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2023 | OriginalPaper | Buchkapitel

A Comprehensive Review on Various Data Science Technologies Used for Enhancing the Quality of Education Systems

verfasst von : Olfat M. Mirza

Erschienen in: Intelligent Systems and Machine Learning

Verlag: Springer Nature Switzerland

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Abstract

Education is one of the major sources for determining the growth of country with high economic development. But the challenges facing by the education systems are poor decision-making ability, high difficulties in adapting new curriculums, inefficient teaching, and training. These factors could inherently affect the performance of education sectors in terms of increased unemployment, reduced workforce, and dissatisfaction outcomes. In order to solve these problems, this research work aims to deploy the data science technologies for improving the learning strategies in education systems. Here, the data mining techniques are mainly used to extract the relevant or useful information from the data and is widely used for solving the higher education problems. Also, this work investigates some of the challenges associated to the deployment of big data in education systems, which includes consequentialism, scientism, privacy, and security. Moreover, operating characteristics and features of the cyber security model are assessed and validated in Sect. 5. Finally, the overall paper is summarized with its obtainment and future work.

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Vorheriges Kapitel Novel Deep Learning Techniques to Design the Model and Predict Facial Expression, Gender, and Age Recognition
Nächstes Kapitel AI/ML Based Sensitive Data Discovery and Classification of Unstructured Data Sources
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Metadaten
Titel
A Comprehensive Review on Various Data Science Technologies Used for Enhancing the Quality of Education Systems
verfasst von
Olfat M. Mirza
Copyright-Jahr
2023
Buch
Intelligent Systems and Machine Learning

Print ISBN: 978-3-031-35080-1

Electronic ISBN: 978-3-031-35081-8

Copyright-Jahr: 2023

DOI
https://doi.org/10.1007/978-3-031-35081-8_30

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