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Tales from the Trenches	

                     - OR –	

Replicating things that have already been said at this meeting	


                  Robert R. Hoffman, Ph.D.	




 “Data Coding, Analysis, Archiving, and Sharing for Open Collaboration: 	

             From OpenSHAPA to Open Data Sharing,” 	


                                                    © 2011 Robert R. Hoffman All rights reserved
Me




  Experimental Psychology 	

(Cognitive, Psycholinguistics)	

    U of Cinti, U of Minn	


      Expertise Studies	

Cognitive Systems Engineering	

       Human Factors



                             © 2011 Robert R. Hoffman All rights reserved
Macrocognition as a paradigm in 	

        Cognitive Systems Engineering


  Gunnar Johansson	

           Mental simulation	

       1980                     Problem detection	

Cacciabue & Hollnagel	

          Coordination	

        1995                       Re-planning	

      Klein et al	

          Expertise development	

         2002	

IEEE Intelligent Systems	

       (2 seconds ?)




                                      © 2011 Robert R. Hoffman All rights reserved
© 2011 Robert R. Hoffman All rights reserved
Communities of Practice

“Behavior”	

  Versus 	

 Activity
                Activity	

                Theory	

                              Work 	

                              Analysis	


                                            Sociotechnics	


                                             © 2011 Robert R. Hoffman All rights reserved
Ancient History	





“How fast was the car going when it 	

(bumped, crashed) into the other car?”	



Barbara Tversky, et al.	


                                   © 2011 Robert R. Hoffman All rights reserved
That was then, this is….	



	

     	

   	

   	

   	

   	

then. . . . . . 	



                                   © 2011 Robert R. Hoffman All rights reserved
Myth of the Normal Curve	



Examples:	

    	

Sampling under a stopping rule	

    	

Traffic delays (lots of brief ones, rare long ones)	

    	

Achieving progressive criteria in pole vaulting	

    	

Errors in motor coordination tasks	



Patil, G. P. (1960). On the evaluation of the negative binomial
distribution with examples. Technometrics, 2, 501-505. 	


Sichel, H. S. (1951). The estimation of parameters of a negative
binomial distribution with special reference to psychological
data. Psychometrika, 16, 107-127. 	



                                                                   © 2011 Robert R. Hoffman All rights reserved
"Call For Data"	




•  Usability/Learnability analysis	

•  Performance at the very first trials 	

  of learning any task; any DVs	

•  Exact modeling of discrete 	

  non-Gaussian distributions 	


                                     © 2011 Robert R. Hoffman All rights reserved
Learning geometrical patterns	

Learning to use a cell phone by the elderly	

Learning to operate an automotive GPS (route-finding)	

Learning to recognize voices in auditory localization	

Learning to control an avatar in a virtual world	

Learning of the structure of biological categories 	

Learning to fly a cockpit simulator	


     	

    	

9 data sets on hand, 9 more pending	


                                          © 2011 Robert R. Hoffman All rights reserved
?




    © 2011 Robert R. Hoffman All rights reserved
?




    © 2011 Robert R. Hoffman All rights reserved
?




    © 2011 Robert R. Hoffman All rights reserved
?




    © 2011 Robert R. Hoffman All rights reserved
Rule #1
                           	



           Clean-up is always necessary
                                      	


Retabbing	

Fonts	

Column widths	

Etc.	



                                     © 2011 Robert R. Hoffman All rights reserved
Rule #2
                            	

  You always have to go back and talk to the
                  researcher
                           	


What does "No OT" mean?	

What did you really do?	

Did I fix the tab delineations correctly?	


                   Worse. . . . 	

                   People forget things about their
                   own data, even short-term	

                                      © 2011 Robert R. Hoffman All rights reserved
The Control Challenge	



How do you cope with the consequences of
these Rules?	

Do you impose constraints?	

                    - OR -
                         	

Do you acknowledge that clean-up will always
  be necessary, and figure out ways to make it
  easier.	


                                 © 2011 Robert R. Hoffman All rights reserved
Requirements v. "Desirements"	

    	

("help" versus "impose")	

Designing for kluges and work-arounds	



        Hoffman, R. R. & Elm, W. C. (2006, January/February). 	

        HCC implications for the procurement process. 	

        IEEE: Intelligent Systems, pp. 74-81.	


        Koopman, P. & Hoffman, R. R., (November/December 2003). 	

        Work-Arounds, Make-Work, and Kludges. 	

        IEEE: Intelligent Systems, pp. 70-75. 	

                                                     © 2011© Robert R. Hoffman All rights reserved	

                                                            Robert R. Hoffman All rights reserved
The Search Challenges	


Challenge #1	

Finding data by data constraint (e.g., data type,	

meaning)	

Challenge #2	

Finding data by design constraint (e.g., between
v. within, etc.)	



                                       © 2011 Robert R. Hoffman All rights reserved
The Representation Challenges	


 Challenge #3	

 Frame problems (a priori categories v. search
 categories)	


Challenge #4	

Practicalities of representation - cryptograms,
     	

acronyms, abbreviations	



                                    © 2011 Robert R. Hoffman All rights reserved
The Purpose Challenges	


Challenge #5	

Chiding resarchers re: design limitations,
    	

methodological questions	



Challenge #6	

Topical research data v. Statistics itself as an
     	

area of research	



                                      © 2011 Robert R. Hoffman All rights reserved
Having seen all the Tools & Systems. . . 	


Usefulness	

Usability	

                          These features are measurable
Understandability	

Learnability	


      e.g., Data on Researcher time, effort, resources	

                     “labor intensive”	

                  “efficient data mining”

                                            © 2011 Robert R. Hoffman All rights reserved
© 2011 Robert R. Hoffman All rights reserved
Thank you!	





www.ihmc.us	

       www.ihmc.us/users/rhoffman/main	

                                    © 2011 Robert R. Hoffman All rights reserved

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Hoffman nsf presentation hoffman-25-aug11.ppt

  • 1. Tales from the Trenches - OR – Replicating things that have already been said at this meeting Robert R. Hoffman, Ph.D. “Data Coding, Analysis, Archiving, and Sharing for Open Collaboration: From OpenSHAPA to Open Data Sharing,” © 2011 Robert R. Hoffman All rights reserved
  • 2. Me Experimental Psychology (Cognitive, Psycholinguistics) U of Cinti, U of Minn Expertise Studies Cognitive Systems Engineering Human Factors © 2011 Robert R. Hoffman All rights reserved
  • 3. Macrocognition as a paradigm in Cognitive Systems Engineering Gunnar Johansson Mental simulation 1980 Problem detection Cacciabue & Hollnagel Coordination 1995 Re-planning Klein et al Expertise development 2002 IEEE Intelligent Systems (2 seconds ?) © 2011 Robert R. Hoffman All rights reserved
  • 4. © 2011 Robert R. Hoffman All rights reserved
  • 5. Communities of Practice “Behavior” Versus Activity Activity Theory Work Analysis Sociotechnics © 2011 Robert R. Hoffman All rights reserved
  • 6. Ancient History “How fast was the car going when it (bumped, crashed) into the other car?” Barbara Tversky, et al. © 2011 Robert R. Hoffman All rights reserved
  • 7. That was then, this is…. then. . . . . . © 2011 Robert R. Hoffman All rights reserved
  • 8. Myth of the Normal Curve Examples: Sampling under a stopping rule Traffic delays (lots of brief ones, rare long ones) Achieving progressive criteria in pole vaulting Errors in motor coordination tasks Patil, G. P. (1960). On the evaluation of the negative binomial distribution with examples. Technometrics, 2, 501-505. Sichel, H. S. (1951). The estimation of parameters of a negative binomial distribution with special reference to psychological data. Psychometrika, 16, 107-127. © 2011 Robert R. Hoffman All rights reserved
  • 9. "Call For Data" •  Usability/Learnability analysis •  Performance at the very first trials of learning any task; any DVs •  Exact modeling of discrete non-Gaussian distributions © 2011 Robert R. Hoffman All rights reserved
  • 10. Learning geometrical patterns Learning to use a cell phone by the elderly Learning to operate an automotive GPS (route-finding) Learning to recognize voices in auditory localization Learning to control an avatar in a virtual world Learning of the structure of biological categories Learning to fly a cockpit simulator 9 data sets on hand, 9 more pending © 2011 Robert R. Hoffman All rights reserved
  • 11. ? © 2011 Robert R. Hoffman All rights reserved
  • 12. ? © 2011 Robert R. Hoffman All rights reserved
  • 13. ? © 2011 Robert R. Hoffman All rights reserved
  • 14. ? © 2011 Robert R. Hoffman All rights reserved
  • 15. Rule #1 Clean-up is always necessary Retabbing Fonts Column widths Etc. © 2011 Robert R. Hoffman All rights reserved
  • 16. Rule #2 You always have to go back and talk to the researcher What does "No OT" mean? What did you really do? Did I fix the tab delineations correctly? Worse. . . . People forget things about their own data, even short-term © 2011 Robert R. Hoffman All rights reserved
  • 17. The Control Challenge How do you cope with the consequences of these Rules? Do you impose constraints? - OR - Do you acknowledge that clean-up will always be necessary, and figure out ways to make it easier. © 2011 Robert R. Hoffman All rights reserved
  • 18. Requirements v. "Desirements" ("help" versus "impose") Designing for kluges and work-arounds Hoffman, R. R. & Elm, W. C. (2006, January/February). HCC implications for the procurement process. IEEE: Intelligent Systems, pp. 74-81. Koopman, P. & Hoffman, R. R., (November/December 2003). Work-Arounds, Make-Work, and Kludges. IEEE: Intelligent Systems, pp. 70-75. © 2011© Robert R. Hoffman All rights reserved Robert R. Hoffman All rights reserved
  • 19. The Search Challenges Challenge #1 Finding data by data constraint (e.g., data type, meaning) Challenge #2 Finding data by design constraint (e.g., between v. within, etc.) © 2011 Robert R. Hoffman All rights reserved
  • 20. The Representation Challenges Challenge #3 Frame problems (a priori categories v. search categories) Challenge #4 Practicalities of representation - cryptograms, acronyms, abbreviations © 2011 Robert R. Hoffman All rights reserved
  • 21. The Purpose Challenges Challenge #5 Chiding resarchers re: design limitations, methodological questions Challenge #6 Topical research data v. Statistics itself as an area of research © 2011 Robert R. Hoffman All rights reserved
  • 22. Having seen all the Tools & Systems. . . Usefulness Usability These features are measurable Understandability Learnability e.g., Data on Researcher time, effort, resources “labor intensive” “efficient data mining” © 2011 Robert R. Hoffman All rights reserved
  • 23. © 2011 Robert R. Hoffman All rights reserved
  • 24. Thank you! www.ihmc.us www.ihmc.us/users/rhoffman/main © 2011 Robert R. Hoffman All rights reserved