The Philosophy Of Science

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‘Describe and understand how science works within a wide range of sciences. This does not have to include every kind of science. But it had better not be confined to a single branch of a single science, for such an understanding would add little to what scientists working in that area already know’ (Forster, 2004). It is concerned with all the assumptions, foundations, methods, implications of science, and with the use and feature of science. This is meant to be a characterization of general philosophy of science. It also includes studies in the foundations of science, which legitimately narrow their focus to particular sciences” (Forster, 2004).

Another way is looking to the science is that the science aims at practical recommendations and problem- solving. This discipline sometimes overlaps metaphysics, ontology and epistemology. Teaching and Learning Ontology and Epistemology in Science. The teaching and learning of ontology and epistemology is an important element of science, as it helps scholar to appraise, differentiate and choose between competing philosophies, theories and analytical traditions.

Theories, concepts and issues must be rendered accessible, while at the same time remaining accurate. Thus, the necessary act of simplification, which enables initial understanding, must maintain the possibility of critical engagement, yet not result in any distortion which would misrepresent positions and confuse subsequent learning processes.

As such, teaching and learning within science should not be about the instruction and regurgitation of knowledge. Instead, teaching should mean alerting students to different ways of thinking. It should provide a non-prescriptive basis from which students can reflexively engage with the material in order to uncover relationships, connections and underlying patterns and, consequently, partake in critical analysis.

Engaging in this ‘critical analysis’ does not constitute an attempt to teach students to be critical theorists, critical realists or a particular kind of critic, in any theoretical sense. Rather, critical analysis refers to the crucial capacity to engage with, interrogate and challenge other perspectives. Teaching and learning ontology and epistemology are important in science for fostering the processes and strategies of inquiry, role taking and benign disruption, which enable this reflexive learning.

Developing a capacity for inquiry – the ability to ask questions – is crucial if students are to interrogate and challenge the differences between, the assumptions made, and the knowledge produced by, particular theoretical and analytical traditions.

In general, role-taking experiences are important for intellectual development because they enable students to critique their own position from the point of view of another and, concurrently, allow them to comprehend another’s position. The vital movement towards reflexive learning can be facilitated through engaging with ontological and epistemological issues, as it enables understanding and adjudication between contending theoretical and analytical traditions. (Bates & Jenkins, 2007).

The Paradigm

A paradigm consists of the following components: ontology, epistemology, methodology, and, methods. Each component is explained, and then the relationships between them are explored.

Epistemological assumptions are concerned with how knowledge can be created, acquired and communicated, in other words what it means to know. Every paradigm is based upon its own ontological and epistemological assumptions. Since all assumptions are conjecture, the philosophical underpinnings of each paradigm can never be empirically proven or disproven. Different paradigms inherently contain differing ontological and epistemological views. Research methods can be traced back, through methodology and epistemology, to an ontological position. It is impossible to engage in any form of research without committing.

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The scientific paradigm rose to prominence during the Enlightenment. The ontological position of positivism is one of realism. Realism is the view that objects have an existence independent of the knower. The positivist epistemology is one of objectivism. Positivists go forth into the world impartially, discovering absolute knowledge about an objective reality. Thus, phenomena have an independent existence which can be discovered via research. Positivistic statements are descriptive and factual. The scientific paradigm is foundational as scientific propositions are founded on data and facts.

The scientific paradigm seeks predictions and generalizations; thus, methods often generate quantitative data. Examples include: standardized tests, closed ended questionnaires and descriptions of phenomena using standardized observation tools. Analysis involves descriptive and inferential statistics. Inferential statistics allow sample results to be generalized to populations. Research is deemed good if its results are due to the independent variable, can be generalized/transferred to other populations or situations, and different researchers can record the same data in the same way and arrive at the same conclusions. Additionally, research needs to be as objective as possible and robust to empirical refutation. (Scotland, 2012).

The Logic

Logic and probability are the standard tools of philosophy of science. Probability can be seen as an extension of logic, so it is important to understand the basics concepts of logic first. Logic has many branches. The best known branch of logic is called deductive logic. Briefly, deduction is what mathematicians do, except when they use simplifying approximations, which happens a lot in science. (Forster, 2004). An argument is a set of claims, one of which is the conclusion and the rest of which are the premises. The conclusion states the point being argued for and the premises state the reasons being advanced in support the conclusion. They may not be good reasons. There are good and bad arguments. An argument is deductively valid if and only if it is impossible that its conclusion is false while its premises are true. According to intuitivism, the problem is to understand how a hypothesis like? All planets move in ellipses? Is supported by, or confirmed by, the fact that all the instances of the generalization observed so far have been true. One inductivity strategy is to ask what missing premise must be added to the argument to make it deductively valid, and then to evaluate the truth of the added premise (Hitchcock, 2004).

Simple ideas tend to be more complicated that they appear at first sight. In the end, it defend the view that science has a logic, albeit one that reaches beyond deductive logic into the murkier realm of statistical inference (Forster, 2004).

Explanation

Although the subject of explanation has been a major concern of philosophy, modern philosophical discussion of this topic, at least as it pertains to science, begins with the so-called deductive-nomological (DN). This model has many advocates but unquestionably the most detailed.

The basic idea of the deductive-nomological (DN) model is that explanations have the structure of sound deductive arguments in which a law of nature occurs as an essential premise. One deduces the explanandum, which describes the phenomenon to be explained, from an explaining, consisting of one or more laws, typically supplemented by true sentences about initial conditions. The model is intended to apply both to the explanation of “general regularities” by other laws and the explanation of particular events, although subsequent developments have largely focused on the latter.

The DN model is meant to capture explanation via deduction from deterministic laws and this raises the obvious question of the explanatory status of statistical laws. Much of the appeal of the deductive- nomological (DN) model lies in the undeniable fact that in some areas of science, such as physics, many explanations do seem to involve derivations from laws.It claims that all explanations conform to the requirements of the model, and that everything conforming to those requirements is an explanation.

We need to ask whether these claims are correct and whether the key components of the model such as the notion of a law, are sufficiently clear and well-understood to play the role the model assigns to them. (Machamer & Silberstein, 2002).

Conclusion

Philosophy of Science It’s have a lot of discus on world wild view from different Scientists and Philosopher. It’s a subjective, discover, knowledge.

Understanding the philosophical assumptions that underpin each paradigm and how these assumptions manifest themselves within methodology and methods. Ontological and epistemological consideration can facilitate reflexive learning. For this to flourish further, we must improve the accuracy of definitions, as well as providing a framework which renders concepts accessible. Alerting researchers to this dissension is particularly important because it encourages them to challenge assumptions and premises.

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The Philosophy Of Science. (2022, February 24). Edubirdie. Retrieved July 6, 2022, from https://edubirdie.com/examples/the-philosophy-of-science/
“The Philosophy Of Science.” Edubirdie, 24 Feb. 2022, edubirdie.com/examples/the-philosophy-of-science/
The Philosophy Of Science. [online]. Available at: <https://edubirdie.com/examples/the-philosophy-of-science/> [Accessed 6 Jul. 2022].
The Philosophy Of Science [Internet]. Edubirdie. 2022 Feb 24 [cited 2022 Jul 6]. Available from: https://edubirdie.com/examples/the-philosophy-of-science/
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