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The researcher’s blind spot: 6 cognitive biases we shouldn’t ignore in research

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There are cognitive biases lurking everywhere in the research process. Cognitive biases are psychological tendencies that cause the human brain to draw incorrect conclusions.

We all want our research to provide reliable input into our projects and most of us wouldn’t deliberately distort data. Yet, we’re human, and we’re all susceptible to many cognitive biases that can affect the outcomes at any stage of our projects. Biases is unavoidable, but being a good researcher is about understanding our inherent biases and how we can minimise the effects.

Distorted or misleading results can be very detrimental to a project. It can misinform the direction of a project, or provide false confidence about decisions.

This session will highlight five common cognitive biases in research, from recruitment, to the actual sessions, and the analysis and reporting of research findings. This will be illustrated with examples and stories, along with how we can minimise the bias.

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The researcher’s blind spot: 6 cognitive biases we shouldn’t ignore in research

  1. 1. The researcher’s blind spot: 6 cognitive biases we shouldn’t ignore in research UX Australia 2016, Melbourne Ruth Ellison, Principal User Researcher, PwC’s Experience Centre
  2. 2. @RuthEllison from PwC’s Digital Services
  3. 3. @RuthEllison from PwC’s Digital Services $7$3 $6.50
  4. 4. @RuthEllison from PwC’s Digital Services $7$3
  5. 5. @RuthEllison from PwC’s Digital Services $7$3 $6.50
  6. 6. @RuthEllison from PwC’s Digital Services
  7. 7. @RuthEllison from PwC’s Digital Services The Decoy Effect is a Cognitive Bias
  8. 8. @RuthEllison from PwC’s Digital Services What is a cognitive bias? Mental shortcut
  9. 9. @RuthEllison from PwC’s Digital Services We are all human
  10. 10. @RuthEllison from PwC’s Digital Services Image source: http://www.businessinsider.com.au/what-new-coke-looked-like-in-1985-2013-3
  11. 11. @RuthEllison from PwC’s Digital Services Applying it to design research Preparing Running Analysing
  12. 12. @RuthEllison from PwC’s Digital Services Preparing for research
  13. 13. @RuthEllison from PwC’s Digital Services
  14. 14. @RuthEllison from PwC’s Digital Services Selection bias
  15. 15. @RuthEllison from PwC’s Digital Services 15
  16. 16. @RuthEllison from PwC’s Digital Services Multiple channels - mix of recruitment companies, social media, trusted networks Avoid professional respondents Careful screeners Behavioural based recruitment
  17. 17. @RuthEllison from PwC’s Digital Services Running research sessions Photo available under a CC by 2.0 licence: https://www.flickr.com/photos/gdsteam/20649386153
  18. 18. @RuthEllison from PwC’s Digital Services Observer-Expectancy effect
  19. 19. @RuthEllison from PwC’s Digital Services The way we frame our questions matter
  20. 20. @RuthEllison from PwC’s Digital Services Loftus, E. F., & Palmer, J. C. Reconstruction of automobile destruction: An example of the interaction between language and memory. Journal of Verbal Learning and Verbal Behavior, 1974, 13, 585-589. McLeod, S. A. (2014). Loftus and Palmer. Retrieved from www.simplypsychology.org/loftus-palmer.html About how fast were the cars going when they smashed into each other?
  21. 21. @RuthEllison from PwC’s Digital Services About how fast were the cars going when they collided into each other? About how fast were the cars going when they bumped into each other? About how fast were the cars going when they contacted into each other?
  22. 22. @RuthEllison from PwC’s Digital Services Triangulate research Use observational methods Keeping positive-neutral body language, watch the tone of your voice Avoid leading questions
  23. 23. @RuthEllison from PwC’s Digital Services 23 I need a volunteer please
  24. 24. 24 2 4 8
  25. 25. PwC’s Digital Services What’s going on?
  26. 26. @RuthEllison from PwC’s Digital Services Confirmation bias
  27. 27. 27 Take the opposing view
  28. 28. 28 Don’t just confirm your hypothesis, see if you can prove it wrong Analysis of Competing Hypotheses (ACH)
  29. 29. 29 Use open ended questions Some people think that soft drinks are bad for you. What do you think? What’s your opinion about soft drinks?
  30. 30. @RuthEllison from PwC’s Digital Services List assumptions Be skeptical, especially if everyone agrees with you Remain open Consider all evidence equally Multiple user researchers Leave your ego by the door. @RuthEllison from PwC’s Digital Services
  31. 31. @RuthEllison from PwC’s Digital Services Groupthink & the Bandwagon effect
  32. 32. @RuthEllison from PwC’s Digital Services 32 https://youtu.be/MDD4IkVZWTM?t=52s
  33. 33. @RuthEllison from PwC’s Digital Services Triangulate with other research methods (e.g. observational) Use a mixture of individual and group exercises Avoid stating preferences and expectations at start Give someone the devil’s advocate role to question assumptions
  34. 34. @RuthEllison from PwC’s Digital Services Anchoring bias
  35. 35. @RuthEllison from PwC’s Digital Services 35
  36. 36. 36https://www.flickr.com/photos/naotakem/17105160150/
  37. 37. @RuthEllison from PwC’s Digital Services Consider the order of questions and designs carefully Open ended questions Alternate order in which participants are shown concept or design versions Show version A first 1 3 5 2 4 6 Show version B first
  38. 38. @RuthEllison from PwC’s Digital Services Analysing
  39. 39. @RuthEllison from PwC’s Digital Services 39
  40. 40. @RuthEllison from PwC’s Digital Services Apophenia 40Source: https://au.pinterest.com/pin/249738741807276910/
  41. 41. @RuthEllison from PwC’s Digital Services Clustering illusion & reporting bias
  42. 42. @RuthEllison from PwC’s Digital Services Breadcrumbs
  43. 43. @RuthEllison from PwC’s Digital Services Sample sizes – it’s about the WHY Consider evidence equally – not just the ones that confirm your belief/assumption Collaborative analysis sessions Strive for objectivity
  44. 44. @RuthEllison from PwC’s Digital Services 44 How vulnerable are you to these biases?
  45. 45. @RuthEllison from PwC’s Digital Services What percentage of the population will be more biased than the average person?
  46. 46. @RuthEllison from PwC’s Digital Services Are you more biased than the average person?
  47. 47. @RuthEllison from PwC’s Digital Services Blind spot bias
  48. 48. @RuthEllison from PwC’s Digital Services Listen with an open mind Become more rational, but less rationalising Continuous learning 48 Always assess your method, your analysis and yourself for bias
  49. 49. @RuthEllison from PwC’s Digital Services 49 We are all human
  50. 50. @RuthEllison from PwC’s Digital ServicesImage source: https://en.wikipedia.org/wiki/Twenty_Questions#/media/File:20_questions_1954.JPG
  51. 51. Thank you :) Say hello @RuthEllison
  52. 52. @RuthEllison from PwC’s Digital Services Further reading List of cognitive biases You are not so smart: a celebration of self delusion 9 Biases In Usability Testing 52

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