Introduction
Philosophy is all about questioning and setting the rules to find out the truth and its different approaches. It defines the abstract concepts and emphasizes on logic with rules of argumentation. Philosophy has researched science with good detail and influenced scientific inventions by thorough reasoning and intellectual thought (Popper, 2014). The subject of philosophy went deep down and developed various approaches, scientific method, and practices of science, adopting the strategy of discovering the facts, mechanisms, and laws to study the natural world. Science is a collection of knowledge, which is based upon predictions and testable explanation. As a result, science and philosophy have a strong connection to support each other in finding out truths and exploring creative thoughts. In the system of sciences, they take a worldview, draw methodological principles, and use method of cognition.
In order to get the scientific knowledge, scientific method applies that develops the knowledge of physical world and its phenomena. Based upon the experiments and principles of reasoning, a specific method of enquiry is chosen. This allows the collection of measurable and observable evidence. In order to generate the useful scientific knowledge, a scientific method is available that helps to collect data, formulate, and test hypotheses. According to Driver et.al science has become the major subject of philosophy that does the scientific enquiry, maintains skepticism, and works on different dimensions of scientific knowledge that resides human mind too (Driver et.al, pp. 287-312). Science involves subjective and objective study of knowledge by using creativity, discovery, methods, and processes to get the empirical evidence. Scientific knowledge keeps changing due to the examinations and re examinations. When new investigations, frequent examinations and scientific argumentation continue to develop then scientific knowledge gets stronger. Therefore, scientific knowledge is quite open to change, durable and robust.
Discussion
New evidences continually change the scientific explanations and establish theories and ideas to go beyond the boundaries of scientific explanations. Scientific knowledge is rather general and simple. It is cumulative, transmissible, and explanatory as it is based upon thorough research and empirical evidence. Malterud is of the view that science inquiry requires genuine knowledge to create evidence for the natural phenomena’s explanations (Malterud , pp. 483-488). Empirical work in science is highly associated with ambiguity and complexities, encouraging educative, diagnostic, and formative assessments, reinforcing the review and creation of arguments. As a result, there are two types of reasoning used to collect data and information named as Deductive and Inductive.
In order to provide a rationale, analyze a problem, and support a conclusion scientists make a use of various modes for reasoning related to scientific knowledge. By using their creativity, they invent new explanations, tests, and ideas. For any reasoning of scientific knowledge, it is important to use that process or mode of reasoning which relies on logical consideration (McComas, pp. 53-70). Evidence should be based on careful consideration to prove an idea. To generate the knowledge of science and observe the truth of a particular idea, various scientists use Inductive research.
Inductive reasoning focuses upon the evidence to come up to a general conclusion and is an open-ended approach. By using the evidence, it develops a theory that supports the truth of an idea. It determines the consequences by making use of probabilities and as a result, results are not guaranteed to be true. Even if the facts are right and true, the conclusion drawn is most likely to be true. Inductive has an advantage of being a bottom up approach that moves from observations to theories and abstract generalizations and begins with measures and observations (Zimmerman, pp. 99-149). Regularities and patterns become a part of this process until tentative hypotheses are formulated. Based upon them, explorations are done and then finally theories and results are drawn. Moreover, at the beginning it allows the user to take the benefit of its explanatory nature so that he can observe the roots of scientific information. While using inductive, observation is cognitive and involves perception. In an inductive reasoning observation requires active engagement that includes the sensory data from surrounding. Observation is said to be theory laden meaning that while observing one understands the functions of world and that understanding affects the way he notices and perceives the things that need consideration.
Induction proves a reliable method for collecting scientific knowledge by working within theoretical context (Mayo and Spanos, pp.323-357). With theoretical interpretation, the information is useful as it is based upon observed assumptions. Inductive reasoning is more helpful to get scientific information when there is a need to know the possibilities of future and predicting what and how one might encounter his future. Its strength lies in establishment of probability that allows the determination of whether theory or observation is right or wrong, using different patterns to reach a conclusion. Observation sets a path, makes direction for investigation of information, and forms a reason for any truth of scientific knowledge. It starts with the results and effects and then generates the reason of information. Inductive reasoning proves to be very flexible while evaluation of hypothesis is going on and when the information is incompatible with the known causes. It has a pure logic of relying on empirical experience and use knowledge claims to make its way from specific to general. It applies the real world scenarios and forms reasonable conclusions to form reasonable principles. Various ancient philosophers are said to be using inductive so that their developed theories could be based upon logic. They believed that inductive would need no experiments as results could be drawn through observation. Additionally, the work of Charles Darwin a naturalist and geologist, known for his great contribution, is also based upon induction research. His evolutionary theory still applies in accepting the advantages of inductive reasoning.
The best thing about inductive reasoning as a method of gaining scientific knowledge is that it starts with observing and collecting data without any bias. In its analysis stage, it identifies the regularity pattern and classifies the facts. Next stage searches the relations between facts and then finally observation is confirmed. Scientific knowledge based upon inductive research can be in form of predictions, extrapolations, and part to whole. For any research inductive can prove to be very useful to find out scientific knowledge as it occupies neutral observation. It starts with small with observation of data and then moving towards big to create laws, finds out similarities, rules, and principles. A social scientist Erving Goffman is also known for using inductive research who believed that such information is easy to convince, as it is open to any question (Hillyard, pp. 421-440). According to him, it relies upon conclusion rather than the evidence on which it is founded. Inductive reasoning for scientific knowledge is more likely to be valid when it is found out with integrity and trust.
Inductive is a major part and has a great contribution towards the growth of scientific knowledge (Zimmerman, pp. 99-149). However, inductive reasoning does not have the advantages of being objective and certain. Inductive is more of considering already existing theories that were developed according to the topic of interest. Theoretical foundations experience addition and extension of information and then development of hypothesis. In order to conduct a new theory, a hypothesis is tested for a new study. In that way, inductive is good and reliable to be thorough and extensive, but it lacks certainty. Inductive reasoning gives inductive arguments and quality results only if empirical evidence is of high quality. If the level of probability is high then generalizations can said to be reliable otherwise they cannot be trustworthy. For any theory or information, often it is unknown about the exact quantity of evidence needed for a qualitative research and it is only when inductive proves useful as it allows generalizations. In any experimentations of generating scientific knowledge, inductive may not prove reliable method of reasoning. Inductive research does not find out the casual relationship and relation to linearity. However, inductive research deals with the enquiry of phenomenal descriptions, is meaningful and very interesting method but it requires the user to go beyond boundaries and be actively involved in a process. However, at the same time, it requires active and careful selection of data to reach towards an authentic evidence and conclusion. In addition to that, it takes time to come to conclusion as studying a phenomenon, generating hypothesis, and then explaining that phenomenon is time consuming. .
Conclusion
In order to scratch the surface of scientific information, the choice of inductive reasoning depends upon the ability of researchers. Scientists have different ideas about different theories, using observation at one point and relying upon existing rules at the other time. If the scientist has the creativity to come up to the right and valid questions of research and specific results can be used to bring out the general rules, then inductive is reliable method as seen in natural sciences. However, if the research and reasoning is based upon the known data/information and starts with the theory, as in mathematics, then inductive research may not be useful. The user should not rely upon inductive reasoning if already existing rules are applied and then a hypothesis is determined to create ideas and new information.
Similarly, if a new theory is checked and compared with the original one to analyze whether additional information approves or disproves the original one, inductive may not prove successful idea as such research ends up to based upon known theory and known information.
Chakravartty, (2007) suggest that the inductive is a naturalistic approach that acquires knowledge rather than using existing ones. It is reliable when there is a need for qualitative data analysis and inquiry.
Works Cited
Chakravartty, A. "A metaphysics for scientific realism." Knowing the Unobservable (2007).
Driver, R, Newton, P, and Osborne, J. "Establishing the norms of scientific argumentation in classrooms." Science education 84.3 (2000): pp. 287-312.
Hillyard, S. "Ethnography’s capacity to contribute to the cumulation of theory: a case study of Strong’s work on Goffman." Journal of Contemporary Ethnography 39.4 (2010): pp. 421-440.
Malterud, K. "Qualitative research: standards, challenges, and guidelines." The lancet 358.9280 (2001): pp. 483-488.
Mayo, D, G., and Spanos, A. "Severe testing as a basic concept in a Neyman–Pearson philosophy of induction." The British Journal for the Philosophy of Science 57.2 (2006): pp.323-357.
McComas, W, F. "The principal elements of the nature of science: Dispelling the myths." The nature of science in science education. Springer Netherlands, 2002. pp. 53-70.
Popper, K. The logic of scientific discovery. Routledge, 2014.
Zimmerman, C. "The development of scientific reasoning skills." Developmental Review 20.1 (2000): pp. 99-149.
