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This essay focused on research theories. It showed the differences between deductive, inductive, grounded, and axiomatic theories in scientific research. These theories have both strengths and weaknesses, and no single theory is superior to other theories or more valid. Theories and hypotheses differ in several aspects, but they also share a few characteristics. For instance, theories are based on tested evidence while hypotheses are mere suggestions. Finally, study variables remain vital aspects of any scientific research because they are used to measure differences and associations between factors under investigation.
When conducting research, the fundamental distinction to remember between the inductive and deductive methods is that while the deductive method focuses on evaluating theories, the inductive method concentrates on creating new theories using available data.
The deductive approach, as a rule, starts with a hypothesis, while the inductive method will typically rely on research questions to limit the scope of the study (Rubin & Rubin, 2012).
For deductive methodologies, the focus is commonly on causality, while for inductive methodologies, the approach is largely centered on investigating new occurrences or analyzing already examined phenomena from an alternate point of view. Additionally, the deductive approach is narrower in scope and is focused on testing or confirming hypotheses (Gay & Weaver, 2011).
Inductive methodologies are mostly applied in subjective or qualitative studies, whereas deductive methodologies are more generally used in quantitative studies (Hashemnezhad, 2015). Nevertheless, there are no set specific guidelines and some qualitative studies may have the deductive introduction.
One particular inductive method that is habitually alluded to in research writing is the grounded theory, spearheaded by Glaser and Strauss (Gay & Weaver, 2011).
Grounded theory alludes to a theory that is formulated inductively from a body of information or data collected and analyzed on a specific research issue. If formulated effectively, this implies the ensuing theory at minimum fits one dataset properly. This appears differently about a theory that got deductively from grand theory without relying on data, and it might thus end up fitting no data in the slightest degree.
The grounded theory focuses on a case as opposed to a variable standpoint, even though the difference is almost difficult to draw. This implies to a limited extent that the researcher takes various cases to be wholes, in which the variables associate as a unit to deliver some expected results. A case-based viewpoint usually assumes that variables relate in complex manners. Cases are analyzed based on both variations and similarities to determine casual differences and common factors to demonstrate potential causes and outcomes.
Grounded theory is not an alternative to be applied lightly. It requires broad and rehashed scrutinizing through data, investigating, and re-examining different circumstances with a specific end goal to recognize a new theory. It is a method most appropriate to research studies in which the issue to be examined has not been earlier investigated.
Axiomatic theory reflects the use of a set of axioms to generate a theory. Assumptions (axioms) for the theory are useful here, and they are considered relevant and effective without any more testing. Therefore, a logical theory emanates from a set of axioms, and the theory may be assessed or reviewed based on available empirical evidence, research, or new studies. Earlier economic theories, for instance, were developed from multiple assumptions. Thus, these axioms assist researchers to develop new theories, and it is important to note that the new theory can be later empirically tested, revised, or overruled.
In any case, axiomatic theories are hard to extricate irrespective of evidence from empirical data showing that they fail to anticipate or clarify phenomena. One method for reinforcing they claim to offer possible axioms in which empirical research exhibits prominent descriptive and predictive capabilities. That being said, researchers focused on the underlying assumptions of such theories just denounce them gradually, if at all.
Validity of Theories
From a general perspective, no one theory is superior to any other theory. All these theories have their strengths and limitations. For instance, researchers have highlighted the challenges and strengths of both inductive (qualitative) and deductive (quantitative) studies. Inductive methods focus on determining and understanding experiences, perspectives, and thoughts of research subjects. That is, inductive methodologies explore the meaning, purpose, or reality of a study issue. On the other hand, deductive approaches strive to enhance research impartiality, consistency when repeated, and applicability of findings to general populations, and they are generally interested in prediction. These explanations show that the two theories are the opposite of each other. The grounded theory could be difficult to apply, particularly when large volumes of data are presented and no specific rules are used to identify suitable categories. Additionally, researchers interested in grounded theory must be extremely skilled to use it. Axiomatic theory may even ignore empirical data to promote general assumptions held for longer periods. Nevertheless, axiomatic theory cannot tolerate any irrelevant factors of a problem. It provides strong terms and conditions for any problems under investigation. Thus, assumptions not included in the axioms nor obtained from them can be a part of the theory.
Researchers have now introduced new methods to account for the limitations and strengths of some theories. A mixed-methods methodology, for instance, is developed to account for both weaknesses of quantitative and qualitative studies. The mixed-methods approach is seen as an alternative for enhancing research design to support thorough research of phenomena that are considered worth investigating.
Theory vs. Hypothesis
A hypothesis is either a proposed account for a noted phenomenon or an envisioned prediction of a potential causal association among numerous phenomena. In science, on the other hand, a theory is tried, very much substantiated, unifying clarification for a wide range of confirmed, demonstrated factors. There is always evidence to support a theory, but a hypothesis is just a proposed potential result and is testable and falsifiable.
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From the above definitions, one can observe that a hypothesis explains a notable phenomenon while a theory offers explanations that are well supported with verifiable facts. A hypothesis is founded on suggestions, assumptions, projections, possibilities, or predictions with no clear certainty on outcomes. A theory presents hard evidence, is repeatedly tested, verified, and often has a wide scientific consensus.
It is imperative to recognize that both a theory and a hypothesis are testable and falsifiable, but the latter is not well substantiated.
The hypothesis is normally founded on limited sets of data. On the other hand, a theory is based on extremely large sets of tested data under different conditions. That is, multiple studies have been conducted to confirm or disapprove a given theory.
Further, a hypothesis is used in specific instances. That is, a hypothesis cannot include other cases not specified within a study. It is only restricted to that specific single cause. Conversely, theory tends to be general. It reflects the establishment of a common rule gained using many tests and experiments. The resulting principle is usually applicable to several specific cases.
The overall purpose of a hypothesis is to present a tentative possibility, which can be assessed further using observations and experiments, but the purpose of a theory is to account for consistently observed phenomena.
Many criminology theories, such as social control theory and rational choice theory, have been tested over time, and results are always consistent. Nevertheless, testing scientific theories does not stop at any given moment because new evidence may emerge to support or refute earlier findings. A hypothesis is always been seen as an ‘informed guess’, and scientific methods can be applied to test and verify it. The result may support it and recommend further studies or disapprove it as false. A hypothesis that has been consistently demonstrated as true (a working hypothesis) may well become another theory (Shields & Rangarajan, 2013; Halvorson, 2012).
There are multiple common misconceptions about theories and hypotheses. One may talk of a theory while in reality they mean a hypothesis. In such cases, a hypothesis appears a legitimately contemplated proposition in light of the observation. Even if such observations were true, yet regardless of the possibility of its validity, such observations could have been brought on by some different factors. Since this observation is just a contemplated possibility, it can be tested and falsified, which makes it speculation (a hypothesis) rather than a theory.
Variables can be referred to as any elements of a theory that can change or differ as a factor of interaction in a given theory (Al-Riyami, 2008). Alternatively, a variable is any factor that influences the outcome of a study. Each study must have variables becomes they are required to comprehend variations in relationships. Age, color, and country for example are variables because they can change and take on different values based on a wide range of ages, colors, and countries involved in a study. Further, factors, such as height, weight, and time, are quantifiable values in scientific experiments. Answers based on rates, such as ‘1 – agree, ‘2- strongly agree’, and ‘3 -strongly disagree’ are variables, which allow researchers to analyze and assess thoughts and opinions statistically. An investigator should identify specific variables to manipulate to produce quantifiable findings (Al-Riyami, 2008).
Variables are therefore important for generating results that can be interpreted. Variables can also be classified as independent or dependent. The way of planning any research is to identify what research factors could influence the result. While there are multiple sorts of variables in research methods, attention has been directed to independent and dependent variables. Researchers usually identify the independent variable in their study designs for manipulation and consider the dependent variable as the measurable results based on the manipulation of the independent variable. For most experiments, it could be simple to identify, isolate, and manipulate the independent variable to measure the dependent variable.
In other studies, it could be more troublesome to identify independent and dependent variables. Thus, researchers develop robust designs with variable operationalization to evaluate unclear concepts with no specific variables. Additionally, other confounding variables (extraneous), which are not independent, may also cause changes in independent variables. Further, variables that are difficult to control (intervening variables) also have effects on dependent variables.
Al-Riyami, A. (2008). How to prepare a research proposal. Oman Medical Journal, 23(2), 66–69.
Gay, B., & Weaver, S. (2011). Theory building and paradigms: A primer on the nuances of theory construction. American International Journal of Contemporary Research, 1(2), 24-32.
Halvorson, H. (2012). What scientific theories could not be. Philosophy of Science, 79(2), 183–206. doi: 10.1086/664745.
Hashemnezhad, H. (2015). Qualitative content analysis research: A review article. Journal of ELT and Applied Linguistics, 3(1), 54-62.
Rubin, H. J., & Rubin, I. S. (2012). Qualitative interview: The art of hearing data (3rd ed.). Los Angeles, CA: Sage Publications.
Shields, P. M., & Rangarajan, N. (2013). A playbook for research methods: Integrating conceptual frameworks and project management. Stillwater, OK: New Forums Press.