R ELIABILITY AND V ALIDITY

Validity is a situation specific concept, it is dependent on the purpose, population and situational factors in which measurement take place. Instrument validity is the extent to which inferences and uses made on the basis of scores from an instrument are reasonable and appropriate.

The following strategies were used to enhance the validity of this study (Mc Millan & Schumacher, 2006:324; Creswell, 2012:243):

82 - Multi-method strategies

- Participant verbatim language - Low inference description - Mechanically recorded data - Participant researcher - Member checking - Negative data

Reliability refers to the consistency of measurement, or the extent to which the scores are similar over different forms of the same instrument or occasions of data collection. The following strategies have been used to enhance the reliability of this study (McMillan & Schumacher, 2006:184):

- Standard conditions of data collection - Multiple items on questionnaire

- Single administrator

- Use of counterbalancing instruments - Heterogeneous sample group

3.3.7 DATA ANALYSIS

According to Egwuonwu (2008:59), “Data analysis is an ongoing process which literally

means to take apart words, sentences and paragraphs, which is an important act in the research project in order to make sense of, interpret and theorize data”. Mc Millan and

Schumacher (2006:364) concur with Egwuonwu stating that inductive analysis is an ongoing cyclical process that is integral to all phases of qualitative research.

This involves a relatively systematic process of coding, categorising and interpreting data to provide explanations of a single phenomenon of interest, in this case the disciplinary system of the secondary school (Flick, 2014:420). There seems to be no standard procedure of analysing data and making sense of the data seems to be primarily dependent on the researcher.

83 The following strategy was followed:

- Read relevant sources to gain a sufficient background of the problem - Completion of questionnaires by participants

- Summarised and screened all data collected from the field (questionnaires) for possible ideas and categories in contrast to background information

- Summarised quantitative data in the form of tables and graphs

- Coded and categorised common themes and ideas amongst qualitative data - Analysed categories to identify patterns and conditions

- Conducted focus group interviews based on identified patterns from questionnaires

- Transcribed interviews. Coded and categorised common themes and ideas - Tested the themes and categories across the data set (focus groups) - Synthesised data

3.3.7.1 QUANTITATIVE DATA ANALYSIS

Analysis of data in a research project involves summarizing the mass of data collected and presenting the results in a way that communicates the most important features. Quantitative research analysis involves factors such as the frequencies of variables, differences between variables, statistical tests designed to estimate the significance of the results and the probability that they did not occur by chance (Hancock 2002:17; Bryman, 2012:564).

In this study a mixed methods approach was used. Although not the primary focus, a certain amount of quantitative data was collected from the questionnaires. Structured questions in the questionnaires had specific predetermined answers which were recorded and analysed. These findings were then presented in the form of tables or graphs.

3.3.7.2 QUALITATIVE DATA ANALYSIS

In qualitative research, there may be some data which are measurable and statistically valid but for the most part we are interested in using the data to describe a

84 phenomenon, to articulate what it means and to understand it (Hancock, 2002:17; Flick, 2014:420).

Content analysis is a procedure for the categorisation of verbal or behavioural data, for purposes of classification, summarisation and tabulation. This involves identifying from the transcripts the extracts of data that are informative (Hancock, 2002:17; Silverman, 2010:439).

Initially the data were divided into three broad categories, namely, possible reasons for poor behaviour amongst learners, strengths and weaknesses of the discipline system, and possible solutions. The procedure involved a series of steps which had been adapted from Mc Millan and Schumacher (2006:367) and Hancock (2002:17):

- All focus groups and individual interviews were transcribed (i.e. recordings were transformed verbatim into typed text) before data was analysed.

- Segmenting involved dividing the data into meaningful analytical units. Such segments (words, sentences or several sentences) were bracketed in order to indicate where they begin and end.

- Each transcript was carefully read. Brief notes were made in the margin about the nature of the information noticed.

- Using the notes in the margin, a list of the different types of information that had been gathered from this transcript was composed.

- The possible linking of some of the categories was considered. They would then be listed as major categories and the original, smaller categories as minor categories.

- The lists of minor and major categories of data were studied, compared to and contrasted with the various categories.

- The next transcript was done and the process repeated. Eventually new categories ceased and the researcher investigated if all the items of relevant and

85 interesting information could be accommodated in the existing categories. Colour code categories were used to highlight items of data in the transcripts.

- Once the researcher had sorted out all the categories and made sure that all the items of data were in the right category, the researcher looked at the range of categories to see whether two or more categories seemed to fit together. If so, they could form a major theme in the research.

- Now the researcher had the themes, major categories and minor categories clearly sorted, and considered whether any of the previously excluded data was relevant and should be included in the results.

- The frequency with which observations were made was noted in order to help to identify important ideas and prominent themes occurring in the research group as a whole.

The process of content analysis involves continually revisiting the data and reviewing the categorisation of data until the researcher is sure that the themes and categories used to summarize and describe the findings are a truthful and accurate reflection of the data (Hancock, 2002:19; Creswell, 2012:145).