Research Terminology and The scientific Method

MOD06 – Research Terminology and The scientific Method

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MOD06- Research Terminology

Concepts

            A concept can be defined as a collection of aspects or meanings that relate to the subject of the research, its conditions, objects, and events. A successful research establishes a concise explanation about the concepts and elaborates on their correlational relationships (Gauch, 2003). Failure to clearly conceptualize the concepts can create confusion in explaining the importance and significance of the research work done. Examples: Availability, Integrity, Confidentiality, Non-repudiation

Constructs

Constructs are considered as expressions of people, ideas, events, organizations, or things that are mental abstracts (Oliver, 2010). The importance of a construct is to explain the componential aspects and factors of a theory or concept. Additionally, it can be utilized to observe or measure behavioral tendencies or trends (Oliver, 2010). Research usually entails the use of theories to explain the various concepts surrounding the research topic. Using concepts, one is able to elaborate on why and how a particular phenomenon occurs or behaves (Oliver, 2010). The meaning of a construct in a research project is highlighted using nominal and theoretical definitions. Examples: IT security, Information systems threats, Information assurance

Definitions

             Definitions within a research are listed in the glossary. In this section, the terms used when conducting the research are listed and their definitions elaborated. Some of the terminologies that are defined include measurements, describing methods, statistical methods, and ideas within the field of research. Examples: Multimedia database, Big data, intelligent database, Fuzzy logic, Data engineering, Data integration, Semantic web, Knowledge based systems, Data analysis, Recommender systems.

Variables

A variable can be defined as a trait, characteristic, event, or attribute in research work. It is usually assigned categorical values and measured to validate the hypothesis generated by the researcher after conducting data collection and gathering. Variables are categorized into different groups depending on how they relate with each other. A dependent variable is affected when the independent variable is changed or manipulated. Independent variables are usually manipulated by the researcher to impose an effect on the dependent variable (Gravetter & Forzano, 2009). Intervening variables are abstract during data analysis and collection. However, they are used to establish the correlational factor between dependent and independent variables. Extraneous variables are defined as those that might affect the dependent variable. These variables exist within the research environment. Examples: Access control, Classification of information, Authorization

Propositions

Proposition is considered a fundamental aspect that constitutes research. This is because the evaluation of a research is validated by the relevance of its propositions. The importance of this element is it provides information about the measurements taken, definitions within the research, its associations, as well as the compounding factors (Gauch, 2003). Externally, it allows deductions to be made. A proposition can be categorized as non-relational or relational. Examples: Impact of Risk Management on Efficiency of Information Systems

Hypotheses

           In its truest definition, a hypothesis can be described as a statement made from an informed angle (Oliver, 2010). Additionally, it seeks to indicate the existence of probable relations between the measured variables that are part of the research (Gravetter & Forzano, 2009). Simply, hypothesis is termed as educated or informed guesses on the correlation of variables in an experimental unit. Examples: Efficient risk management practices reduce incidence of systems failure.

Theory

The development of a theory is to establish rationale to an aspect, event, occurrence, or situation that is incomprehensive. Theories provide solutions to difficult problems by shedding light on the intricate details compounded within the issue (Gauch, 2003). It also explains on the measurable elements within the experiment as well as their cause and effects. Examples: risk management, incident management, cryptography, security governance

Reasoning

            When conducting research, reasoning elucidates on explaining several elements of research. They are inclusive of the hypothesis, observations made, confirmation of the results and the theory. Examples: Disaster Recovery Planning, Change management, business continuity

Models

Research work requires that data collection and analysis to be based on a theoretical model. The important element of a model in research is that it enables the researcher to work effectively and decisively (Oliver, 2010). It also improves the logical processes when conducting an analysis.

Difference between Induction and Deduction Reasoning

Induction and deduction reasoning are often confusing because they focus on different aspects of the research. It is important to understand the importance and meaning of both types in order to identify proper logic. First difference is inductive reasoning develops broader generalizations, which are derived from observations specific to the research (Gauch, 2003). Contrary to this, deductive reasoning exhibits specificity as it moves from broader generalizations and narrows down to the logical and specific conclusions. Second difference is that deduction reasoning is applied when testing theories and hypothesis whereas induction reasoning is applicable in formulation of these constituting elements of research (Gravetter & Forzano, 2009). When executing deductive reasoning, the particular theory of interest becomes the basis of the research hence it is validated or nullified by the results and findings conferred.

The third difference that presents itself is that, in deductive reasoning, an aspect that is valid for a class of element or things is also true for the members that belong to this class (Gravetter & Forzano, 2009). For instance, “All cats are furry animals. Pat is a pet cat. Therefore, Pat is a furry animal”. From this example, it is true that cats are furred animals. Additionally, it is also true that Pat is a pet cat. The deduction will then be “Pat is a furred animal”. Contradictorily, inductive reasoning allows the conclusive statement to be untrue. For instance, “Kayleen is a grandmother. Kayleen is bald. Therefore, all grandmothers are bald” (Gauch, 2003). It is clear to observe that the conclusive statement fails to align with the logical reasoning elaborated by other statements.

Conclusion

Research processes are guaranteed to improve understanding and knowledge of the various elements within the environment. They provide a guideline on how to conduct research and deduce findings afterwards. Understanding the key elements of scientific methodology in research allows a researcher to identify the proper procedures to implement when conducting the fieldwork (Gravetter & Forzano, 2009). This understanding is gained from possessing knowledge on the intricate details of the terminologies and important elements that are considered in research.

References

Gauch, H. (2003). Scientific method in practice. New York: Cambridge University Press.

Gravetter, F., & Forzano, L. (2009). Research methods for the behavioral sciences. Belmont, CA: Wadsworth Cenage Learning.

Oliver, P. (2010). Understanding the research process. Los Angeles: SAGE.