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

    Product form

    £123.49

    Includes FREE delivery

    RRP £129.99 – you save £6.50 (5%)

    Order before 4pm tomorrow for delivery by Sat 4 Jul 2026.

    A Hardback by Marian Cristian Mihăescu

    1 in stock

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of Data Analytics in e-Learning: Approaches and by Marian Cristian Mihăescu

      Publisher: Springer Nature Switzerland AG
      Publication Date: 23/03/2022
      ISBN13: 9783030966430, 978-3030966430
      ISBN10: 3030966437

      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


      Recently viewed products

      © 2026 Book Curl

        • American Express
        • Apple Pay
        • Diners Club
        • Discover
        • Google Pay
        • Maestro
        • Mastercard
        • PayPal
        • Shop Pay
        • Union Pay
        • Visa

        Login

        Forgot your password?

        Don't have an account yet?
        Create account