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framework for collecting and analysing data. They go on to say that it enables the researcher to examine the research problem.
This study was designed as an exploratory interpretive case study. According to Zaidah (2007) an exploratory case study seeks to investigate or explore a phenomenon of interest in a chosen field. For the current study, a case study enabled the researchers to get in-depth and detailed understanding of the mathematics teachers’ knowledge of students’ learning styles and how the teachers used the knowledge in mathematics teaching. The choice of a case study was supported by a number of scholars who argued that a case study allows for an in depth study of a phenomenon in a real life situation (Baker, 1999; Creswell, 2010; McMillan
& Schumacher, 2010; Yin, 2009). The number of mathematics teachers who participated in this study also made a case study the most suitable design. This was in line with the assertion by Welman and Kruger (2001) that a case study deals with a small number of units (individuals, groups or institutions) which are studied intensively. Thirty-four mathematics teachers participated in this study.
64 4.3.2 The participants
Secondary school mathematics teachers at selected secondary schools participated in the study. Table 4.1 shows the demographic information of the mathematics teachers who participated in this study.
Table 4.1: Participants’ demographic information (n=34)
Sex
Teaching experience in full years Highest professional qualifications Less
than 5
Between 5 and 10
More than 10
Diploma in Education
Bachelor’s degree
Master’s degree
Males 10 6 6 4 14 4
Females 2 1 9 4 8 0
Total 12 7 15 8 22 4
All the mathematics teachers who participated in this study had at least a diploma in education as their highest professional qualifications. All of them were qualified teachers who were trained to teach mathematics at secondary school level. Both male and female teachers participated in the study.
4.3.3 Sampling method
Creswell (2010) described sampling as a process used to select a portion of a given population for purposes of carrying out a study. The portion of the population that is selected for study purposes is called a sample (McMillan &Schumacher, 2010). The sample is studied in an effort to understand the population from which it is drawn. Researchers are interested in describing the sample, not primarily as an end in itself, but rather as a means of helping them to explain some facet of the population (De Vos, Strydom, Fouche & Delport, 2000; Bryman, 2012).
There are two main categories of sampling methods that can be used in research. These are probability sampling and non probability sampling. With probability sampling every member of the population has a chance of being selected while with non probability sampling some members of the population have better chances of being selected than others. (Machaba, 2013). According to Machaba, probability sampling methods include simple random sampling, stratified sampling and cluster sampling. Simple random sampling is the basic form of probability sampling in which all the members have an equal chance of being selected and
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the members are selected at random. Stratified sampling involves dividing the population into clusters. Members are then chosen from each cluster in a proportional manner so that each cluster is represented. Cluster sampling involves treating clusters as sampling units. Simple random sampling is then used to select clusters at random. All the members in the selected clusters participate in the study.
On the other hand, non probability sampling methods include convenience sampling and purposive sampling among others (Bryman, 2012). Convenience sampling is a sampling method in which the researcher chooses a sample that is most convenient to him or her.
Purposive sampling involves choosing members that bear the most wanted characteristics.
Both probability and non probability sampling methods can be used in qualitative research (Machaba, 2013). According to Creswell (2010), sampling in qualitative research is flexible and often continues until new themes no longer emerge from the data collection process. This is referred to as data saturation. Qualitative researches usually require smaller sample sizes as compared to quantitative researches (Machaba, 2013). However the researcher should make sampling decisions that lead to selection of the richest possible sources of data in order to rightfully answer the research questions.
For this study, different sampling methods were applied at different levels of selection.
Makoni District in Manicaland Province was selected using convenience sampling. As stated earlier in this report, convenience sampling is a non probability sampling method that involves the sample being drawn from a portion of the population that is close at hand (Dudovskiy, 2012). The district was found to be convenient to the researcher. Its size as compared to other districts in the country was also considered. The use of convenience sampling at this level had some advantages. It made the research less expensive and the mathematics teachers were easy to get.
The secondary schools that were used in the study were selected using stratified random sampling method. Stratified random sampling refers to a probability sampling method in which the researcher divides the population into separate groups called strata and the subjects are then selected proportionally from the different strata (Foley, 2018). Black (1999) supported the use of stratified random sampling by saying that stratified random sampling ensures that groups are proportionally represented in the sample. The schools were first grouped according to their responsible authorities: Zimbabwe government, individuals, churches and local councils. The responsible authorities were treated as the strata. Ten
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secondary schools were selected from the eight-nine schools in the district. Stratified sampling method at this stage had the following advantages:
(i) The researcher made sure that the sample is heterogeneous
(ii) The sample was representative of the population of the schools in the district since each category of schools was represented.
Table 4.2 shows the number of schools selected from each group of responsible authorities.
Table 4.2: Number of schools selected from each group of responsible authorities in the district
Responsible authorities Total
Zimbabwe government Individual Church Local council
Number selected 1 1 2 6 10
Total in district 4 4 12 69 89
Mathematics teachers at the sampled schools were chosen to participate in this study. All of them participated in the study at one stage or the other. These teachers were selected purposefully because the aim of the study was to explore mathematics teachers’ knowledge of their students’ learning styles and how they used the knowledge in mathematics teaching.
For that reason, mathematics teachers were the richest source of the required data for this study. The use of purposive sampling method in selecting the mathematics teachers was supported by White (2005) who stated that in purposive sampling the researcher chooses the
‘information rich’ participants as they are possibly knowledgeable in the phenomenon under study. White goes further to say that the judgment in purposive sampling rests entirely with the researcher.
The sample comprised thirty-four mathematics teachers who were all trained to teach mathematics at secondary school level. As stated earlier, they were holders of at least a diploma in education. Their teaching experience ranged from two to thirty six years.