logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Machine Learning Paradigms Advances In Learning Analytics 1st Ed Maria Virvou

  • SKU: BELL-10796436
Machine Learning Paradigms Advances In Learning Analytics 1st Ed Maria Virvou
$ 31.00 $ 45.00 (-31%)

5.0

28 reviews

Machine Learning Paradigms Advances In Learning Analytics 1st Ed Maria Virvou instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 5.77 MB
Author: Maria Virvou, Efthimios Alepis, George A. Tsihrintzis, Lakhmi C. Jain
ISBN: 9783030137427, 9783030137434, 3030137422, 3030137430
Language: English
Year: 2020
Edition: 1st ed.

Product desciption

Machine Learning Paradigms Advances In Learning Analytics 1st Ed Maria Virvou by Maria Virvou, Efthimios Alepis, George A. Tsihrintzis, Lakhmi C. Jain 9783030137427, 9783030137434, 3030137422, 3030137430 instant download after payment.

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.

Related Products