Machine Learning Paradigms: Advances in Learning Analytics

ISBN-13: 9783030137427 / Angielski / Twarda / 2019 / 223 str.

Maria Virvou; Efthimios Alepis; George A. Tsihrintzis

Recenzje

"The book ... exposes its readers to the full spectrum of related research problems and progress. ... Each chapter is carefully written to be self-contained and complete. ... Professors, graduate students and researchers in Learning Analytics, will find this book as a valuable resource for conducting their research. ... I congratulate the Editors for their outstanding work. I consider their book as an important addition to the Learning Analytics literature and I provide my highest and unreserved recommendation to it." (Ioannis Hatzilygeroudis, Intelligent Decision Technologies, Vol. 15 (2), 2021)

Blurb

This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators’ and learners’ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including:

• Using learning analytics to measure student engagement, to quantify the learning experience and to  facilitate self-regulation;

• Using learning analytics to predict student performance;

• Using learning analytics to create learning materials and educational courses; and

• Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning.

The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.