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Predicting Pupil’s Successfulness Factors Using Machine Learning Algorithms and Mathematical Modelling Methods

  • Solomia FedushkoEmail author
  • Taras Ustyianovych
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 938)

Abstract

Taking into account the challenges and problems that are faced by the modern educational process, it is considered to use modern intelligent systems and algorithms to improve the education and teaching levels in educational institutions. The article describes an algorithm of actions on machine learning using, determining the students success level and analyzing the obtained data. This research can be efficiently used to find out and detect the modern educational problems, and individual and collective pupils sample features, implement the classification process and regression analysis of the data set. Results obtained from the algorithms usage, data analysis are described and demonstrated. The main features, knowledge and insights obtaining methods from the dataset are determined. The applied method is quite efficient and is capable of assessing pupil’s performance metrics. Predicting student’s and pupil’s characteristics will help to segment and divide them into different classes so that it will allow pupils to develop communication, leadership, and self-management skills while studying at school or university. The results show that performance metrics assessment is an integral part of modern education process that is slightly crucial for its improvement and pupil’s trends in education exploration.

Keywords

Machine learning Intelligent systems Data processing EDA Education Modern educational system School educational process 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Lviv Polytechnic National UniversityLvivUkraine

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