Shulph Ink
Data Analytics in e-Learning: Approaches and Applications
Data Analytics in e-Learning: Approaches and Applications
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- More about Data Analytics in e-Learning: Approaches and Applications
This book provides a roadmap for building data analytics workflows in e-learning applications, covering steps from raw datasets to interpretable models, enhancement, and evaluation of engagement and usability. It offers practical examples and guidelines for designing and implementing new algorithms, making it a valuable resource for researchers and practitioners in educational datamining and learning analytics.
Format: Hardback
Length: 165 pages
Publication date: 23 March 2022
Publisher: Springer Nature Switzerland AG
This comprehensive book delves into the intricate realm of research and development in constructing data analytics workflows tailored to address the diverse challenges faced by e-learning applications. It serves as a valuable guide for building a data analysis workflow from the ground up, encompassing each step of the process, from acquiring an available dataset to developing interpretable models, refining models, and addressing key aspects of evaluating engagement and usability.
Through a thorough examination of related work, it becomes evident that numerous papers have centered on the utilization and advancements of machine learning within e-learning systems. However, there has been a scarcity of discussions that provide a comprehensive and detailed roadmap, spanning from raw datasets to addressing engagement and usability issues. To address this gap, the book offers practical examples and guidelines for designing and implementing novel algorithms that specifically address specific problems or functionalities.
This roadmap serves as a valuable resource for researchers and practitioners in the fields of educational data mining and learning analytics, offering a roadmap for advancing their knowledge and expertise in this rapidly evolving domain. By leveraging the insights and methodologies presented in this book, stakeholders can develop more effective and efficient data analytics solutions that enhance the learning experience and optimize educational outcomes.
Weight: 436g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030966430
Edition number: 1st ed. 2022
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