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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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樓主: 搖尾乞憐
41#
發(fā)表于 2025-3-28 18:08:02 | 只看該作者
42#
發(fā)表于 2025-3-28 21:20:11 | 只看該作者
Investigation of the Influence of Hint Type on Problem Solving Behavior in a Logic Proof Tutortep hints and more abstract high-level hints) on students’ behavior in a college-level logic proof tutor, Deep Thought. The results suggest that hint types can affect student behavior, including hint usage, rule applications, and time in-tutor.
43#
發(fā)表于 2025-3-29 02:32:01 | 只看該作者
Exploring Gritty Students’ Behavior in an Intelligent Tutoring System, perseverance and recovery from failure. We use rare Association Rule Mining to explore how students’ grit may be associated with students’ behavior within MathSpring, an intelligent tutoring system, as a first step.
44#
發(fā)表于 2025-3-29 05:23:16 | 只看該作者
Conference proceedings 2018, 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 cr
45#
發(fā)表于 2025-3-29 09:37:05 | 只看該作者
46#
發(fā)表于 2025-3-29 13:11:23 | 只看該作者
47#
發(fā)表于 2025-3-29 16:07:23 | 只看該作者
Providing Proactive Scaffolding During Tutorial Dialogue Using Guidance from Student Model Predictios are within the student’s ability to answer when appropriately supported; that is, the tutor aims to stay within its estimate of the student’s zone of proximal development for the targeted concepts. The scaffolding provided by the tutor is further adapted by adjusting the way the questions are expressed.
48#
發(fā)表于 2025-3-29 21:49:22 | 只看該作者
Where Is the Nurse? Towards Automatically Visualising Meaningful Team Movement in Healthcare Educatition. Combining role-based nurses’ movement data with high fidelity manikin logs, we have implemented a zone-based classification model, and are able to automatically visualise movements within an emergency response team, providing the data needed to design near real-time feedback for both educators and students.
49#
發(fā)表于 2025-3-30 03:40:19 | 只看該作者
https://doi.org/10.1007/978-3-319-93846-2Education; Computer-assisted instruction; Interactive learning environments; Collaborative learning; E-l
50#
發(fā)表于 2025-3-30 06:08:18 | 只看該作者
978-3-319-93845-5Springer International Publishing AG, part of Springer Nature 2018
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