Chi-Square Function Applied to Learning Objects Intelligent Learning Mechanisms
Linked Agent
Cota, Manuel Pérez, Author
Country of Publication
Bahrain
Place Published
Sakhir, Bahrain
Publisher
University of Bahrain
Date Issued
2014
Language
English
English Abstract
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)
Keywords: Learning, Evaluation, Chi-square, Cognitive, Profile, Genetic Algorithm
Member of
Identifier
https://digitalrepository.uob.edu.bh/id/e0a768a2-6c75-49ae-a550-6d98ee69e99c