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Titlebook: Artificial Intelligence in Education; 19th International C Carolyn Penstein Rosé,Roberto Martínez-Maldonado,B Conference proceedings 2018 S

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發(fā)表于 2025-3-23 13:12:22 | 只看該作者
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發(fā)表于 2025-3-23 18:58:20 | 只看該作者
Human-Agent Assessment: Interaction and Sub-skills Scoring for Collaborative Problem Solvings entering the workforce will be expected to have a level of proficiency with both cognitive and social-emotional skills. This paper presents an approach to measuring features and sub-skills associated with CPS ability and provides a methodology for CPS based performance assessment using an educatio
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發(fā)表于 2025-3-24 00:45:05 | 只看該作者
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發(fā)表于 2025-3-24 05:19:18 | 只看該作者
Modeling Math Success Using Cohesion Network Analysisal differences and click-stream variables that may also predict math success. Linear models indicated that math success was related to days spent on the forum and by students who more regularly posted in the online class forum and whose posts generally followed the semanticity of other students.
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發(fā)表于 2025-3-24 06:43:40 | 只看該作者
Amplifying Teachers Intelligence in the Design of Gamified Intelligent Tutoring Systemslitate problem-solving, and to drive desired learning behaviors. In fact, although the desire of teachers to be active users of gamified ITS, these systems are not personalized according to teachers’ preferences. Several research problems might arise when trying to empower teachers in the design of
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發(fā)表于 2025-3-24 14:20:07 | 只看該作者
Where Is the Nurse? Towards Automatically Visualising Meaningful Team Movement in Healthcare Educatir complexity. Focusing on emergency procedures on patient manikins, our prior work has demonstrated the feasibility of using multimodal data capture and analysis to generate visualisations of student movement, talk and treatment actions. The limitation to date has been the need for manual steps in t
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發(fā)表于 2025-3-24 15:06:02 | 只看該作者
Exploring Gritty Students’ Behavior in an Intelligent Tutoring Systemstudent models and feature sets that can help tutors predict student behavior and determine whether tutors might foster improvements in students’ grit, perseverance and recovery from failure. We use rare Association Rule Mining to explore how students’ grit may be associated with students’ behavior
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發(fā)表于 2025-3-24 22:29:26 | 只看該作者
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發(fā)表于 2025-3-25 01:04:02 | 只看該作者
Adaptive Learning Goes to Chinaective learning tools. This paper introduces an adaptive learning system, “Yixue,” that was developed and deployed in China. It diagnostically assesses students’ mastery of fine-grained skills and presents them with instructional content that fits their?characteristics and abilities. The Yixue syste
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