Fang Zhao

Fang Zhao serves as Junior Research Group Leader of the Multimedia group at FernUniversität Hagen's Center of Advanced Technology Assisted Learning and Predictive Analytics (CATALPA) since April 2021. As a cognitive and educational psychologist, she conducts interdisciplinary research on multimedia learning and multitasking within this university-funded research center, collaborating with partners across psychological and educational domains.

Her academic credentials include a 2024 Habilitation from FernUniversität Hagen, a Ph.D. in Psychology from University of Koblenz Landau (2012-2015), an M.A. in Linguistics and Translation Studies from Durham University, U.K. (2010-2012), and a B.A. in Linguistics and English Language from Henan University, China (2006-2010).

Dr. Zhao's research examines how individuals process multimedia information through text-picture integration, interactive simulations, and video-based instruction, with particular focus on exploration-exploitation dynamics in learning environments. Her sequence learning investigations extend to multitasking scenarios involving basic sequences, timing patterns, and complex hierarchical structures like Origami folding. This work bridges cognitive theory with practical educational technology applications through rigorous experimental methodologies.
Recent publication analysis reveals consistent emphasis on optimizing visual representations for data comparison, measuring cognitive load in online learning, and evaluating guidance structures in asynchronous courses. Her research demonstrates that while interactive elements are generally preferred by learners, their educational benefits remain context-dependent with significant individual differences in effectiveness.

Leading the Multimedia junior research group at CATALPA, Dr. Zhao directs investigations into how interactive and multimedia components influence learning processes across diverse student populations. The team operates within an interdisciplinary framework that integrates psychological theory with technological innovation to develop predictive analytics for learning enhancement.