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Chapter 8

Chapter 8. Observation Studies. Learning Objectives. Understand . . . When observation studies are most useful. Distinctions between monitoring. nonbehavioral and behavioral activities Strengths of the observation approach in research design.

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Chapter 8

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  1. Chapter 8 Observation Studies

  2. Learning Objectives Understand . . . When observation studies are most useful. Distinctions between monitoring. nonbehavioraland behavioral activities Strengths of the observation approach in research design. Weaknesses of the observationapproach in research design.

  3. Learning Objectives Understand . . . Three perspectives from which the observer- participant relationship may be viewed. Various designs of observation studies.

  4. Pull Quote “Today, scores of built-in sensors in Formula One cars continuously capture a multiplicity of variables—including RPMS, weather, road conditions, the angles on a track’s s-bends, wear on tires, to pit stop now or next lap—and process it into data for active simulation models that inform a drivers’ instantaneous decisions. Formula One racing today is as much about deriving Continuous Intelligence and decision-making as it is about engine speed and driving expertise.” John Chen, CEO, Sybase

  5. Observation and the Research Process

  6. Selecting the Data Collection Method

  7. Selecting an Observation Data Collection Approach

  8. Who? Where? What? (event or time) How? When? Research Design Task Details

  9. Content of Observation

  10. Data Collection Watching Listening Touching Smelling Reading

  11. Using Observation Systematic planning Properly controlled Consistently dependable Accurate account of events

  12. Nonbehavioral Physical condition analysis Process or Activity analysis Record analysis Behavioral Nonverbal Linguistic Extralinguistic Spatial Observation Classification

  13. Selecting an Observation Data Collection Approach:Nonbehavioral

  14. Nonbehavioral Observation Record Analysis Physical Condition Analysis Physical Process Analysis

  15. Selecting an Observation Data Collection Approach: Behavioral

  16. Behavioral Observation “We noticed people scraping the toppings off our pizza crusts. We thought at first there was something wrong, but they said, ‘We love it, we just don’t eat the crust anymore.” • Tom Santor, • Donatos Pizza

  17. Standardized procedures Structured Trained observers Encoding observation information Recording schedules Systematic Observation Systematic

  18. Flowchart:Observation Checklist Design

  19. Video camera Pupilometer Audio recorder Tachistoscope Eye camera Galvanometer Mechanical/Digital Behavioral Observation Devices

  20. Observer-Participant Relationship Direct vs. indirect Known vs. unknown Involved vs. uninvolved

  21. Extralinguistic Observation Vocal Temporal Interaction Verbal Stylistic

  22. Desired Characteristics for Observers Concentration Detail-oriented Unobtrusive Experience level

  23. Errors Introduced by Observers Halo Effect Observer Drift

  24. Evaluation of Behavioral Observation Strengths • Securing information that is otherwise unavailable • Avoiding participant filtering/ forgetting • Securing environmental context • Optimizing naturalness • Reducing obtrusiveness Weaknesses • Enduring long periods • Incurring higher expenses • Having lower reliability of inferences • Quantifying data • Keeping large records • Being limited on knowledge of cognitive processes

  25. Key Terms • Concealment • Event sampling • Halo effect • Observation • Direct • Extralinguistic • Indirect • Linguistic • Nonverbal • Participant • Simple • Spatial • Systematic

  26. Key Terms • Observation checklist • Observer drift • Physical condition analysis • Physical trace • Process (activity) analysis • Reactivity response • Record analysis • Spatial Relationships • Time sampling • Unobtrusive measures

  27. Chapter 8 Additional Discussion opportunities

  28. Research Thought Leader “Once a pattern becomes predictable, the brain starts to ignore it. We get bored; attention is a scare resource, so why waste it on something that’s perfectly predictable.” Jonah Lehrer neuroscientist and author, How We Decide

  29. PulsePoint: Research Revelation 3 The number of minutes the average cubicle dweller works before being interrupted by phone, e-mail, instant message, or social networking activities.

  30. PicProfile: BestBuy Redesign Store associates as observers Eastern European ship workers as subjects Display relocation Increasedsales

  31. Snapshot: Cutting Edge or Black Box Neuroimaging techniques Better conceptual understanding of latent constructs of behavior PET scan Magnetic resonance imaging

  32. Snapshot: Wal-Mart Implements RFID Labels “We can certainly understand and appreciate consumer concern about privacy. That’s why we want our customers to know that RFID tags will not contain nor collect any additional data about our customers. In fact in the foreseeable future, there won’t even be any RFID readers on our stores’ main sales floors.” Linda Dillman EVP & Chief Information Officer Wal-Mart

  33. Snapshot: Eyes Have It Understand peoples’ reactions to stimuli Reveal the see-say gap No lab needed Calibrated to your computer Anything presented on screen can be tested

  34. Snapshot: Physicians and Patients Reveal core emotional experiences Reveal motivations for parents’ decisions Video & audio observation Respect sensitivity of subject & environment Obtain parent consent

  35. Lexus Observation at Autoshow

  36. SizeUSA Body Measurement System

  37. Portable People Meters

  38. Extralinguistic Observation Vocal Temporal Interaction Verbal Stylistic

  39. Chapter 8 Observation Studies

  40. Photo Attributions

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