![[Person photo]](https://www.lrdc.pitt.edu/people/images/rottman_b.jpg)
Office: 726 LRDC
Phone: (412) 624-7493
Benjamin Rottman
Associate Professor, University of Pittsburgh Department of Psychology
Research Scientist, Learning Research & Development Center
Research Interests
- Causal learning, reasoning, and judgment
- Medical diagnosis and decision-making
Rottman, B.M., Wyatt, G., Crane, T.E. & Sikorskii. (2020). Expectancy and utilisation of reflexology among women with advanced breast cancer. Applied Psychology: Health and Well-Being.
Soo, K., & Rottman, B. (2020). Distinguishing causation and correlation: Causal learning from time-series graphs with trends. Cognition.
Blatt, L., Schunn, C. D., Votruba-Drzal, E., & Rottman, B. M.(2020). Variation in which key motivational and academic resources relate to academic performance disparities across introductory college courses. International Journal of STEM Education, 7(1), 1-25.
Soo, K., & Rottman, B. M. (2018). Causal strength induction from time series data. Journal of Experimental Psychology: General, 147(4), 485-513.
Derringer, C., & Rottman, B.M. (2018). How people learn about causal influence when there are many possible causes: A model based on informative transitions. Cognitive Psychology, 102, 41-71.
Betancur, L., Rottman, B. M., Votruba-Drzal, E., & Schunn, C. (2019). Analytical assessment of course sequencing: The case of methodological courses in psychology. Journal of Educational Psychology. 111,91-103.
Soo, K. , & Rottman, B. M. (2018). Switch rates do not influence weighting of rare events in decisions from experience, but optional stopping does. Behavioral Decision Making, 31(5) 644-661
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.
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.
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).
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.
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.
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.
July 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."
August 2014
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.
May 2014