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Robert J. Marzano is an educational researcher in the United States. He has done educational research and theory on the topics of standards-based assessment, cognition, high-yield teaching strategies, and school leadership, including the development of practical programs and tools for teachers and administrators in K–12 schools.
Rules of inference are syntactical transform rules which one can use to infer a conclusion from a premise to create an argument. A set of rules can be used to infer any valid conclusion if it is complete, while never inferring an invalid conclusion, if it is sound.
A rule of inference is a way or schema of drawing a conclusion from a set of premises. [17] This happens usually based only on the logical form of the premises. A rule of inference is valid if, when applied to true premises, the conclusion cannot be false. A particular argument is valid if it follows a valid rule of inference.
Knowledge representation goes hand in hand with automated reasoning because one of the main purposes of explicitly representing knowledge is to be able to reason about that knowledge, to make inferences, assert new knowledge, etc. Virtually all knowledge representation languages have a reasoning or inference engine as part of the system. [17]
The resulting inference rule is refutation-complete, [6] in that a set of clauses is unsatisfiable if and only if there exists a derivation of the empty clause using only resolution, enhanced by factoring. An example for an unsatisfiable clause set for which factoring is needed to derive the empty clause is:
Educational research refers to the systematic collection and analysis of evidence and data related to the field of education. Research may involve a variety of methods [1] [2] [3] and various aspects of education including student learning, interaction, teaching methods, teacher training, and classroom dynamics.
In statistics education, informal inferential reasoning (also called informal inference) refers to the process of making a generalization based on data (samples) about a wider universe (population/process) while taking into account uncertainty without using the formal statistical procedure or methods (e.g. P-values, t-test, hypothesis testing, significance test).
The inference engine applied logical rules to the knowledge base and deduced new knowledge. This process would iterate as each new fact in the knowledge base could trigger additional rules in the inference engine. Inference engines work primarily in one of two modes either special rule or facts: forward chaining and backward chaining. Forward ...