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Intelligent Tutoring Systems

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Cover of 'Intelligent Tutoring Systems'

Table of Contents

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    Book Overview
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    Chapter 1 Understanding Procedural Knowledge for Solving Arithmetic Task by Externalization
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    Chapter 2 Do Erroneous Examples Improve Learning in Addition to Problem Solving and Worked Examples?
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    Chapter 3 Automatic Question Generation: From NLU to NLG
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    Chapter 4 Using Eye-Tracking to Determine the Impact of Prior Knowledge on Self-Regulated Learning with an Adaptive Hypermedia-Learning Environment
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    Chapter 5 Informing Authoring Best Practices Through an Analysis of Pedagogical Content and Student Behavior
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    Chapter 6 Timing Game-Based Practice in a Reading Comprehension Strategy Tutor
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    Chapter 7 Evaluation of the Formal Models for the Socratic Method
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    Chapter 8 Stealth Assessment in ITS - A Study for Developmental Dyscalculia
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    Chapter 9 Mastery-Oriented Shared Student/System Control Over Problem Selection in a Linear Equation Tutor
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    Chapter 10 Providing the Option to Skip Feedback in a Worked Example Tutor
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    Chapter 11 Tell Me How to Teach, I’ll Learn How to Solve Problems
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    Chapter 12 Scale-Driven Automatic Hint Generation for Coding Style
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    Chapter 13 Estimating Individual Differences for Student Modeling in Intelligent Tutors from Reading and Pretest Data
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    Chapter 14 Building Pedagogical Models by Formal Concept Analysis
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    Chapter 15 Predicting Learning from Student Affective Response to Tutor Questions
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    Chapter 16 Integrating Real-Time Drawing and Writing Diagnostic Models: An Evidence-Centered Design Framework for Multimodal Science Assessment
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    Chapter 17 The Bright and Dark Sides of Gamification
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    Chapter 18 Behavior Changes Across Time and Between Populations in Open-Ended Learning Environments
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    Chapter 19 Are Pedagogical Agents’ External Regulation Effective in Fostering Learning with Intelligent Tutoring Systems?
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    Chapter 20 Intervention-BKT: Incorporating Instructional Interventions into Bayesian Knowledge Tracing
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    Chapter 21 “i-Read”: A Collaborative Learning Environment to Support Students with Low Reading Abilities
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    Chapter 22 Integrating Support for Collaboration in a Computer Science Intelligent Tutoring System
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    Chapter 23 Wheel-Spinning in a Game-Based Learning Environment for Physics
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    Chapter 24 Using Multi-level Modeling with Eye-Tracking Data to Predict Metacognitive Monitoring and Self-regulated Learning with Crystal Island
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    Chapter 25 The Mobile Fact and Concept Training System (MoFaCTS)
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    Chapter 26 Coordinating Knowledge Integration with Pedagogical Agents
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    Chapter 27 An Investigation of Conversational Agent Interventions Supporting Historical Reasoning in Primary Education
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    Chapter 28 Impact of Question Difficulty on Engagement and Learning
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    Chapter 29 Are There Benefits of Using Multiple Pedagogical Agents to Support and Foster Self-Regulated Learning in an Intelligent Tutoring System?
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    Chapter 30 Can Peers Rate Reliably as Experts in Small CSCL Groups?
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    Chapter 31 Peer Review in Mentorship: Perception of the Helpfulness of Review and Reciprocal Ratings
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    Chapter 32 Motivational Gamification Strategies Rooted in Self-Determination Theory for Social Adaptive E-Learning
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    Chapter 33 Adaptive Training of the Metacognitive Skill of Knowledge Monitoring in Intelligent Tutoring Systems
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    Chapter 34 Persuading an Open Learner Model in the Context of a University Course: An Exploratory Study
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    Chapter 35 Blinded by Science?: Exploring Affective Meaning in Students’ Own Words
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    Chapter 36 A Framework for Parameterized Design of Rule Systems Applied to Algebra
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    Chapter 37 Cognitive Tutors Produce Adaptive Online Course: Inaugural Field Trial
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    Chapter 38 Optimizing Pattern Weights with a Genetic Algorithm to Improve Automatic Working Memory Capacity Identification
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    Chapter 39 Stratified Learning for Reducing Training Set Size
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    Chapter 40 Combining Worked Examples and Problem Solving in a Data-Driven Logic Tutor
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    Chapter 41 NDLtutor: An Automated Conversational Agent to Facilitate Metacognitive Skills in Fully-Negotiated OLMs
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    Chapter 42 Concept Maps Similarity Measures for Educational Applications
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    Chapter 43 Can Adaptive Pedagogical Agents’ Prompting Strategies Improve Students’ Learning and Self-Regulation?
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    Chapter 44 Automatic Extraction of Prerequisites Among Learning Objects Using Wikipedia-Based Content Analysis
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    Chapter 45 Using Electroencephalogram to Track Learner’s Reasoning in Serious Games
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    Chapter 46 Behavior and Learning of Students Using Worked-Out Examples in a Tutoring System
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    Chapter 47 The Frequency of Tutor Behaviors: A Case Study
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    Chapter 48 Towards an Effective Affective Tutoring Agent in Specialized Education
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    Chapter 49 Embedding Intelligent Tutoring Systems in MOOCs and e-Learning Platforms
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    Chapter 50 Using Cloze Procedure Questions in Worked Examples in a Programming Tutor
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    Chapter 51 The Effect of Friendship and Tutoring Roles on Reciprocal Peer Tutoring Strategies
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    Chapter 52 CRISTAL: Adapting Workplace Training to the Real World Context with an Intelligent Simulator for Radiology Trainees
Attention for Chapter 16: Integrating Real-Time Drawing and Writing Diagnostic Models: An Evidence-Centered Design Framework for Multimodal Science Assessment
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Chapter title
Integrating Real-Time Drawing and Writing Diagnostic Models: An Evidence-Centered Design Framework for Multimodal Science Assessment
Chapter number 16
Book title
Intelligent Tutoring Systems
Published in
Lecture notes in computer science, June 2016
DOI 10.1007/978-3-319-39583-8_16
Book ISBNs
978-3-31-939582-1, 978-3-31-939583-8
Authors

Andy Smith, Osman Aksit, Wookhee Min, Eric Wiebe, Bradford W. Mott, James C. Lester

Editors

Alessandro Micarelli, John Stamper, Kitty Panourgia

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 3%
United States 1 3%
Unknown 33 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 31%
Student > Bachelor 4 11%
Lecturer 3 9%
Student > Doctoral Student 3 9%
Researcher 3 9%
Other 5 14%
Unknown 6 17%
Readers by discipline Count As %
Computer Science 9 26%
Social Sciences 8 23%
Engineering 2 6%
Linguistics 2 6%
Business, Management and Accounting 1 3%
Other 6 17%
Unknown 7 20%