Qualitative Techniques

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Qualitative Techniques
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Overview of Lecture

• Explore basic ideas of research methodology
• Evaluating what makes qualitative research good
• Review and contrast qualitative research examples
• Critique common data gathering techniques
  reviewing ethical considerations
• Explore methods for data analysis
• Summarise Key Issues

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Research Methodology

• Positivist
• Experiments and Surveys
• Quantitative
• Objective Measurement
• Independent of researcher
• Data Collection
• Questionnaires
• Secondary Sources
• Analytical Tools
• Statistical Techniques

• Anti Positivist
• Case Studies
• Action research
• Interpretism
• Qualitative
• Search for Meaning
• Subjective interpretation by researcher
• Data Collection
• Interviews
• Focus Groups
• Secondary Sources
• Analytical Tools
• Content Analysis

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Characteristics of Good Research

• Positivist
• Validity
• Does it tell you what you are concluding?
• Reliability
• Can you replicate the results?
• Generalisability
• Can they be generalised to other people and
  places and times?

• Anti Positivist
• Validity
• Does it have meaning richness and depth?
• Reliability
• Is it truthful? Has bias been recognised and
  managed?
• Generalisability
• Can it give new or aid understanding of
  situations?

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Contrasting Qualitative Research Methods

• What is the difference between Circus and
  Non-Circus Lives?
• Ron Beadle
• What limits the effectiveness of ABM
  implementation in companies?
• Jane Gibbon, Karen Johnson, Jan Loughran
• Differences in environmental reporting practices
  in the UK and US
• Leigh Holland and Yee Boon Foo

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Common Data Gathering Techniques

• Textual Analysis of secondary sources
• Interviews
• Semi structured and in-depth
• Focus Groups
• Observation
• Participant observation
• Structured Observation

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Qualitative Analytical Techniques

• Based on Meanings expressed through words
• Collection results in non standardised data
  requiring classification into categories
• Analysis conducted using conceptualisation
• Adapted from Saunders, Lewis and Thornhill 2003

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Qualitative Data Analysis

• Understanding characteristics of language
• AND
• Discovering regularities
• Structured Analytic strategies Deductive
  (derived from theory)
• Comprehending the meaning of text or action
• AND
• Reflection
• Researchers interpretation Inductive

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Qualitative Data Analysis

• Disaggregating data into meaningful and related
  categories
• Allows
• Comprehension and management
• Integration of related data from different
  sources
• Identification of key themes or patterns
• Development or testing of hypothesis
• Draw and verify conclusions

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Qualitative Data Analysis

• Categorisation
• Unitisation
• Recognising Relationships
• Key Theme is interactive nature of process

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Qualitative Data Analysis Key Strategies

• Using a theoretical or descriptive framework
• Use theory to formulate research questions and
  objectives
• Use theory to devise a framework for analysis
• Does lead to bias and may close researchers mind
• However does help to get started, link research
  to existing knowledge base

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Qualitative Data Analysis Key Strategies for
Deductive work

• Use theory to formulate research questions and
  objectives use predicted explanations
• Use theory to devise a framework for analysis
• Does lead to bias and may close researchers mind
• However does help to get started, link research
  to existing knowledge base

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Key Issues for Success

• Reliability of Evidence
• Has it been triangulated?
• Has bias been recognised and eliminated?
• Does data have richness and depth?
• Validity of Evidence
• Have you asked the right subjects the right
  questions?
• Generalisability
• Does it have give meaning and understanding?