qualitative data analysis: many ways to understand user insights

aga szóstek(at)gmail.com

the interpretation of the data is at least as important as the data itself

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

key features of qualitative research

-  relatively open-ended, exploratory research design

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

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

principles of qualitative research

-  people differ in their experience and understanding of reality

principles of qualitative research

-  people differ in their experience and understanding of reality

-  social phenomenon cannot be understood outside its own context

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

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

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

types of qualitative analysis

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.

Ethnographic research focuses on the sociology of meaning through close field observation of sociocultural phenomena. Typically, the ethnographer focuses on a community.

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.

Phenomenological analysis describes the structures of experience as they present themselves to consciousness, without recourse to theory, deduction, or assumptions from other disciplines. .

Content analysis is a procedure for the categorization of verbal or behavioural data for the purpose of classification, summarization and tabulation.

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.

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.

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.

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.

so, we have data – what now?

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  

-  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

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

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

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).

quality in the study

http://onlineqda.hud.ac.uk/Intro_QDA/qualitative_analysis.php

deduction versus induction

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

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

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

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

strategies for analyzing qualitative data

-  chronology -  key events -  different settings -  different people -  types of processes -  types of issues

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

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)

reporting qualitative research

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

data interpretation

-  identifying and explaining the meaning of the data

-  generalizing -  ensuring credibility

-  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

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

exemplary analysis method: affinity diagramming

-  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

exemplary method of framework analysis: segmentation by behaviour

-  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

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