Methodology in Computer Science - Case Study Example

Research Methods and Methodology in Computer Science Research Methods and Methodology in Computer Science The quantitative research methodology approaches research from an objective point of view. This approach is chosen in order to measure the relationship between and among variables and this helps in testing and ascertaining their hypotheses (Warfield 2010, p.29). It is conducted in five steps. Identification of the research question, determination of participants, selection of methods to help answer the research question, selection of data analysis tools and interpretation are the five steps in qualitative research (Swanson & Holton 2005, p.30). The designing of the question depends on whether the study is an experimental, descriptive, quasi-experimental, or correlational research. For experimental quantitative research, the question has to be set in a way that it seeks to capture the relationship between the independent and dependent variables under the specified conditions. A causal relationship between variables is indicated by one variable following the other logically. On the other hand, the question for quasi-experiment, descriptive and correlational quantitative research does not seek to manipulate variables. Rather, it seeks to guide the gathering of existing data and deduce the relationship between variables without going by causality. There are categorical, ordinal, and continuous variable measurements in quantitative research (Swanson & Holton 2005, p.29). The choice of the participants of a study is guided by the need to ensure a sample size and composition that is representative of the population to which the findings of the study are generalized. The choice of participants is also influenced by the consideration of the nature of participants – whether human or nonhuman – because of ethical issues and this impacts the choice of the most appropriate research design. The decision of which methods to use in answering the research question posed is guided by the variables, research design and participants. This decision considers the quantity and quality of the source of the data, validity and reliability. The findings of a study can be invalidated or undermined by the lack of validity and reliability. The analysis and interpretation of data is founded on the statistical significance deduced. Data analysis in quantitative research utilizes statistics to explain how variables predict, associate, compare, and describe how the outcomes of a study answer the propositions of the study. Data analysis tools are chosen on the basis of the propositions of the study, the type of data and type of research (Swanson & Holton 2005, p.29). Qualitative approach is preferred when there is need for a rich and in-depth description of a phenomenon (Ellis & Levy 2008, p.18). Phenomenology is used in qualitative research when the study is about life experiences of one or more people. Qualitative research uses ethnography when studying entire cultural groups. Definition of the question of interest, selection of the research instrument, identification of the gatekeepers, data collection, analysis, and report writing are steps followed in conducting qualitative research. Qualitative research is guided by open-ended questions and can develop new question through the research process. Since the research is a participant observer in qualitative research, the choice of the research instrument should help control biases and values. The gatekeeper allows a researcher access to documents, events, people and places needed for the study. This can be an organizational leader or a government officer and a researcher have to cultivate a relationship with them. The data collection techniques used in qualitative research includes observation and interviews. Data analysis in qualitative research involves coding that happens through organization and categorization of data based on pattern and theme. Open coding is the first step in coding and it involves going through data searching for persistent themes (Farber 2006, p.368 - 371; Chenail 2011, pp.1716 - 1718). The mixed methods research combines qualitative and quantitative research in either the same or in a number of studies. Mixed methods approach can be complementary in which case it would will combine the outcomes of one method with those of the other. Developmental mixed methods approach entails the development of the results of one method using the results of the other method. When it takes the form of initiation, a researcher recasts the outcomes of one method to the results or questions of the other method. When using a mixed methods approach for the purposes of expansion, different methods are used in extending the range or breadth of a study. The decision to combine different methods in a study can be guided by the need to enhance the validity of the findings since it is triangulation. Additionally, mixed methods approach help in the enrichment of participants, fidelity of the instrument and significance of the study. Participant enrichment draws from the way that using qualitative and quantitative techniques optimizes the sample (Warfield 2010, p.30). The steps involved in mixed methods approach starts with a determination of whether the study is confirmatory or exploratory. The second step is the determination of the operation and data collection techniques. Thirdly, the research proceeds to data analysis and the making of inferences (Warfield 2010, p.33). Deductive research approach starts from a theory and narrows down to a specific case (Ramesh, Glass & Vessey 2002, p.171). The findings of this research support the theory. On the other hand, inductive research approach originates from a specific case and proceeds to derive generalizations and theories (Jebreen 2012, p.172; Nickles & Meheus 2009, p.99). Inductive reasoning is the best to be applied in computer science research because it takes into account the impact of researcher bias on the outcome of the study (Sane 2007, p.8; Srydom 2011, p.148). This is important because different researchers will have different notions and orientations on a given subject and this affects the outcome of studying such a subject (Stadler 2004, p.21; Groarke 2009, p.103). Finally, inductive research involves making observations, identifying patterns, making tentative hypothesis about the phenomenon under study, testing the hypothesis and deriving a theory from findings. According to Aristotle, an inductive researcher starts the inquiry with ideas about the expected results. Induction provides a researcher with metaphysical and logical laws, universals, concepts, and definitions that help in the accurate conception of the initial insights (Groarke 2009, p.9). Reference List Chenail, R. (2011). Ten Steps for Conceptualizing and Conducting Qualitative Research Studies in a Pragmatically Curious Manner. The Qualitative Report, 16(6) November 2011: 1713 – 1730. Ellis, T. & Levy, Y. (2008). Framework of Problem-Based Research: A guide for Novice Researchers on the Development of a Research-Worthy Problem. The International Journal of an Emerging Transdiscipline, 11: 18 – 33. Farber, N. (2003). Conducting Qualitative Research: A practical guide for School Counselors. ASCA, June 2006: 367 – 375. Groarke, L. (2009). An Aristotelian account of induction creating something from nothing. Montréal [Que.], McGill-Queens University Press. p. 103. Jebreen, I. (2012). Using Inductive Approach as Research Strategy in Requirements Engineering. International Journal of Computer and Information Technology, 1(2): 162 – 173. Meheus, J., & Nickles, T. (2009). Models of discovery and creativity. Dordrecht, Springer. p. 99. Ramesh, V. Glass, R. & Vessey, I. (2004). Research in Computer Science: an empirical study. The Journal of Systems and Software, 70: 165 – 176. Sane, S. S. (2007). Theory of computer science. Pune, India, Technical Publications Pune. p. 8. Stadler, F. (2004). Induction and deduction in the sciences. Dordrecht [u.a.], Kluwer Acad. Publ. p. 21. Strydom, P. (2011). Contemporary Critical Theory and Methodology. New York, NY: Routledge. p. 148. Swanson, R. A., & Holton, E. F. (2005). Research in organizations foundations and methods of inquiry. San Francisco, Calif, Berrett-Koehler. p. 30. Warfield, D. (2010). IS/IT Research: A research methodologies review. Journal of Theoretical and Applied Information Technology, 2010: 28 – 35. Read More