Tales from the Trenches	                     - OR –	Replicating things that have already been said at this meeting	       ...
Me  Experimental Psychology 	(Cognitive, Psycholinguistics)	    U of Cinti, U of Minn	      Expertise Studies	Cognitive Sy...
Macrocognition as a paradigm in 	        Cognitive Systems Engineering  Gunnar Johansson	           Mental simulation	    ...
© 2011 Robert R. Hoffman All rights reserved
Communities of Practice“Behavior”	  Versus 	 Activity                Activity	                Theory	                     ...
Ancient History	“How fast was the car going when it 	(bumped, crashed) into the other car?”	Barbara Tversky, et al.	      ...
That was then, this is….		     	   	   	   	   	then. . . . . . 	                                   © 2011 Robert R. Hoffm...
Myth of the Normal Curve	Examples:	    	Sampling under a stopping rule	    	Traffic delays (lots of brief ones, rare long o...
"Call For Data"	•  Usability/Learnability analysis	•  Performance at the very first trials 	  of learning any task; any DVs...
Learning geometrical patterns	Learning to use a cell phone by the elderly	Learning to operate an automotive GPS (route-find...
?    © 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...
Rule #2                            	  You always have to go back and talk to the                  researcher              ...
The Control Challenge	How do you cope with the consequences ofthese Rules?	Do you impose constraints?	                    ...
Requirements v. "Desirements"	    	("help" versus "impose")	Designing for kluges and work-arounds	        Hoffman, R. R. &...
The Search Challenges	Challenge #1	Finding data by data constraint (e.g., data type,	meaning)	Challenge #2	Finding data by...
The Representation Challenges	 Challenge #3	 Frame problems (a priori categories v. search categories)	Challenge #4	Practi...
The Purpose Challenges	Challenge #5	Chiding resarchers re: design limitations,    	methodological questions	Challenge #6	T...
Having seen all the Tools & Systems. . . 	Usefulness	Usability	                          These features are measurableUnde...
© 2011 Robert R. Hoffman All rights reserved
Thank you!	www.ihmc.us	       www.ihmc.us/users/rhoffman/main	                                    © 2011 Robert R. Hoffman...
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Hoffman nsf presentation hoffman-25-aug11.ppt

  1. 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. 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. 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. 4. © 2011 Robert R. Hoffman All rights reserved
  5. 5. Communities of Practice“Behavior” Versus Activity Activity Theory Work Analysis Sociotechnics © 2011 Robert R. Hoffman All rights reserved
  6. 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. 7. That was then, this is…. then. . . . . . © 2011 Robert R. Hoffman All rights reserved
  8. 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 binomialdistribution with examples. Technometrics, 2, 501-505. Sichel, H. S. (1951). The estimation of parameters of a negativebinomial distribution with special reference to psychologicaldata. Psychometrika, 16, 107-127. © 2011 Robert R. Hoffman All rights reserved
  9. 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. 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. 11. ? © 2011 Robert R. Hoffman All rights reserved
  12. 12. ? © 2011 Robert R. Hoffman All rights reserved
  13. 13. ? © 2011 Robert R. Hoffman All rights reserved
  14. 14. ? © 2011 Robert R. Hoffman All rights reserved
  15. 15. Rule #1 Clean-up is always necessary Retabbing Fonts Column widths Etc. © 2011 Robert R. Hoffman All rights reserved
  16. 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. 17. The Control Challenge How do you cope with the consequences ofthese 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. 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. 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., betweenv. within, etc.) © 2011 Robert R. Hoffman All rights reserved
  20. 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. 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. 22. Having seen all the Tools & Systems. . . Usefulness Usability These features are measurableUnderstandability Learnability e.g., Data on Researcher time, effort, resources “labor intensive” “efficient data mining” © 2011 Robert R. Hoffman All rights reserved
  23. 23. © 2011 Robert R. Hoffman All rights reserved
  24. 24. Thank you! www.ihmc.us www.ihmc.us/users/rhoffman/main © 2011 Robert R. Hoffman All rights reserved

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