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.
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Marian Cristian Mihaescu 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.
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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. Codice articolo 826164766
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 176 pp. Englisch. Codice articolo 9783030966461
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Taschenbuch. Condizione: Neu. Data Analytics in e-Learning: Approaches and Applications | Marian Cristian Mih¿escu | Taschenbuch | Intelligent Systems Reference Library | vii | Englisch | 2023 | Springer | EAN 9783030966461 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Codice articolo 126667715
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 176 pp. Englisch. Codice articolo 9783030966461
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