Associate Professor Paul Ginns serves in the Sydney School of Education and Social Work within the Faculty of Arts and Social Sciences at the University of Sydney. He holds a BA (Hons), MPsych, and PhD, with his academic career focused on educational psychology. Ginns' research specializations include cognitive load theory, embodied cognition, motivation and engagement in learning, academic buoyancy and adaptability, Load Reduction Instruction, tracing and pointing gestures to support learning, and the integration of generative AI in education. His work examines how instructional strategies influence student outcomes across high school, university, and museum settings, often employing experimental designs, meta-analyses, longitudinal studies, and cross-cultural comparisons involving Australian, Chinese, and international contexts. Ginns has progressed through roles at the University of Sydney, contributing to teaching in educational psychology and supervising postgraduate students, for which he received the Supervisor of the Year Award in 2019.

Ginns has authored or co-authored 136 publications, accumulating over 7,300 citations. His most influential works include the highly cited 'Meta-analysis of the modality effect' (2005, 875 citations), which synthesized evidence on auditory-visual processing advantages in learning; 'Quality in blended learning: Exploring the relationships between on-line and face-to-face teaching and learning' (2007, 817 citations); and 'Integrating information: A meta-analysis of the spatial contiguity and temporal contiguity effects' (2006, 583 citations). Other key contributions encompass 'E-learning in higher education: some key aspects and their relationship to approaches to study' (2009, 504 citations), 'Phenomenographic pedagogy and a revised approaches to teaching inventory' (2005, 467 citations), and 'Students’ perceptions of teaching quality in higher education: The perspective of currently enrolled students' (2007, 454 citations). Recent publications address practical applications such as 'Rest breaks aid directed attention and learning' (2023), 'Tracing and Pointing Support Multimedia Learning: A Cross-Cultural Replication' (2025), and 'Integrating generative AI and Load Reduction Instruction to individualize and optimize students’ learning' (2025). Ginns has edited special issues on cognitive load theory and his research informs instructional design to reduce cognitive load and enhance retention and transfer in subjects like mathematics, science, and anatomy.

Professional Email: paul.ginns@sydney.edu.au