According to Babbie and Mouton (2001:74), the research design is a plan or blueprint of how a researcher systematically collects and examines the data required to answer the research questions. It is the scheme, outline, or plan that is used to generate answers to research problems.
When designing a mixed methods study, three issues need consideration, namely, priority, implementation and integration (Creswell and Clark 2018). Priority refers to which method, either quantitative or qualitative, is given more emphasis in the study. Implementation refers to whether the quantitative and qualitative data collection and analysis come in sequence or chronological stages, that is, one following another or in parallel or concurrently.
Integration refers to the phase in the research process where the mixing or connecting of quantitative and qualitative data occurs.
The research design in this study falls within what Teddlie and Tashakkori (2009) call “quasi-mixed” designs.
This is because the study followed a dominant and a less dominant design. The quantitative strand in the study was the dominant strand. The dominant and less dominant designs are designs where two types of data are collected, namely, quantitative and qualitative, with little or no integration of the two types of data. Hence Teddlie and Tashakkori (2009:147) argue that “dominant and less dominant designs are quasi-mixed in nature rather than being genuinely mixed”. The term quasi-mixed design helps the researcher distinguish technically mixed studies from studies that are truly mixed because the latter are able to meaningfully integrate quantitative and qualitative findings (Teddlie and Tashakkori 2009).
There are several designs in mixed methods research such as embedded, multi-level and sequential designs. The study adopted the partial concurrent dominant status design because it mixes the results only at the interpretation stage. Moreover, the concurrent design saved the researcher’s time as the study phases occurred in a parallel manner. In this design, quantitative and qualitative data collection is done concurrently, with the quantitative strand being the dominant strand. The less dominant qualitative strand played a complementary role and corroborated the quantitative results with qualitative findings. Thus, data collection was conducted concurrently at the implementation stage, and integration of the results was done during the interpretation phase. A partially mixed methods design, therefore, involves conducting a study in which one mixes the quantitative and qualitative portions of the study at specific stages. Scholars such as Doyle, Brady and Byrne (2009), and Venkatesh, Brown and Sullivan (2016) hold that mixing occurs at the data interpretation stage in partially mixed designs.
96 To achieve integration, the study used the triangulation protocol. The quantitative and qualitative data were collected and analysed separately from each other to produce two data sets in the triangulation protocol. The purpose of the triangulation protocol is to describe corroborations between the two sets of findings. The process of triangulating findings from the two different methods occurred at the interpretation stage of the study when both data sets had been analysed separately. According to O’Cathain, Murphy and Nicholl (2010), the process of triangulation comprises several steps, namely, sorting, convergence coding, convergence assessment, completeness assessment, researcher comparison, and feedback. To implement the triangulation protocol in the current study, the researcher sorted the findings related to the research questions from each data set, that is, the survey and interviews. The researcher then reviewed the analysis to identify themes emerging from the data sets to create a unified list of themes to compare for presence, frequency, and meaning. According to O’Cathain, Murphy and Nicholl (2010), these themes form the rows of the convergence coding matrix used to summarise similarities and differences between the two sets of data. Finally, the researcher conducted convergence coding which involves comparing the data sets to understand the meaning and interpretation of themes, their frequency and their prominence. The researcher also assessed what Fetters, Curry and Creswell (2013) call the “fit” of data integration, which is the coherence of the quantitative and qualitative findings.
The nature of the study also warranted the use of the design because of the need to understand the multi- dimensional aspects of information culture and records management. The benefits of using a parallel design method include the efficiency of data collection.
4.4.1 Survey
A survey is one of the oldest research designs and the most regularly used design across disciplines (Babbie 2013).
According to Leedy and Ormrod (2010:186), “survey research involves acquiring information about one or more groups of people about their characteristics, opinions, attitudes or previous experiences by asking those questions and tabulating their answers”. Surveys are a popular data collection method for academic or marketing research in various fields. With the increase of internet penetration globally, internet-based data collection techniques such as online questionnaire surveys have become popular in recent years.
This study conducted an online survey. An online survey is similar to a paper version of the survey. However, the data collection strategies differ in that in an online survey, as its name indicates, questionnaires are distributed and the responses are received via the internet. Regmi, Waithaka, Paudyal, Simkhada and Teijlingen (2016) posit that data collection through an online survey appears to have the potential to efficiently collect large amounts
97 of data economically and within relatively short time frames. The online survey approach is also beneficial when collecting data from hard-to-reach populations. Moreover, the Covid-19 pandemic had minimised face-to-face human interaction and the online survey, in these circumstances, is very useful; hence its employment in the current study. The survey was managed using REDCap, a web application for conducting online surveys. A link to the questionnaire was sent via email to the study participants.
One of the characteristics of a survey that made it attractive to this study is that it describes trends and helps identify individuals’ beliefs and attitudes. The researcher, via the survey, collected quantitative data and used statistical analysis to describe trends in the responses to the questions and to test research questions. The researcher adopted an online survey design because it is less expensive and can be conducted in a short time.
Moreover, as alluded to above, it helped the researcher to adhere to the Covid-19 social distancing rules. The design was appropriate as it allowed for the description, classification and interpretation of the research questions posed. Importantly, Babbie (2013) asserts that a survey is suitable for measuring attitudes and orientations. The advantages of the method lies in the possibility of scanning a broad spectrum of issues, populations and programmes (Cohen, Manion and Morrison 2007). A survey uses a predetermined sampling plan, which determines how respondents are to be selected. Therefore, it is possible to estimate how accurately the sample represents the population. Unlike other designs such as observational or experimental studies, the sample in a survey tends to be larger. A survey is inexpensive, is thought to be more objective because of standardised measurements, and can cover a large sample (Neuman 2014).
Critics of surveys mostly focus on philosophical, technique-based and political reasons to reject them. According to De Vaus (2013:7), the philosophical reason for rejecting the survey is its inability to get meaningful social action aspects. Surveys only look at particular aspects of people’s beliefs and actions without looking at the context in which they occur. Surveys seem to assume that human activities are determined by external forces and neglect the role of human consciousness (De Vaus 2013). A technique-based criticism of surveys is that they are restrictive, relying on a highly structured questionnaire. Political criticism is based on the survey being ideologically manipulative. In this regard, De Vaus (2013:123) points out that “it does not produce knowledge about reality but is an ideological reflection whose acceptance by the public furthers particular interests”.
Furthermore, Creswell (2014) points out that a survey cannot explain cause and effect as experimental research can do. It describes trends in data rather than offering explanations. The survey’s focus is directed towards learning about the population and less on relating variables or predicting outcomes.
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