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OPEN A.I.R Strengthening Research Methodologies

OPEN A.I.R Strengthening Research Methodologies. Donna Podems, PhD, MPA Christa Oosthuizen , MA. Introduction. Objective: To have improved written research methodologies for your case studies.

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OPEN A.I.R Strengthening Research Methodologies

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  1. OPEN A.I.R Strengthening Research Methodologies Donna Podems, PhD, MPA Christa Oosthuizen, MA

  2. Introduction • Objective: To have improved written research methodologies for your case studies. • This will lead to a stronger presentation of your methodology sections that will result in more credible research findings • It may result in additional field work

  3. Working Style for the Workshop • Discuss one topic at a time • Provide time to fix your section, make notes, ask questions, discuss • If your section is ok (e.g. sampling is clear) then please use this time to catch up on emails, work, calls, etc. SERIOUSLY!

  4. Case Study Research • Case study is not a methodological choice but a choice of what is to be studied • Well-constructed case studies are holistic and context sensitive

  5. Case Study Research • According to Robert Stake (1995) “Case study is the study of the particularity and complexity of a single case, coming to understand its activity within important circumstances.” • The case is a specific, complex, functioning thing.

  6. Case Study Research • We are interested in cases for their uniqueness and commonality • We seek to understand them • We would like to hear the stories • We are interested in how something functions, and we need to put aside many presumptions while we learn (Stake, 1995)

  7. Case Study Research • Intrinsic Case Study - we are interested in it not because studying we learn about other cases, but because we need to learn about THAT particular case • Instrumental case study—when we have the need for a general understanding • Collective case study -

  8. Research Reports • Introduction –set the scene and research questions • Literature Review – what is out there already and refine research questions • Description of Methodology • Discussion of Results • Conclusion-recommendation-way forward

  9. MethodologyJust Some Basics • Methodology comes at the start before you describe a method • Methodology vs. method

  10. Questions and Boundaries • Research Questions • Most of these are already set and clear • Do not confuse the research question with the questions that you ask the interviewee • All decisions link back to your questions • Confusion between action and question • Boundaries Do you clearly state your research boundaries?

  11. Unit of Analysis • No matter what you are studying, always collect data at the lowest level unit of analysis possible • Collect data about individuals not households • You can always aggregate, but you can never disaggregate data collected in groups

  12. Unit of Analysis • What is the phenomena you are studying(Subject of your case)? Caution: Must be real life and not something abstract, argument or hypothesis • What is the context (Data external to your case)

  13. Unit of Analysis

  14. Literature Review

  15. Literature Review – What Is It? “A literature review is an effective evaluation of selected documents on a research topic that should provide background to the proposed study.” Hart, 1998

  16. Literature review - Steps to Follow and Describe • Defining parameters • Search for literature • Sort and prioritise retrieved literature • Analytical and evaluative reading of literature • Comparison across studies • Organising the content • Writing the review

  17. Literature reviews –Define Parameters? • Language  • Subject area  • Geographic area  • Sector  • Publication period • Literature type 

  18. Literature reviews – What to Aim For • Summarize, Analyze, Interpret ---refer to! • LOOK AT: Research reports and journal articles in the field to see how other researchers have described and evaluated the literature, and to examine how they have ordered and classified their findings and the findings of others.

  19. The Methodology Section: Why Have One? • From the description of the methodology, the reader should know exactly what was done so that • It can replicated and get similar results (internal validity) We need to ensure that your methodologies meet this requirement

  20. Revisiting Your Methodology • These are already written –we need to improve them. • What belongs in a methodology section? • Methods of data collection • Sampling • Research instrument and how it was designed • Data analysis • Process – time frame • Ethical considerations • Weaknesses to design

  21. What Does NOT Belong in a Methodology Section? We found some things that didn’t belong. These were: • Data • Results • Findings Please review your case studies and highlight or remove these items

  22. Methods • Interviews • Focus groups • Direct observation • Surveys • Documentary review – literature, policy documents (secondary data)

  23. Interviews • Structured, semi-structured, open ended questionnaires: • Depending on what you use, your reason for that, and your data analysis would change Please review your case studies and describe these tools and who they were used for (which group)

  24. Focus Group

  25. Focus Group • Why use a Focus Group and not an interview? • Please don’t say time was the factor • Want several perspectives at the same time • Discussion and group interaction will produce the most useful data • It is a way of listening and learning from discussion

  26. Direct Observation • Not as easy as it seems…. • Not appropriate for these studies Brief demonstration

  27. Questionnaires for Interviews • Structured • Semi structured • Unstructured

  28. Questionnaires for Surveys • Surveys are used to collect primary quantitative and qualitative data with the aim of gathering valid, reliable, unbiased and discriminatory data from a representative sample of respondents to obtain generalized results that is applicable to the population.

  29. Document Review • Different than a literature review • Secondary data- may still need to analyse • Assessment of the quality, novelty, and importance of the article • Need to clarify why you chose certain data and why you didn’t review other data

  30. Sampling- Selecting a Case • Might be useful to select cases which are typical of other cases but a sample of a few is unlikely to be a strong representation of others • Case study research is not sampling research • We do not study a case primarily to understand other cases

  31. Sampling- Selecting a Case • Our first obligation is to understand this ONE case • Sometimes a typical case works well • Sometimes an unusual case illustrates matters we would otherwise over look- How did you select your case?

  32. Sampling- Selecting a Case • Maximise what we can learn • Feasible and accessible • Not all cases will work out well

  33. SampleQualitative –Thoughts

  34. SamplingQualitative – Who To Interview • Extreme Case Sampling – weakness is lack of generalising • Intensity Sampling – Same as extreme with less emphasis on the extreme • Maximum variation sampling – any patterns that emerge from great variation are of interest

  35. SampleQualitative – Who To Interview • Homogeneous samples – direct contrast to max variation. Purpose is to describe some small group in depth • Typical case sampling – describe a culture or program; a qualitative profile • Critical case sampling- those that make the point quite dramatically

  36. SampleQuantitative – Who To Interview • Snowball or chain sampling- information should diverge and then converge • Criterion sampling- review and study all cases that meet some predetermined criterion of importance --Critical incidence • Theory-based sampling – sample based on potential manifestation or representation of important theoretical constructs

  37. SampleQualitative – Who to Interview • Confirming and disconfirming cases- • Confirming is to identify additional examples of already identified patters; elaborate and , add richness, depth and credibility • Disconfirming are examples that do not fit; place boundaries around the findings – Who has this in their Case Study?

  38. SampleQualitative– Who to Interview • Stratified purposeful sampling- sample within a sample. Stratify within a larger case • Opportunistic or emergent sampling- new opportunities after field work has begun • Purposeful random sampling- random sample of even a small case can increase credibility—not for representativeness

  39. SampleQualitative – Who to Interview • Sampling politically important cases • Convenience sampling – what’s fast and convenient • Key to deciding which one? Select information rich cases; cases from you can learn a great deal about matters of importance and worthy of in-depth study

  40. SampleQualitative – Sample Size • What is the appropriate number to sample? It depends • There are no rules for sample size in qualitative inquiry. • Credibility is –does the sample strategy support the study’s purpose? For some, redundancy in the data, for others…

  41. Sampling Genie

  42. Before Moving On To Quantitative Sampling…. • Choice between quant and qual well explained in your methodology? • Quant want explanation and control (explain) while Qual want understanding for the complex interrelationships among all that exists (inquiry) Check to see that you have this well explained

  43. SamplingQuantitative • Probability - random selection • Large numbers • Known population • Large scale surveys using quant technique (usually) • Non probability – selection is not chance All have weaknesses (to address later)

  44. Data AnalysisQualitative • Need to explain how you analysed your data • Organise by cases • Can shift your unit of analysis at this stage • Rubrics, computer programs, hand sorting Who needs to go back and change their unit of analysis after they analyse the data?

  45. Data AnalysisQualitative • Content, Pattern and Theme- • core consistencies Inductive to find theme and then deductive to confirm the analysis ---needs to be explained in your methodology.

  46. Data AnalysisQuantitative • In quantitative research, you end up with "numbers" after carrying out your research.  These are analyzed, and then interpreted in light of the research question and other relevant theory and research findings. • In order to create the "numbers" for quantitative research (data), a measurement process needs to take place.  In other words, you need to convert some human phenomenon (in the human sciences) accurately into numerical data. • Descriptive • Multivariate

  47. Credibility • Weakest part of most methodologies • Rationale ---why is this research credible? • Credible, transferable, dependable, confirmable • Transparent methodology

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