How to Build theories in future psychology PhD research directions for 2022?
A psychological theory is a fact-based concept that defines a human behaviour phenomenon. A hypothesis is the foundation of a theory supported by evidence. A psychological approach is made up of two parts:
- It must first and foremost define a behaviour.
- It must create future behaviour predictions.
Studying PhD research theories may improve how scientific explanations for behaviour and other natural phenomena are generated, investigated, and accepted by the scientific community. This blog attempts to enhance theory development in psychology by proposing an outline for a university curriculum that can systematically educate psychologists in theory creation.
Introduction
One of humanity’s most powerful inventions is a scientific theory. The most outstanding scientific theories—Copernicus’ heliocentric model, Darwin’s theory of evolution, and Einstein’s theory of relativity—enabled fundamentally new intellectual perspectives that have marked specific times in our species’ history. But PhD psychology research theories are also extremely practical: they allow us to foresee and manage our environment through strategic interventions and technology by enhancing our knowledge of empirical facts. The only thing that can surpass a psychology dissertation scientific theory in terms of the traditional aims of comprehension, prediction, and control is a better scientific theory.
Theories in future psychology
The strategies for creating explanatory theories are discussed here. Science requires such theories since they are the principal means of achieving the vital objective of scientific understanding. Explanatory theories are valued in general because they aid in explaining the facts for which they were developed. Explanatory theories are a series of related assertions, at least one of which states a general principle. The positive manifold of intelligence, for example, has traditionally been explained by a doctorate in psychology positing an available intelligence component; a person’s degree of general intelligence is therefore viewed as a feature that influences their capacity to solve issues. This is a general explanatory concept since it explains the positive link between numerous cognitive abilities.
Relations between theories, data, and phenomena
The following is how theories, data, and phenomena are related (Fig. 1): For starters, facts demonstrate the presence of empirical phenomena. As previously stated, phenomena are sometimes interpreted as strong generalizations of observed data patterns; for example, the positive manifold is a generalized property of cognitive test correlations. Abstract phenomena, like a generalization, aid in defining actual data patterns. The presence of the positive manifold, for example, suggests that if we choose two specific cognitive tests or create two new ones, we should anticipate them to correlate positively.
Fig. 1. In the framework of the mutualism model of intelligence, a general structure of relationships between theories, facts, and phenomena, as well as a particular collection of instances
Methodology for theory construction:
A scientific technique is a set of processes that help a researcher get from a certain beginning point to a particular end state. A putative hypothesis is the beginning point of scientific study in the traditional hypothetic deductive system, then tested. In TCM, on the other hand, the beginning point is a collection of relevant phenomena, and the end state is a PhD topic in psychology theory that is significant in explaining these phenomena. A minimum technique for theory creation consists of the five phases listed below in order:
- Identifying relevant phenomena
- Formulating a prototheory
- Developing a formal model
- Checking the adequacy of the formal model
- Evaluating the overall worth of the constructed theory
| Step | Example |
| Identify empirical phenomena | IQ subtest scores form a positive manifold; cognitive capacities grow with age; IQ scores have a hierarchical factor structure; heredity rises with age. |
| Develop prototheory | Perhaps cognitive talents are similar to mutualistic species in that they support each other’s development. |
| Formalize theory and phenomena | Lotka-Volterra equations mathematically define or establish an artificial environment (e.g., by computer simulation) in which cognitive talents grow mutualistically; phenomena represented as relations between measurements of mental capacities. |
| Check explanatory adequacy | The positive manifold emerges naturally in simulated mutualism scenarios; other phenomena necessitate several rounds of theory improvement (e.g., making growth nonlinear, introducing individual differences in upper bounds of development, structuring the matrix of interactions to accommodate hierarchical-factor structure); in the final simulated world that incorporates mutualism, all intended empirical phenomena emerge naturally. |
| Evaluate theory | Pros:
• The theory is logically sound. • Explanatory strength of theory; theory supports new predictions: Mutualistic relationships indicate previously unknown statistical patterns in developmental data, which inspire new study directions. Cons: • Parsimony: Theory employs highly parameterized complex networks to explain basic occurrences. • Mathematical structure: Theoretical structures feature powerful mathematical idealizations that may or may not be feasible. |
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The identification of empirical phenomena begins the cycle. Putative explanatory concepts are encoded in a prototheory by abduction. One can develop a formalized model of theory and facts by abstracting these concepts into mathematical form. This is a simulation model that is used to test the explanatory power. The theory is evaluated as a consequence of theoretical analysis. If the theory is inadequate, it may be improved in many ways; if it is beyond repair, it can be abandoned; if it is adequate, it can feed new studies by identifying new (unknown) phenomena.
Fig. 2. The theoretical cycle.
Conclusion
The TCM presented in this article outlines a realistic process for developing explanatory theories. The organization of TCM makes it clear that theory creation is a talent that requires both education and purposeful practice. Psychology dissertation Students cannot learn theory construction, just as they cannot be expected to assess statistical hypotheses or devise good experimental designs without significant instruction. Charting phenomena, creative theorizing, generating formal modelling, and evaluating the best explanatory theories are all part of TCM theory creation. Thorough hypotheticodeductive theory testing based on derived predictions is a valuable addition, and these techniques should combine to achieve the methodological mix of creative speculation and rigorous examination.
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References
- Haig, B. D. (2009). Inference to the best explanation: A neglected approach to theory appraisal for psychology. American Journal of Psychology, 122, 219–234.
- Borsboom, Denny, et al. “Theory construction methodology: A practical framework for building theories in psychology.” Perspectives on Psychological Science 16.4 (2021): 756-766.
