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Titlebook: Artificial Intelligence in Education; 22nd International C Ido Roll,Danielle McNamara,Vania Dimitrova Conference proceedings 2021 Springer

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31#
發(fā)表于 2025-3-27 00:44:12 | 只看該作者
Ordering Effects in a Role-Based Scaffolding Intervention for Asynchronous Online Discussionsous discussions. Previous work has demonstrated how this type of scaffolding can result in student contributions of greater depth and quality. However, since students necessarily experience the roles in varying orders, it is important to consider whether the ordering impacts the outcome. This paper
32#
發(fā)表于 2025-3-27 03:38:14 | 只看該作者
Option Tracing: Beyond Correctness Analysis in Knowledge Tracingtions. One key limitation of most existing knowledge tracing methods is that they can only estimate an . knowledge level of a student per knowledge component/skill since they analyze only the (usually binary-valued) correctness of student responses. Therefore, it is hard to use them to diagnose spec
33#
發(fā)表于 2025-3-27 07:22:56 | 只看該作者
34#
發(fā)表于 2025-3-27 12:18:41 | 只看該作者
Discovering Co-creative Dialogue States During Collaborative Learning, and very little is known about the dialogue mechanisms that support learning during collaborative co-creativity. To address this need, we analyzed the structure of collaborative dialogue between pairs of high school students who co-created music by writing code. We used hidden Markov models to ana
35#
發(fā)表于 2025-3-27 15:21:50 | 只看該作者
36#
發(fā)表于 2025-3-27 19:01:29 | 只看該作者
37#
發(fā)表于 2025-3-27 23:19:25 | 只看該作者
Investigating Students’ Reasoning in a Code-Tracing Tutorsight into students’ cognitive processes as they used a computer tutor to study code-tracing examples and work on code-tracing problems, using either a high-scaffolding or a reduced-scaffolding tutor interface. For the cognitive processes, we included both self-explanation and reading behaviors, rel
38#
發(fā)表于 2025-3-28 03:16:14 | 只看該作者
Evaluating Critical Reinforcement Learning Framework in the Fielded great success in inducing effective pedagogical policies for various interactive e-learning environments. However, it is often prohibitive to identify the . pedagogical decisions that actually contribute to desirable learning outcomes. In this work, by utilizing the RL framework we defined . to b
39#
發(fā)表于 2025-3-28 09:28:52 | 只看該作者
Artificial Intelligence in Education978-3-030-78292-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
40#
發(fā)表于 2025-3-28 14:23:30 | 只看該作者
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162434.jpg
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