Machine learning, neural networks, internet of things, blockchain technologies in education

Abstract

The purpose of the article is to study the using of technologies: Machine Learning (ML), Neural Networks (NN), Internet of Things (IoT) and Block Chain (BC) to improve the effectiveness of education. The study examines the limitations of traditional education and the impact of digitalization. The advantages and systems from the separate use of machine learning and neural networks are presented: predicting academic performance, analyzing student behaviour, and verifying knowledge. The IoT architecture in education is considered, consisting of three levels: perception, network and applications. The process of integrating ML, NN, IoT, and BC technologies has been developed, including data collection using IoT devices, analytical data processing using ML and NN, and reliable data storage using blockchain. Based on this scheme, the structure of the integration system is proposed, consisting of modules for data collection, intelligent analysis and storage, confirmation, and data protection.