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Artificial Intelligence in Education: 22nd International Conference, Aied 2021, Utrecht, the Netherlands, June 14-18, 2021, Proceedings, Part I

Artificial Intelligence in Education: 22nd International Conference, Aied 2021, Utrecht, the Netherlands, June 14-18, 2021, Proceedings, Part I (Paperback, 2021)

Vania Dimitrova, Rose Luckin, Sergey Sosnovsky, Ido Roll, Danielle McNamara (엮은이)
Springer
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Artificial Intelligence in Education: 22nd International Conference, Aied 2021, Utrecht, the Netherlands, June 14-18, 2021, Proceedings, Part I
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· 제목 : Artificial Intelligence in Education: 22nd International Conference, Aied 2021, Utrecht, the Netherlands, June 14-18, 2021, Proceedings, Part I (Paperback, 2021) 
· 분류 : 외국도서 > 컴퓨터 > 인공지능(AI)
· ISBN : 9783030782917
· 쪽수 : 518쪽
· 출판일 : 2021-06-11

목차

Full Papers.- RepairNet: Contextual Sequence-to-Sequence network for automated program repair.- Seven-year longitudinal implications of wheel spinning and productive persistence.- A Systematic Review of Data-driven Approaches to Item Difficulty Prediction.- Annotating Student Engagement Across Grades 1-12: Associations with Demographics and Expressivity.- Affect-Targeted Interviews for Understanding Student Frustration.- Explainable Recommendations in a Personalized Programming Practice System.- Mutilingual Age of Exposure.- DiSCS: A New Sequence Segmentation Method for Open-Ended Learning Environments.- Interpretable Clustering of Students' Solutions in Introductory Programming.- Adaptively Scaffolding Cognitive Engagement with Batch Constrained Deep Q-Networks.- Ordering Effects in a Role-Based Scaffolding Intervention for Asynchronous Online Discussions.- Option Tracing: Beyond Correctness Analysis in Knowledge Tracing.-  An approach for detecting student perceptions of the programming experience from interaction log data.- Discovering Co-creative Dialogue States during Collaborative Learning.- Affective Teacher Tools: Affective Class Report Card and Dashboard.- Engendering Trust in Automated Feedback: A Two Step Comparison of Feedbacks in Gesture Based Learning.- Investigating students' reasoning in a code-tracing tutor.- Evaluating Critical Reinforcement Learning Framework In the Field.- Machine learning models and their development process as learning affordances for humans.- Predicting Co-Occurring Emotions from Eye-Tracking and Interaction Data in MetaTutor.- A Fairness Evaluation of Automated Methods for Scoring Text Evidence Usage in Writing.- The Challenge of Noisy Classrooms: Speaker Detection During Elementary Students’ Collaborative Dialogue.- Extracting and Clustering Main Ideas from Student Feedback using Language Models.- Multidimensional Team Communication Modeling for Adaptive Team Training: A Hybrid Deep Learning and Graphical Modeling Framework.- A Good Start is Half the Battle Won: Unsupervised Pre-Training for Low Resource Children's Speech Recognition for an Interactive Reading Companion.- Predicting Knowledge Gain during Web Search based on Multimedia Resource Consumption.- Deep Performance Factors Analysis for Knowledge Tracing.- Gaming and confrustion explain learning advantages for a math digital learning game.- Tackling the Credit Assignment Problem in Reinforcement Learning-Induced Pedagogical Policies with Neural Networks.- TARTA: Teacher Activity Recognizer from Transcriptions and Audio.- Assessing Algorithmic Fairness in Automatic Classifiers of Educational Forum Posts.- “Can you clarify what you said?”: Studying the impact of tutee agents’ follow-up questions on tutors’ learning.- Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT.- A Multidimensional Item Response Theory Model for Rubric-based Writing Assessment.- Towards Bloom's Taxonomy Classification Without Labels.- Automatic Task Requirements Writing Evaluation With Feedback via Machine Reading Comprehension.- Temporal Processes Associating with Procrastination Dynamics.- Investigating Students’ Experiences with Collaboration Analytics for Remote Group Meetings.- “Now, I Want to Teach it for Real!”: Introducing Machine Learning as a Scientific Discovery Tool for K-12 Teachers,. Better Model, Worse Predictions: The Dangers in Student Model Comparisons.


저자소개

Vania Dimitrova (엮은이)    정보 더보기
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Rose Luckin (엮은이)    정보 더보기
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Sergey Sosnovsky (엮은이)    정보 더보기
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Ido Roll (엮은이)    정보 더보기
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Danielle McNamara (엮은이)    정보 더보기
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