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Artificial Intelligence Supported Educational Technologies

Overview of attention for book
Cover of 'Artificial Intelligence Supported Educational Technologies'

Table of Contents

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    Book Overview
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    Chapter 1 Open Learning Analytics: A Systematic Literature Review and Future Perspectives
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    Chapter 2 Non-distracting Feedback in Artificial Intelligence Supported Learning
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    Chapter 3 Research on Human-Computer Cooperative Teaching Supported by Artificial Intelligence Robot Assistant
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    Chapter 4 A New Conceptual Framework for Measuring Online Listening in Asynchronous Discussion Forums
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    Chapter 5 Self-Improvable, Self-Improving, and Self-Improvability Adaptive Instructional System
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    Chapter 6 Can Sensors Effectively Support Learning?
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    Chapter 7 A Prototype System of Search: Finding Short Material for Science Education in Long and High-Definition Documentary Videos
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    Chapter 8 A Learning Attention Monitoring System via Photoplethysmogram Using Wearable Wrist Devices
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    Chapter 9 Toward Improving Social Interaction Ability for Children with Autism Spectrum Disorder Using Social Signals
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    Chapter 10 Personalized Citation Recommendation Using an Ensemble Model of DSSM and Bibliographic Information
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    Chapter 11 Augmented: Academic Performance Prediction Based on Digital Campus
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    Chapter 12 Joint Embedding Learning of Educational Knowledge Graphs
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    Chapter 13 Modeling the Self-Regulated Learning Behaviors of Graduate Students in Online Academic Reading and Writing Environments
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    Chapter 14 Mapping Machine-Generated Questions to Their Related Paragraphs in the Textbook
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    Chapter 15 Change Management for Learning Analytics
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    Chapter 16 Lessons Learned from Designing Adaptive Training Systems
Attention for Chapter 5: Self-Improvable, Self-Improving, and Self-Improvability Adaptive Instructional System
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Citations

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Chapter title
Self-Improvable, Self-Improving, and Self-Improvability Adaptive Instructional System
Chapter number 5
Book title
Artificial Intelligence Supported Educational Technologies
Published by
Springer, Cham, April 2020
DOI 10.1007/978-3-030-41099-5_5
Book ISBNs
978-3-03-041098-8, 978-3-03-041099-5
Authors

Zhou Long, Frank Andrasik, Kai Liu, Xiangen Hu

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 40%
Student > Postgraduate 1 10%
Student > Ph. D. Student 1 10%
Unknown 4 40%
Readers by discipline Count As %
Computer Science 4 40%
Engineering 1 10%
Unknown 5 50%

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