A couple of important questions should be considered as you deter-mine your method of inquiry. First, you must ask yourself: what is my intent or purpose of the research? Second: what are my research questions? These initial components will drive the method you select. You may deter-mine that a quantitative analysis will suffice in answering your research question or will respond to your purpose. On the other hand, you may conclude that it is qualitative, the deeper understanding of the topic, that responds to your purpose, or ultimately, you may decide that a mixed methods approach, using both quantitative and qualitative analyses, is the best method of inquiry for your dissertation.

Just as in quantitative research, also in qualitative research, you must ask yourself: what is my intent or purpose of the research? Second, you must ask: what are my research questions? Again, these initial components will drive the method you select. If you conclude that you need to go obtain a deeper understanding of the topic, you will select qualitative methodology. Ultimately, you may decide that a mixed methods approach, using both quantitative and qualitative analyses, is the best method of inquiry for your dissertation.

However, in case of computer Science and Engineering a slightly different approach to methodology is used. Although scientific and engineering studies can be conducted based on purely quantitative and qualitative approach but there are some exceptions. Given that such disciplines require design and implementation of a prototype, which is then to be tested against a set of benchmarks, a flow chart is to be designed. Some of the popular models for implementation include Waterfall method, Early Prototype, and Agile. Based on the focus area and the kind of experiment proposed the choice of research models can vary.

Your research design or method of inquiry for research will fall into one of ten categories of research (First five are Quantitative and last five are Qualitative, with Mixed Method presented at the end):

1. Descriptive research,

This type of research involves the description of phenomena in our world. In this type of inquiry, the phenomena described are basic information, actions, behaviors, and changes of phenomena, but always the description is about what the phenomena look like from the perspective of the researcher or the participants in the research; it is not about how the phenomena function. Prior to beginning the research, you will need to have established from theory or from prior research what it is about the phenomenon you will study; from this perspective, descriptive research is theory or research driven.

2. Correlational research,

Correlational research is based in “relationship” just as its name implies. Itis grounded in interactions of one variable to another; for example, as scores on one variable go up the related scores on another variable go down. You might find an inverse correlation between positive praise and acting out behavior—as the amount of praise increases, the amount of acting out behavior decreases. In correlational research, the degree to which the variables are related is important as well as the direction of the relationship. This type of research is not specifically causal-comparative research nor is it ex post facto research. Where correlational research actually relates scores from two or more variables from the same sample, ex post facto research compares scores from two or more groups on the same variable. Generally, correlational research does not signify causality, but some correlational research designs, such as path analysis and cross-lagged panel designs, allow for causal conclusions. In correlational research, if a relationship is found between two or more variables, then the variables are correlated. This correlation must be interpreted based on the strength and direction via the correlational coefficient that ranges between −1 and +1. The direction of the correlation or the association between the two variables can indicate a positive association (0 to +1). This means that as one variable increases, the other variable also increases, and vice versa. Correlation coefficients between 0 and −1represent a negative association. In this sense, as one variable increases, the other variable decreases. The magnitude or strength of the correlation or association between the two or more variables is signified as stronger by correlation coefficients closer to 1 (either positive or negative). A correlation coefficient of +1 indicates a perfect positive relationship, while a coefficient of 0 indicates no relationship, and a coefficient of −1 indicates a perfect negative relationship.

Correlational research is used in a wide array of studies that intend, of course, to determine relationships, but also that aim to assess consistency, as well as predictions. As you may have learned from the chapter on statistics or your course in statistics, when the p-calculated is less than p-critical (in education it is usually established before a study is conducted and set as .05), such a relationship is significant. In correlational research, sample size is an important consideration. As you already know the smaller the sample size, the larger the size of the correlation has to be to be statistically significant; on the other hand, the larger the sample size, the more likely a significant correlation will be found even if it is with small magnitude. Therefore, in research with large sample size, reporting effect size is meaningful and critical. Here are some commonly employed techniques of correlation: Bivariate Correlation, Regression and Prediction, Multiple Regression, Canonical Correlation, Discriminant Analysis, Factor Analysis, Path Analysis, and Cross Lagged Panel.

3. Causal-comparative research, 

Causal-comparative research, or ex post facto (after the fact) research, is the most basic design for determining cause-and-effect relationships between variables. Causal-comparative research is different from experimental research in that you do not manipulate the independent variable since it has already occurred, and as already indicated, you cannot control it. Additionally, causal-comparative research will not meet the experimental research requirement for random assignment of participants from a single population or pool of participants. At least two comparison groups are needed in causal-comparative research to be compared on a dependent variable. One group may be students who have been identified by their teachers as being potentially gifted, and the other group may be those students not identified by their teachers as being potentially gifted. These two groups could be measured on standardized IQ tests to determine if the group differences identified by the teacher perception are accurate as compared by the standardized measures. When you discuss the groups, you will want to make certain you describe the groups and their characteristics in detail and the independent variable that distinguishes the groups. Why is this important? It is important because the group constitution and definitions can affect the generalizability of your findings. Give ample detail to understand all about each of the groups in terms of their comparability and differences. You may obtain your groups from two independent established populations, such as those students who have had public school prekindergarten and those who did not. You may want to compare these students on English reading achievement at the end of kindergarten or first grade. To obtain your sample you may conduct random sampling (not random assignment from one single population as in experimental research). You will want your groups to be as similar as possible on some variables. For example, in the prekindergarten versus no prekindergarten groups, you may want to go through the random samples and match the samples (to have better control) on age, ethnicity, socioeconomic status, and gender. You want the groups to be as similar as possible so that the difference or lack of differences you see in the end of your research is more likely to be attributed to your independent variable. Because causal-comparative research does not rest on randomization or manipulation or control of variables, you will know upfront that is a weakness if you so choose this type of design.

4. Quasi-experimental research

Even though the best causal research is reflected in true experimental designs, most research in education that requires causal inferences cannot be conducted under true experimentation due to the inability to randomly assign participants to experimental and control groups or the inability to secure a control or comparative group. Additionally, much of true experimentation is expensive in that it often requires training in the intervention and always monitoring for fidelity. In this case, quasi-experimental designs are available to give you adequate control over threats to validity. There are several types of quasi-experimental designs, which we believe would be advantageous to the development of your dissertation research. Two kinds of design of such experiments are Time Series Design and Non-equivalent Control Group Design.

5. Experimental research.

Experimental design allows you to determine whether a program or treatment intervention is the cause of the outcome, and in such a case, you must have strong internal validity. It requires the manipulation of at least one independent variable and an attempt to hold all other variables except for the dependent variable constant. The essence of a truly experimental design is its random selection from population of interest and random assignment to treatment and control groups.

6. Theory Development

Developing and testing theory takes research to a level of synthesis, analysis, and evaluation. Because theory is the essence of what drives our actions and because theory describes, explains, and even predicts human phenomena, it is important for theory developers to “get it right,” or at least “get it on the right track.” Kerlinger (1986) stated of theory, “The ultimate aim of science is the generation and verification of theory” (p. 7). According to Dorin, Demmin, and Gabel (1990), theory (a) provides a general explanation for observations made over time, (b) explains and predicts behavior, (c) can never be established beyond all doubt, (d) may be modified, and (e) seldom have to be thrown out completely if thoroughly tested, but sometimes may be widely accepted for a long time and later disproved. Theory can be developed and tested quantitatively.

7. Phenomenological research design

Phenomenological research is one of the most basic forms of research. This type of research involves the description of phenomena in our world. In this type of inquiry, the phenomena described are basic information, actions, behaviors, and changes of phenomena, but always the description is about what the phenomena “look like” from the perspective of the researcher and the participants in the research; it is not about how the phenomena function. Prior to beginning the research, you will need to have established from theory or from prior research what it is about the phenomenon you will study; from this perspective, descriptive research is theory or research driven. Husserl, the twentieth-century philosopher and the father of phenomenology, was concerned with the study of “experience” from the perspective of the individual, and believed that the researcher could approximate those experiences through intuiting and rigorous examination of the subjects, objects, or people’s lived experiences, behaviors, or actions. He believed that researchers could gain subjective experience, essential realities, and insights into a person’s or persons’ motivations and actions; thus, researchers could minimize presuppositions and traditionally held beliefs. The researchers’ interpretations of the phenomena allows it to, as in action research, inform, support, or challenge policy, procedures, and actions in society or organizations. Methods Phenomenological research can be based in either single-case designs or purposefully selected samples. A variety of qualitative techniques, approaches, or methods can be used in phenomenological research, including interviews, focus groups, participant or direct observation, and document or personal entry analyses. Of course, in any of these approaches, the establishment of trust is important via good rapport and empathetic listening.

8. Case Study Research Design

Case studies are specific explorations of individuals, but also such investigations can be on groups, cohorts, cultures, organizations, communities, or pro-grams. If a case study is based in biography, it may be called life history, which focuses on major circumstances, situations, events, problems, celebrations, and/or decisions of a person, group, or organization. If a case study is focused on one individual or group, it is called single-case design. If the case targets multiple individuals and the same phenomena or it targets various communities related to a similar phenomenon, then this type of design is called multiple-case study design. It may even be called a phenomenological case study, combining as we indicated the case study and phenomenology. More than likely, you will be using purposeful sampling in case study design. You must describe your sampling procedure and case selections in detail. Share all the characteristics of the selection criteria and distinctive and uncommon features. Also indicate the duration of the study, as that may have a bearing on the outcome.

Your case data may include, but not be limited to: (a) basic demo-graphic information about the individual that is written in narrative for-mat, (b) family history (or if the case is about a program or organization, it would relate the program’s or organization’s history), (c) document analyses relating to the individuals or programs, (d) interview data, and/or (e) observational records. Once you have sufficient data, you will compile the case data that tells the story of the individual, program, or organization. You likely will have themes, which may be by type of phenomena revealed or from a chronological perspective. When you write, you will need to provide sufficient explanation with deep description, so nothing is left for the reader to surmise. If you have definitions specific to your study, be certain to explain those as well.

9. Ethnographic Research Design

Ethnographic research requires that you conduct fieldwork to become involved with the individuals or group in a personal manner, using participant observation as a technique for gathering data for telling the group’s or individual’s story via rich narrative description. You will typically gather the data via interviews during the participant observation, videography, photography, and document analysis. These techniques of data gathering will yield thick and rich descriptions necessary for your ethnographic dissertation in the form of quotations (low inference descriptors), descriptions of the group and the contexts, and parts of documents. You will, as in participant observation, investigate the behaviors of the people, their language, their actions, and their artifacts. You will look for norms, mores, and customs. Prior to going in to conduct such research, you must be clear about your own biases, about colonization, about who the “other” is, about your impact on the group to be studied, and about basic respect. To conduct fieldwork for the ethnography, you will need to gain the trust of the individuals in charge; these are the gatekeepers. In ethnographic studies, depending on your purpose, you may use convenience sampling (as explained previously under case study method).You may use stratified sampling that seeks out groups from various levels such as socioeconomic levels. Snowball sampling may also be used where referrals from your initial contacts are made to add to the group.

Ethnography does not come without serious consideration. Some critical features to consider prior to the selection of an ethnographic design are: (a) your own understanding of culture and cultural anthropology, the foundation of ethnography; (b) your ability to write in a narrative style so that others may understand the cultural occurrences and norms of the group; (c) your ability to be a part of the group, yet remain apart from the group as the researcher, thus creating a fine line and balance between the researcher and the researched; (d) the ethical implications for studying the group or individuals; and (e) an extensive time commitment for the fieldwork.

10. Grounded Theory Research

Grounded theory, first described by Glaser and Strauss (1967), is intended to generate or discover a theory inductively from data gathered about a specific phenomenon. Three elements of grounded theory are concepts, categories, and propositions. Concepts are the basic units of analysis.

Four research criteria are important in grounded theory for validation of the study and for establishing reliability of the findings of the study. Actually, these are recommended for review for all qualitative studies. They are: (a) construct validity, (b) internal validity, (c) external validity, and (d) reliability. Construct validity is accomplished by establishing clearly specified operational procedures. Internal validity can be reached by establishing causal relationships in which certain conditions are shown to lead to other conditions, as distinguished from false relationships, and it addresses the findings’ credibility or “truth value.” External validity is the extent to which the study’s findings can be generalized and to the extent that you, as the researcher, establish the context in which it can be generalized. Generalization is usually to some broader theory or other valid studies (quantitative and qualitative) and not the population. Finally, reliability requires demonstrating that the operations of a study—such as data collection procedures—can be repeated with the same results. Triangulation is another method for ensuring that the study is robust, valid, and reliable. Triangulation may appear as four basic types: (a) data tri-angulation, involving time, space, and persons, (b) investigator triangulation, which consists of the use of multiple, rather than single researcher/observers,(c) theory triangulation, which consists of using more than one theoretical frame in the interpretation of the phenomenon, and (d) methodological triangulation, which involves using multiple methods. Multiple triangulation maybe used when you combine in one dissertation, multiple observers, theoretical perspectives, sources of data, and methodologies.

11. Mixed method research design

Mixed methods research can refer to those studies that have engaged both quantitative and qualitative research questions and/or that have used both probability and purposeful sampling. It is a field of research that is still emerging. According to Johnson and Onwuegbuzie (2004), mixed methods research is “the class of research where the researcher mixes or combines quantitative and qualitative research techniques, methods, approaches, concepts, or language into a single study” (p. 17). They further indicated: Mixed methods research offers great promise for practicing researchers who would like to see methodologists describe and develop techniques that are closer to what researchers actually use in practice. Mixed methods research as the third research paradigm can also help bridge the schism between quantitative and qualitative research (Onwuegbuzie & Leech, 2004a). Methodological work on the mixed methods research paradigm can be seen in several recent books(Brewer & Hunter, 1989; Creswell, 2007; Greene, Caracelli, & Graham,1989; Johnson & Christensen, 2004; Newman & Benz, 1998; Reichardt & Rallis, 1994; Tashakkori & Teddlie, 1998, 2003). (p. 15)

Johnson and Onwuegbuzie further iterated eight distinct steps in mixed methods design: (a) determine the research question, (b) determine whether a mixed design is appropriate, (c) select the mixed methods or mixed-model research design, (d) collect the data, (e) analyze the data,(f) interpret the data, (g) legitimate the data, and (h) draw conclusions (if warranted) and write the final report.