1. Capella University ~ Psychology Club February 2, 2016 SWallis@MeaningfulEvidence.com Steven E. Wallis, Ph.D. Fulbright Specialist, Consulting on theory, policy, and strategy Director, Foundation for the Advancement of Social Theory Adjunct Faculty, Capella University Director of Meta-Analysis, Meaningful Evidence, LLC Meta-Analyst, Center for Scientific Analysis of Policy Don't fear the theory: Easy approaches to demystify one of your most important tools

2. Some Words for Conceptual Systems  Lens (Hämäläinen & Saarinen, 2008)  Model (Craig, 2001)  Narrative (Jacobson, 2001)  Schema (Blatt, 2009)  Metaphor (Hung, 2002)  Grand Theories (Behnke, 2001)  Theories of the Middle Range (Woodside, 2003)  Grounded Theories (Charmaz, 2006)  Theory (Metcalfe, 2004)  Ethics (Andrews, 2004)  Policy (Shackelford, 2014)  Law (Schrunk, 2005)  Map (Axelrod, 1976)  Mind map (Eppler, 2006)  Assumptions (Dent & Umpleby, 1998)  Strategic Plan (Bryson, 2011)  Concept Map (Eppler, 2006) DEFINITION: A theory is a set of interrelated propositions. (they are all useful for understanding and engaging the world) 2

3. Concepts in our Minds 345 BCE – Aristotle “Pictures in the mind” 1955 – Kelly “Personal Construct” 1955 – Cronbach & Meehl “Nomological Network” 1961 – Harvey, et al.“Integrative Complexity” 3

4. Key Stuff – Looking at the THEORY – not the Data 1.Causality 2.Structure 4 Understand theory Ask excellent questions Predict usefulness of theory Improve theory Apply theory for successful practice

5. Importance of Causality 5 Improves Understanding (Johnson-Laird, 1980) Useful for Creating Knowledge Maps (Axelrod, 1976) Best Path for Scientific Understanding (Pearl, 2000) KEY = Nothing Happens Without Causality. Causality enables application.

6. Importance of structure for Communication this is a clear sentence 6 si tsih a cetsenen lcera sentence a is clear this With More Structure (Clear Rules) Language is More Useful / Effective for Communication Scale of Clarity - Coherence c I t s h a e e r t s n e n l c e s i a

7. Evaluating Structure with Integrative Propositional Analysis (IPA) 1.Identify propositions within one or more theories 2.Diagram those propositions with one box for each concept and arrows indicating directions of causal effects 3.Find linkages/overlaps between causal concepts and resultant concepts between all propositions 4.Identify the total number of concepts 5.Identify concatenated concepts 6.Divide the number of concatenated concepts by the total number of concepts 7

8. Finding Useful Propositions – Example derived from (Hawke, 1983) There is wide agreement, however, that sustained economic recovery… will require a steady improvement in business and consumer confidence… 8 NO NEED for discussion/ evidence Do NOT infer relationships Does not say HOW (Atomistic Statement) GOOD Clear causal relationships …the basic rights of women should be recognized and protected… There are signs of improvement in the world economy and of an end to the drought in the eastern States.

9. IPA – Step 1 Identify propositions within one or more theories For Example: More steady improvement in business and consumer confidence will lead to more sustained economic recovery. 9

10. IPA – Step 2 Diagram propositions one box for each concept arrows indicating directions of causal effects “Concept A” Steady improvement in business and consumer confidence “Concept B” S ustained economic recovery Proposition #1 10 Causes More

11. IPA – Step 3 Find overlaps between causal concepts and resultant concepts 11 A B P #1 Causes C P #2 B Causes A C B

12. IPA – Step 4 Identify the total number of concepts AB C Total Number of Concepts = 3 12 Causes

13. IPA – Step 5 Identify concatenated concepts ABC Number of Concatenated Concepts = 1 13 Causes

14. IPA – Step 6 Divide the number of concatenated concepts by the total number of concepts Total Number of Concepts = 3 Number of Concatenated Concepts = 1 Systemicity = 0.33 (result of one divided by three) AB C 14 Causes

15. Pop Quiz!!! Example from Complex Adaptive Systems: Three Simple Propositions CASs that are closer to the edge of chaos (EOC) will experience more self-organization. Members (agents) self-organize toward more stable patterns of activity The more that agents follow rules and the more they interact, the more they will improve on their behavior. 15

16. Pop-quiz #1 … Total number of concepts = ? Number of concatenated concepts = ? Systemicity = ? (number of concatenated concepts divided by total number of concepts) Closer the CAS is to the EOC Self- organization 16 Total number of concepts = 2 Number of concatenated concepts = 0 Systemicity = 0.0 (number of concatenated concepts divided by total number of concepts) Causes More

17. Total number of concepts = ? Number of concatenated concepts = ? Systemicity = ? (number of concatenated concepts divided by total number of concepts) 17 Total number of concepts = 3 Number of concatenated concepts = 0 Systemicity = 0.0 (number of concatenated concepts divided by total number of concepts) Pop-quiz #2 … Agents interacting Self-organization Stable patterns of activity Causes More

18. Total number of concepts = ? Number of concatenated concepts = ? Systemicity = ? (number of concatenated concepts divided by total number of concepts) 18 Total number of concepts = 3 Number of concatenated concepts = 1 Systemicity = 0.33 (number of concatenated concepts divided by total number of concepts) Pop-quiz #3 … Rule-following Interactions Improved behavior Causes More

19. Comparing Theories TheorySystemicityComplexity #1 S = 0.0 C = 2 #2 S = 0.0 C = 3 #3 S = 0.33 C = 3 19

20. Integrating three into One Wallis, S. E. (2014). Existing and emerging methods for integrating theories within and between disciplines. Organisational Transformation and Social Change, 11(1), 3-24. Total number of concepts = 6 Number of concatenated concepts = 2 Systemicity = 0.33 (number of concatenated concepts divided by total number of concepts) 20 Closer the CAS is to the EOC More self- organization Causes More Agents interacting More self- organization More stable patterns of activity Causes More rule- following More interactions Causes More improved behavior More rule- following More interactions Causes More improved behavior More self- organization More stable patterns of activity Causes Closer the CAS is to the EOC Causes

21. 21 Professor may ask questions to support reflection. Learner may ask questions in discussion threads (and of self). How might Maslow’s Hierarchy be connected here? What other things might be causal to this? What existing research or experience supports or contradicts this link? What NEW research might we conduct to test new connections? Asking Good Questions

22. Creating a Snapshot 22 More Successful Theories of Psychology will be Found Here Theories/Laws of Physics and Engineering Trivia Games & Rambling Speeches Most Theories are Here

23. Plot Development (or Devolution) of Theory 23

24. Plot Development (or Devolution) of Theory 24

25. Resources Russel, D., Wallis, S. E. (2015). Designing a Learning Analytic System for Assessing Immersive Virtual Learning Environments. Chapter in Handbook of Research on Gaming Trends in P-12 Education. Donna Russell and James Laffey (Eds.). Hershey, PA: IGI Global. Wallis, S. (2015). Integrative Propositional Analysis: A New Quantitative Method for Evaluating Theories in Psychology. Review of General Psychology, Vol 19(3), 365-380. http://dx.doi.org/10.1037/gpr0000048http://dx.doi.org/10.1037/gpr0000048 Wallis, S. (2015). The Science of Conceptual Systems: A Progress Report. Foundations of Science (in press). http://link.springer.com/article/10.1007/s10699-015-9425-z http://link.springer.com/article/10.1007/s10699-015-9425-z http://meaningfulevidence.com/publications http://projectfast.org/ http://scipolicy.org/ https://www.academia.edu/ https://www.researchgate.net 25 swallis@MeaningfulEvidence. com

26. 26 THANK YOU! Questions?

27. 27 Some extra slides….

28. Concatenated structures support good empirical research (results are more reliable with more independent variables). More A More C More B Empirical Base Philosophical Base Dual description Holon Dialectic Multiple variables Partial Cause Research Streams Integrative Complexity Propositional Analysis

29. Meaningful Learning (e.g. Novak, Russel, etc.) Better with: 1.“Structure” of knowledge 2.Links new knowledge to existing knowledge 3.Small group work 4.Creativity 5.Conversation & Language (Vygotsky) Results in: 1.Longer term memory 2.More useful (more supportive of success) in the real world Concept Mapping: 1.Supports visual learners 2.Enables processing of more information 3.Helps in the exchange of ideas 29

30. Larger theories require more collaboration (each researcher takes a piece – linked by causal relationships) Some Implications for Collaboration 30

31. Uses: Finding “core” & “belt” of a conceptual system 31 “Core” concepts are those with MORE connections “Belt” concepts are those with FEWER connections Suggests which areas are better known (core) or need more research (belt)

32. Uses: Evaluating Research 32 From: Ong, Lai & Wang – Factors affecting Engineers’ Acceptance of Asynchronous E-learning systems in High-Tech Companies Before the study… Total number of concepts = 5 Number of concatenated concepts = 3 Systemicity = 0.60

33. Uses: Finding High-Leverage Research Opportunity “Be brave” (Ritzer, 2005) Valentinov, V. 2015. From equilibrium to autopoiesis: A Luhmannian reading of Veblenian evolutionary economics. Economic Systems, 39: 143-155. & Valentinov, V. 2014. Institutional Economics and Social Dilemmas: A Systems Theory Perspective. Systems Research and Behavioral Science ES-7: Autonomy from societal and ecological environments ES-13: Sustainability of systems Causes Less ES-11: Systems ignore complexity of environment ES-10: Deviation from behaviors that their environments can support Causes More SRBS-3: Operational Closure Causes More ES-9, SRBS-5: Structural coupling (environmental constraints) Valentinov, V. 2015. From equilibrium to autopoiesis: A Luhmannian reading of Veblenian evolutionary economics. Economic Systems, 39: 143-155. SRBS-4: Evolution of increasing autonomy from environment 33

34. Importance of Structure for Navigation 34