Triangulation

Triangulation refers to the use of multiple sources of data to improve the quality of the research findings (Merriam, 2009: 166). These together ensure inclusion of multiple perspectives in the data collection process and thus the possibility of errors or misinterpretation can be reduced. Typically, triangulation fulfils the ethical need to validate the research findings through inclusion of varied sources of data that provide a better understanding of the research subject. Triangulation also increases confidence in the findings of the research due to the inclusion of multiple perspectives (Brannen, 2004: 314). Ritchie and Lewis (2003: 44) however point out that even though triangulation enables development of the broad picture, the certainty of the findings cannot be fully assured through this. However, multiple perspectives and triangulation still improve the validity of qualitative research (Creswell, 2014: 525).

Triangulation can be accomplished through various manners, and there are four common models of triangulation in research: methodological triangulation, data source triangulation, multiple researchers triangulation and theory triangulation (Patton, 1999). Probably the most common type, the triangulation of methodological approaches typically involves a combination between qualitative and quantitative methods of data collection and analysis (Yeasmin and Rahman, 2012). As Patton (1999: 1193-1194) argues, the fundamental benefit of this approach is that “quantitative methods and

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qualitative methods are used in a complementary fashion to answer different questions that do not easily come together to provide a single, well-integrated picture of the situation”, thus effectively attempting to surpass the weaknesses of both methods. However, there are several disadvantages for employing this method, given that may take a long period of time (Knafl and Breitmayer, 1991), that researchers may not be capable of conducting both qualitative and quantitative research (Patton, 1999), or that it does not guarantee the desired effects if it is improperly implemented (Thurmond 2001).

Another common type of triangulation focuses on the sources from which the data is collected, and through the use of multiple methods, to verify “the consistency of information derived at different times and by different means within qualitative methods” (Patton, 1999: 1195). More specifically, for qualitative data triangulation, information should be collected through at least two methods, such as by employing various types of interviews (i.e. semi-structured, structured or unstructured), by collecting information from documents, by employing observations, and so on (Yeasmin and Rahman, 2012). Additionally, regarding primary data, the people who take part in interviews, surveys or questionnaires may be selected from different backgrounds or from different locations, in order to ensure that the findings are valid, and that comprehensive insight into a topic is gathered (Thurmond, 2001). Taking into account secondary data, the collection of a wide array of information can be done by considering various fields of study, locations (such as different countries, different institutions), or even at different times, so as to identify similarities and discrepancies (Knafl and Breitmayer, 1991). However, as Knafl and Breitmayer (1991) argue, this type of triangulation can be lengthy, and the large amount of gathered data would mean that an ample data analysis process also needs to be conducted if all of the information is to be taken into account.

The third type of triangulation refers to the involvement of multiple investigators in the collection and interpretation of data (Yeasmin and Rahman, 2012). While this type of triangulation may help overcome researcher bias (Patton, 1999: 1195), it can only be successful if the researchers have similar perspectives, objectives and understandings of the targeted phenomena (Thurmond, 2001). Any discrepancies in said factors may thus result in confusion and in a lack of research clarity.

Lastly, the fourth type of triangulation requires the employ of several theoretical perspectives when interpreting the chosen phenomena (Thurmond, 2001). It is a common

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understanding that these perspectives need to be chosen from established theoretical frameworks (for instance, phenomenology, ethnography, and so on). However, Patton (1999: 1196) suggests that theoretical triangulation may also refer to the interpretation of data “from the perspective of various stakeholder positions within different theories of action about a program”. Patton (1999: 1196-1197) continues to explain that stakeholders commonly “disagree about program purposes, goals, and means of attaining goals”, and that “these differences represent different theories of action that cast findings in a different light”. Similarly, Denzin (1989: 239-240) has argued that theoretical triangulation should concern itself with the interpretation of multiple “theoretical points of view”. The triangulation case argued by Patton (1999) thus allows for a more thorough examination of data in a local setting, especially when seeking to pinpoint inconsistencies or to validate the actions taken within an institution.

Triangulation in the Current Study

The triangulation types that have been employed in the current study consist of the model for triangulation data based on theory, and the model regarding the sources of the data gathered.

Concerning the former triangulation model, the primary data that was collected through interviews, although collected from the same location (i.e. the women’s section of KAU), it has been collected from 3 groups of stakeholders, with the goal of avoiding participant bias and revealing possible discrepancies. This allowed me to identify and examine the perspectives, understandings and experiences of various employees at KAU, who unsurprisingly offered different answers to numerous questions. I sincerely believe that, had I not contacted 3 different groups of KAU employees, I would have ended up with less reliable, less diverse and less realistic primary data. As an example, the managers at KAU have typically responded in a more optimistic manner to some questions, while the employees and lecturers have offered more critical answers. This discrepancy allowed me to further examine some issues (see for instance sec. 4.1.3. – I. Governance), which could have been disregarded or insufficiently explored under different circumstances.

Regarding the latter, the process of data source triangulation is present in the current study from two perspectives. Firstly, the secondary data has gone through all the elements of this process, as I have collected information from a wide variety of sources, including

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peer-reviewed material from different time periods, sources (both individual and official) and worldwide locations. This allowed me to ensure that the secondary data is critical and diverse. Secondly, the researcher made use of two methods to gather primary information, respectively semi-structured interviews and documentation. In the research process, the data was collected through interviews conducted with employees at various levels in KAU and afterwards cross-checked with data from official documents, to ensure the trustworthiness of the research findings. As a result, the researcher was able to confirm or disprove the details surrounding the implementation of the SE process in the women’s section of KAU in 2012, the lack of funding and research, issues relating to centralisation, QA standards and SE procedures, and so on. More specifically, the process of source triangulation started with an extensive examination of numerous official documents from the Ministry of Higher Education (MoHE) in the KSA, from the NCAAA and from the chosen HEI, the KAU. The researcher proceeded to systematically identify which of the documents that were made available could offer information that was relevant to the subject. It is important to note that not all of the documents used in this study have been identified at the time when I went to gather data in the KSA. Nevertheless, after examining various official documents throughout a three-year period (2012-2015), such as reports, records, archives, the researcher decided that 7 documents, which are outlined in Section 3.3.2. (Documents), were the most useful in both supporting and advancing the topic of QA in the KSA. To clarify, once I had concluded the interviews and commenced with their analysis, and especially once the coding process for the interviews had been finalised, I decided to also seek out the identified codes in the documents, as I believed that following them in the documentation analysis would allow me to further systematise my findings. In essence, I sought to find key words and phrases that were similar or relevant to the codes from the interviews, and once everything had been labelled, I began to verify the validity of the participants’ answers by cross-checking them with information from the chosen documents. As a result, the findings chapter and each subsequent subchapter not only details the remarks given by the interview participants, but also features the official interpretations and observations of the MoHE, the KAU and the NCAAA.

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