Pei-Ying Chiang

National Taipei University of Technology

Papers

Total Citations

H-Index

About

Pei-Ying Chiang is a leading researcher at the intersection of artificial intelligence, educational technology, and human-computer interaction. Her work focuses on harnessing anticipatory computing and emotional big data to create adaptive learning environments that enhance student motivation and sustainable learning efficiency. Chiang’s most cited paper, “ARCS-Assisted Teaching Robots Based on Anticipatory Computing and Emotional Big Data for Improving Sustainable Learning Efficiency and Motivation” (2020, 56 citations), demonstrates her pioneering approach to integrating AI-driven teaching robots with the ARCS (Attention, Relevance, Confidence, Satisfaction) motivational model. This research shows how learning analytics can predict student needs and personalize instruction, offering a transformative framework for next-generation classrooms. By combining emotional data analysis with robotic teaching assistants, Chiang addresses critical challenges in maintaining learner engagement over time. Her contributions are particularly significant for developing countries seeking scalable, AI-enhanced educational solutions. With growing recognition in the fields of smart pedagogy and affective computing, Chiang continues to shape how technology can humanize and optimize the learning experience for diverse student populations.