Chapter 3. METHODOLOGY

Objective 1 – Give guidelines on how to write methodology section.

Objective 2 – Explain the qualitative research method and designs.

Objective 3 – Explain the quantitative research method and designs.

Objective 4 – Explain the mixed research method and designs.

Objective 5 – Explain how to write mixed research method and designs.

Objective 6 – Explain how to write population/sample/study group section in terms of the research method.

Objective 7 – Explain the essentials of data collection tools and process.

Objective 8 – Give guidelines on how to report the validity, reliability, and trustworthiness of the study.

Methodology in research serves as a structured approach to acquiring scientific knowledge, drawing upon reasoning, senses, and intuition as sources of knowledge (Paltridge & Starfield, 2007). During the production of knowledge, these three sources are used alone or sometimes together. However, for acquiring or creating scientific knowledge, it must have certain characteristics. Foremost among these is that scientific knowledge must proceed in accordance with a discipline at all stages and fully realize the application of certain procedures. In addition, in the study prepared for scientific information, the limitations, past experiences or prejudices of the researcher that may affect the result of the study should be explained in detail. Thus, methods in scientific studies can be called as procedural templates that contain all these contents together. Researchers choose one of these templates that is suitable for their purposes and the conditions of their studies and follow it from the beginning to the end of the research process. By this way, information emerges, each stage of which can be controlled by different researchers and can be repeated and confirmed when necessary. Since following the scientific process fit methodological requirements is the only way to achieve to create scientific knowledge for researchers, methodology knowledge becomes more important.  Figure 3 gives a brief overview of the sub-headings of methodology. However, all the elements in methodology are more detailed.  

Figure 3 is a visual map of the research methodology and shows typical components of the research methodology. This map guides researchers to understand the steps, methods, and strategies in the research process. For example, methodological elements such as data collection methods, analysis techniques, participant selection, sampling methods, and ethical guidelines are represented in this map. Researchers can use this map to create a conceptual framework when planning their own studies or when they want to understand existing methodological approaches.

Selecting the appropriate research method is essential to address the study's purpose and research questions. Research design is a plan to answer your research question.  A research method is a strategy used to implement that plan.  Research design and methods are different but closely related, because good research design ensures that the data you obtain will help you answer your research question more effectively.

Qualitative research is a means for exploring and understanding the meaning individuals or groups ascribe to a social or human problem. The process of research involves emerging questions and procedures, data typically collected in the participant’s setting, data analysis inductively building from particulars to general themes, and the researcher making interpretations of the meaning of the data. The final written report has a flexible structure. Those who engage in this form of inquiry support a way of looking at research that honors an inductive style, a focus on individual meaning, and the importance of rendering the complexity of a situation. Figure 4 adapted from Creswell (2007), shows the main qualitative research designs.

Figure 4 is adapted from Creswell's (2007) work and shows basic qualitative research designs. Qualitative research is a tool for exploring and understanding the meaning individuals or groups give to a social or human problem. The research process involves emerging questions and procedures, data are generally collected in the participant's environment, data analysis takes place deductively from the general to the specific, and the researcher interprets the meaning of the data. The final written report has a flexible structure. Participants in this type of inquiry endorse a reductionist style of inquiry, a focus on individual meaning, and a perspective that affirms the importance of reflecting the complexity of a situation.

Quantitative research is a means for testing objective theories by examining the relationship among variables. These variables, in turn, can be measured, typically on instruments, so that numbered data can be analyzed using statistical procedures. The final written report has a set structure consisting of introduction, literature and theory, methods, results, and discussion (Creswell, 2008). Like qualitative researchers, those who engage in this form of inquiry have assumptions about testing theories deductively, building in protections against bias, controlling for alternative explanations, and being able to generalize and replicate the findings. Figure 5 shows the types of the quantitative research methods. 

Figure 5 shows the types of quantitative research methods. Descriptive Research: Aims to explain phenomena through the collection, organization, presentation and interpretation of data. Experimental Research: Aims to manipulate the interaction between independent and dependent variables to determine causal relationships. Correlational Research: Aims to evaluate relationships between variables but does not establish a causal relationship. Quasi-Experimental Research: Rather than providing all the controls of experimental research, it is conducted with a slightly looser level of control, so it is a transitional type between correlational and experimental research. Quantitative research is a way to test objective theories by examining the relationship between variables. Meta-analysis is a statistical method that aims to bring together the results of similar studies in a research field and reach more reliable results. These variables, in turn, can typically be measured, usually on instruments, so that numerical data can be analyzed using statistical procedures. The final written report has a specific structure consisting of introduction, literature and theory, methods, results, and discussion sections.

Mixed methods research is an approach to inquiry that combines or associates both qualitative and quantitative forms. It involves philosophical assumptions, the use of qualitative and quantitative approaches, and the mixing of both approaches in a study. Thus, it is more than simply collecting and analyzing both kinds of data; it also involves the use of both approaches in tandem so that the overall strength of a study is greater than either qualitative or quantitative research (Creswell & Plano Clark, 2007). In Table 6, Abeza, et. al. (2015)’s table modified from Creswell and Plano-Clark’s studies, contains main characteristics of different kinds of mixed research designs and their specific requirements were given. Researchers should choose their research methods in terms of the nature of their research, their own data usage tendencies, analyzing choices, and the way they design the process. 

Table 6 contains the main characteristics and specific requirements of different types of mixed research designs. Researchers should choose research methods based on the nature of their study, their own data use tendencies, their analysis choices, and the way they design the process. The table covers sequential and concurrent mixed research designs, their theoretical perspectives, timing, weighting, and integration stages. These designs provide researchers with a framework for planning and designing their studies and offer solutions tailored to different research needs.

In scientific research, terms such as population, sample, study group, or participants refer to people, situations, thoughts, or objects on which research is conducted. Depending on the type of study to be conducted, your ability to reach the population you will work on and the result you want to achieve, the type and the size of the population may vary. Thus, identifying the population and determining the sample size is crucial for generalizability and validity (Cohen, Manion, & Morrison, 2013). For example, in one quantitative study, the population could include academics from various disciplines and career levels but in qualitative study researcher can work with just one scholar for getting deeper information from his or her thoughts and specific experiences on the current research topic. Also, in qualitative studies researchers should take “participants” in their studies and take into account the participants’ main features, thoughts, perspectives…etc. as different variables affect the results of the study. On the other hand, the population, target population, and sample terms have different features. In Figure 6 Creswell’s classification on them was given.

In academic studies, due to the various reasons, researchers usually are not able to reach entire the research population. Thus, choosing correct sampling which successfully represent the whole is crucial. Sampling methods can divide into two parts as random and non-random (purposeful) sampling. Although in purposeful sampling researchers select individuals and sites to learn or understand the central phenomenon intentionally; in random sampling they select representative individuals randomly to generalize results from these individuals to a population (Creswell, 2009). Figure 7, visualize the main sampling methods under the categories of random and non-random sampling. 

Figure 7 presents the main sampling methods under the categories of random and non-random sampling. Sampling methods include different strategies that researchers use to select a representative sample from a population. Random sampling methods include methods in which each member has an equal probability of being selected, while non-random sampling methods include methods that guide sample selection based on a particular characteristic of the population. This table provides researchers with guidance in choosing an appropriate sampling method and helps them better understand their sampling strategies. Also, these sampling methods have some advantages and disadvantages. In table 9 they can be seen.

The Table 7 outlines five different sampling methods—Random, Stratified, Cluster, Systematic, and Convenience Sampling—each with specific advantages and disadvantages. Random Sampling is simple and unbiased, but not practical for large populations and may miss minority subgroups. Stratified Sampling ensures proportional representation and facilitates subgroup comparison but requires prior information to divide the population. Cluster Sampling reduces costs by focusing on a limited number of groups, though it may not provide a genuinely random sample and can be less representative. Systematic Sampling is easy to implement and evenly distributes across the population but can introduce bias if the sampling pattern aligns with a population pattern. Lastly, Convenience Sampling is less time-consuming and reduces costs by using an accessible sampling frame but does not represent the population well, introducing significant bias. Each method offers trade-offs between ease of implementation, cost, time efficiency, and the potential for bias, making the choice of method dependent on the specific requirements and constraints of the research study.

Different tools like surveys, interviews, and observations can be utilized depending on the research method. Standardizing these tools is critical to ensure consistency (Bryman, 2016). Data collection can be divided into two types as primary and secondary data collection methods. While in primary data collection researchers collect data by themselves in secondary data collection, they use the data gathered from published sources. Thus, the secondary data already gathered by someone else for another reason, but these data can be used by other researchers in their researches (Taherdoost, 2021). In figure 8, main characteristics of primary and secondary data collection methods were given.

Figure 8 shows the key features of primary and secondary data collection methods. Primary data collection methods represent data collected directly by researchers, while secondary data collection methods refer to data collected previously.

Ensuring validity and reliability is crucial for the credibility of your study. For quantitative aspects, statistical tests for reliability can be employed, while for qualitative aspects, techniques like triangulation can be used (Lincoln & Guba, 1985).

Cronbach's alpha could be used to measure the reliability of the questionnaire, while the validity of qualitative data might be assessed through member checks.

In order to ensuring trustworthiness of qualitative research four main criteria as credibility, transferability, dependability and confirmability should be provided (Stahl and King, 2020). All researchers work on qualitative research, should prove that they implemented all phases of research design in accordance these criteria. These criteria can be summarized as Table 10.

Table 10 summarizes the four basic criteria researchers apply for trustworthiness in qualitative research. These criteria: It is defined as credibility, transferability, dependability and confirmability. Credibility aims to determine how consistent the findings are with reality, and this can be achieved through various triangulation processes such as data, investigator, theoretical and environmental triangulation. Transferability refers to the ability to transfer patterns and descriptions from one study to another. Dependability aims to ensure that the researcher is a reliable source in the creation of data, and information is exchanged or evaluated with colleagues to increase reliability. Confirmability aims to match qualitative research to objective reality as much as possible, and researchers strive to further their research in terms of accuracy and precision.