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Qualitative data analysis: many approaches to understand user insights

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The fifth lecture at HITLab, Canterbury University in New Zealand was all about how important it is to run a proper analysis of the qualitative data. We discussed the value in looking at data from individual (phenomenological) perspective versus combined (reductionist) perspective. But we agreed that regardless of the chosen approach it is crucial to look at the data from more than just one perspective to be sure the interpretation is not biased by researcher's on view of the world.

Publicado en: Datos y análisis, Diseño
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  • thanks, Madhu! and great to hear from you!:) As for the insights - I typically have this small framework dividing the collected data points as: problems, status quo descriptions (it is the way it is and don't you dare to change that:), hopes and suggestions for change. Any one of them can be seen as an insight, so I mark those that trigger ideas (and associate ideas with these relevant insights). This is no official framework but it helps me to keep my ideas and the user comment separate. You could also do data triangulation (my next presentation will be about that:) One other way is to do multiple qualitative analyses on the data set to be sure your interpretation is as least biased as possible. I tend to combine affinity diagramming with behaviour analysis to get to personas and scenarios as the analysis path. It feels reliable although a bit longitudinal. Another way is to do the analysis with a few persons, so that you discuss the categorization of the insights together. I am not sure if this answers your question - if not keep on asking and I will try to be more precise.
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Qualitative data analysis: many approaches to understand user insights

  1. 1. qualitative data analysis: many ways to understand user insights aga szóstek(at)gmail.com
  2. 2. the interpretation of the data is at least as important as the data itself
  3. 3. qualitative research Development of concepts which help to understand social phenomena in natural (rather than experimental) settings, giving due emphasis to the meanings, experiences and views of the participants. Pope & Mays BMJ 1995; 311:42-45
  4. 4. key features of qualitative research -  relatively open-ended, exploratory research design
  5. 5. key features of qualitative research -  relatively open-ended, exploratory research design -  collection of unstructured forms of data -  transcripts from interviews -  field-notes from observations -  audio- or video-recordings -  written documents of various kinds -  photographs, drawings -  electronic data from virtual interactions
  6. 6. key features of qualitative research -  relatively open-ended, exploratory research design -  collection of unstructured forms of data -  transcripts from interviews -  field-notes from observations -  audio- or video-recordings -  written documents of various kinds -  photographs, drawings -  electronic data from virtual interactions -  plans for data collection and analysis, and even research questions themselves, may change during the course of inquiry
  7. 7. principles of qualitative research -  people differ in their experience and understanding of reality
  8. 8. principles of qualitative research -  people differ in their experience and understanding of reality -  social phenomenon cannot be understood outside its own context
  9. 9. principles of qualitative research -  people differ in their experience and understanding of reality -  social phenomenon cannot be understood outside its own context -  qualitative research is used to describe a given phenomenon or generate theory grounded in data
  10. 10. principles of qualitative research -  people differ in their experience and understanding of reality -  social phenomenon cannot be understood outside its own context -  qualitative research is used to describe a given phenomenon or generate theory grounded in data -  understanding human behaviour emerges slowly and non-linearly
  11. 11. principles of qualitative research -  people differ in their experience and understanding of reality -  social phenomenon cannot be understood outside its own context -  qualitative research is used to describe a given phenomenon or generate theory grounded in data -  understanding human behaviour emerges slowly and non-linearly -  some cases may yield insights in to a problem or new idea for further inquiry
  12. 12. types of qualitative analysis
  13. 13. Case studies are attempts to shed light on a phenomenon by studying in depth a single case example of that phenomenon.  The case can be an individual person, an event, a group or an institution.
  14. 14. Ethnographic research focuses on the sociology of meaning through close field observation of sociocultural phenomena. Typically, the ethnographer focuses on a community.
  15. 15. Grounded theory is an analytic induction method where an examination of the data starts with a single case from a‘pre-defined’population with the goal to formulate a general statement about a population, a concept or a hypothesis. Then all subsequent cases are compared to see if they fit the initial hypothesis.
  16. 16. Phenomenological analysis describes the structures of experience as they present themselves to consciousness, without recourse to theory, deduction, or assumptions from other disciplines. .
  17. 17. Content analysis is a procedure for the categorization of verbal or behavioural data for the purpose of classification, summarization and tabulation.
  18. 18. Narrative analysis focuses on narratives as transcribed experiences. The researcher aims to sort out and reflect upon these narratives, enhance them and present them in a revised shape.
  19. 19. Discourse analysis is a method of analyzing a naturally spoken interaction and all types of written texts. It focuses on how people produce and make sense of everyday social life.
  20. 20. Historic analysis is a systematic collection and objective evaluation of data related to past occurrences in order to test hypotheses concerning causes, effects or trends of these events that may help to explain present events and anticipate future events.
  21. 21. Framework analysis is a method of finding patterns and interrelations in the collected data in order to develop, expand, confirm or reject an initial research hypothesis, or to find a systematic answer to a given research question.
  22. 22. so, we have data – what now?
  23. 23. Qualitative Data Analysis (QDA) is the range of processes and procedures whereby we move from the qualitative data that have been collected into some form of explanation, understanding or interpretation of the people and situations we are investigating. http://onlineqda.hud.ac.uk/Intro_QDA/what_is_qda.php
  24. 24. -  data is related to concepts, opinions, values and behaviours of people in context and thus chaotic -  issues seem too large and complex to grasp and order -  data that are not easily reduced to numbers
  25. 25. characteristics of qualitative data analysis -  circular and not linear -  iterative and progressive -  close interaction with the data -  different levels of analysis -  different ways of sorting data
  26. 26. answering research questions -  descriptions of people and their attitudes, dispositions, patterns of behaviour, and of places and activities that take place in the context of the study -  explanations for the identified patterns along with evidence showing the presence of the causal factors and their effects for the studied contexts
  27. 27. data analysis -  iterative process of data exploration -  art of finding patterns -  beginning with general open-ended questions, moving toward greater precision as more information emerges -  pre-defined variables are not identified in advance -  checking reliability of assumptions, interpretations and conclusions -  integrating data of multiple kinds (from observations, interviews, photographs, etc).
  28. 28. quality in the study http://onlineqda.hud.ac.uk/Intro_QDA/qualitative_analysis.php
  29. 29. deduction versus induction
  30. 30. stages of data analysis -  coding the data: generating categories from the data by finding what is‘in’the data with regards to the research questions posed
  31. 31. stages of data analysis -  coding the data: generating categories from the data by finding what is‘in’the data with regards to the research questions posed -  identifying framework: determining categories and subcategories, and sorting data into the framework
  32. 32. stages of data analysis -  coding the data: generating categories from the data by finding what is‘in’the data with regards to the research questions posed -  identifying framework: determining categories and subcategories, and sorting data into the framework -  using the framework for descriptive analysis: comparing data placed in the same conceptual category to clarify and develop ideas about each category and its interrelations with other categories
  33. 33. stages of data analysis -  coding the data: generating categories from the data by finding what is‘in’the data with regards to the research questions posed -  identifying framework: determining categories and subcategories, and sorting data into the framework -  using the framework for descriptive analysis: comparing data placed in the same conceptual category to clarify and develop ideas about each category and its interrelations with other categories -  second order analysis: validating the importance and the dominance of the discovered phenomena
  34. 34. strategies for analyzing qualitative data -  chronology -  key events -  different settings -  different people -  types of processes -  types of issues
  35. 35. terms used in qualitative data analysis -  theory: set of interrelated concepts, definitions and propositions presenting a systematic view of the data -  themes: categories emerging from grouping of lower-level data -  characteristic: a single item or event, the smallest unit of analysis -  coding: the process of attaching labels to lines of text so that the researcher can group and compare related pieces of information -  coding sorts: compilation of similarly coded elements from different sources in to a single file -  indexing: generating a word list comprising all substantive words and their location within the texts
  36. 36. computer assisted qualitative data analysis (CAQDAS) -  facilitates the coding, storage, and retrieval of data -  worthwhile if dealing with a large amount of data -  popular programs: -  Atlas ti 6.0 (www.atlasti.com) -  HyperRESEARCH 2.8 (www.researchware.com) -  Max QDA (www.maxqda.com) -  The Ethnograph 5.08 -  QSR N6 (www.qsrinternational.com) -  QSR Nvivo (www.qsrinternational.com) -  Weft QDA (www.pressure.to/qda) -  Open code 3.4 (www8.umu.se)
  37. 37. reporting qualitative research
  38. 38. Qualitative research generates rich information - thus deciding where to focus and the level of sharing is very challenging. http://www.psy.dmu.ac.uk/michael/qual_writing.htm
  39. 39. data interpretation -  identifying and explaining the meaning of the data -  generalizing -  ensuring credibility
  40. 40. -  choose a format: research report, scientific article, field report, evaluation report, inspiration report -  determine your focus: -  academic: conceptual frameworks and theories, methodology and interpretation -  practical: concrete suggestions and recommendations -  general public: describing the problem, suggesting appropriate practices -  use quotes from the data: illustrative, representing a range of issues, presenting opposing views -  list the discovered issues in a rank or a sequence order -  describe types: of behaviour, strategies, experiences -  report proportions -  add flow diagrams: decision-making, event sequencing
  41. 41. traditional research format -  introduction -  literature review -  goal and motivation of the study -  brief description of the study -  description of study context -  methodology -  results -  discussion and conclusions -  implications -  acknowledgements -  references
  42. 42. exemplary analysis method: affinity diagramming
  43. 43. -  write each of your insights on a separate Post-It note -  spread notes on the table so they are visible to everyone -  gather the team around the cards -  together look for ideas that are related and place them side by side -  it is okay to have “loners” that do not fit any group -  if a card seems to belong in two groups, make a second card with the same finding and put cards in both groups -  once all cards are grouped select a title, a short description for each group and a representative finding
  44. 44. exemplary method of framework analysis: segmentation by behaviour
  45. 45. -  for each category look for extreme behaviours and attitudes: positive – negative, dependent – independent, extrovert – introvert, aware – unaware, etc. -  put the extremes on the two ends of the same axis -  place other behaviours between the two extremes -  choose behaviours, which you would like to design your solution for
  46. 46. personas type of the mobile phone brand of the phone looks of the phone physicality of the phone choosing the phone smartphone feature phone important unimportant important important unimportant unimportant independent requires advice

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