A New Learning Cognitive Architecture Using a Statistical Function and Genetic Algorithms: An Intelligent New e-Learning Model

Abstract

Cognition, as an act of assimilation, integration and ability to express and develop information, prepares us as a species to understand our past and build our future. Surroundings of an evolutionary process as a species stems from the informational and communication between plurineuronal sensory systems (Input) and motors (output) and is unavoidably in the genesis of adaptability and learning [1]. A motivated individual be automatically a better skills receiver, a genius is 1% talent and 99% work [2]. The proposed architecture is based on an intelligent structure supported by a statistical function - Chi-square and a Genetic Algorithm (GA), that evaluate the results of the learned through what we designated as a Knowledge Block (KB). The (GA) and its evaluation function are used to construct an optimal learning path for each learner [3]. This paper makes three critical contributions: 1- It presents a genetic-based curriculum sequencing approach, that will generate a personalized cognitive profile that will be supported by the (KB), 2 - It creates the bases of a new paradigm - the (KB) structure - as a standard to implement a new way of content learning, 3 - Uses a non-linear format conducting to a correct learning path, based on individual learner needs.