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Data analytics in e-learning = appro...

Mihaescu, Marian Cristian.

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Data analytics in e-learning = approaches and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data analytics in e-learning/ edited by Marian Cristian Mihaescu.
Reminder of title:	approaches and applications /
other author:	Mihaescu, Marian Cristian.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	vii, 165 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence - Educational applications. -
Online resource:	https://doi.org/10.1007/978-3-030-96644-7
ISBN:	9783030966447

Data analytics in e-learning = approaches and applications /
Data analytics in e-learningapproaches and applications /[electronic resource] :edited by Marian Cristian Mihaescu. - Cham :Springer International Publishing :2022. - vii, 165 p. :ill. (some col.), digital ;24 cm. - Intelligent systems reference library,v. 2201868-4408 ;. - Intelligent systems reference library ;v. 220..

This book focuses on research and development aspects of building data analytics workflows that address various challenges of e-learning applications. This book represents a guideline for building a data analysis workflow from scratch. Each chapter presents a step of the entire workflow, starting from an available dataset and continuing with building interpretable models, enhancing models, and tackling aspects of evaluating engagement and usability. The related work shows that many papers have focused on machine learning usage and advancement within e-learning systems. However, limited discussions have been found on presenting a detailed complete roadmap from the raw dataset up to the engagement and usability issues. Practical examples and guidelines are provided for designing and implementing new algorithms that address specific problems or functionalities. This roadmap represents a potential resource for various advances of researchers and practitioners in educational data mining and learning analytics.

ISBN: 9783030966447

Standard No.: 10.1007/978-3-030-96644-7doiSubjects--Topical Terms:

567577
Artificial intelligence
--Educational applications.

LC Class. No.: LB1028.43 / .D38 2022

Dewey Class. No.: 371.334

Data analytics in e-learning = approaches and applications /
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260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a vii, 165 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Intelligent systems reference library, $x 1868-4408 ; $v v. 220
520 $a This book focuses on research and development aspects of building data analytics workflows that address various challenges of e-learning applications. This book represents a guideline for building a data analysis workflow from scratch. Each chapter presents a step of the entire workflow, starting from an available dataset and continuing with building interpretable models, enhancing models, and tackling aspects of evaluating engagement and usability. The related work shows that many papers have focused on machine learning usage and advancement within e-learning systems. However, limited discussions have been found on presenting a detailed complete roadmap from the raw dataset up to the engagement and usability issues. Practical examples and guidelines are provided for designing and implementing new algorithms that address specific problems or functionalities. This roadmap represents a potential resource for various advances of researchers and practitioners in educational data mining and learning analytics.
650 0 $a Artificial intelligence $x Educational applications. $3 567577
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