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Axial coding in grounded theory is the process of relating codes (categories and concepts) to each other, via a combination of inductive and deductive thinking. According to Strauss and Corbin (1990, 1998) who propose the use of a "coding paradigm", the basic framework of generic relationships is understood to include categories related to:
Researchers and analysts typically use RQDA using two types of coding approaches: inductive and deductive. In inductive coding, a researcher codes a body of text "from the ground up". That is, the textual units that are coded are not pre-determined by specific theory/literature/concepts but the texts are coded to discover new concepts/ideas ...
While inductive methods select items based upon factor loadings, empirical items are selected based upon validity coefficients and their ability to accurately predict group membership. However, the empirical method shares many of the strengths and weaknesses of atheoretical item creation with inductive methods, while also having an initial item ...
Coding is the primary process for developing themes by identifying items of analytic interest in the data and tagging these with a coding label. [4] In some thematic analysis approaches coding follows theme development and is a deductive process of allocating data to pre-identified themes (this approach is common in coding reliability and code ...
This theory of deductive reasoning – also known as term logic – was developed by Aristotle, but was superseded by propositional (sentential) logic and predicate logic. [citation needed] Deductive reasoning can be contrasted with inductive reasoning, in regards to validity and soundness. In cases of inductive reasoning, even though the ...
Inductive reasoning is any of various methods of reasoning in which broad generalizations or principles are derived from a body of observations. [1] [2] This article is concerned with the inductive reasoning other than deductive reasoning (such as mathematical induction), where the conclusion of a deductive argument is certain, given the premises are correct; in contrast, the truth of the ...
Inductive logic programming (ILP) is an approach to machine learning that induces logic programs as hypothetical generalisations of positive and negative examples. Given a logic program representing background knowledge and positive examples together with constraints representing negative examples, an ILP system induces a logic program that ...
The inductive approach to solving this problem is to use the labeled points to train a supervised learning algorithm, and then have it predict labels for all of the unlabeled points. With this problem, however, the supervised learning algorithm will only have five labeled points to use as a basis for building a predictive model.