DATA ANALYSIS AND INTERPRETATION METHODS 1 Deductive

For quantitative method, analysis of data was done from the general views and responses to questionnaires on the questions asked and comments made, e.g. this comment: ‘Most young women choose careers in the social fields and few choose from the STEM fields’, was analysed as ‘Young women prefer social rather than STEM fields as careers’. Such analysis and interpretation helped me to understand the situation as it is and I then sought further explanation to determine the cause of that situation.

Creswell (2014:93) explains that in quantitative studies, one uses theory deductively and places it at the beginning of the proposed study. In this case, the researcher advances a theory, collects data to test it and reflects on its confirmation or disconfirmation by the results, with the aim of testing or verifying a theory rather than developing it. The theory turns out to be the framework of the entire study, an organizing model for the research questions or hypotheses and for the data collection procedure. The researcher tests or verifies a theory by examining hypotheses or questions derived from it. These hypotheses or questions contain variables or constructs that the researcher needs to define. Therefore, the researcher locates an instrument to be used in order to measure or observe the attitudes or behaviours of participants in a study. Finally, the researcher collects scores on these instruments to confirm or disconfirm the theory.

The best advice, as provided by Creswell (2014:93), is to introduce the theory early, whilst planning the study, i.e. in the introduction, in the literature review section, immediately after stating the hypotheses or research questions, to ensure that there are connections among the variables. He also advises (2014:95) that theory be identified in advance to explain the relationship between independent and dependent variables.

The theory that I advanced in this study, as a result of the gender disparity in the STEM fields, was prompted by the negative sex-based stereotypes, mentioned in the introductory section of this study, which were going to be tested through the use of

questionnaires. The findings of different studies like that of Reubena et al. (2014:1403) were consulted and their report states that women outnumber men in undergraduate enrolments in the US whereas very few of them major in mathematics or science subjects. Such reports planted the seed of both feminism and sexism as theories that were suitable for my study, which would better be proven wrong or right by the findings of this research. The questions that I developed for questionnaires were categorised according to themes derived from the research question for this study. For example, under the theme: ‘University education’, one of the questions that the respondents had to answer, by agreeing or disagreeing was: Your university has a role to play in improving the participation of young women in the STEM fields.

4.7.2 Inductive

For qualitative research, the interview results of individual young women helped me to understand what influenced most of them, as this was revealed by the pattern of their responses to the same questions, e.g. Why did you choose the STEM fields as your career and not any other field?

Davies (2007:10) says that qualitative research involves an interpretive and naturalistic approach to the world. This means that qualitative researchers study things in their natural setting, attempting to make sense of or to interpret phenomena in terms of the meaning people bring to them. As mentioned in the introduction of this study, experience had taught me that there were more girls than boys in both primary and secondary schools. This was confirmed by a number of researchers. What I did not understand was that even in institutions of higher learning, young women were still in the majority although their numbers were significantly low in the STEM fields, which are critical to the labour market and their economic emancipation.

The interpretive paradigm became the most suitable choice for the qualitative method since it was necessary for me to interpret data collected and presented in the social context of the participants. For example, to understand whether the choice of careers of young women in South African universities is influenced by their nature based on general social expectation, cultural beliefs, economic values or any other aspect, that would have been presented during data collection processes.

The inductive analysis of data is a process where data is organised into categories and then patterns of these categories are identified (Le Compte, 2000). This method seeks to demonstrate the meaning of written or visual material by allocating their content systematically in order to pre-determine the detailed categories, quantifying and interpreting the outcomes (Payne & Payne, 2004). Data analysis is an ongoing process, comprising integrating the data collection, processing, analysing and reporting. All data that has been collected, either electronically or digitally, should be transcribed. This is the function of the researcher as this may need to be strengthened with, for instance, non-verbal cues and silent moments during engagement with the participants, which may attach meaning to the behaviour of the participants, like emotional distress or expression of any other gesture (Creswell et al., 2010:105). This was evident during an interview with a young woman who became emotional when responding to the question why she chose a career in the STEM fields. She became emotional when explaining that she wanted to be a doctor but did not have sufficient funding. As a result, she became a STEM teacher, which was a consolation for her. My interpretation to this was that the STEM fields are more expensive than some of the social sciences; hence most young women flock to these fields.

Terre Blanche et al. (2006:7) find that interpretive and constructionist research is linked to the inductive approach because the researcher starts with a vaguely speculative research question. Thereafter, the researcher will try to put meaning to the phenomenon by observing a set of particular instances or occurrences. After conducting the first set of interviews common trends, patterns and themes emerge and a second set of interviews may be conducted, based on the developed theory and understanding. Subsequently, more focused and refined interviews will provide a deeper understanding of the subject.

I concur with this approach because during the first set of interviews, it almost felt as if my questions would not provide me with relevant answers and that the time allocated, i.e. 30–40 minutes was too lengthy. That perception changed as I asked probing questions to the answers that were provided to obtain more information. I found that the more information I got the more adequate was the time frame.

For data analysis, I used a coding system. Creswell et al. (2010:105) define it as the marking of segments of data with symbols, descriptive words or unique identifying

names. The process of coding enables the researcher to retrieve and rapidly collect together all the text and other data that is associated with some thematic ideas, in order that the sorted bits can be examined together and different cases may be compared. In this study, data collected was also sorted according to the four themes developed for questionnaires and interviews: (i) youth development; (ii) economic empowerment and social transformation; (iii) career choice; and, (iv) university education. Under each theme there were four to five questions. Therefore, within each category there were more codes that represented each question. That made analysis easier to handle.

4.7.3 Document analysis

Another technique used in this study was document analysis since I had requested documents from participating institutions, to establish how the planned awareness programme could fit into those already existing and also to check if partnership in implementing them was possible. From the documents that were collected and analysed, it was clear that good plans were in place but not yet implemented. This helped me to identify gaps as well as plan on how those would be closed as an outcome of this study. Some areas needed to be strengthened as they were talking about improving the participation of women in the academic world but not necessarily young women. Moreover, the issue of improving participation of young women in the STEM fields did not feature anywhere in the documents. That confirmed the need for this study and its ultimate awareness programme.

In her doctoral thesis, Mokhele (2011:96–97) mentions that document analysis is classified as probably one of the most important research techniques in the social sciences. It can also be referred to as content analysis. Here, the analyst views data as representative texts, images, and expressions that are created to be seen, read, interpreted, and acted upon, in order to find their meanings. As Cohen, Manion and Morrison (2007) add, content analysis can therefore be defined as summarisation of, or reporting of, written data, its key messages and the main contents thereof. Krippendorp (2004:18) further alludes to the fact that this research technique can be used to make replicable and valid inferences from texts or ‘other meaningful matter’. It can also be used to analyse interview transcripts and media products. Regrettably, an observation has been made that there are a number of official documents in

different organisations, in the form of minutes with important resolutions from meetings, reports with necessary information etc, that are abundant (Mokhele, 2011:

96–97). I believe such documents contain the institutional memories of most organisations and employees need to be made aware of such information.

For this study, the documents that were significant for the analysis that would add value in this study were, an email from university 1, with a table, populated with statistical information (2015-2016), extracted from the HEMIS submission to the Department of Higher Education and Training; the Staffing South Africa’s Universities Framework (DHET, 2015); and the Ministerial Statement on the Implementation of the University Capacity Development Programme through Effective Management and Utilisation of the University Capacity Development Grant 2018-2020 (DHET, 2017). In some cases, the interviewees made me aware of such documents by referring to them from time to time, which triggered my interest to find, read and analyse as part of this research. For instance, one of the documents with which I was provided, revealed sound plans by an institution, which have unfortunately not yet been fully implemented due to budgetary constraints. That fact contributed to the final product of this study in terms of the structure of a programme and also shed light on other factors that may need to be researched beyond this study.

4.8 VALIDITY AND RELIABILITY/CREDIBILITY AND TRUSTWORTHINESS