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Machine Learning Paradigms

Overview of attention for book
Cover of 'Machine Learning Paradigms'

Table of Contents

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    Book Overview
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    Chapter 1 Machine Learning Paradigms
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    Chapter 2 Using a Multi Module Model for Learning Analytics to Predict Learners’ Cognitive States and Provide Tailored Learning Pathways and Assessment
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    Chapter 3 Analytics for Student Engagement
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    Chapter 4 Assessing Self-regulation, a New Topic in Learning Analytics: Process of Information Objectification
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    Chapter 5 Learning Feedback Based on Dispositional Learning Analytics
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    Chapter 6 The Variability of the Reasons for Student Dropout in Distance Learning and the Prediction of Dropout-Prone Students
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    Chapter 7 An Architectural Perspective of Learning Analytics
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    Chapter 8 Multimodal Learning Analytics in a Laboratory Classroom
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    Chapter 9 Dashboards for Computer-Supported Collaborative Learning
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    Chapter 10 Learning Analytics in Distance and Mobile Learning for Designing Personalised Software
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    Chapter 11 Optimizing Programming Language Learning Through Student Modeling in an Adaptive Web-Based Educational Environment
Attention for Chapter 8: Multimodal Learning Analytics in a Laboratory Classroom
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Citations

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Chapter title
Multimodal Learning Analytics in a Laboratory Classroom
Chapter number 8
Book title
Machine Learning Paradigms
Published by
Springer, Cham, January 2020
DOI 10.1007/978-3-030-13743-4_8
Book ISBNs
978-3-03-013742-7, 978-3-03-013743-4
Authors

Man Ching Esther Chan, Xavier Ochoa, David Clarke, Chan, Man Ching Esther, Ochoa, Xavier, Clarke, David

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 18%
Lecturer 4 8%
Researcher 4 8%
Professor 4 8%
Student > Bachelor 4 8%
Other 13 27%
Unknown 11 22%
Readers by discipline Count As %
Computer Science 13 27%
Arts and Humanities 7 14%
Social Sciences 4 8%
Medicine and Dentistry 2 4%
Engineering 2 4%
Other 7 14%
Unknown 14 29%

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