Mario Fifić

Mario Fific

Associate Professor - Cognitive Psychology

  • B.A., Belgrade University
  • Ph.D., Indiana University, Bloomington

Office: 2217 Au Sable Hall

Phone: (616) 331-5061

Email: [email protected]

Lab: Cognitive Science Lab



Cognitive Psychology

Courses Taught

PSY 300 - Research Methods in Psychology

PSY 400 - Advanced Research in Psychology

PSY 361 - Perception

Research Interests

Professor Fific's research interests center on developing a process-tracing approach that allows for the precise determination of rigorously defined properties fundamental to the mental processes that underlie cognitive actions. Much of Professor Fific's research has been focused on the development of a highly diagnostic and sophisticated methodology for uncovering mental architecture, known as the systems factorial technology (SFT). His work as a research scientist at the Center for Adaptive Behavior and Cognition, at the Max Planck Institute for Human Development, has aimed to apply process-tracing techniques in the area of complex decision making. The work thus far has involved validation, theoretical refinement, extensions, and further application of SFT.

Selected Publications

Hsieh, C.-J., Fifić, M., & Yang, C.-T. (2020). A new measure of group decision-making efficiency. Cognitive Research: Principles and Implications, 5(1), 45.

Fifić, M., Houpt, J. W., & Rieskamp, J. (2019). Response times as identification tools for cognitive Processes underlying decisions. In Schulte-Mecklenbeck, M. (Ed.), Kuehberger, A. (Ed.), Johnson, J. (Ed.). A Handbook of Process Tracing Methods. New York: Routledge, 2nd Edition.

Yang, C. T., Hsieh, S., Hsieh, C. J., Fifić, M., Yu, Y. T., & Wang, C. H. (2019). An examination of age-related differences in attentional control by systems factorial technology. Journal of Mathematical Psychology, 92, [102280]. [R. Duncan Luce Outstanding Paper Award, 2020]

Glavan, J. J., Fox, E. L., Fifić, M., & Houpt, J. W. (2019). Adaptive design for systems factorial technology experiments. Journal of Mathematical Psychology, 102278.

Little, D. R., Eidels, A., Fifić, M., & Wang, T. S. L. (2018). How do information processing systems deal with conflicting information? Differential predictions for serial, parallel and coactive processing models. Computational Brain & Behavior, 1, 1–21.

Page last modified July 14, 2023