Research Areas

Our lab studies diverse topics related to cognition and education. Below you will find descriptions of our research foci along with representative publications.

Scientific Reasoning

Much of the BAAC lab’s research explores how people process and reason about scientific information: When are people good at reasoning? When do heuristics lead people to make incorrect assumptions, leading to errors in judgment? What interventions enhance reasoning ability? 

We are currently performing a direct replication of scientific reasoning studies first done 40 years ago at the University of Michigan by Darrin Lehman and Richard Nisbett. We will assess how a UM education improves (or, perhaps, doesn’t improve) an undergraduate student’s ability to apply formal reasoning to scientific and everyday problems.

Another component of scientific reasoning we study is “number absolutism,” or how strict one regards numerical cut-off points when making decisions. This is quite relevant in medical contexts – for example, should a doctor diagnose a patient with an illness even if their fever is 0.2° below the diagnostic criteria threshold? 

Other projects focus on how individuals judge scientific papers:

 A current line of research is how people reason about causality and correlation. One study is evaluating if people are more likely to infer causality from a paper that uses a “reductive” explanation (such as a biological measure, like a hormone in the bloodstream or brain region activation) rather than a higher-level behavioral explanation (such as reported anxiety feelings), even if both papers are only correlational. 

Another researcher is evaluating whether laypeople are capable of identifying sample and selection bias errors when reading scientific studies, and how that capability relates to other cognition-related individual difference measures. 

Past research has examined whether people can be trained to be better consumers of science, and how people value evidence versus authority.

Shah, P., Michal, A.L., Ibrahim, A., Rhodes, R. & Rodriguez, F. (2017). What makes everyday scientific reasoning so challenging? In Ross, B.H. (Ed.), Psychology of Learning and Motivation, Volume 66.

Rhodes, R., Rodriguez, F., & Shah, P. (2014). Explaining the alluring influence of neuroscience in scientific reasoning. Journal of Experimental Psychology: Learning, Memory, & Cognition, 40, 1432-1440.

Shah, P., & Miyake, A. (1999). Models of working memory: An introduction. In A. Miyake & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 1-26). New York: Cambridge University Press

Shah, P., & Miyake, A. (1996). The separability of working memory resources for spatial thinking and language processing: An individual differences approach. Journal of Experimental Psychology: General, 125, 4-27.

Since March 2020 lab members have been studying how laypeople understand topics related to COVID-19. We have studied how to get people to understand the concept of exponential growth, how to change vaccine attitudes, how to teach people about “flattening the curve,” and how to best communicate risk using icon arrays. Our interventions focus on increasing understanding and risk avoidance through data visualization.

Currently, our lab is collaborating with Dr. Rick Lewis, Dr. John Jonides, and Dr. Ayşecan Boduroğlu to develop an online, interactive decision making tool for COVID and Flu vaccinations. We are studying how a combination of tailoring to an individual and using communication techniques (like icon arrays) can influence vaccines attitudes and uptake. We aim to develop a tool that can educate, correct misconceptions, and reduce vaccine hesitancy among Americans.

This project is part of the Social Science Research Council’s Mercury Consortium; more information can be found here. 

Lalwani, P., Fansher, M., Lewis, R. L., Borduro, A., Shah, P., Adkins, T. J., … & Jonides, J. (2020). Misunderstanding “Flattening the Curve. PsyArXiv. 

Fansher M, Adkins TJ, Lewis RL, Boduroglu A, Lalwani P, Quirk M, Shah P, Jonides J. How well do ordinary Americans forecast the growth of COVID-19? Mem Cognit. 2022 Oct;50(7):1363-1380. doi: 10.3758/s13421-022-01288-0

Witt, J., Hao, C., & Shah, P. (2022). The Impact of Visualizing the Process of Disease Spread on Social Distancing Intentions and Attitudes. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 66(1), 2026-2030. https://doi.org/10.1177/1071181322661172
Fansher, M., Adkins, T. J., Lalwani, P., Boduroglu, A., Carlson, M., Quirk, M., Lewis, R. L., Shah, P., Zhang, H., & Jonides, J. (2022). Icon arrays reduce concern over COVID-19 vaccine side effects: a randomized control study. Cognitive research: principles and implications, 7(1), 38. https://doi.org/10.1186/s41235-022-00387-5

Michal, A.L. & Franconeri, S.L. (2017). Visual routines are associated with specific graph interpretations. Cognitive Research: Principles and Implications, 2:20, 1-10. doi: 10.1186/s41235-017-0059-2

Michal, A.L., Shah, P., Uttal, D. & Franconeri, S.L. (2016). Visual routines for extracting magnitude relations. Psychonomic Bulletin & Review, 23(6), 1802-1809. doi: 10.3758/s13423-016-1047-0.

Shah, P., & Freedman, E. G. (2011). Bar and Line Graph Comprehension: An Interaction of Top-Down and Bottom-Up Processes. Topics in Cognitive Science.

Shah, P., & Freedman, E. G. (2011). Bar and Line Graph Comprehension: An Interaction of Top-Down and Bottom-Up Processes. Topics in Cognitive Science.

Shah, P., Freedman, E., & Vekiri, I. (2006). The comprehension of quantitative information in graphical displays. In P. Shah and A. Miyake, (Eds.). The Cambridge handbook of visuospatial thinking (pp. 426-476). New York: Cambridge University Press.

Wu, H., & Shah, P. (2004). Exploring visuospatial thinking in chemistry. Science Education, 88, 465-492.

Shah, P., & Hoeffner, J. (2002). Review of graph comprehension research: Implications for instruction. Educational Psychology Review, 14, 47-69.

Shah, P., Mayer, R. E., & Hegarty, M. (1999). Graphs as aids to knowledge construction: Signaling techniques for guiding the process of graph comprehension. Journal of Educational Psychology. 91, 690-702.

Carpenter, P. A., & Shah, P. (1998). A model of the perceptual and conceptual processes in graph comprehension. Journal of Experimental Psychology: Applied, 4, 75-100.

We have studied cognitive training in both ADHS and older adult populations. One recent cognitive training project focused on older adults and was funded by the National Institute of Aging with Susanne Jaeggi (PI), John Jonides, Patricia Reuter-Lorenz, & Martin Buschkuehl.

Katz, B., Shah, P., & Meyer, D. (2018). How to play 20 questions with nature and lose: Reflections on 100 years of brain-training research. Proceedings of the National Academy of Sciences, 115, 9897-9904.

Wang, Z., Zhou, R., & Shah, P. (2014). Spaced cognitive training promotes training transfer. Frontiers in Human Neuroscience, 8, 217.

Katz, B., Jaeggi, S., Buschkuehl, M., Stegman, A., & Shah, P. (2014). Differential effect of motivational features on training improvements in school-based cognitive training. Frontiers in human neuroscience, 8, 242. http://doi.org/10.3389/fnhum.2014.00242

Jaeggi, S. M., Buschkuehl, M., Shah, P., & Jonides, J. (2014). The role of individual differences in cognitive training and transfer. Memory & Cognition, 42(3), 464-480.

Jaeggi, S. M., Buschkuehl, M., Jonides, J., & Shah, P. (2011). Short- and long-term benefits of cognitive training. Proceedings of the National Academy of Sciences.

Lustig, C., Shah, P., Seidler, R., & Reuter-Lorenz, P. (2009). Aging, training, and the brain: A review and future directions. Neuropsychology Review, 19, 504-522.

We collaborate with the Jonides lab, including Dr. John Jonides and Dr. Han Zhang, to study mind-wandering and distraction. One current study uses a “forced response” method of administering cognitive tasks. This paradigm allows us to compare how well ADHD individuals perform at ignoring distractors or resolving conflict when they are on their ADHD medication, compared to when they are off their medication. 

Another ADHD-related study in collaboration with the Jonides lab is testing and validating an automated version of a popular ADHD assessment protocol. Our research demonstrates that an automated version may be a reliable way to confirm prior clinician ADHD diagnoses in research participants. 

Previous work includes a study about hyperfocus in ADHD, and a study looking at mind-wandering and cell phone use.

White, H.A., Shah, P. (in press). Attention in urban and natural environments. Yale Journal of Biology and Medicine.

White, H. A., & Shah, P. (2011). Creative style and achievement in adults with attention deficit/hyperactivity disorder. Personality and Individual Differences, 50(5), 673-677.

White, H. A., & Shah, P. (2011). Creative style and achievement in adults with attentiondeficit/hyperactivity disorder. Personality and Individual Differences, 50(5), 673-677

White, H., & Shah, P. (2006). The uninhibited imagination: Creativity and attention deficit hyperactivity disorder. Personality and Individual Differences, 40, 1121-1131.

White, H., & Shah, P. (2006). Training attention-shifting in adults ADHD. Journal of Attention Disorders, 10, 44-53.