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Modeling the Mind and the Milieu :

Modeling the Mind and the Milieu :. Computational Modeling for Organizational Psychologists. "Mathematics is the language with which God has written the universe."   --   Galileo Galilei. Mathematics has not tended to be the language of theories in psychology and organizational science

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Modeling the Mind and the Milieu :

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  1. Modeling the Mind and the Milieu: Computational Modeling for Organizational Psychologists

  2. "Mathematics is the language with which God has written the universe."   --  Galileo Galilei • Mathematics has not tended to be the language of theories in psychology and organizational science • Math models need to be solved, but often seen as intractable when describing human or organization behavior • Computational models do not need to be solved • Computational models are algorithmic descriptions of process details, typically operationalized as computer programs that are dynamic and can be simulated (Taber & Timpone, 1996) • JAP has only published one computational model, ever (Vancouver, Weinhardt, & Schmidt, 2010) • 0.3% of AMJ articles are computational models • in last 11 years, only 1.3% of AMR articles included computational models (nearly all macro or meso)

  3. Yet, Computational Models: • Increase precision and transparency • Less ambiguity of concepts and explanations • Specific predictions (compared to natural language theories) • Assure internal (logical) consistency • Model works • Accounts for phenomena claimed • Identify unanticipated consequences • Simulations can lead to new findings

  4. Dynamically Challenged • Human ability to predict values in dynamic variables is low (even among those in STEM fields) • Dynamic variables are variables with memory • Stocks, levels • Predicting the behavior of dynamic, nonlinear processes, interacting subsystems • Forget about it

  5. Hintzman (1990) “To have one's hunches about how a simple combination of processes will behave repeatedly dashed by one's own computer program is a humbling experience that no experimental psychologist should miss” (p. 111).

  6. Objectives:By the end of this workshop you will know how to … • Identify a problem worthy of modeling • Define the system to be modeled • Build a model • Evaluate a model

  7. Step 1: Identify Problem • Dynamic phenomena • All phenomena? • Existing theory • Lot’s of talk, no models • Existing computational architectures • Neural networks • Systems dynamics • Cybernetics

  8. Job Attitudes and Stress • Cybernetic, natural language theories on both topics

  9. The Ubiquitous Comparator • Hulin & Judge’s (2003) review of job attitude models

  10. Step 2: System Definition • Unit(s) of analysis • Individual in context • Problem boundary: just enough • Core dynamic processes • Restrictions • Time frame (100 days) • Variables: add as needed

  11. Part of Edward’s Theory of Stress and Well-Being Importance Desires Discrepancy Well-Being Coping Perception Physical and Social Environment

  12. Step 3: Building the Model • Vensim • System Dynamics platform (Forrester) • Units often organizations or other larger systems • Coopting for psychological modeling • Individual cognitive processes • Individual in context • Open software • Model setting: Unit of time; “Days”

  13. Main Toolbar Simulation Menu Sketch Tools Output File Window Build Window (Where you build your model) Analysis Tools

  14. Sketch tools Lock Move Variable Level Variable Arrow Rate Shadow Variable Input Output Comment Delete Equation Reference

  15. Key Variables in the Model

  16. Types of Desires • Optima: Not too much; not to little • Minima: Only values exceeding desire a problem (e.g., budget) • Maxima • Hard maxima: values exceeding desire ignored • Soft maxima: more is better, but with diminishing returns

  17. Step 4: Evaluating the model • Simulations that works • Postdiction • Assess assessment strategies • Will past designs and analysis have been diagnostic? • Hypothesis generation and testing • Strong inference via model comparison • Differing predictions • Model fitting • Complexity (# parameters) vs. fit

  18. Don’t Marry your Model! Questions? • Further information: • ORM tutorial: Vancouver, J.B., & Weinhardt, J.M., (online). Modeling the mind and the milieu: Computational modeling for micro-level organizational researchers. Organizational Research Methods. • Modeling in Org Psych: Weinhardt, J. M. & Vancouver, J. B. (in press). Is there a computational model in your future? Only the math will tell. Organizational Psychology Review. • Symposium: Understanding Dynamics Conceptually, Analytically, Computationally, and Empirically. Tuesday, Aug 7 201211:30AM - 1:00PM. Boston Park Plaza, Beacon Hill Room. • Web site: https://sites.google.com/site/motivationmodeling/home • Help from: Justin Weinhardt; Mike Warren; Amanda Covey; Justin Purl; Xiaofei Li

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