Description

Book Synopsis

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.




Table of Contents

Introduction to Data Analytics in e-Learning


Data Analytics in e-Learning: Approaches and

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    A Hardback by Marian Cristian Mihăescu

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      Book details

      Publisher Springer Nature Switzerland AG
      Published 23 March 2022
      ISBN-13 9783030966430
      978-3030966430
      ISBN-10 3030966437
      Also in:
      Artificial intelligence (AI)

      Description

      Book Synopsis

      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.




      Table of Contents

      Introduction to Data Analytics in e-Learning


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