The assumptions to detailed methods of data

The research approaches refer to the plan, strategies and the procedures for the research that set out the steps from broad assumptions to detailed methods of data collection, analysis and interpretation (Creswell, 2014). There are three types of approaches of inquiry – quantitative, qualitative and mixed-method. A quantitative approach refers to the collection of data that is inherently numerical in nature or can be easily converted to numbers (Leedy & Ormond, 2015). In essence, quantitative researchers use numbers and large samples to test theories.

A qualitative approach in contrast, as described by Corbin (1998), is any type of research that produces findings not arrived at by numerical procedures. Saldana (2011) argues that the qualitative research approach refers to the study of natural social life and the data collected is usually, but not always, non-quantitative in essence. This approach typically involves the study of complex events. Qualitative researchers use words and meanings of a smaller sample size to build theories (Easterby-Smith, Thorpe, Jackson & Lowe, 2012). The researcher moves back and forward between data collection and analysis.

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Creswell (2014) concurs that qualitative research is the collection of data in a natural setting where participants experience the issue under study, use of multiple methods for data collection, for example unstructured interviews and open ended questions. The researcher is the key instrument and the analysis of data is through inductive, deductive and abductive reasoning or approach (Saunders, Lewis & Thornhill, 2016). An inductive approach applies when the researcher collects data and then builds or generates a theory from the data.

This means that the researcher has to go back and forth; through the data and themes until a wide-ranging set of themes is available. In contrast, Saunders, Lewis & Thornhill (2016) state that the deductive approach refers to the building or generating of a theory building on empirical evidence by other scholars and then testing the theory with the data to be collected. Finally, the adductive approach refers to the process where data are collected and themes identified but they will be tested through additional data to be collected (Saunders, Lewis & Thornhill, 2016).

This study opted for a deductive approach because the relevant literature was first studied and then deductions were made based on the data collected. A mixed-method approach involves combining both quantitative and qualitative approaches in the same study (Lichtman, 2014) and this was done in this study. The arguments for this approach lie in the advantages as described by Greene, Caracelli and Graham (1989). This advantage is that the research problem could only be addressed by the collection of quantitative and qualitative data. This study collected qualitative data via in depth semi-structured face-to-face interviews with the SRC, representative on councils, the Vice-Chancellor and the chairpersons of the councils of UNAM and NUST. The quantitative and qualitative data were obtained from the semi closed delivery and collection survey questionnaires for the Pro/Deputy Vice-Chancellors and Deans and with the electronic administrative survey questionnaires employed for the HODs. The Pro Vice- Chancellors refers to the Deputy Vice-Chancellor Academic Affairs and Research at NUST, the Pro Vice-Chancellor: Academic Affairs at UNAM and the Pro Vice-Chancellor Research, Innovation and Development at UNAM.

Document analysis was undertaken by studying the acts and statutes that govern these two public institutions.The data collected via the in depth semi-structured interview (qualitative data), can be complemented by the data collected from the semi closed ended delivery and collected survey questionnaires as well as the electronic administrative survey questionnaires. This will increase the trustworthiness, validity and reliability of the data to be collected. A quantitative study, where results can sometimes seem unpredictable, can be supported by the qualitative data that may disclose underlying meanings and differences that can help a study to make sense of the numbers. Methodological triangulation can be strived for if the quantitative and qualitative data lead to the same conclusion.According to Creswell (2014), there are four types of mixed-method designs – convergent, embedded, explanatory and multiphase iterative. The convergent design refers to time when quantitative and qualitative data are collected simultaneously in regard to the same problem. The researcher gives equal weight to both quantitative and qualitative data, and strives for methodological triangulation.

In an embedded design, the second approach, both quantitative and qualitative data are collected concurrently with regards to the same research problem, but one approach is more dominant, normally the qualitative one. The embedded design consists of two stages. In stage one the researcher uses one or more qualitative instruments, for example interviews and observation, to get a general overview associated to the topic to construct the survey which is used as a quantitative instrument in stage two. The benefit of this design is that the researcher can construct a survey, based on a few interviews, with a large sample. The third approach, namely the explanatory design, works the opposite to an embedded design.

The difference between an explanatory and embedded design is that in the explanatory design the quantitative data is collected in stage one while the qualitative data is collected in stage two. The advantages of this design is that the qualitative data at stage two give more meaning to the quantitative (numbers) collected in stage one and can lead to better instruments when one instrument is not well suited for a sample (Tashakkori & Teddlie, 2010). By contrast the fourth design, the multiphase iterative design comprises three or more phases. The data collected in the earlier phases set the foundation for the data to be collected in the later phases. The outstanding characteristic of this design is that the researcher moves backward and forward between quantitative and qualitative methods. This study opted to employ a convergent design, the first type described above, because the quantitative data and qualitative data are of equal importance to develop a normative leadership model to guide organisational transformation at public institutions of higher learning in Namibia. The characteristic of a convergent design is the quantitative data and qualitative data are collected concurrently.

The concurrent collection of both quantitative and qualitative data can assist to check the accuracy (validity) of the other data base (Tashakkori & Teddlie, 2010). The researcher gives equal weight to both quantitative and qualitative data to ensure methodological triangulation. This study collected the qualitative and quantitative data at the same time.

The quantitative and qualitative data were weighted equally because this study aimed to strive for methodological triangulation.4.3.1 Qualitative research strategiesA research strategy is a step-by-step plan of action that gives direction to the researcher’s thoughts and inputs, enabling the researcher to conduct research systematically within a time schedule to produce quality results and detailed reporting (McKenzie, 2009). Creswell (2014) refers to a case study as a strategy, when a programme, organisation, occasion, activity or process is studied in all its intricacy for a specified period of time.

Leedy and Ormrod (2015) have a very similar definition for a case study which, according to them, is when a particular individual, programme or event is studied in detail for a distinct period of time (Leedy ; Ormrod, 2015). An ethnographic strategy in contrast can be selected when describing the culture and social interaction of a particular group or subgroup (Lichtman, 2014). Creswell (2014) recommends that this strategy is most useful, when the study targets an entire cultural group in a natural location over a lengthy period. A phenomenological strategy applies when one needs to describe and understand the importance of lived experiences of individuals who have experienced a particular phenomenon (Lichtman, 2014) while Leedy and Ormrod (2015) describe the same strategy as a study undertaken to discern people’s opinion and viewpoints in relation to a specific situation.Grounded theory was developed in 1967 by Glaser and Strauss. This approach is used to generate a theory that arises from the data collected (Lichtman, 2014).

Content analysis means an in depth and logical assessment of a particular set of material of human interactions for the purpose of identifying patterns or bias. This material can include books, journals, legal documents, audio visual tapes, and bulletin boards (Leedy & Ormrod, 2015). Historical research strategy refers to the study of how human life activities and institutions change over time. These activities may include languages, art, customs, religions, philosophies and architecture (Leedy & Ormrod, 2015). Stake (2005) argues that a case study is not a strategy, but merely a choice of the place and time of what is to be studied. Merriam (1998), Denzin and Lincoln (2005) and Yin (2014) argue that case studies are strategies. This study concurs with Merriam (1998); Denzin and Lincoln (2005) and Yin (2014) and views a case study as a strategy for inquiry. Creswell (2014) states that there are three types of case studies.

These are a single instrumental case study, collective/ multiple case studies and the intrinsic case study. The first scenario is when a problem or concern is selected and only one case is chosen to illustrate the problem under study. In contrast, a collective case study applies when more than one case is selected to explain the problem under study. The intrinsic case study, on the other hand, focuses on the issue or problem. This study employed a collective case study because the research problem needed to be investigated at both UNAM and NUST to develop a leadership model to guide organisational transformation at public institutions of higher learning in Namibia. Yin (2014) asserts that the process of data collection for a collective case study use, reappearance. This implies that the researcher repeats the procedures for each case.

UNAM and NUST as the two public institutions of higher learning in Namibia were studied as cases.A normative leadership model can be developed to guide organisational transformation at public institutions of higher learning in Namibia. This proposed model can be developed, centred in the literature and on the data collected. The following reasons according to Creswell (2014) support the choice for this particular strategy, namely that a theory is not yet available to explain the impact of the internal perception of leadership on organisational transformation at public institutions of higher learning in Namibia. This study wanted to understand how the responses of the council, executive, middle and lower management of academia perceive leadership at these institutions and how it may impact organisational transformation. A model can be developed from the data collected taking into consideration the following approaches as claimed by (Clarke, 2003).

These approaches include situational social arena and positional cartographic maps. 4.3.

2 Quantitative strategyThe research genre distinguishes between five types of quantitative strategies. These strategies are descriptive, experimental, quasi-experimental-, ex post facto and factorial research strategies (Leedy & Ormrod, 2015). The aim of descriptive strategies is not to change the situation under study nor to determine the cause-and-effect relationship. On the contrary, an experimental researcher considers all possibilities that may influence a particular occurrence. The researcher will then take all possible efforts to control all influencing factors, except those whose possible effects are the focus of the study. Creswell (2014) argues that the test of the impact of an interference on an outcome might control all other factors that might influence that outcome. Observation studies as a design can be applied to study all living organisms, except animals (Leedy & Ormrod, 2015). When this strategy is employed for animals one should consider that observation design has a limited and predetermined goal.

This means that the behaviour and/or characteristics should be quantifiable. A correlation strategy examines the range to which variances in one variable relate with variances in one or more other variables (Leedy & Ormrod, 2015). A development design can be realistic when a researcher wants to study how certain characteristics change when people get older (Leedy and Ormrod, 2015). The two developmental designs that can be used are either a cross-sectional or a longitudinal study. Survey research, according to Creswell (2014), provides a numerical description of trends, opinions and attitudes of a population, by sampling that population. Welman and Kruger (2005) deny that all types of experimental research are characterised by interference. That means all the participants are exposed to the same interference that they would not have been exposed previously. Pre-experimental strategy according to Leedy and Ormrod (2015) is applicable when no relationship exists between the population and the problem being studied.

This denotes that the independent variable does not vary and that the population groups do not consist of equal or randomly selected individuals. True experimental strategy, by contrast, offers a greater degree of control by the researcher over the variables and the population. This will ensure internal validity. A quasi-experimental strategy is used when it is impractical and impossible to apply randomness when choosing the group members or groups. The advantage of this type of study (Leedy & Ormrod, 2015) is that it eliminates different explanation of the results. The ex post facto strategy applies when the researcher first identifies events or actions that already took place. The data is then collected to assess the relationship of these events and actions on the behaviour and characteristics on the stratum of the population (Leedy & Ormrod, 2015).

The factorial strategy applies when the researcher want to examine the impact of two or more independent variables (Leedy & Ormrod, 2015). Quasi-experimental strategy in contrast is use when the variables cannot be controlled, which means the researcher cannot entirely rule out alternative explanations for the data when it is obtained (Leedy & Omrod, 2015). Ex-post facto in contrast provide an alternative means by which a researcher can investigate the extent to which a specific independent variable (for example; history of a family, lack of education, personality trait, may possibly affect the dependent variable of interest, for example; leadership (Leedy & Omrod, 2015). The study employed the Quasi-experimental strategy because the researcher cannot entirely rule out alternative explanations for the data when it is obtained.


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