kv713 session 3
TRANSCRIPT
Session 3 Keith Turvey and Irena Andrews
MA Education (Teaching Leaders) KV713 Research Project The Dissertation 2014/15
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)
Your data might be:
• Interview transcripts • Questionnaire response • Observation schedules • Action research: baseline + innovation +
recordings of effect • Content analysis
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
Presentation of data 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
(Bassey, 1981, p.85)
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
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 charts; histograms • Think about how you will weave quotations into
the narrative
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
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
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?
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
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 presented
The literature Elements of your project
Rationale Research design
Topic literature Methodological literature
Findings
Discussion Conclusions Recommendations
Relationship between literature and project elements
Structure
Abstract Acknowledgements 1. Introduction 10% 2. Literature review 25% 3. Methodology 20% 4. Findings and Analysis 35% 5. Conclusions and recommendations 10% References Appendices
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?
August