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Titlebook: Intelligent Tutoring Systems; 13th International C Alessandro Micarelli,John Stamper,Kitty Panourgia Conference proceedings 2016 Springer I

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51#
發(fā)表于 2025-3-30 10:44:18 | 只看該作者
Stealth Assessment in ITS - A Study for?Developmental Dyscalculia enough information to identify children at risk of DD with high accuracy and validity and reliability comparable to traditional assessments. Our model is able to adapt the duration of the screening test to the individual child and can classify a child at risk of DD with an accuracy of 91?% after 11?min on average.
52#
發(fā)表于 2025-3-30 14:54:42 | 只看該作者
Tell Me How to Teach, I’ll Learn How to Solve Problemsted tutor learning (regardless of the presence of the cognitive scaffolding), whereas cognitive scaffolding had virtually no effect. The same pattern was confirmed by two additional datasets collected from two previous school studies we conducted.
53#
發(fā)表于 2025-3-30 19:34:38 | 只看該作者
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發(fā)表于 2025-3-31 00:47:37 | 只看該作者
Conference proceedings 2016 technologies, understanding human learning on the web; adaptive support for learning, models of learners, diagnosis and feedback; modeling of motivation, metacognition, and affect aspects of learning; recommender systems for learning; virtual pedagogical agents and learning companions; ontological
55#
發(fā)表于 2025-3-31 04:15:47 | 只看該作者
56#
發(fā)表于 2025-3-31 06:25:15 | 只看該作者
57#
發(fā)表于 2025-3-31 09:46:40 | 只看該作者
Mastery-Oriented Shared Student/System Control Over Problem Selection in a Linear Equation Tutorg outcomes, as compared to fully system-controlled problem selection, as well as better declarative knowledge of a key problem-selection strategy. Nevertheless, there was no effect on future problem selection and future learning. Our experiment contributes to prior literature by demonstrating that w
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發(fā)表于 2025-3-31 13:36:29 | 只看該作者
59#
發(fā)表于 2025-3-31 18:30:08 | 只看該作者
Integrating Real-Time Drawing and Writing Diagnostic Models: An Evidence-Centered Design Framework fs of each exercise, as well as the curricular unit as a whole, was constructed. Then, evidence models were created to map between student written and drawn artifacts and the shared competency model. Finally, the scores obtained using the evidence models were used to train a deep-learning based model
60#
發(fā)表于 2025-4-1 00:03:55 | 只看該作者
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