Qualitative Research - PowerPoint PPT Presentation

1 / 35
About This Presentation
Title:

Qualitative Research

Description:

The interviewer asks a small number of questions on a topic in ... E.g. VPL 'cellphone-friendly zone' Unobtrusive? Us watching them vs. them watching us ... – PowerPoint PPT presentation

Number of Views:293
Avg rating:3.0/5.0
Slides: 36
Provided by: lis692
Category:

less

Transcript and Presenter's Notes

Title: Qualitative Research


1
Qualitative Research
  • Interviews
  • Observation
  • Focus Groups
  • Diaries/Journals
  • Triangulation of Multiple Methods
  • draw on strengths of individual methods to
    examine phenomena from a variety of perspectives
    (e.g. interviews diaries participant
    observation)
  • Case Study Methodology commonly used

2
Focus Group Interviews
  • A small group of people (or several small groups)
    who have been chosen based on a particular
    characteristic
  • The interviewer asks a small number of questions
    on a topic in order to explore the participants
    perceptions/ideas
  • Heavily used in market research to test peoples
    reactions to a product/service
  • More useful than questionnaires for in-depth
    responses
  • Can be used with other techniques

3
Case Study Methodology
  • May focus on individuals, organizations,
    departments/teams
  • Purpose to understand phenomena within a
    particular context
  • Cases to be studied constitute purposive sampling
  • May use a wide variety of techniques (interviews,
    questionnaires, observation)

4
Observation a Survey Methodology
  • Descriptive, quantitative research
  • To examine/document the world as it is (What is
    happening? How often does it happen?)
  • Typically uses checklists, log analysis, etc.
  • Exploratory, qualitative research
  • Ethnographic approach typically with
    interviews, etc. to document the natural setting
    where behaviours occur as part of larger
    investigation of individuals perceptions
  • Typically uses video/photos, etc.
  • Or a bit of both!

5
Where do Observational Methods Fit?
  • First step what do you want to know?
  • To map the social activity space of the library
  • To watch patrons in the moment as they engage
    in tasks
  • Focus here typically on what is actually
    happening in a particular space
  • To document what/where/how research questions
    related to patron/staff activities
  • Context for quantitative data (e.g.,
    questionnaires)
  • Context for qualitative (why) questions (e.g.,
    interview)
  • Original data for GIS mapping or other
    visualization techniques
  • To document taboo or other activities (e.g.,
    eating defacing books) that are difficult to
    gather

6
Observation Different Approaches
  • Overt Methods
  • Individuals are aware that you are gathering data
  • Signs posted at door alerting individuals to
    study under way
  • Individuals asked to engage in an activity (e.g.,
    computer search) which will be videotaped
  • Researcher may be engaged in activity under study
  • Covert Methods
  • Individuals are not aware that you are gathering
    data
  • Researcher as disengaged observer who documents
    and reflects on activities going on in the
    library
  • Researcher as engaged observer, but participants
    unaware they are being studied

7
Data Collection Tools of the Trade
  • Observation Checklists Journals (paper vs.
    digital)
  • Created in advance to guide observation
  • Created during field notes of what is
    happening in the space
  • Digital video/photographs (is audio required?)
  • Of spaces, alone or of patrons
  • Of computer screens, storytime groups, etc.
  • Maps (paper vs. digital)
  • Hand-drawn vs. blueprints
  • Analysis software
  • Quantitative Excel, SPSS, etc.
  • Qualitative (including images) Atlas.ti
  • GIS visualization ArcGIS

8
Toronto Reference Library
9
Toronto Reference Library
5th Floor
10
TRL Information Desk Foyer
11
Vancouver Public Library
12
Vancouver Public Library
13
VPL Indoor Street Library
14
Seating Sweeps Method
  • Observational walks (or sweeps)
  • 3 times per day over a one week period
    (1015-1130am 2-330pm 6-730pm)
  • Covered all library spaces separate floors,
    café area, circulation desk, etc.
  • Systematic detailed observations of 60
    different variables
  • Who is present in specific locations? What are
    they doing? What possessions do they have with
    them?

15
Seating Sweeps contd
  • First step scour library space to develop
    locational acronyms
  • CW computer workstation
  • BT book truck
  • Second count seats in/outside library space
  • Benches, sofas, carrels, worktables, etc.
  • Photos/maps of spaces (with/without patrons)
  • Third develop coding worksheet
  • Academic library settings used PDA for this
    task, so also needed to pilot test equipment
  • Benefit much less obtrusive and easier to prep
    for analysis
  • Downside more time-consuming, up-front

16
Sweeps Method Issues
  • Daily debriefing re codes
  • E.g. searching vs. physical searching
  • Differences between sites
  • E.g. VPL cellphone-friendly zone
  • Unobtrusive?
  • Us watching them vs. them watching us
  • Individuals in motion
  • People leave, pick up new books, start to talk to
    the person next to them, etc

17
Individuals Activities in Library
18
How Might we Extend Sweeps?
  • Use furniture counts (quantitative) to determine
  • How much of the library seating space is actually
    being used?
  • How are patrons using that space sleeping?
    Staying all day? Do these trends vary by location
    in library?
  • Observational shadowing following patrons
    throughout their visits (qualitative)
  • Mapping data with GIS to compare patterns
    across floors, across time periods, etc.
  • Active use of photos to paint a full picture
    of the spaces and activities under study

19
Bringing Data to Life
  • Alex 2nd year, Business/Commerce
  • When Im really trying to study, I like the
    reading room in Rutherford, that big room with
    paintings on the wall, at the top. I think for me
    its almost like an historical sense and I almost
    have like a duty to study in there, you know?
    Its just kind of that atmosphere in there so
    thats where I go to really studyI think its
    pretty open and its quiet in there, theres
    space for you to go at the tables, spread all
    your work out, youre not like at a little,
    little desk thing

20
A Photo tells the Story
21
Why Use Observational Methods?
  • A snapshot
  • Who are our patrons? What are they doing in the
    library?
  • A chance to see what patrons really do
  • How do staff interact with patrons (or one
    another) in the library space?
  • This information is invaluable for
  • Allocating staff within the library
  • Determining financial support
  • Organizing furniture (re)designing library space

22
Sampling Access
  • Always start by thinking about the population you
    wish to study then make decisions about sample
    selection
  • Will you study the population or a sample?
  • How will you find participants/documents and
    can you gain access?
  • Target population the population to which you
    would like to generalize or transfer results
  • All librarians or only those in academic
    settings
  • All teenagers or only those with diabetes

23
Sampling Frame
  • The set of all cases from which the sample is
    drawn
  • 2 ways to construct this frame
  • (1) listing all cases
  • e.g. directory of academic librarians
  • (2) providing a rule to define membership
  • e.g. teenagers diagnosed with diabetes during
    early teen (13-15) years
  • How many participants?

24
Non-probability Sampling
  • Convenience Sampling
  • Individuals chosen who are available or easy to
    find
  • Give questionnaire as people enter the library
  • Purposive Sampling
  • Each sample case is selected for a purpose
    because of its unique position
  • A typical rural library a typical urban
    library
  • Quotas set so sample represents certain
    characteristics in population
  • LIS programs 80 female, 20 male
  • Snowball Sampling
  • Identify one member of the population and get
    that individual to identify others

25
Probability Sampling
  • Simple Random Sampling
  • Each case in the population has an equal chance
    of being included in the sample
  • Systematic Random Sampling
  • First case is randomly selected, then every nth
    case
  • Stratified Random Sampling
  • Population is first subdivided into 2 or more
    strata based on mutually exclusive categories
    of one or more relevant variables (e.g.,
    male/female)
  • Simple random samples are then drawn from each
    stratum, and these sub-samples are joined to form
    the complete stratified sample

26
Probability Sampling (2)
  • Cluster sampling
  • The population is broken down into groups of
    cases (called clusters), and a sample of
    clusters is selected at random
  • The clusters generally consist of natural
    groupings (e.g. geographic - city blocks
    organizational library branches in one city)

27
Quality Research - Criteria
  • Quantitative
  • Validity
  • Generalizability
  • Reliability
  • Objectivity
  • Qualitative
  • Credibility
  • Transferability
  • Dependability
  • Confirmability

28
Quantitative - Validity
  • The degree to which you are truly measuring what
    you intend to measure
  • E.g. Hawthorne Effect (Study of productivity at
    an Electric company)
  • Looking for evidence that a particular
    independent variable (e.g. bright lights) has
    caused a change in an observed dependent variable
    (e.g. productivity)
  • Use control groups triangulation of methods
    focus on operational definitions

29
Qualitative - Credibility
  • Does the description developed through the
    inquiry ring true for members of the group
    under study?
  • Assessed through - prolonged engagement,
    persistent observation, triangulation, assessment
    of contextual materials, peer debriefing, member
    checks

30
Quantitative Generalizability
  • The ability to generalize findings across
    different settings or populations
  • Asks whether the results of the study apply to
    cases not included in the study
  • E.g. study of MLIS students use of OPACs not
    generalizable to the general population, as
    library students have special knowledge
  • Select sample carefully repeat measure
    (different setting/time of day/etc.)

31
Qualitative Transferability
  • Can the findings be applied in other contexts or
    with other respondents?
  • Key to focus on those elements which will not
    shift with context/time (and recognize
    limitations of context/time to your findings)
  • E.g. will Canadian studys findings transfer to
    U.S. context?

32
Quantitative - Reliability
  • Will the research yield stable, consistent
    results when applied repeatedly? Can the study
    be replicated?
  • E.g. How many books have you borrowed this
    year? may be unreliable they may not recall
    the exact (so they guess) they may feel that
    they should have borrowed more books (so they
    inflate )
  • Use pilot studies interviewer training apply
    measure consistently etc.

33
Qualitative - Dependability
  • If the study were replicated with the same (or
    similar) respondents in the same (or similar)
    context, would the findings be repeated?
  • Key not looking for invariance but for
    trackable variance - that if there are
    inconsistent findings, these are attributable to
    particular sources (e.g. reality shifts, better
    insights)

34
Quantitative - Objectivity
  • Quantitative measures are value-free and
    therefore objective
  • Key here idea that subjectivity leads to
    results that are both unreliable and invalid
  • Eliminate sources of bias and error that may
    distort results
  • E.g. use several, independent observers withhold
    information from participants to not taint
    opinions tape record events etc.

35
Qualitative - Confirmability
  • Researcher as Instrument
  • The degree to which the findings are the product
    of the focus of the inquiry and not of the biases
    of the researcher (i.e. key neutrality)
  • Not to ensure that data is free from
    contamination (as objectivity is an illusion),
    but to show that the data (assertions, facts,
    etc.) can be tracked to their sources
  • E.g. inter-coder checks on interview data
Write a Comment
User Comments (0)
About PowerShow.com