore the critical factors shaping student engagement with humanoid robots. By demonstrating that perceived ease of use and usefulness are pivotal drivers of adoption, Chen’s research provides actionable insights for designing more intuitive and effective educational robots. This contribution is particularly timely given the rapid integration of AI in classrooms, and it has already influenced subsequent studies on learner-technology dynamics. Chen’s work stands out for its practical implications, bridging theoretical frameworks with real-world educational challenges. As a rising voice in the field, their findings help educators and developers create AI tools that are not only advanced but genuinely accepted by students, paving the way for more seamless human-robot collaboration in education.