Joseph Johnson

Education

Ph.D. Psychology and Cognitive Science, Indiana University, 2004

Teaching Interests

I have taught the undergraduate statistics and research methods courses for 20 years, and genuinely enjoy teaching these courses although admittedly they are never the most favored among psychology majors. There are several elements that I have found seem to benefit students in this course, including open resources, returning students as TAs, and segmenting content. At both undergraduate and graduate levels, my seminars allow students a great deal of autonomy and flexibility which improves their attitudes towards the course and my ability to accurately assess their proficiency. Specifically, they select from a menu of topics that interest them most, as well as multiple possible assignment formats to express their understanding each week. An important component of both my graduate and undergraduate seminars is an attention to real-world applications of the basic scientific content, such as utilizing “nudges” or choice architecture to produce choices that benefit individual and/or societal welfare. More recently, I have been very focused on courses that advance the professional development of our graduate students.

• PSY 293 | Intro to Psychological Statistics
• PSY 410/470 | Seminar in Cognition

Research Interests

I have always been interested in how, presented with the same information and circumstances, different people could arrive at different decisions, with each believing they made the correct choice. Thus, with degrees in Psychology, Economics, and Cognitive Science, it is perhaps no surprise that my research focus has been centered on the cognitive processes underlying human judgment and decision making. Furthermore, my training and work has always had a significant focus on quantitative methods. Together, these experiences have produced my research program currently characterized by three important and complementary themes: sequential sampling models of decision making, process tracing techniques to verify and inform these models, and the development and application of quantitative methods to do so. First, rather than relying on economic or descriptive psychological theories of that predict observable choices, I focus on the underlying cognitive processes, such as shifting attention and momentary evaluation, in order to model how the final choice is determined over time. Then, I use methods such as eye-tracking, movement-tracking, ratings, response times, and more to measure more than just what is ultimately chosen to allow for better inferences regarding those processes. Finally, these methods and models produce large, complex data sets that require the development of novel and sophisticated techniques in statistics and parameter estimation and interpretation.

Dr. Johnson supervises graduate students in Psychology. Please see the lab website for current projects, students, and opportunities!

Professional Recognition

• Naus Family Faculty Scholar, 2012
• E. Philips Knox Teaching Award for excellence and innovation in undergraduate teaching, 2010
• Hillel J. Einhorn New Investigator Award, Society for Judgment and Decision Making, 2004
• Decision Analysis Society Publication Award Finalist, 2007
• Faculty Teaching Associate, Center for the Enhancement of Learning, Teaching, and University Assessment

Selected Publications

• Johnson, J. G. , & Busemeyer, J. R. (2023). Computational models of decision making. Cambridge Handbook of Computational Cognitive Sciences.
• Frame, M. E., Houpt, J. W., & Johnson, J. G. (2021). Functional analysis of trajectories from multiple devices during a preferential choice task. Decision.
• Schulte-Mecklenbeck, M., Kuhberger, A., & Johnson, J. G. (Eds.) (2019). A Handbook of Process Tracing Methods (2nd Edition). New York: Routledge.
• Franco-Watkins, A. & Johnson, J. G. (2016). The ticking time bomb: Using eye-tracking methodology to capture attentional processing during gradual time constraints. Attention, Perception, & Psychophysics.
• Johnson, J. G. & Busemeyer, J. R. (2016). A computational model of the attention process in risky choice. Decision.
• Koop, G. J., & Johnson, J. G. (2013). The response dynamics of preferential choice. Cognitive Psychology. Raab, M., Johnson, J. G., and Heekeren, H. (Eds.) (2009). Mind and Motion: The Bidirectional link between thought and action. Progress in Brain Research, vol. 174. New York: Elsevier.
• Johnson, J. G., & Busemeyer, J. R. (2005). A dynamic, stochastic, computational model of preference reversal phenomena. Psychological Review

Funding

Dr. Johnson has received multiple previous awards from DoD and NSF.

• National Science Foundation, Decision making under stress, 2009-2012 (PI)