Session 3Keith Turvey and Irena Andrews

MA Education (Teaching Leaders)

KV713 Research Project

The Dissertation 2014/15

Data analysis: unraveling

Reasoning

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 onceRead it again and this time annotate the transcript to identify any themes that emerge for youShare your keywords/themes with a partner. Are there any similaritiesDiscuss with the rest of the group. What themes/codes would you identify in this transcript

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

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

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

Relationship between literature and project

elements

The literature Elements of your project

Rationale

Research design

Topic literature

Methodological

literature

Findings

Discussion

Conclusions

Recommendations

Structure

Abstract

Acknowledgements

1. Introduction 10%

2. Literature review25%

3. Methodology 20%

4. Findings and Analysis35%

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

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).