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Data Analytics in e-Learning: Approaches and Applications
Details
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 datamining and learning analytics.
Presents in a structured way the experiences of using various machine learning techniques Provides theoretical and practical reference with a rich set of approaches and applications Focuses several successful approaches along with their corresponding developed applications implemented for Tesys
Autorentext
Marian Cristian Mih escu is Associate Professor at the Department of Computer Science and Information Technologies, Faculty of Automatics, Computers and Electronics, University of Craiova, Romania. He has published over 70 articles refereed journals, conference proceedings, and chapters. He is Co-founder of Tesys e-Learning system currently running at the University of Craiova, while more than 15 articles are related to its research issues. He has taught the course "Educational Data Mining" at Tallinn University at doctorate level and was Visiting Researcher at "Knowledge Discovery and Intelligent Systems" research group at the University of Cordoba during his postdoctoral program with the title "Software system for enhancing the quality of educational services offered by e-learning platforms" during 2010-2012.
Inhalt
Introduction to Data Analytics in e-Learning
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783030966461
- Genre Technology Encyclopedias
- Editor Marian Cristian Mih escu
- Lesemotiv Verstehen
- Anzahl Seiten 176
- Herausgeber Springer
- Größe H235mm x B155mm x T10mm
- Jahr 2023
- EAN 9783030966461
- Format Kartonierter Einband
- ISBN 3030966461
- Veröffentlichung 24.03.2023
- Titel Data Analytics in e-Learning: Approaches and Applications
- Untertitel Intelligent Systems Reference Library 220
- Gewicht 277g
- Sprache Englisch