Modeling of multiple intelligence theory with Bayes theorem

Abstract

In this work, multiple intelligence theory proposed by Gardner, a professor of education at Harvard University, is tried to be modeled by Bayesian Theorem under two hypotheses. Howard Gardner initially formulated a list of seven intelligences, and then added two more. As a different approach, if set theory for multiple intelligences is used, the structure of multiple intelligences to set theory under four properties of intelligence algebra can be generalized. Assuming that the number of intelligences increases, n, Boolean algebra in set theory can be applicable. At this point, Bayesian theorem, application of conditional probability, generates a good structure for multiple intelligences. In this work, Bayesian Theorem was applied to two hypotheses, mutually intersections of n intelligences are empty and non-empty sets, and using conditional probability, it can be shown that multiple intelligences and Bayesian Theorem are in good harmony or multiple intelligences can be clarified by Bayesian theorem.