Tareas de Sentidos no literales del lenguaje

It is important to note that the fifty teachers who completed pilot questionnaires were not included in the sample who later took part in the main study, following the advice of Bryman (2012) that the “the pilot should not be carried out on people who might have been members of the sample that would be employed in the full study” (p.264).

This section discusses the principles of sampling, their application to the main questionnaire survey, then its administration and conduct.

4.10.1 Sampling

The population and target population of any study should be clearly and accurately defined to ascertain an appropriate and archetypal sample. Population can be defined as “an aggregate of all cases that conform to some designated set of criteria” (Blaikie, 2010, p.173). A survey population is the people or phenomena involved in the study and from whom the researcher selects a sample (Lewin, 2005). The researcher must choose suitable subjects in a suitable environment representative of the general population. According to Gall et al. (2007) and Naoum (2007), a sample may be in the form of a specimen that can be drawn by the researcher to reveal what the entire population is like and to which research results can then be generalised.

Whenever a researcher seeks to make a generalisation about the findings of a study, it is essential to consider the sampling process. The two primary sampling procedures are probability and non-probability sampling. A probability sample is representative and

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the results can be applied to the entire population, as every member of that population has a known and equal chance of inclusion (Adler & Clark, 2011; Cohen et al., 2011; Pole and Lampard, 2002; Robson, 2011). Rubin and Babbie (2013) assert that probability sampling is more representative than other methods because it avoids selection bias. There are many different forms of probability sampling, including simple random sampling, systematic sampling, stratified sampling, cluster sampling and multi- stage sampling (Cohen et al., 2011; David & Sutton, 2011).

By contrast, non-probability sampling does not entail representing a larger population. Several authors advise of the risks of likely bias in sampling when every person in the target population does not have the same chance of being chosen for the study sample. According to Adler and Clark (2011), bias from that source may generate deceptive or inaccurate results. Consequently, generalisations cannot safely be made about the population (Pole & Lampard, 2002). Nevertheless, where there is no means to draw a random sample, the researcher will have to use a non-probability sample to gain access to members of the population who are willing to participate (David & Sutton, 2011). The three major kinds of non-probability sampling are convenience sampling, quota sampling and snowball sampling (Bryman & Bell, 2011; Cohen et al., 2011).

There is no ideal sample size applicable to all studies, as the nature of the population and the study objectives will vary (Bryman & Bell, 2011; Cohen et al., 2011). In practice, a number of scholars propose that quantitative research should use larger samples than qualitative research, where the sample size is generally smaller (Cohen et al., 2011; Sarantakos, 2013; Punch, 2009). Although concerns of time, money and organisational help, among other practical resources, may affect sample size (Cohen et al., 2011), a large sample is often favoured in order to ensure accuracy and reliability (Juliet, 2002). Thus, VanderStoep and Johnston (2009) posit that “The more people in the sample, the more it will ‘look like’ the population and thus the variability (margin of error) will be reduced” (p.29). Likewise, Robson (2011) suggests that the larger the sample, the smaller the possible error in generalising.

4.10.2 Sampling procedures for the questionnaire

In the current study, the researcher decided to use probability sampling, in order to ensure that the informants were representative of a specific identifiable population, namely male secondary school teachers in Saudi Arabia, and to allow the generalisation

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of the findings from the sample to the whole of this population. The specific method used was multi-stage cluster sampling, which Adler and Clark (2011) describe as “a probability sampling procedure that involves several stages, such as randomly selecting clusters from a population, then randomly selecting elements from each of the clusters” (p.122). This procedure was implemented as described by Robson (2011) and Bryman (2012).

Before selecting the final sample elements, the researcher conducted three stages of cluster selection. In the first stage, an educational province (Riyadh) was selected from the total of 13 Saudi provinces. Subsequently, the Riyadh District was also chosen from the 12 national educational regions, being the largest amongst them. In addition, Riyadh city, which lies within the Riyadh district, is the most populous city in the Kingdom and its capital. It should also be noted that there are 11 educational supervision centres in Riyadh, covering the 89 male secondary schools spread throughout the city. Each centre is responsible for supervising and managing several schools and educational institutions, which may differ greatly from one centre to another.

To ensure proportionality in the selection of schools, the researcher used the random sampling technique. First, he calculated the number of schools in each centre and sought to obtain a list of the names of all schools under each educational centre, then assigned a code number to each school. The researcher wrote the numbers on slips of paper and put these into a container, from which he picked one number at a time until he had reached an appropriate sample of four schools from the first educational centre, a procedure which he repeated for the remaining centres. In this way, he selected 40 schools with a total of about 1020 teachers, each of whom was invited to complete a self-administered questionnaire.

There were a number of reasons for selecting the sample from the population of Riyadh City, apart from its being the capital city of the Kingdom of Saudi Arabia and the largest city with the greatest number of inhabitants. Importantly, the city represents a truly diverse societal mix within the Kingdom. Riyadh also has the largest number of schools, students and teachers in Saudi Arabia (MoE, 2009). Another consideration is that it is the researcher’s home city, where he was formerly employed in the education sector, which was seen a factor facilitating the data collection process. In a country as large as Saudi Arabia, it would have been extremely difficult to obtain a sample of

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schools representative of the entire country, given the limited time and funding available to the researcher for data collection. The same limitations made it unfeasible to sample the wide geographical area of a whole educational district. However, the Saudi educational system is under the centralised and unified control of the MoE, so that any developments can be assumed to affect equally all regions and all parts of any given region. Thus, a sample limited to Riyadh City could be seen to represent the various districts within the region. Similarly, aspects of job satisfaction and motivation in that city could be seen as analogous to those applicable to secondary schools situated in other cities in Saudi Arabia.

As a final point, it is worth noting that the majority of the research carried out by male researchers in Saudi Arabia has so far been confined to all-male educational institutions. The current study was no exception since, as stated in Chapter Two, an important aspect of Saudi culture is that boys and girls are not permitted to interact in any educational settings. It would therefore have been difficult for the researcher himself (being male) to gain access to girls’ schools, so the study was confined to boys’ secondary schools.

4.10.3 Administrative preparation for the questionnaire

Before leaving the UK to conduct the questionnaire survey, the researcher was required to obtain permission from the Saudi Ministry of Education to collect this quantitative data from teachers. First, the researcher’s university supervisor addressed a letter to the Saudi Cultural Bureau in London, stating the researcher’s need to conduct this phase of the study (Appendix C). The Cultural Bureau accordingly issued a letter to the MoE requesting the facilitation of the data collection process, along with a letter from the researcher himself requesting permission to conduct the field study without hindrance (Appendix C). The Ministry granted preliminary approval and communicated it to the cultural attaché in London, which allowed the researcher to implement the research tools providing that an application was made specifying the requirements (Appendix C). In addition, the researcher had to attach forms outlining the research tools to be used and describing the study sample. In order to save time, he attached a copy of the questionnaire in an email to the Cultural Bureau, which stated that it was willing to cooperate and grant such access.

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Upon arrival in Saudi Arabia, the researcher approached the MoE again, submitting another formal request to be approved by the relevant authorities. To meet the Ministry’s requirements, he supplied a copy of the questionnaire. Within three days, the MoE (General Directorate for Research) issued an approval letter informing the Director of Education Planning and Administration in the General Directorate of Education in Riyadh of the Ministry’s willingness to facilitate the field study and the researcher’s application of his research tool (Appendix C). A final letter of approval was also issued on January 2011, addressed to the headteachers of schools where the research would take place, which the researcher presented upon request during his visits to these schools (Appendix C). The survey was conducted during January and March 2011.

4.10.4 Conductof the questionnaire survey

The researcher visited each school by arrangement, introduced himself to the principal and delivered the permission letter, elucidating the aim of the research and its significance. All principals were helpful, supportive and very welcoming. The researcher then handed over enough copies of the questionnaire for one to be distributed to each teacher at the school. While requesting the participants’ assistance in replying to the questionnaire, the researcher stressed that their participation was entirely voluntary. The researcher allocated a week for completing the questionnaires, after which he returned to each school to collect them. However, some respondents needed more than a week, in which case the researcher returned later to collect any remaining completed questionnaires. In total, 1020 questionnaires were distributed and 737 were completed, representing a 72% response rate, while a further 15 were returned but were not completed.

The questionnaire data were then collated and analysed as outlined in the next section.