Triangulation, Validation, and Verification

4.10.1. Triangulation of Data and Methods

The triangulation approach to research puts an emphasis on increasing the quality and reliability of the research by using more than one source of data or employing more than one methodology. Yin (2009) believes that “any of the preceding sources of evidence can and have been the sole basis for entire studies. For example, some studies have relied only on participant-observation but have not examined a single document; similarly, numerous studies have relied on archival records but have not involved a single interview. This isolated use of sources may be a function of the independent way that sources have typically been conceived - as if an investigator should choose the single most appropriate source or the one with which she or he is most familiar. Thus, on many an occasion, investigators have announced the design of a new study by identifying both the problem to be studied and the prior selection of a single source of evidence - such as ‘interviews’ as the focus of the data collection effort”.

Regarding the rationale for employing data triangulation, Yin (2009) mentions “the approach to individual source of evidence as just described, however, is not recommended for conducting case studies. On the contrary, a major strength of case study data collection is the opportunity to use many different sources of evidence.

Furthermore, the need to use multiple sources of evidence far exceeds that in other research methods, such as experiments, surveys, or histories. Experiments, for instance, are largely limited to the measurement and recording of actual behaviour in a laboratory and generally do not include the systematic use of survey or verbal information. Surveys tend to be the opposite, emphasising verbal information but not the measurement or recording of individual behaviour. Finally, histories are limited to events in the ‘dead’ past and therefore seldom have any contemporary sources of evidence, such as direct observations of a phenomenon or interviews with key actors.

“Each of these strategies can be modified, creating hybrid strategies in which multiple sources of evidence are more likely to be relevant. An example of this is the evolution of ‘oral history’ studies in the past several decades. Such studies involve extensive interviews with key leaders who have retired, on the stipulation that the interview information will not be reported until after the leader’s death. Later, the

historian will join the interview data with the more conventional array of historical evidence. Nevertheless, such a modification of the traditional methods does not alter the fact that the case study inherently deals with a wide variety of evidence, whereas the other methods do not.

"The use of multiple sources of evidence in case studies allows an investigator to address a broader range of historical and behavioural issues. However, the most important advantages presented by using multiple sources of evidence is the development of converging lines of inquiry, a process of triangulation and corroboration emphasised repeatedly in the previous section of this chapter. Thus, any case study finding or conclusion is likely to be more convincing and accurate if it is based on several different sources of information, following a corroboratory mode”

(Yin, 2009).

Patton (2002) discusses four types of triangulation in doing evaluations. The types of triangulation are as follows: Data triangulation (of data sources), Investigator triangulation (among different evaluators), Theory triangulation (of perspectives in the same data set), and Methodological triangulation (of methods).

4.10.2. Validity and Reliability

Validity relates to whether the research instrument assesses what the researcher envisioned to study and measure (Kirk & Miller, 1986). Five types of validity exist, namely: content, predictive, concurrent, construct and face validity (Burns, 2000).

This research does involve some measurements (calculating Frequency of 'agree' or 'disagree' views with each proposition) by using a Likert scale (five-scale form).

Therefore, the validity of the study is relatively high in all types of validity.

Reliability relates to the dependability and the consistency of the research findings.

This means, that if the research was repeated, would the findings be the same (Saunders et al., 2009). In addition to very comprehensive Research Methodology chapter, this research has developed its own ‘Research Protocol’, which illustrates details of every step in the ‘Research Process’. So the research can be repeated.

The reliability and validity of this research is high, as reliability of primary data collected have been increased via face-to-face interviews to reduce vague and missing responses and increase the rate of response. Furthermore, the stratified random sampling has ensured that all Saudi and British academics have an equal chance of

being selected and there is no bias in selection. Thus, reliability and validity of data collected will be ensured.

Academics’ perspectives regarding quality of education may change with time.

Nevertheless, since the study has been cross-sectional and not longitudinal, this reduces validity of findings (Babbie, 2010; Landsheer & Boeije, 2010) as in order to comprehensively study the influential factors on quality of education, data requires to be collected more than once over a period of time (Cook & Campbell, 1979).

Analysis of the findings show strong proof of the validity of the Education Quality Model; however, for more certainty about the model it was decided to ask participants (those who already given interviews) views about the model.

Consequently, the researcher randomly selected 30 academics who had already participated, 15 Saudi and 15 British. The researcher emailed the model to these 30 academics to ask their opinions. Twenty-six academics replied. As a result, all of them agreed that the model is valid (100% validation) and the model demonstrates the influential factors on the quality of education in a very logical way.

4.10.3. Verification

Data collection, data analysis and the development and verification of propositions are very much an interrelated and interactive set of processes (Kvale 1996).

According to Saunders and his colleagues (2009), verification is a form of triangulation. Verification is the process of checking, confirming, making sure, and being certain. In qualitative research, verification refers to the mechanisms used during the process of research to incrementally contribute to ensuring reliability and validity and, thus, the rigour of a study (Morse et al., 2002).

It is highly recommended to try triangulating the findings with other independent data sources. This is sometimes referred to as a cross-check verification (Patzer 1996). Where data from two or more independent sources suggest similar conclusions, researchers can have more confidence that the data on which they are based are not distorted. Conversely, where data suggest different conclusions researchers need to be more wary of the results (Saunders et al., 2009).

One type of verification is ‘informant verification’. In ‘informant verification’, a researcher conducts an informal discussion with participants, then writes these up, including her/his own conclusions as to the meanings of the discussions in the light of

her/his research hypothesis. The researcher then presents the written text to the informants (research participants) for them to verify the content. Not only is this a form of triangulation, but it can be a source of new interpretations that have not occurred to the researcher. This method of triangulation is also one that can be used with more formal interview results (Saunders et al., 2009).

Although Guba and Lincoln (1981) described member checks as a continuous process during data analysis (for example, by asking participants about hypothetical situations), this has largely been interpreted and used by researchers as verification of the overall results with participants. While it is an attractive idea to return the results to the original participants for verification, it is actually not a verification strategy. In fact, several methodologists (Hammersley, 1992; Morse, 1998), including Guba and Lincoln (1981), have warned against the tendency to define verification in terms of whether readers, participants, or potential users of the research judge the analysis to be correct, stating that it is actually more often a threat to validity (Morse et al., 2002).

Verification strategies that ensure both reliability and validity of data are activities such as ensuring methodological coherence, sampling sufficiency, developing a dynamic relationship between sampling, data collection and analysis, thinking theoretically, and theory development (Morse et al., 2002). In this research, an attempt was made to use all of these verification strategies by relying on a mainly qualitative research design instead fully qualitative one, using a probability sampling techniques (stratified sampling), having a relatively good sample size (63 participants), findings are analysed based not only on 15 cases, but are also country-based (Saudi and Britain), developing the Education Quality Model instead of testing one existing non-customised model, and finally, the Education Quality Model was sent to participants and had their approval.