Modeling of Reading Problems Experienced by Primary School Students Through Artificial Neural Networks

Abstract

This study intends to identify the shortcomings caused by educational practices that underlie the problems that students experience in reading and to develop a forecast and classification model through artificial neural networks. Drawing on the exploratory sequential pattern, this study is performed in two parts. In the qualitative part, a data pool with 35 items is created for the shortcomings caused by educational practices that underlie the reading problems experienced by the students through the opinions of 47 classroom teachers participating in this study. The second part is where the checklist designed based on the data obtained in the first part is administered to 174 classroom teachers who lecture the third graders. The numerical values are processed into MATLAB, and two different models, forecast and classification models, are developed for the shortcomings caused by educational practices that underlie the reading problems experienced by the students through artificial neural networks. In this regard, this study intends to identify solutions to the potential reading problems that students may experience due to the shortcomings caused by educational practices before they arise, and to develop preventive actions.