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KV713 Session 3


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Getting to grips with coding and data analyis

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KV713 Session 3

  1. 1. Session 3 Keith Turvey and Irena Andrews MA Education (Teaching Leaders) KV713 Research Project The Dissertation 2014/15
  2. 2. Data analysis: unraveling
  3. 3. Reasoning
  4. 4. Inductive and deductive reasoning “Although both deduction and induction have their weaknesses, their contributions to the development of science are enormous and fall into three categories:1 the suggestion of hypotheses; 2 the logical development of these hypotheses; and 3 the clarification and interpretation of scientific findings and their synthesis into a conceptual framework.” Cohen, Manion & Morrison (2000, P.5)
  5. 5. Your data might be: •Interview transcripts •Questionnaire response •Observation schedules •Action research: baseline + innovation + recordings of effect •Content analysis
  6. 6. Activity: Coding and thematic analysis Using the extract from a group interview with student teachers: Read through the transcript once Read it again and this time annotate the transcript to identify any themes that emerge for you Share your keywords/themes with a partner. Are there any similarities Discuss with the rest of the group. What themes/codes would you identify in this transcript
  7. 7. Presentation of data (Bassey 1981:85) An important criterion for judging the merit of a case study is the extent to which the details are sufficient and appropriate for a teacher working in a similar situation to relate his decision- making to that described in the case study. The relatability of a case study is more important than its generalisability
  8. 8. In analysis, interpretation and presentation of data Do not attempt generalisations based on insufficient data Do not claim more for your results than the evidence warrants Small scale studies can inform, illuminate and provide a basis for policy decisions within an institution
  9. 9. Reporting the findings • Look for similarities, groupings, clusters and items of particular significance • You may have ideas about this before you start collecting your data – a balance of ‘informed hunch’ and the influence of pre-conceived ideas • The literature can provide helpful guidance • It is worthwhile thinking about which types of data and how it can be analysed at the start • Experiment with different ways of presenting findings: Bar charts; pie
  10. 10. Statement of Results Text, supported by tables, figures, quotations Tables, charts, graphs and quotes should illustrate and illuminate the text and help the reader to understand complex data The text should not describe what the data shows but draw attention to what is most important Number tables and figures Be clear about what information is needed in the text and what should be in the appendices
  11. 11. Presentation of data Use sub –headings – these could be • Research questions •Identified themes Present data under each • Integrate data – bring together data from questionnaires, interviews, observations etc • Explain the data , be precise: ‘ A majority (4 out of 5) of respondents indicated that.....’ • Let the data do the talking
  12. 12. Sample chapters •Look at the examples provided •Draw up a list of good ideas/things that work well •Questions coming out of this •What will you do?
  13. 13. Analysis and Discussion Re-state the research question – remember context • Synthesise the results in such a way as to allow a new perspective to be reached • Make links, comparisons and contrasts, juxtapose results with the findings of others • Consider the results in the light of the literature • And also in the light of the methodological approach
  14. 14. Analysis and Discussion •Explain limitations in research design -suggest more appropriate approaches •Draw out implications for improvement of practice • What evidence do you have now to support new knowledge? •Avoid speculation that goes beyond the evidence
  15. 15. Relationship between literature and project elements The literature Elements of your project Rationale Research design Topic literature Methodological literature Findings Discussion Conclusions Recommendations
  16. 16. Structure Abstract Acknowledgements 1. Introduction 10% 2. Literature review 25% 3. Methodology 20% 4. Findings and Analysis 35% 5. Conclusions and recommendations 10% References
  17. 17. Timescales March 07 Data coding and presentation DRAFT Methodology Updated Lit Review? April Skype/ telephone call Planning fieldwork? May 08 Skype/ telephone call Progress review Sample of data analysis? 20 June 08.45 – 15.30 Round table discussion Defend methodology Ethical issues? 03 July Progress review and formative assessment to discuss: • Data analysis and writing up • September 17 or November 19 submission?
  18. 18. Round table discussion • 10 minutes to introduce their research problem and question and justify their chosen research methodology. • Following this, the presenter can choose to ask the audience for comments on one or two methodological issues or invite the audience to ask questions (5 minutes).