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Artificial Intelligence in Education

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Cover of 'Artificial Intelligence in Education'

Table of Contents

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    Book Overview
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    Chapter 1 Modelling Learners in Crowdsourcing Educational Systems
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    Chapter 2 Interactive Pedagogical Agents for Learning Sequence Diagrams
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    Chapter 3 A Socratic Tutor for Source Code Comprehension
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    Chapter 4 Scientific Modeling Using Large Scale Knowledge
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    Chapter 5 Examining Students’ Intrinsic Cognitive Load During Program Comprehension – An Eye Tracking Approach
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    Chapter 6 Sequence-to-Sequence Models for Automated Text Simplification
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    Chapter 7 The Potential for the Use of Deep Neural Networks in e-Learning Student Evaluation with New Data Augmentation Method
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    Chapter 8 Investigating Transformers for Automatic Short Answer Grading
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    Chapter 9 Predicting Learners Need for Recommendation Using Dynamic Graph-Based Knowledge Tracing
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    Chapter 10 BERT and Prerequisite Based Ontology for Predicting Learner’s Confusion in MOOCs Discussion Forums
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    Chapter 11 Identification of Students’ Need Deficiency Through a Dialogue System
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    Chapter 12 The Double-Edged Sword of Automating Personalized Interventions in Makerspaces: An Exploratory Study of Potential Benefits and Drawbacks
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    Chapter 13 EdNet: A Large-Scale Hierarchical Dataset in Education
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    Chapter 14 Exploring Automatic Short Answer Grading as a Tool to Assist in Human Rating
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    Chapter 15 Multi-document Cohesion Network Analysis: Visualizing Intratextual and Intertextual Links
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    Chapter 16 Mastery Learning Heuristics and Their Hidden Models
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    Chapter 17 Towards Practical Detection of Unproductive Struggle
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    Chapter 18 What Happens When Gamification Ends?
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    Chapter 19 Using Eye-Tracking and Click-Stream Data to Design Adaptive Training of Children’s Inhibitory Control in a Maths and Science Game
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    Chapter 20 Prediction of Group Learning Results from an Aggregation of Individual Understanding with Kit-Build Concept Map
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    Chapter 21 Automatic Classification for Cognitive Engagement in Online Discussion Forums: Text Mining and Machine Learning Approach
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    Chapter 22 Explaining Errors in Predictions of At-Risk Students in Distance Learning Education
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    Chapter 23 A General Multi-method Approach to Design-Loop Adaptivity in Intelligent Tutoring Systems
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    Chapter 24 Towards Improving Sample Representativeness of Teachers on Online Social Media: A Case Study on Pinterest
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    Chapter 25 A Framework for Exploring the Impact of Tutor Practices on Learner Self-regulation in Online Environments
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    Chapter 26 Automated Personalized Feedback Improves Learning Gains in An Intelligent Tutoring System
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    Chapter 27 Allowing Revisions While Providing Error-Flagging Support: Is More Better?
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    Chapter 28 Learner-Context Modelling: A Bayesian Approach
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    Chapter 29 Distinguishing Anxiety Subtypes of English Language Learners Towards Augmented Emotional Clarity
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    Chapter 30 Siamese Neural Networks for Class Activity Detection
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    Chapter 31 Deep-Cross-Attention Recommendation Model for Knowledge Sharing Micro Learning Service
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    Chapter 32 Investigating the Role of Politeness in Human-Human Online Tutoring
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    Chapter 33 Raising Academic Performance in Socio-cognitive Conflict Learning Through Gamification
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    Chapter 34 Towards Interpretable Deep Learning Models for Knowledge Tracing
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    Chapter 35 Early Prediction of Success in MOOC from Video Interaction Features
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    Chapter 36 Predicting Reading Comprehension from Constructed Responses: Explanatory Retrievals as Stealth Assessment
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    Chapter 37 An Approach to Model Children’s Inhibition During Early Literacy and Numeracy Acquisition
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    Chapter 38 Confrustion and Gaming While Learning with Erroneous Examples in a Decimals Game
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    Chapter 39 Learning Outcomes and Their Relatedness Under Curriculum Drift
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    Chapter 40 Promoting Learning and Satisfaction of Children When Interacting with an Emotional Companion to Program
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    Chapter 41 Automatic Grading System Using Sentence-BERT Network
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    Chapter 42 Extended Multi-document Cohesion Network Analysis Centered on Comprehension Prediction
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    Chapter 43 Supporting Empathy Training Through Virtual Patients
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    Chapter 44 Generating Game Levels to Develop Computer Science Competencies in Game-Based Learning Environments
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    Chapter 45 An Evaluation of Data-Driven Programming Hints in a Classroom Setting
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    Chapter 46 Deep Knowledge Tracing with Transformers
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    Chapter 47 Relationships Between Body Postures and Collaborative Learning States in an Augmented Reality Study
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    Chapter 48 Effect of Immediate Feedback on Math Achievement at the High School Level
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    Chapter 49 Automated Prediction of Novice Programmer Performance Using Programming Trajectories
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    Chapter 50 Agent-in-the-Loop: Conversational Agent Support in Service of Reflection for Learning During Collaborative Programming
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    Chapter 51 Toward an Automatic Speech Classifier for the Teacher
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    Chapter 52 Constructing Automated Revision Graphs: A Novel Visualization Technique to Study Student Writing
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    Chapter 53 When Lying, Hiding and Deceiving Promotes Learning - A Case for Augmented Intelligence with Augmented Ethics
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    Chapter 54 Understanding Collaborative Question Posing During Computational Modeling in Science
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    Chapter 55 Machine Learning and Student Performance in Teams
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    Chapter 56 Scanpath Analysis of Student Attention During Problem Solving with Worked Examples
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    Chapter 57 Helping Teachers Assist Their Students in Gamified Adaptive Educational Systems: Towards a Gamification Analytics Tool
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    Chapter 58 Understanding Rapport over Multiple Sessions with a Social, Teachable Robot
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    Chapter 59 Exercise Hierarchical Feature Enhanced Knowledge Tracing
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    Chapter 60 Relationships Between Math Performance and Human Judgments of Motivational Constructs in an Online Math Tutoring System
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    Chapter 61 Automated Short-Answer Grading Using Deep Neural Networks and Item Response Theory
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    Chapter 62 Automatic Dialogic Instruction Detection for K-12 Online One-on-One Classes
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    Chapter 63 Exploring the Role of Perspective Taking in Educational Child-Robot Interaction
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    Chapter 64 Evaluating Student Learning in a Synchronous, Collaborative Programming Environment Through Log-Based Analysis of Projects
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    Chapter 65 Adaptive Forgetting Curves for Spaced Repetition Language Learning
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    Chapter 66 Learning from Interpretable Analysis: Attention-Based Knowledge Tracing
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    Chapter 67 Identifying Beneficial Learning Behaviors from Large-Scale Interaction Data
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    Chapter 68 A Gamified Solution to the Cold-Start Problem of Intelligent Tutoring System
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    Chapter 69 Bridging Over from Learning Videos to Learning Resources Through Automatic Keyword Extraction
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    Chapter 70 A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM
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    Chapter 71 Contingent Scaffolding for System Safety Analysis
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    Chapter 72 The Exploration of Feeling of Difficulty Using Eye-Tracking and Skin Conductance Response
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    Chapter 73 Sense of Agency in Times of Automation: A Teachers’ Professional Development Proposal on the Ethical Challenges of AI Applied to Education
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    Chapter 74 Improving Students’ Problem-Solving Flexibility in Non-routine Mathematics
Attention for Chapter 34: Towards Interpretable Deep Learning Models for Knowledge Tracing
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Citations

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Chapter title
Towards Interpretable Deep Learning Models for Knowledge Tracing
Chapter number 34
Book title
Artificial Intelligence in Education
Published by
Springer, Cham, June 2020
DOI 10.1007/978-3-030-52240-7_34
Book ISBNs
978-3-03-052239-1, 978-3-03-052240-7
Authors

Yu Lu, Deliang Wang, Qinggang Meng, Penghe Chen, Lu, Yu, Wang, Deliang, Meng, Qinggang, Chen, Penghe

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 18%
Researcher 9 16%
Student > Master 6 11%
Student > Postgraduate 2 4%
Student > Bachelor 2 4%
Other 3 5%
Unknown 23 42%
Readers by discipline Count As %
Computer Science 21 38%
Medicine and Dentistry 2 4%
Engineering 2 4%
Nursing and Health Professions 1 2%
Linguistics 1 2%
Other 5 9%
Unknown 23 42%