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some thoughts about design research


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this is work in progress, which deserves a lot more thinking and elaboration, still ....

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some thoughts about design research

  1. 1. Some thoughts on design research, models and simulations Peter SloepFriday, May 4, 12
  2. 2. Overview • Part I: ‘ordinary research’, the essentialia • Part II: design research, the differences • Part III: modelsFriday, May 4, 12
  3. 3. Caveat • A quick and dirty introduction to some aspects of the philosophies of science and technology • Sometimes less than accurate, sometimes plain wrong, but always in an attempt to be useful.Friday, May 4, 12
  4. 4. Ordinary research, aimed at understanding and controlFriday, May 4, 12
  5. 5. Theoretical models Ia Ib S1 S2 S3 IcFriday, May 4, 12
  6. 6. Theoretical models smoke therapy Ia Ib S1 S2 S3 healthy Ic cancer dead therapyFriday, May 4, 12
  7. 7. • for a model to be useful, you need • descriptive apparatus, vocabulary • rules for how to use it, grammar, syntax • rules that uses the vocabulary and syntax to describe possible model behavioursFriday, May 4, 12
  8. 8. • rules about possible behaviours are interesting • they are generalizations, subsume instances of model behaviour • form: whenever X then YFriday, May 4, 12
  9. 9. • all kinds of vocabularies and syntaxes • math.: diff. equations, finite automata, probability calculus • computer languages: Stella, Netlogo • ordinary language (but formal languages are much more powerful because they allow inferences from axioms)Friday, May 4, 12
  10. 10. What use are models? • Are the generalizations true of the world? • you test a model • predict future behaviour, check if it occurs • yes: more confidence • no: adapt or fully reject modelFriday, May 4, 12
  11. 11. • A word on statistics • some models are stochastic, their behaviour is stochastic • but all data are subject to chance variation; you use statistics for the latter, to quantify uncertainty in your decision to accept the model or reject itFriday, May 4, 12
  12. 12. What use are models? • Are the generalizations useful in the world? • you explain the world by using model generalizations on phenomena • you control the world by using the model to predict phenomenaFriday, May 4, 12
  13. 13. Design research, focused on artefact design for controlFriday, May 4, 12
  14. 14. • artefacts are designed and developed to help control the empirical world • there always are desired phenomena, the artefact causes them to occur • there thus is a targeted state of the world and an obtained state of the worldFriday, May 4, 12
  15. 15. St Si So IFriday, May 4, 12
  16. 16. • building an aeroplane to fly • setting up an organization (bank) to lend money to investors • building a learning network to facilitate competence development, creativity and knowledge sharing of non-formal learnersFriday, May 4, 12
  17. 17. Artefactual models • As the artefact is to perform a function, you now build a model that describes the artefact’s behaviour, using bits and pieces of relevant theoretical models • Such a model I call an artefactual model, to distinguish it from theoretical modelsFriday, May 4, 12
  18. 18. Test • to the extent it incorporates theoretical models, confidence carries over from them • to the extent it rests on untested assumptions (structural and parametric) you test it • experts, independent tests • you thus contribute to theor. model dev.!Friday, May 4, 12
  19. 19. Simulate • Use the artefuactual model to explore the artefact’s behaviour through simulations • Empirical tests are costly, dangerous, unethical, etc. • Simulations are pseudo-performance tests of the artefact • They may lead to design improvementsFriday, May 4, 12
  20. 20. Empirical test • Carry out empirical tests of artefact performance • effectiveness - gap between actual and desired behaviour • efficiency - costs of obtaining desired performance level increase • sustainability - costs of maintenanceFriday, May 4, 12
  21. 21. HowFriday, May 4, 12
  22. 22. Model ingredients 1. identify the system and its boundaries: draw a causal network 2. identify variables and constants 3. identify state variables (‘laws of succession’, variables that describe state transitions) and and input variables (variables that drive change)Friday, May 4, 12
  23. 23. 1. choose output variables, what changes you want to measure (could be a state variable) 2. choose a suitable modelling language • analytic, using math. equations, often differential equations • numerical, using computers, dedicated language, e.g. Netlogo, Stella, Brahms, ...Friday, May 4, 12