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HEIDi Lab

HEIDi is an interdisciplinary group of scientists devoted to understanding human behavior in all its complexity. In particular, the group focuses on mapping out (preferably computationally) the important variables or properties of both individuals and their environments and how those variables influence each other over time and across levels of analysis (from biological to social). Specific recognition is given to the notion that a human?s environment often includes other humans (i.e., is social), and that models (both computational, machine, and animal) can be used to represent and test understandings of human-environmental interaction over time.

Model of Multiple-Goal Pursuit with Deadline: This and other models can be downloaded as a computational model that can be simulated. See Current Projects and Recent Publications below for links to models.

Current Projects

Vancouver, J. B., Weinhardt, J.M., Vigo, R (2013). Change one can believe in: Adding learning to a computational model of self-regulation. Unpublished manuscript, Department of Psychology, Ohio University, Athens, Ohio.

Download software for viewing, running, and editing model at www.vensim.com.

  • Vensim model of learning within the multiple goal pursuit model (Vancouver, Weinhardt, & Schmidt, 2010). This is the model in Appendix A of the above paper.
  • Vensim model of DeShon and Rench (2009) featuring choice among targets based on opportunity and need (Appendix B).
  • Vensim model of learning about opportunities and disturbances (Appendix C)

Lab Members

Director: Jeffrey B. Vancouver (I-O)

Affiliated Faculty

Graduate Students

  • XiaoFei Li (I-O)
  • Justin Purl (I-O)

Publications

Vancouver, J. B., Weinhardt, J. M., & Schmidt, A. M. (2010). A formal, computational theory of multiple-goal pursuit: Integrating goal-choice and goal-striving processes. Journal of Applied Psychology, 95, 985-1008.

Vancouver, J.B., & Weinhardt, J.M., (2012). Modeling the mind and the milieu: Computational modeling for micro-level organizational researchers. Organizational Research Methods, 15, 602-623.

Weinhardt, J. M. & Vancouver, J. B. (2012). Computational models and organizational psychology: Opportunities abound. Organizational Psychology Review, 2, 267-292.

Related Links

Grants

Modeling the Underlying Dynamic Processes in Motivation and Decision Making: A Parsimonious Self-Regulatory Approach. National Science Foundation; PI 09-12.