Advanced Coaching Analysis

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Qualitative Research Dr Ian Jones Centre for
Event and Sport Research Bournemouth University
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• Today NOT an outline of methods, but an outline
  of underlying considerations
• 1. A few common myths/misconceptions
• 2. Some challenges facing the qualitative
  researcher
• 3. Some possible issues in fieldwork

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• 1. A few common myths/misconceptions

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Qualitative research is soft, unscientific and
atheoretical

• True
• if done badly (as with all forms of research)

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You cant have a hypothesis with qualitative
research

• False
• Can be a useful tool to guide you
• e.g. Cresseys (1953) study of fraud
• Hypothesis 1 people felt it was a technical
  offence. Rejected with initial data collection
• Hypothesis 2 people undertook the behaviour
  when they felt other means unavailable - Rejected
  with further data collection
• Hypothesis 3 people undertook the behaviour
  when they felt other means unavailable and
  problem non-shareable

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You should have an audit trail

• True
• Explain through an "audit trail" (Maykut
  Morehouse 1994) aspects such as
• theoretical decisions/choices
• practical contingencies
• rendering your research transparent
• Allowing others to
• Critique your research
• Emulate your research

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The researcher should be part of the research
process

• True part of the audit trail
• Explaining your position clarifies to others your
  choices, analyses, interpretations etc
• Reflexivity a key element of any qualitative
  write up

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You should be flexible with your choice of methods

• True
• Dont restrict yourself to one method
• Bricoleur
• Interviews
• Observation
• Autoethnography
• Content analysis
• Let your methods emerge!

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Analysis should commence as soon as data
collection starts

• True
• Qualitative research should be emergent early
  analysis will allow refinement of research
  questions/hypotheses

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You should use computer software to analyse your
data

• False AND True
• Each method has strengths and weaknesses
• Depends on purpose
• e.g. analysis software objective, good for
  large data sets, reliable
• Manual analysis feel for data, easier to
  identify idiosyncrasies

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• Krane, et al. (1997 215) note with regard to
  computer versus manual analysis
• none of these procedures directly affects the
  value of the study they are merely ways for the
  inquirers to work with their data... If
  individuals use NUDIST or Hyperqual computer
  programs, or 3 x 5 cards and paste them to the
  wall, they are really doing the same thing
  conceptually.

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Numbers arent important

• True
• placing a frequency count after a category of
  experiences is tantamount to saying how important
  it is thus value is derived by number. In many
  cases, rare experiences are no less meaningful,
  useful, or important than common ones. In some
  cases, the rare experience may be the most
  enlightening one (Krane et al. 1997, p.214).

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Your analysis should be a lone endeavour

• False
• e.g. Ask a fellow researcher to code the data,
  and compare findings. will identify problems in
  coding, and ensure a valid set of codes.
• Check reliability through comparing your coding
  with others.
• Miles Huberman (1994) suggest the following
• Reliability number of agreements /(number of
  agreements disagreements).
• you may begin with a low score (e.g. 60) but
  with continual discussion and clarification you
  should achieve a score of up to 90 (if not
  higher).
• Use of devils advocate

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Qualitative research must be generaliseable

• False
• many qualitative researchers don't even care
  about generalizing focus is often upon
  generating rich descriptions of the phenomena

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• 2. Some challenges facing the qualitative
  researcher

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Challenges to the qualitative researcher
(Gummesson 1991)

• Access to reality
• Availability to the detailed rich data required
• Characteristics of the researcher

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• 2. Pre-understanding and understanding
• What is your understanding of the topic before
  data collection?
• How does this influence your understanding
  developed during data collection?

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• 3. Ensuring quality?
• Reliability
• Validity
• Plausibility/Authenticity
• Credibility
• Relevance
• Transparency

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• Ask yourself a number of questions to assist the
  analysis
• What type of behaviour is being demonstrated?
• What is its structure?
• How frequent is it?
• What are its causes?
• What are its processes?
• What are its consequences?
• What are people's strategies with dealing with
  the behaviour?
• Frankfort-Nachimas and Nachimas (1996)

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• 3. Some possible issues in fieldwork

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Potential Errors

• Some errors are more accidental
• Selection bias
• Measurement bias
• Confirmation bias
• Hartman et al (2002) identified 64 sources of
  bias
• Need to be aware of the range, e.g

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Selection Bias

• You can easily get the results you want by
  biasing your sample
• Attitudes towards Low Cost airlines
• If you want a positive response, ask those
  waiting for an EasyJet flight??
• What about a negative response?

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Measurement Bias

• http//uk.youtube.com/watch?v2yhN1IDLQjo

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Positivity Effect

• Was tourism better in the past?
• Were tour operators more knowledgeable?
• As time progresses, our memories are distorted in
  a positive direction (positivity effect)
• So we dont tend to remember the negatives
• Impacts upon any question that requires recall

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Lake Wobegon effect

• How well do you get along with others?
• Almost ALL respondents respond that they get
  along with others much better than average
• A place where "all the women are strong, all the
  men are good-looking, and all the children are
  above average".
• This is often how people perceive themselves!

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• You are
• More sociable
• More popular
• More intelligent
• Get on better with others
• May relate to aspects of your research question

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Researcher led bias

• The researcher can also influence behaviour
  through their (often unconscious) actions

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Clever Hans

• A horse who could answer simple sums set by his
  owner, hence
• Understanding language
• Understanding mathematical concepts
• Importance of non verbal influence
• Interviews
• Focus groups

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Confirmation Bias

• We can easily select data that supports our own
  point of view
• We can also reject data that goes against our
  point of view
• Egocentric thinking especially with sport
• if I do it /think /act this way, then everyone
  else does as well

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• MANY other sources of bias. So
• Think about all sources of potential bias before
  and during fieldwork and analysis

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Finally What do examiners look for?

• How were the setting and the subjects selected?
• What was the researcher's perspective, and has
  this been taken into account?
• What methods did the researcher use for
  collecting dataand are these described in
  detail?
• Were the data appropriately and systematically
  analysed? Is there discussion as to how themes
  were derived?
• What conclusions were drawn, and are they
  justified by the results?
• Is context presented?
• Are the quotes representative or exemplary?
• Have alternative interpretations been considered?
• Is a clear distinction made between data and
  interpretation?