Chi-Square Function Applied to Learning Objects Intelligent Learning Mechanisms

Abstract

The massive data set obtained from the analysis of a particular cognitive profile requires an evaluation function versatile enough for application to a Genetic Algorithm (GA) in order to be able to make decisions that involve a high degree of reliability - in the order of 90 to 95%. The problem to be studied is whether it is possible or not to evolve in cognitive terms, through the choice of learning object [7] more suitable, which we denominate as Knowledge Block (KB) - a Sharable Content Object Reference Model (SCORM) compatible structure – see Fig. 2. The Pearson’s Chi-square test (X2) is the evaluation function selected, because of its simplicity. By observation of merely two parameters — Observed Value (Oj)