Michael Young, Ph. D.
Dr. Michael Young began his career as a computer scientist out of the University of Illinois in 1984 with a specialization in Artificial Intelligence. He received his MS in Computer Science in 1990 and a Ph.D. in Experimental Psychology from the University of Minnesota/Twin Cities in 1995. After spending 12 years at Southern Illinois University at Carbondale, Dr. Young joined Kansas State University in 2012 as the Head of the Department of Psychological Sciences.
Dr. Young's primary research program involves the study of decision making in dynamic environments. He is currently studying (a) the variables that influence the identification of causes in continuously unfolding environments and (b) the situational and individual variables related to impulsive and risky choice in video game environments. He continues to integrate his background in computer science with his interest in psychology through the development of computational models of environment-behavior relations. Dr. Young's love of mathematics also is revealed by his occasional side project evaluating various statistical and design methods using Monte Carlo simulation.
For more information, go to Dr. Young's laboratory web page.
Undergraduate students begin in the lab by getting involved in the conduct of ongoing research on judgment and decision making. The lab normally requires a two-semester commitment so that the student can progress to learning additional skills after mastering the basics. Undergraduate and graduate students attend weekly laboratory meetings where everyone is required to present at least once during the term in order to develop their presentation skills. Graduate students usually begin by getting involved in an ongoing project in order to learn the ropes. As their research interests evolve, they begin to develop independent projects as well as continuing to collaborate with Dr. Young and his students in their projects. His goal in graduate training is to prepare the student to function as an independent scientist.
By the way, Dr. Young loves to talk about research design and statistics, so you will come out with a strong skill set in these areas. Because of their strong statistical training, many of his previous graduate students have ended up teaching graduate statistics or doing significant statistical consulting as professors or postdoctoral scientists.
Current Graduate Students
- Tony McCoy
- Angela Crumer
- Lisa Vangsness
- Brian Howatt
Grant Funding (last 5 years)
- Factors affecting consumer choice of confectionaries. PI of grant funded by the Hershey Company. Total award: $50,000. 2014.
- Waiting for a better future: Deciding when to “cash in” when outcomes are continuously improving. PI of grant funded by the National Institute for Drug Abuse (E.A. Jacobs, Co-Investigator). Total award: $218,250. 2010 – 2014.
- Loschky, L.C., Szaffarczyk, S., Beugnet, C., Young, M.E., & Boucart, M. (in press). The contributions of central and peripheral vision to scene gist recognition with a 180° visual field. Journal of Vision.
- Peissig, J.J., Young, M.E., Wasserman, E.A., & Biederman, I. (in press). Pigeons spontaneously form three-dimensional shape categories. Behavioural Processes.
- *Vangsness, L., & Young, M.E. (in press). Central and peripheral cues to difficulty in a dynamic task. Human Factors.
- Young, M.E., & *McCoy, A.M. (in press). Variations on the balloon analogue risk task: A censored regression analysis. Behavior Research Methods.
- Young, M.E. (in press). Modern statistical practices in the experimental analysis of behavior: An introduction to the special issue. Journal of the Experimental Analysis of Behavior.
- Young, M.E. (in press). Bayesian data analysis as a tool for behavior analysts. Journal of the Experimental Analysis of Behavior.
- *Cooper, T., **Liew, A., ***Andrle, G., **Cafritz, T., **Dallas, H., Niesen, T., **Slater, E., **Stockert, J., **Vold, T., Young, M., & Mendelson, J. (2019). Latency in problem solving as evidence for learning in varanid and helodermatid lizards, with comments on foraging techniques. Copeia, 107, 78-84.
- Young, M.E. & *Crumer, A. (2019). Reaction times. In J. Vonk & T.K. Shackelford (Eds.), Encyclopedia of Animal Cognition and Behavior. Springer. doi.org/10.1007/978-3-319-47829-6_731-1
- Jackson, A.T., Culbertson, S.S., Kausel, E.E., Young, M.E., & *Loftis, M.E. (2018). The impact of escalation decisions on investments, anger, and confidence over time. Frontiers in Psychology, 9:1136. doi: 10.3389/fpsyg.2018.01136.
- Young, M.E., *Vangsness, L., & *McCoy, A.M. (2018). The temporal dynamics of waiting when reward is increasing. Behavioural Processes, 149, 16-26.
- Young, M.E. (2018). A place for statistics in behavior analysis. Behavior Analysis: Research and Practice, 18, 193-202. dx.doi.org/10.1037/bar0000099.
- Young, M.E., Sutherland, S.C., & *McCoy, A.W. (2018). Optimal go/no-go ratios to maximize false alarms. Behavior Research Methods, 50, 1020-1029. doi.org/10.3758/s13428-017-0923-5.
- Young, M.E. (2018). Discounting: A practical guide to multilevel analysis of choice data. Journal of the Experimental Analysis of Behavior, 109, 293-312.
- *Vangsness, L., & Young, M.E. (2017). The role of difficulty in dynamic risk mitigation decisions. Journal of Dynamic Decision Making, 3, 5. online pdf.
- Smith, T.R., Young, M.E., & Beran, M. J. (2017). Gambling in rhesus macaques (Macaca mulatta): The effects of cues signaling risky choice outcomes. Learning and Behavior, 45, 288-299.
- Young, M.E. (2017). Discounting: A practical guide to multilevel analysis of indifference data. Journal of the Experimental Analysis of Behavior, 108, 97-112.
- **Eckels, E.N., *Schlabach, M., Young, M.E., Eckels, S. (2017). Measured thermal comfort and sensation in highly transient environments. ASHRAE Transactions – 2017 Winter Conference – Las Vegas,123.
- Young, M.E., *McCoy, A.M., *Hutson, J.P., *Schlabach, M., & Eckels, S. (2017). Hot under the collar: The impact of heat on game play. Applied Ergonomics, 59, 209-214.