TSL3113Action Research I – TESL

(Methodology)TOPIC 10

Action research: data analysis

Content analysis Categorising the data Coding the data Arranging the data into analysis grids Identifying the issues/themes/assertions Further research activities

Qualitative data

In action research, data collection is carried out throughout the process.◦ Routine reflection notes could have

pre-dated your intent to conduct the research and continued through till the end.

◦ Such routine reflection notes are valid data for your research.◦ Observation notes may be taken while the action is being

implemented. ◦ Interviews may be conducted after each cycle and also at

the end of the action.◦ Tests may be administered before and after the action.◦ Questionnaires may be given at any stage of the action to

gather feedback about its effectiveness.

INTRODUCTION

Irrespective of the means of data collection, as the researcher, decide how your data is to be collected.

Your explanation of the procedure should be clearly written so that your reader will have no problem duplicating the action.

Your writing should include:a) What data are collected?b) How are the data collected?c) When are the data collected?d) Who is responsible for collecting or recording the data?e) Where are the data stored?f) How do you ensure that the data collection procedures are

ethical?

Data Collection

Be mindful that the validity of all statement made in your action research report depends on data to support its claims of change in, and an explanation of, an identified problem.

According to Laidlaw (1996), “claims to validity in action are connected to claims about pupils learning. If you can point to evidence of pupils learning then your action can make greater claims to validity. This is because action research exists to enhance the quality of learning of the learner.”

Research Validity

The research code of ethics aims to:a) Protect the interest of those involved in the

research so that they are not adversely affected by your action.

b) Allow you as the researcher to be free to declare that your work is without prejudice and favour.

Research Ethics

Before you analyse your data, the qualitative or quantitative data you have collected need to be process. a) Transcribing the interview data.b) Analysing the qualitative datac) Coding the qualitative data.d) Processing the questionnaire datae) Qualitative data analysisf) Triangulating the datag) Interpreting the data

Analysing the data

Transcribing the interview data conversation is difficult and tedious work, and requires precise listening skills, patience and careful editing.

Decide the level of accuracy at which you intend to transcribe the conversation◦ Are you looking only for the main points and ideas

in the contents?◦ Are you looking for the nuances in the speech and

behaviour? (high level of accuracy)

Transcribing the Interview Data

Qualitative data is mostly in the form of words, phrases, sentences like the interview transcripts.

It may also include visual images, audio and video recordings of interviews, field notes, observation notes, and analysis of documents as well as reflective notes of the researcher.

This mass of information have to be organised, summerised, described and interpreted.

Qualitative data analysis is the range of process and procedures whereby we move from the qualitative data that have been collected into some form of explanation, understanding or interpretation of people and situation we are investigating (Lewins, Taylor & Gibbs, 2005)

Analysing the qualitative data

Content analysisa) Examine the datab) Highlight important details that pertain to the

research questionsc) Determine category or code namesd) Label the relevant sections of data with

corresponding category or code name

Ways to analyse qualitative data (Somekh, 1996)

Pattern analysisa) What patters can be seen?b) What significance do the patterns hold?c) What are the effects of such patterns?d) How do the patterns/effects align whit the

research objectives?e) What theories/hypothesis can be drawn from the

patterns?

Ways to analyse qualitative data (Somekh, 1996)

Dilemma analysisa) Examine the data to determine the dilemmab) Write a clear statement about the dilemmac) Explore the dilemma to understand the factors

that caused it, the effects and the degree of its significances.

d) Look for solutions to the dilemma.

Ways to analyse qualitative data (Somekh, 1996)

In order to make sense of the vast amount of words, you need to code your data.

Coding is the process of examining the words, phrases, sentences or paragraphs in your text fro pertinent information related to your research and assign different codes or labels.

Based on the coded data, you will find it easier to make analysis later on.

The process of coding will allow you to form the categories of your findings to aid you in writing out the results

Qualitative softwares: Atlasti, Ethograph and Nvivo

Coding the Qualitative Date

a) Themes, Topicsb) Ideas, Conceptsc) Terms, Phrasesd) Keywords

Codes can be based on…

Coding responses in categories is helpful for identifying common ideas expressed by the respondents. In your write-up, you may explain how you took the following steps to manually code your qualitative data:a) Create a complete list of all the responses based on

the questionsb) Scrutinise your text, visual or audio thoroughlyc) Look for information that is relevant to your

research questiond) Make note of keywords by the side of the selected

text.

Coding responses

e) You may already have in mind what you want to look for, and have pre-assigned codes or labels

f) Assign codes or labels names that are brief words or phrases which are meaningful to you and which you can remember and retrieve easily. You may use colours with your codes or labels.

g) As you examine the data, assign repeatedly to data that are judged the same.

h) If a theme is identified from the data that does not quite fit the codes that already exist then a new code is created.

i) As you read through your data set, the number of codes you have will evolve and grow as more topics or theme become apparent.

Coding responses

See Dr. Goh’s book page 95 Figure 4.13 & Figure 4.14 Coding Keywords

Coding textual data

Clarify how you processed your Questionnaire data to demonstrate transparency and credibility in doing research.

Explain how you took the following steps in processing the questionnaire data.

Prepare a template for data entry and coding for different types of data. (see page 96; Fig 4.15)a) You may use SPSS, Microsoft Excelb) Enter all the data into the electronic formatc) Check and clean data to remove errors during data entry.d) Do a reliability check (Cronbach alpha) on your data.e) Analyse the data to obtain results required by the research

questions.f) Prepare tables, charts and graphs to present the findings.

Processing the Questionnaire data

There are two kindsa) Descriptive statisticsb) Inferential statistics (seldom used in AR)

Descriptive statistics presents data in a) measures like percentages, frequency, mean, standard deviation b) forms like graphs, charts and tables.◦ Data arranged in this ways facilitates interpretation to

answer your research questions. Inferential statistics draws inferences concerned with

some unknown aspect of a population.a) Example of popular statistical tools: t-test, analysis of

variance (anova), pearson’s correlation, linear regression and multiple regression.

Quantitative Data Analysis

is the practice of using multiple methodologies or data sources to verify the findings of an investigation and prove its credibility.

reduce biasness and increase confidence in reporting your research.

By cross-referencing data from different sources and looking for common denominator as evidence, you provide a clearer and more convincing understanding of the issue.

Example: compare what pupils say in the interview and the data from the questionnaire.

Denzin (1970) listed five types of triangulation:a) data source triangulationb) investigator triangulationc) methodologic triangulationd) theoretical triangulatione) data-analysis triangulation

Triangulation

Data analysis occurs even while you are collecting data. Tentative findings will emerge.

Although these findings can be used to help focus subsequent interviews and observations, these early hypotheses tend to be inconclusive and lack sound judgement.

Be careful not to draw conclusion too early. It may affect your objectivity and you may end up in misrepresentation of conclusion.

Interpreting the Results

1. Analyse – describe and scrutinise an experience, a piece of evidence, data or an activity.

2. Appraise – the actual self-assessment occurs at this stage as you interpret the activity or evidence and evaluate its appropriateness and impact.

3. Transform – this step differentiates action research from other forms of qualitative research. From the insights gained through appraisal, you reflect on how the action has provided you with the opportunity for growth – improving your practice and transforming your professional self. (see page 100)

Three steps in data analysis and interpreting the results