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Learning Analytics Enhanced Online Learning Support

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Paperback / softback
184 Pages
6 May 2025
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Offering the latest developments in online education in the era of big data, this book explores theories, technologies, and practices in the field of data-driven online learning support services using learning analytics.

This book is divided into five chapters. Chapter 1 reflects and reconstructs the connotation of learning support against the backdrop of education reform, the rise of learning analytics, and the upgrading of the demand for learning services in the new era. Chapter 2 presents a P-K-DSE-E model of online learner characteristics and discusses measurement and data representation methods for learner characteristics based on it. Chapters 3–5 focus on the three types of learning support that are closely related to learning performance and satisfaction, including the promotion of social learning, electronic learning assessment based on the learning process, and personalized tutoring and support. This book innovatively develops the concept, theory, and practical methods of student support services in distance education traditional practices in the new era and provides valuable exploration of data-driven personalized learning service methods and technologies in the era of artificial intelligence through rich examples.

This book will be essential reading for students and scholars of distance and online education, educational technology, and audiovisual education.

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    Product Details
    ISBN-13
    9781032637051
    Author
    Shuang Li
    Publisher
    Taylor & Francis
    Published
    6 May 2025
    Format
    Paperback / softback
    Pages
    184

    This product hasn't received any reviews yet. Be the first to review this product!

    RRP: $98.99
    $98.00
    Ships in 2-5 business days

    Delivery estimate

    Hurry up! Current stock:

    Learning Analytics Enhanced Online Learning Support

    RRP: $98.99
    $98.00

    Description

    Offering the latest developments in online education in the era of big data, this book explores theories, technologies, and practices in the field of data-driven online learning support services using learning analytics.

    This book is divided into five chapters. Chapter 1 reflects and reconstructs the connotation of learning support against the backdrop of education reform, the rise of learning analytics, and the upgrading of the demand for learning services in the new era. Chapter 2 presents a P-K-DSE-E model of online learner characteristics and discusses measurement and data representation methods for learner characteristics based on it. Chapters 3–5 focus on the three types of learning support that are closely related to learning performance and satisfaction, including the promotion of social learning, electronic learning assessment based on the learning process, and personalized tutoring and support. This book innovatively develops the concept, theory, and practical methods of student support services in distance education traditional practices in the new era and provides valuable exploration of data-driven personalized learning service methods and technologies in the era of artificial intelligence through rich examples.

    This book will be essential reading for students and scholars of distance and online education, educational technology, and audiovisual education.

    You Can Find This Title In

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