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Data science for analyzing and improving educational processes

1 October 2021
Academic / Journal Article
Publisher : Springer

18471

This article explores the application of data science to enhance educational processes. It discusses how educational data mining and learning analytics can be used to understand student behavior, predict academic performance, and personalize learning experiences. The focus is on leveraging data-driven insights to optimize teaching methodologies, improve curriculum design, and ultimately boost student engagement and success. The paper highlights various techniques and challenges in implementing data science solutions within educational institutions, emphasizing the potential for significant improvements in educational outcomes through analytical approaches.

Author(s) :

Shadi Aljawarneh &Juan A. Lara

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Key topics

Data Science for social impact

Also found in

Operations and Program Management Technology for Social Change and Organisational Efficiency

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