Office: 726 LRDC
Phone: (412) 624-7493
Assistant Professor, University of Pittsburgh Department of Psychology
Research Scientist, Learning Research & Development Center
- Causal learning, reasoning, and judgment
- Medical diagnosis and decision-making
Derringer, C., & Rottman, B. (2018). How people learn about causal influence when there are many possible causes: A model based on informative transitions. Cognitive Psychology.
Soo, K. W., & Rottman, B. M. (2018). Causal Strength Induction from Time Series Data. Journal of Experimental Psychology: General, 147(4), 485-513.
Soo, K. W., & Rottman, B. M. (2018). Switch Rates Do Not Influence Weighting of Rare Events in Decisions from Experience, but Optional Stopping Does. Journal of Behavioral Decision Making.
Rottman, B. M., Marcum, Z. A., Thorpe, C. T., & Gellad, W. F. (2017). Medication adherence as a learning process: Insights from cognitive psychology. Health Psychology Review, 11(1), 17-32.
Rottman, B. M. (2017). Physician Bayesian updating from personal beliefs about the base rate and likelihood ratio. Memory & Cognition, 45, 270-280.
Rottman, B. M. (2017). The acquisition and use of causal structure knowledge. In M.R. Waldmann (Ed.), Oxford Handbook of Causal Reasoning (pp. 85-114). Oxford: Oxford U.P.
Rottman, B. M. (2016). Searching for the best cause: Roles of mechanism beliefs, autocorrelation, and exploitation. Journal of Experimental Psychology: Learning, Memory, & Cognition,42(8), 1233-1256.
Rottman, B. M., Hastie, R. (2016). Do people reason rationally about causally related events? Markov violations, weak inferences, and failures of explaining away. Cognitive Psychology, 87, 88-134.
Rottman, B. (2016). Physician Bayesian updating from personal beliefs about the base rate and likelihood ratio. Memory and Cognition, 1-11.
Rottman, B.M., Prochaska, M.T. & Deaño, R.C. (2016). Bayesian reasoning in residents’ preliminary diagnoses. Cognitive Research: Principles and Implications, 1(5).
Derringer, C. & Rottman, B. M. (2016). Temporal causal strength learning with multiple causes. In A. Papafragou, D. Grodner, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Soo, K. & Rottman, B. M. (2016). Causal learning with continuous variables over time. In A. Papafragou, D. Grodner, D. Mirman, & J. Trueswell (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Soo, K. & Rottman, B.M. (2014) Learning Causal Direction from Transitions with Continuous and Noisy Variables. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Rottman, B.M. (2014) Information Search in an Autocorrelated Causal Learning Environment. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Rottman, B. M., & Hastie, R. (2014). Reasoning about causal relationships: inferences on causal networks. Psychological Bulletin, 140(1), 109-139.
Rottman, B. M., Kominsky, J. F., & Keil, F. C. (2014). Children use temporal cues to learn causal directionality. Cognitive Science, 38, 489-513.
Edwards, B. J., Rottman, B. M., Shankar, M., Betzler, R., Chituc, V., Rodriguez, R., Santos, L. R. (2014) Do Capuchin Monkeys (Cebus paella) Diagnose Causal Relations in the Absence of a Direct Reward? (E. Flynn, Ed.) PLoS ONE, 9(2).
Rottman, B.M., & Keil, F.C. (2012). Causal Structure Learning over Time: Observations and Interventions. Cognitive Psychology. 64, 93-125. doi:10.1016/j.cogpsych.2011.10.003
Rottman, B. M., Genter, D., & Goldwater, M. B. (2012). Causal systems categories: Differences in novice and expert categorization of causal phenomena. Cognitive Science, 36, 919-932.
Rottman, B.M., & Ahn, W. (2011). Effect of grouping of evidence types on learning about interactions between observed and unobserved causes. Journal of Experimental Psychology: Learning, Memory, & Cognition, 37, 1432-1448. doi:10.1037/a0024829
Rottman, B. M., Kim, N. S. Ahn, W., & Sanislow, C. A. (2011). Can personality disorder experts recognize DSM-IV personality disorders from Five-Factor Model descriptions of patient cases? The Journal of Clinical Psychiatry, 72, 630-635.
Rottman, B. M., & Keil, F. C. (2011). What matters in scientific explanations: Effects of elaboration and content. Cognition, 121, 324–337.
Rottman, B. M., Ahn, W., Sanislow, C. A., & Kim, N. S. (2009). Can clinicians recognize DSM-IV personality disorders from Five-Factor model descriptions of patient cases? The American Journal of Psychiatry, 166, 427-433. doi:10.1176/appi.ajp.2008.08070972
Principal Investigator Benjamin Rottman, Associate Professor, Psychology, and LRDC Research Scientist received a National Science Foundation grant for “CAREER: Causal Reasoning in Daily Life and its Role in Science Literacy” on July 1, 2017.
LRDC Research Scientist, Benjamin Rottman, Psychology, has been named a 2016 APS Rising Star. The APS Rising Star designation is presented to outstanding psychological scientists in the earliest stages of their research careers post-PhD.
February 15, 2017
LRDC Research Scientist Benjamin Rottman's research article in clinical diagnosis is mentioned in the Psychonomic Society blog post "#goCRPI: Bayes battling baserate neglect in medical diagnosis."
October 6, 2016
Tim Nokes-Malach, with colleagues, has been awarded a grant from the National Science Foundation for "Build, Understand, & Tune Interventions that Cumulate to Real Impact." This interdisciplinary project includes LRDC researchers Christian Schunn, Benjamin Rottman, Kevin Binning, and Center Associates Chandralekha Singh and Elizabeth Votruba-Drzal and other Pitt faculty across the disciplines of biology, chemistry, and physics.
August 21, 2015
Ben Rottman received a National Science Foundation grant titled "Developing a Theory of Causal Learning over Time."
Ben Rottman received a grant for "Active-Learning of Psychological Research Methods: Authentic Skill Development through Rich Real-World Research Examples and Representations" from the University of Pittsburgh’s recently established dB-SERC (Discipline-Based Science Education Research Center). LRDC Center Associate Chandralekha Singh is the director of the new center.