Chapter 1 Introduction
3.3 Mixed-methods research
70
The researcher would need to ensure that his methodological approach to data collection, data management, coding, analysis and interpretation were given proper attention.
Additionally, the researcher also needed to ensure the privacy and confidentiality of the information and answers from each individual and therefore allow the teachers to be at ease and feelcomfortable, with no coercion and no presence as an authoritative figure in eliciting and collecting answers from them, as he tried to collect and triangulate his data from the teachers. The researcher needed to ensure that he constantly kept an open mind during the interviews, to ask questions when needed and not to assume things: to check on assumptions while maintaining focus on his research topic. Rapport building and a sense of mutual trust in the relationship between the teachers and the researcher were important to elicit the teachers’ experiences, opinions and their wealth of knowledge regarding the research questions. In the data collection, the power imbalance between, the researcher as the lecturer, and the teacher was avoided by conducting the interviews whenever the teachers were free, and prior to the interviews by chatting with the teachers informally. The researcher also informed teachers about preserving each teacher’s privacy and confidentiality.
71
methodologies in the same study (Creswell, 2013). While some scholars remain deeply rooted in distinguishing the value of quantitative versus qualitative research methods, other scholars advocate views of these methods that are complementary. Qualitative results can be used to support or explain quantitative results and vice versa (Creswell, 2013). The mixed-methods approach has emerged, engaging and elaborating the method in journals, at conferences, and in books where specific procedures for “mixing” have been developed, including designs and mixed-methods questions (Creswell, 2013).
3.3.1 Mixed-method research: Strengths and weaknesses
Mixed-method research has strengths and weaknesses (Johnson & Onwuegbuzie, 2004).
Mixed-methods research provides strengths that counterbalance the weaknesses of both quantitative and qualitative research. One might argue that quantitative research is weak in understanding the research context because the verbal responses of participants are not directly heard. Also, quantitative researchers are in the background, and their own personal biases and interpretations are not often discussed. Qualitative research makes up for these weaknesses as Johnson and Onwuegbuzie (2004) point out that in mixed- methods research qualitative data findings in form of words, pictures and narratives can be used to add meaning to quantitative results in form of numbers. On the other hand, qualitative research is seen as incomplete because of the personal interpretations made by the researcher, the resulting bias generated by this, and the difficulty in generalising findings to a large group because of the small number of participants studied. Quantitative research, it is contended, does not have these weaknesses since in mixed-methods research quantitative results in the form of numbers could be used to add precision to qualitative data findings in form of words, pictures and narratives (Johnson &
Onwuegbuzie, 2004). Thus, the combination of strengths of one approach makes up for the weaknesses of the other approach. Mixed-methods research helps to answer questions that cannot be answered by quantitative or qualitative approaches only because the researcher is not solely limited to a single research approach or method (Cronholm &
Hjalmarsson, 2011). Also, researchers can make use of all the tools of data collection available rather than being restricted to the types of data collection typically associated with quantitative research or qualitative research. Thus, the mixed-method approach can
72
manage a broader and more complete range of research questions. Mixed-methods research can provide more robust evidence for a conclusion to a research problem than either quantitative or qualitative research alone by adding insights and understanding that might be overlooked when only a single method is used (Johnson & Onwuegbuzie, 2004).
The use of a mixed method can, through merging and validation of findings, increase the ability to generalise the results compared to a qualitative study (Cronholm & Hjalmarsson, 2011). Thus, qualitative and quantitative approaches when used together, yield more complete knowledge necessary to enlighten theory and practice (Johnson & Onwuegbuzie 2004).
Mixed methods also have several weaknesses (Johnson & Onwuegbuzie 2004). One weakness is that it could be problematic for one researcher alone to carry out both qualitative and quantitative research (Cronholm & Hjalmarsson, 2011). This can be the case if the qualitative and quantitative research should be used concurrently. A design implementing concurrency might require a research team. Concurrency encompasses more participants and more activities, and hence, is time consuming (Johnson &
Onwuegbuzie 2004). Other difficulties that might be associated with the mixing of methods is that the researcher must learn about multiple methods and their rationality in order to mix them accordingly and be able to use them in a professional manner. It is often simpler to focus on a single method or approach. Another weakness is that methodological purists contend that a researcher should always work within either a qualitative or a quantitative paradigm and not mix the two (Johnson & Onwuegbuzie, 2004)
3.3.1.1 Types of mixed methods
Mixed-methods research combines quantitative and qualitative methods to benefit from the strengths of both and to gain a holistic perspective, giving a way to being able to look at the question from different angles. According to Creswell and Clark (2007) there are six types of mixed-method research designs. They are the convergent parallel design, the explanatory sequential design, the exploratory sequential design, the embedded design, the transformative design, and the multiphase design
73
In convergent parallel design quantitative and qualitative data collection and analysis are carried out independently from each other or at the same time. The results of each phase are compared and interpreted at the end. Explanatory sequential design is one where quantitative phase is administered first and according to the results of that phase qualitative phase follows up. Finally, all results are interpreted. Exploratory sequential design is the opposite of the explanatory one, the time qualitative phase being administered first. With the embedded design, researchers conduct one of the phases within the other.
Transformative design is like the explanatory design, but it lays emphasis on the theoretical framework. Multiphase design is used through a period or within a program using the quantitative and qualitative phases repeatedly.
3.3.2 Explanatory sequential design
For this study, the researcher used the explanatory sequential design. In this kind of mixed- methods research, results of the qualitative phase are used to explain the quantitative results of the first phase. The explanatory sequential design is used when a researcher wants to investigate the relationships among quantitative data and to explain the mechanisms behind those relationships. A sequential explanatory design two-phased mixed-methods research approach was used where the qualitative data were required to provide an explanation on the statistical results from the quantitative phase. However, the researcher had to deal with the technical concerns of priority, implementation, and integration of the quantitative and qualitative research approaches (Creswell, 2013).
3.3.2.1 Priority
Priority refers to the choice of giving more consideration to either quantitative data or qualitative data (Creswell, 2013). For instance, in the sequential explanatory design, priority is accorded to the to the quantitative approach because quantitative data collection comes first, representing a main part of the study, while a smaller qualitative data collection section follows in the second stage of the study (Ivankova et al., 2006). In the present study, priority was given to the quantitative approach.
74 3.3.2.2 Implementation
Implementation refers to whether the quantitative or qualitative data is used first, second, or simultaneously in the data collection (Creswell, 2013). In the sequential explanatory design, a researcher first gathers and analyses the quantitative data, and then collects and analyses the qualitative data in the second phase of the study with the intention of clariflying the results obtained from the quantitative phase. The researcher collected the quantitative data using self-administered survey instruments. Analysis of the survey instruments indicated that the data was trustworthy and with no inconveniences such as missing values and outliers and consequently multiple regression analysis could be safely carried out to identify potential explanatory variables that could best predict and explain teachers’ perceptions of Web 2.0 tools and their intention to use these tools in their professional practice, and to elaborate an interview process for the qualitative phase. The researcher then collected and analysed qualitative data to help shed light on the quantitative findings.
3.3.2.3 Integration
Integration refers to the phase when the data is connected, that is, during the design phase of the study, data collection and data analysis, or during interpretation of the findings (Teddlie & Tashakkori, 2009). In this study, the researcher connected both the quantitative and qualitative data at two stages. The first connection of data happened during the design phase of the study when developing interview questions for the qualitative phase, based on the results of the quantitative phase, while the second connection of data happened during the interpretation of the findings.