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Intelligent Tutoring Systems

Overview of attention for book
Cover of 'Intelligent Tutoring Systems'

Table of Contents

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    Book Overview
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    Chapter 1 A Learning Early-Warning Model Based on Knowledge Points
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    Chapter 2 Adaptive Learning Spaces with Context-Awareness
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    Chapter 3 An Adaptive Approach to Provide Feedback for Students in Programming Problem Solving
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    Chapter 4 Analysis and Prediction of Student Emotions While Doing Programming Exercises
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    Chapter 5 Analyzing the Group Formation Process in Intelligent Tutoring Systems
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    Chapter 6 Analyzing the Usage of the Classical ITS Software Architecture and Refining It
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    Chapter 7 Assessing Students’ Clinical Reasoning Using Gaze and EEG Features
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    Chapter 8 Computer-Aided Intervention for Reading Comprehension Disabilities
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    Chapter 9 Conceptualization of IMS that Estimates Learners’ Mental States from Learners’ Physiological Information Using Deep Neural Network Algorithm
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    Chapter 10 Data-Driven Student Clusters Based on Online Learning Behavior in a Flipped Classroom with an Intelligent Tutoring System
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    Chapter 11 Decision Support for an Adversarial Game Environment Using Automatic Hint Generation
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    Chapter 12 Detecting Collaborative Learning Through Emotions: An Investigation Using Facial Expression Recognition
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    Chapter 13 Fact Checking Misinformation Using Recommendations from Emotional Pedagogical Agents
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    Chapter 14 Intelligent On-line Exam Management and Evaluation System
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    Chapter 15 Learning by Arguing in Argument-Based Machine Learning Framework
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    Chapter 16 Model for Data Analysis Process and Its Relationship to the Hypothesis-Driven and Data-Driven Research Approaches
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    Chapter 17 On the Discovery of Educational Patterns using Biclustering
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    Chapter 18 Parent-Child Interaction in Children’s Learning How to Use a New Application
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    Chapter 19 PKULAE: A Learning Attitude Evaluation Method Based on Learning Behavior
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    Chapter 20 Predicting MOOCs Dropout Using Only Two Easily Obtainable Features from the First Week’s Activities
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    Chapter 21 Predicting Subjective Enjoyment of Aspects of a Videogame from Psychophysiological Measures of Arousal and Valence
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    Chapter 22 Providing the Option to Skip Feedback – A Reproducibility Study
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    Chapter 23 Reducing Annotation Effort in Automatic Essay Evaluation Using Locality Sensitive Hashing
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    Chapter 24 Representing and Evaluating Strategies for Solving Parsons Puzzles
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    Chapter 25 Testing the Robustness of Inquiry Practices Once Scaffolding Is Removed
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    Chapter 26 Toward Real-Time System Adaptation Using Excitement Detection from Eye Tracking
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    Chapter 27 Towards Predicting Attention and Workload During Math Problem Solving
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Title
Intelligent Tutoring Systems
Published by
Springer International Publishing, August 2019
DOI 10.1007/978-3-030-22244-4
ISBNs
978-3-03-022243-7, 978-3-03-022244-4
Editors

Coy, Andre, Hayashi, Yugo, Chang, Maiga

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users 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 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 2 11%
Student > Postgraduate 2 11%
Student > Ph. D. Student 1 5%
Professor 1 5%
Researcher 1 5%
Other 1 5%
Unknown 11 58%
Readers by discipline Count As %
Computer Science 5 26%
Psychology 1 5%
Social Sciences 1 5%
Engineering 1 5%
Unknown 11 58%