Pingping Chen

Papers

Total Citations

3,408

H-Index

About

Pingping Chen is a leading researcher at the intersection of artificial intelligence and education, whose work has fundamentally shaped how AI is understood and applied in learning environments. Chen’s primary research areas include AI-driven educational administration, intelligent instructional systems, and the ethical implications of automation in pedagogy. Their landmark 2020 review, “Artificial Intelligence in Education: A Review,” has garnered over 3,400 citations, establishing a foundational framework for assessing AI’s impact across administrative, instructional, and student-support domains. This seminal work systematically categorized AI applications, from adaptive learning platforms to predictive analytics for student success, and critically examined their effects on equity and teacher roles. Chen’s contributions have provided educators and policymakers with a clear narrative for evaluating both the promises and pitfalls of AI in schools. Beyond this review, Chen has advanced research on personalized learning algorithms and data-driven curriculum design, influencing international educational technology standards. Their work is widely cited in policy reports and academic curricula, making Chen a pivotal voice in the ongoing dialogue about technology’s role in shaping the future of education.