Development of an Adaptive Mathematical Education System for Middle Grades Using Machine Learning

Abstract

The aim of the study is to improve the study of mathematics topics for middle school children by developing a software implementation of an adaptive educational system using machine learning. During the research, the topic of quadratic equations was chosen as the basis for the research and development of an adaptive system. During the testing of the adaptive system, mistakes were specifically made to simulate the consolidation of knowledge during the educational process and make sure that it works and is able to adapt to the individual level of each student, increasing the level of knowledge gained and contributing to the consolidation of the material. To achieve this goal, Python code was developed in the Jupyter Notebook development environment. Python libraries were also used, in particular the scikit-learn library for implementing machine learning. The presented approach and software implementation can be used both by teachers to check students and track their progress, and by students themselves to assimilate and consolidate the material and knowledge gained in the lessons. The results obtained during the study demonstrate an increase in the effectiveness of adaptive learning methods using machine learning.