Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part I (Lecture Notes in Computer Science)
This two volume set LNAI 10947 and LNAI 10948 constitutes the proceedings of the 19th International Conference on Artificial Intelligence in Education, AIED 2018, held in London, UK, in June 2018.
The 45 full papers presented in this book together with 76 poster papers, 11 young researchers tracks, 14 industry papers and 10 workshop papers were carefully reviewed and selected from 192 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.
Table of Contents
Chapter 1. Investigating the Impact of a Meaningful Gamification-Based Intervention on Novice Programmers’ Achievement
Chapter 2. Automatic Item Generation Unleashed: An Evaluation of a Large-Scale Deployment of Item Models
Chapter 3. Quantifying Classroom Instructor Dynamics with Computer Vision
Chapter 4. Learning Cognitive Models Using Neural Networks
Chapter 5. Measuring the Quality of Assessment Using Questions Generated from the Semantic Web
Chapter 6. Balancing Human Efforts and Performance of Student Response Analyzer in Dialog-Based Tutors
Chapter 7. An Instructional Factors Analysis of an Online Logical Fallacy Tutoring System
Chapter 8. Using Physiological Synchrony as an Indicator of Collaboration Quality, Task Performance and Learning
Chapter 9. Towards Combined Network and Text Analytics of Student Discourse in Online Discussions
Chapter 10. How Should Knowledge Composed of Schemas be Represented in Order to Optimize Student Model Accuracy?
Chapter 11. Active Learning for Improving Machine Learning of Student Explanatory Essays
Chapter 12. Student Learning Benefits of a Mixed-Reality Teacher Awareness Tool in AI-Enhanced Classrooms
Chapter 13. Opening Up an Intelligent Tutoring System Development Environment for Extensible Student Modeling
Chapter 14. Better Late Than Never but Never Late Is Better: Towards Reducing the Answer Response Time to Questi ...
Chapter 15. Expert Feature-Engineering vs. Deep Neural Networks: Which Is Better for Sensor-Free Affect Detection?
Chapter 16. A Comparison of Tutoring Strategies for Recovering from a Failed Attempt During Faded Support
Chapter 17. Validating Revised Bloom's Taxonomy Using Deep Knowledge Tracing
Chapter 18. Communication at Scale in a MOOC Using Predictive Engagement Analytics
Chapter 19. How to Use Simulation in the Design and Evaluation of Learning Environments with Self-directed Longer-Term Learners
Chapter 20. Students’ Academic Language Use When Constructing Scientific Explanations in an Intelligent Tutoring System
Chapter 21. Automated Pitch Convergence Improves Learning in a Social, Teachable Robot for Middle School Mathematics
Chapter 22. The Influence of Gender, Personality, Cognitive and Affective Student Engagement on Academic Engagement in Educational Virtual Worlds
Chapter 23. Metacognitive Scaffolding Amplifies the Effect of Learning by Teaching a Teachable Agent
Chapter 24. A Data-Driven Method for Helping Teachers Improve Feedback in Computer Programming Automated Tutors
Chapter 25. Student Agency and Game-Based Learning: A Study Comparing Low and High Agency
Chapter 26. Engaging with the Scenario: Affect and Facial Patterns from a Scenario-Based Intelligent Tutoring System
Chapter 27. Role of Socio-cultural Differences in Labeling Students’ Affective States
Chapter 28. Testing the Validity and Reliability of Intrinsic Motivation Inventory Subscales Within ASSISTments
Chapter 29. Correctness- and Confidence-Based Adaptive Feedback of Kit-Build Concept Map with Confidence Tagging
Chapter 30. Bring It on! Challenges Encountered While Building a Comprehensive Tutoring System Using ReaderBench
Chapter 31. Predicting the Temporal and Social Dynamics of Curiosity in Small Group Learning
Chapter 32. Learning Curve Analysis in a Large-Scale, Drill-and-Practice Serious Math Game: Where Is Learning Support Needed?
Chapter 33. Conceptual Issues in Mastery Criteria: Differentiating Uncertainty and Degrees of Knowledge
Chapter 34. Reciprocal Content Recommendation for Peer Learning Study Sessions
Chapter 35. The Impact of Data Quantity and Source on the Quality of Data-Driven Hints for Programming
Chapter 36. Predicting Question Quality Using Recurrent Neural Networks
Chapter 37. Sentence Level or Token Level Features for Automatic Short Answer Grading?: Use Both
Chapter 38. When Optimal Team Formation Is a Choice - Self-selection Versus Intelligent Team Formation Strategies in a Large Online Project-Based Course
Chapter 39. Perseverance Is Crucial for Learning. “OK! but Can I Take a Break?”
Chapter 40. Connecting the Dots Towards Collaborative AIED: Linking Group Makeup to Process to Learning
Chapter 41. Do Preschoolers ‘Game the System’? A Case Study of Children’s Intelligent (Mis)Use of a Teachable Ag ...
Chapter 42. Vygotsky Meets Backpropagation
Chapter 43. Providing Automated Real-Time Technical Feedback for Virtual Reality Based Surgical Training: Is the Simpler the Better?
Chapter 44. Reciprocal Kit-Building of Concept Map to Share Each Other’s Understanding as Preparation for Collaboration
Chapter 45. Early Identification of At-Risk Students Using Iterative Logistic Regression
- Title: Artificial Intelligence in Education: 19th International Conference, Part I
- Length: 632 pages
- Edition: 1st ed. 2018
- Language: English
- Publisher: Springer
- Publication Date: 2018-07-28
- ISBN-10: 3319938428
- ISBN-13: 9783319938424