Psychology

Cognitive Psychology

PSY 300 - Research Methods in Psychology

PSY 400 - Advanced Research in Psychology

PSY 361 - Perception

Professor Mario Fific’s research examines how people gather, organize, and evaluate information in order to make judgments and decisions under uncertainty. His scholarship addresses a unified set of questions across perception, memory, reading, visual search, and belief formation, including how multiple sources of evidence are combined, whether mental processing unfolds serially or in parallel, and why cognitive systems sometimes produce accurate decisions and sometimes systematic errors or resistance to evidence. By linking fundamental theory to applied problems such as medical-image search and human interaction with artificial-intelligence decision aids, his work connects basic cognitive science to real-world challenges. His research draws on experimental methods in cognitive psychology together with mathematical and computational modeling, response-time and accuracy analyses, and process-based behavioral measures to uncover the mechanisms that guide human thought and choice.

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.