Qualitative Data Analysis. Quantitative research Involves information or data in the form of numbers Allows us to measure or to quantify things Respondents.

Qualitative Data Analysis

Quantitative research

Involves information or data in the form of numbers

Allows us to measure or to quantify things Respondents don’t necessarily give numbers

as answers - answers are analysed as numbers

Good example of quantitative research is the survey

Helps us flesh out the story and develop a deeper understanding of a topic

Often contrasted to quantitative research Together they give us the ‘bigger picture’ Good examples of qualitative research are

face-to-face interviews, focus groups and site visits

Quantitative research

Surveys: Questionnaires Think clearly about questions (need to

constrain answers as much as possible) Make sure results will answer your research

question Can use Internet for conducting surveys if

need to cover wide geographic reach

Face-to-face interviews

Must prepare questions Good idea to record your interviews Interviews take up time, so plan for an hour

or less (roughly 10 questions) Stick to your questions, but be flexible if

relevant or interesting issues arise during the interview

Focus groups

Take time to arrange, so prepare in advance (use an intermediary to help you if you can)

Who will be in your focus group? (e.g. age, gender)

Size of focus group (8-10 is typical) Consider whether or not to have separate

focus groups for different ages or genders (e.g. discussing sex and sexuality)

Site visits and observation

Site visits involve visiting an organization, community project etc

Consider using a guide Observation is when you visit a location and

observe what is going on, drawing your own conclusions

Both facilitate making your research more relevant and concrete

Case studies

Method of capturing and presenting concrete details of real or fictional situations in a structured way

Good for comparative analysis

Participatory research

Allows participation of community being researched in research process (e.g. developing research question; choosing methodology; analysing results)

Good way to ensure research does not simply reinforce prejudices and presumptions of researcher

Good for raising awareness in community and developing appropriate action plans

Interviews

Interviews

Unstructured Semi-structured Structured

Interviews

Establish a rapport Treat interviewees with respect Think about your appearance Think about body language Maintain firm eye contact Don’t Invade their space

Interviews

How are you going to record Tape recorder Pen and paper Video recorder

Questionnaires

Questionnaires

Open-ended Close-ended Combination of both

Questionnaires

Open-ended Slower to administer Harder to record responses Does not stifle response Answerer can raise new issues Answerer feels they can speak their mind What does a blank answer mean ????

Questionnaires

Close-ended Faster to administer Easier to record responses Answerer can only give predefined answers Answerer cannot raise new issues Answerer feels constrained More likely to answer all questions (box tick)

Questionnaires

Self-administered Interviewer administered

Questionnaires

Keep questions short and simple Avoid questions with “not” Avoid questions with bias Avoid sensitive questions (ask

indirectly)

Types of Input

Analysing data from; Interviews Open-ended questions

Also (approaches you have seen previously); Laddering Card sorting Repertory grids

Action Research & Participatory Action Research

Action Research versus Participatory Action Research

"If you want to know how things really are, just try to change them"

Action Research versus Participatory Action Research

Difference Or Extension?

Context – Developing world issues V’s Developed world issues?

What do you need?

Mind Map

Conversational Analysis

Introduction Conversation analysis (commonly

abbreviated as CA) is the study of talk in interaction. CA generally attempts to describe the orderliness, structure and sequential patterns of interaction, whether this is institutional (in the school, doctor's surgery, courts or elsewhere) or casual conversation.

MindMap

Conversational Analysis

Practical ExamplesConversations between friendsRelationship counselling sessionsLegal hearings

FieldsEthnomethodologyDiscursive PsychologyQualitative Research

PeopleHarvey SacksEmanuel Schegloff

Ethnography

Ethnography

“Do you mind if I just hang around here and take note of what you’re doing?”

Ethnography - background

What is Anthropology? It is the comparative study of the

physical and social characteristics of humanity through the examination of historical and present geographical distribution, cultural history, acculturation, and cultural relationships.

Ethnography - background

What is Cultural Anthropology? It is one of four fields of anthropology

which has developed and promoted "culture" as a meaningful scientific concept; it is also the branch of anthropology that studies cultural variation among humans.

Ethnography

It is two things The fundamental research method of

cultural anthropology. It is the genre of writing that presents

descriptions of human social phenomena, based on fieldwork; or, the written text produced to report ethnographic research results.

Ethnography

Whilst living among the people, ethnographers engage in participant observation.

This means that they participate, as much as possible, in local daily life (everything from important ceremonies and rituals to ordinary things like meal preparation and consumption) while also carefully observing everything they can about it.

Ethnography

Through this, ethnographers seek to gain what is called an emic perspective, or the native's point(s) of view without imposing their own conceptual frameworks.

The emic perspective is quite different from the etic perspective which is the outsider's view on local life.

Ethnography

Through the participant observation method, ethnographers record detailed fieldnotes, conduct interviews based on open-ended questions, and gather whatever site documents might be available in the setting as data.

This data is then recorded in the database.

Ethnomethodology

Ethnomethodology

“The study of how people use commonsense understandings to get through everyday life ”

These understandings shape our assumptions about social Interactions

In a conversation between two people there are many things that are understood than are actually mentioned.

Ethnomethodology

What are social problems? Damaging conditions resulting in harm

to people or society.

Things are seen, judged, and defined to be problems, i.e. What people THINK they are.

Ethnomethodology

Tacit interpretation – culture, teaching, understanding, experiences.

Explicit Truth – misinterpretations, misunderstanding.

Ethnomethodology

Example: Girl called Anna, unplanned pregnancy, 21 years old, still in school.

Good or Bad?

Ethnomethodology

What if …….?

Anna is an outstanding student, is the sole heiress to a multi-billion dollar business, has the full support of her parents, and will be finished school early into the pregnancy?

Ethnomethodology

Anna Anisimova Daughter of

Russian metals magnate Vassily Anisimov

Worth $1.3 billion

Ethnomethodology

We make assumptions based on our tacit interpretation of the world around us.

We can apply methods to research in order to apply a “neutral” analysis to the subject.

This has been done in HCI to study descriptions of how the users interact with systems, rather than what the system needed to do?

1. The organization of practical actions and practical reasoning. Including

2. The organization of conversation analysis. 3. Talk-in-interaction within institutional or organizational

settings. Identify interactional structures that are specific to particular settings.

4. The study of social activity. The analytic interest is in how that work is accomplished within the setting in which it is performed.

5. The haecceity of work. Just what makes an activity what it is? E.g. what makes a test a test, a competition a competition, or a definition a definition?

Ethnomethodology – (Varieties)

MindMap

Grounded Theory

What is Grounded theory?

"Grounded theory methods are a set of flexible analytic guidelines that enable researchers to focus their data collection and to build inductive middle-range theories through successive levels of data analysis and conceptual development" Charmaz, K. (2005)

What is Grounded theory?

The phrase "grounded theory" refers to theory that is developed inductively from a corpus of data. If done well, this means that the resulting theory at least fits one dataset perfectly. This contrasts with theory derived deductively from grand theory, without the help of data, and which could therefore turn out to fit no data at all - Steve Borgatti

Grounded Theory

Emphasis on empirical material as basis for conceptualization.

Gathering reach empirical material from a variety of sources.

Open data collection Recording data systematically the emphasis is on exploring the nuances of the

data by constantly asking, 'of what is this an example?'

Develop dense and grouded concepts and categories

Example - Data Analysis

Identify ‘critical instances’ -highlight key passages of transcripts.

‘Open coding’ - assign passages to categories (i.e. abstract conceptual labels). Work through all transcripts and collect numerous illustrative quotes to ‘saturate’ categories.

‘Axial coding’ - refine initial list of categories. Delete and amalgamate some. Make connections between the categories and define their properties e.g. context, pre-conditions. These are sub-categories.

‘Selective coding’ - identify a core category and themes from which theory will derive.

Research Design

Five components of research design:

1. A study's questions

2. Its propositions, if any

3. Its unit(s) of analysis

4. The logic linking the data to the propositions

5. The criteria for interpreting the findings

Strengths and Weaknesses Suitable for diagrammatic representation? Complex terminology. Time-consuming, requires concentration but can

adapt a ‘quick-and-dirty’ version. Reductionist - complexity of raw data overcome by

reducing it to the status of variables. Does not lead to any surprising findings. Theory is

inductively built up from data collected so cannot contain anything new. Uncovers a pre-existing reality similar to positivism / realism.

Idea that there is a ‘core’ category which explains all. Issues of generalisation

Narrative Inquiry

A narrative is the description of a sequence of events – a story. It is generally natural for people to remember things as a sequence of events, and to provide a cause.

It can be used as a method of investigation as follows:

While interviewing a person with relevant information, let the interviewee provide their information as a narrative – a story. Then analyse the story using the components of a story – such as a movie screenplay-– identify the scenario -,setting, complicating action, resolution

Narrative Inquiry

The resulting analysis moves towards a reduction of the narration to answer the question "what is the point of this story?" – and how does this fit into the context of the research. (Richmond, 2002)

Narrative Inquiry

An advantage of narrative is that it provides the information along with its context – it provides a more detailed answer to a question.

Narrative Inquiry

A narrative may be more effective than questionnaires. Using a questionnaire means that the investigator has predetermined the nature of what they expect to find before starting the enquiry process. Questionnaires constrain an interviewee – narrative allows them to express the story as they see it. (Snowden, 2003)

Narrative Inquiry

On the other hand ,there are dangers in relying on narrative. By assigning causes and connection events , people make sense of the world . The cause and connection may not be correct.

Narrative Inquiry

Phenomenography

Da Fan Club

Phainomenon Graphei

n

Appearance Description+ = Phenomenography

Edmund Husserl

Plato or Bust

JA, ich liebe Logical

Investigations1900

Maurice Merleau-Ponty

Jean-Paul SartreMartin

Heidegger

Ulrich Sonnemann

Das ist

Phenomenography

1954

In other words…

Phenomenography, a descriptive recording of immediate subjective experience as reported, for example, by a person under psychiatric examination, without questioning the share in such a communication of the ego. (Sonnemann, 1954 )

What's it all About?

Empirical research Based on observation and experience

Applied factors – Intelligence, Motivation, Effort, past and present surroundings, experiences, experiences and individual character traits

Nothing taken for granted?

What does it mean, that some people are better at learning than others?

Why are some people better at learning than others?

Content Analysis

Content Analysis

Content analysis is a standard methodology in the social sciences on the subject of communication content. Earl Babbie defines it as "the study of recorded human communications, such as books, web sites, paintings and laws".

Content Analysis

Harold Lasswell formulated the core questions of content analysis: "Who says what, to whom, why, to what extent and with what effect?". Ole Holsti (1969) offers a broad definition of content analysis as "any technique for making inferences by objectively and systematically identifying specified characteristics of messages"

Content Analysis

Q Methodology

Q Methodology The name "Q" comes from the form of factor

analysis that is used to analyze the data. Normal factor analysis, called "R method," involves finding correlations between variables (say, height and age) across a sample of subjects. Q, on the other hand, looks for correlations between subjects across a sample of variables. Q factor analysis reduces the many individual viewpoints of the subjects down to a few "factors," which represent shared ways of thinking.

Knowledge Elicitation

Card Sorting KA technique in which a collection of concepts

(or other knowledge objects) are written on separate cards and sorted into piles by an expert in order to elicit classes based on attributes.

Also enables significant elicitation of properties and dimensions

Used to capture concept knowledge and tacit knowledge

Use in conjunction with triadic method Can also sort objects or pictures instead of cards

Repertory Grid technique

KA technique used for a number of purposes: to elicit attributes for a set of concepts to rate concepts against attributes using a

numerical scale uses statistical analysis to arrange and group

similar concepts and attributes A useful way of capturing concept knowledge

and tacit knowledge Requires special software (PC-PACK)

Repertory Grid Example

Laddering KA technique that involves the construction,

modification and validation of trees. A valuable method for acquiring concept knowledge

and, to a lesser extent, process knowledge. Can make use of various trees:

concept tree composition tree attribute tree process tree decision tree cause tree

Triadic Elicitation Method

KA technique used to capture the way in which an expert views the concepts in a domain.

Involves presenting three random concepts and asking in what way two of them are similar but different from the other one.

Answer will give an attribute. A good way of acquiring tacit knowledge.

Analysing Text

Analysing Text

Faced with the lack of organisation of data and the sheer amount of rambling can be somewhat overwhelming

With the best will in the world about trying to avoid bias, when there is multiple interpretations of data, selecting the one that best matches your research question becomes very tempting.

Simple Tabulation

Subject Money Fame Power Social Fulfilment Other

1 15 6 4 0 1 38

2 5 3 6 5 4 27

3 1 0 3 12 21 46

…..

Total

Reasons for Choosing a career

Choosing categories

Use ones from the literature Blame someone else / comparison

Use categories connected with your research question

Derive categories from data

Deriving Categories

Verbatim Analysis Knowledge management <> Knowledge engineering <>

Knowledge representation <> Knowledge reasoning “Compatible with Windows” <> “Windows-Compatible”

Gist Analysis “Compatible with Windows” == “Windows-Compatible”

Superordinate Analysis Derive superclasses Windows-Compatible + Linux-Compatible => category of

“Compatibility”

Knowledge Representation

Knowledge Representation

Scripts Sets Schemata

Knowledge Representation

Script Theory

Knowledge Representation

Script Theory Schank states that memory is in the form of meaningful

'stories' (not merely inert decontextualized information) and that problem solving progressed by using 'cases' or examples stored in memory.

So for example, in the 'classical' view, when we walk to the store, we accomplish this because we have access to a stored algorithm that tells us 'step one, open door, step two, step into street' and so on.

In Schank's view on the other hand, we accomplish this because we have access to a stored 'schema' based on previous experience of what it is like to walk to the store, and we don't need rules to describe this.

Knowledge Representation

Set Theory Do we categorise based on similarities or

differences ? Category – Bird

Robin obvious Ostriches and penguins less features

Knowledge Representation

Schema Theory Bartlett arrived at the concept from studies of

memory he conducted in which subjects recalled details of stories that were not actually there. He suggested that memory takes the form of schema which provide a mental framework for understanding and remembering information.