I strongly believe in empowering my students while holding them accountable for their learning progress—I challenge students to challenge themselves, and deliberately provide an abundance of support and resources to help them succeed. I strive to create a comfortable and inviting learning environment by holding relaxed lectures peppered with humor, enthusiasm, lighthearted examples, and connections to students’ daily lives. I feel it is very important to constantly be vigilant about how we can improve our practices, and am a strong proponent of fostering deep learning and understanding of core, abstract concepts rather than rote learning of surface content. I tailor content to different learning styles, such as by offering a “menu” of qualitatively different learning activities from which students may choose. I also recognize the great potential in the judicious use of technology in the classroom, and have a personal interest in fostering the development of students’ quantitative literacy.
Whereas the majority of decision-making research focuses on the outcomes of a decision (i.e., the observable choice), my research distinctively emphasizes the processes that lead to these outcomes, thereby providing a more comprehensive understanding of how people actually make decisions. For example, I have developed a model of how attention shifts among choice options in order to explain how different methods of asking what people prefer lead to different reported preferences—observations which resisted a coherent explanation for nearly 30 years. My work also utilizes innovative experimental techniques and mathematical modeling. For example, I uniquely employ cursor- and eye-tracking during information acquisition anddynamic response tracking, which has prompted me to develop and introduce new methods, measurements, and metrics to the field. I also include immersive decision tasks such as athletes in realistic situations that appreciate the role of the motor system from the perspective of embodied cognition.
- Naus Family Faculty Scholar, 2012
- E. Philips Knox Teaching Award for excellence and innovation in undergraduate teaching, 2010
- National Science Foundation Award, “Decision making under stress,” (PI; 2009 – 2012)
- 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
Koop, G. J., & Johnson, J. G. (2013). The response dynamics of preferential choice. Cognitive Psychology, 67, 151-185.
Wang, X.T., & Johnson, J. G. (2012). A tri-reference point theory of decision making under risk. Journal of Experimental Psychology: General, 141, 743-756.
Franco-Watkins, A. M., & Johnson, J. G. (2011). Decision moving window: Using interactive eye tracking to examine decision processes. Behavioral Research Methods, 43, 853-863.
Johnson, J. G., & Busemeyer, J. R. (2010). Decision making under risk and uncertainty. Wiley Interdisciplinary Reviews (Cognitive science).
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.
Busemeyer, J. R., Jessup, R. K., Johnson, J. G., & Townsend, J. T. (2006). Building bridges between neural models and complex decision making behavior. Neural Networks, 19, 1047-1058.
Johnson, J. G., & Busemeyer, J. R. (2005). A dynamic, stochastic, computational model of preference reversal phenomena. Psychological Review, 112, 841-861.