On Predicting Learning Outcomes Based on Fuzzy Modeling
Abstract
When teaching schoolchildren or students, regardless of the discipline being studied, it is highly desirable to predict the knowledge of students. At the same time, one of the possible factors on the basis of which forecasting is based may be the knowledge of students in previously studied sections of this discipline. The constructed forecast can allow for a more effective individual approach to students, improve the quality of the learning process.
Since all sections of almost any training course are interconnected, it is possible to build a graph that models the structure of connections within the entire discipline or any part of it. Due to the fact that the connections between the sections of the discipline have different degrees of significance, and the definition of this significance is subjective, it is advisable to use a fuzzy graph for modeling, the degrees of belonging of the arcs of which model the closeness of the connection between the sections of the discipline within the framework of the model under consideration. Based on the constructed fuzzy graph, it is possible to build a fuzzy inference system that allows you to predict the results of educational activities in the discipline. It is obvious that the construction of a model in each specific case should be carried out jointly by a teacher or a specialist in the methodology of teaching this discipline and a specialist in the field of fuzzy modeling.
The paper considers an example of constructing a fuzzy graph and a system of rules for predicting the results of training in the algebra course of the 7th grade of high school and a computer implementation of the constructed model using the Fuzzy Logic Toolbox library of the MatLab package and a C# software application developed by us using the Accord library. The comparison of these two approaches to the implementation of the model is carried out.
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