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Titlebook: Intelligent Tutoring Systems; 12th International C Stefan Trausan-Matu,Kristy Elizabeth Boyer,Kitty P Conference proceedings 2014 Springer

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樓主: CURD
21#
發(fā)表于 2025-3-25 03:49:10 | 只看該作者
22#
發(fā)表于 2025-3-25 09:24:15 | 只看該作者
Investigate Performance of Expected Maximization on the Knowledge Tracing Model dataset. By recording the parameter values and convergence states at each iteration, we found that stopping EM earlier leads to problems, as the parameter estimates continue to noticeably change after the convergence of the log-likelihood scores.
23#
發(fā)表于 2025-3-25 12:22:05 | 只看該作者
Stefan Trausan-Matu,Kristy Elizabeth Boyer,Kitty P
24#
發(fā)表于 2025-3-25 19:00:42 | 只看該作者
25#
發(fā)表于 2025-3-25 19:58:43 | 只看該作者
Kurt VanLehn,Winslow Burleson,Sylvie Girard,Maria Elena Chavez-Echeagaray,Javier Gonzalez-Sanchez,Yon the following topical sections: anthropometry and ergonomics; motion modeling and tracking; human modeling in transport and aviation; human modeling in medicine and surgery; quality in health978-3-319-21069-8978-3-319-21070-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
26#
發(fā)表于 2025-3-26 03:08:05 | 只看該作者
27#
發(fā)表于 2025-3-26 05:22:21 | 只看該作者
Virtual Environment for Monitoring Emotional Behaviour in Drivingng EEG systems. By simulating specific emotional situations we can provoke these emotions and detect their types and intensity according to the driver. Then, in the environment, we generate corrective actions that are able to reduce the emotions. After a training period, the driver is able to correct the emotions by himself.
28#
發(fā)表于 2025-3-26 09:22:00 | 只看該作者
29#
發(fā)表于 2025-3-26 13:26:46 | 只看該作者
0302-9743 ulu, HI, USA, in June 2014. The 31 revised full papers, 45 short papers and 27 posters presented were carefully viewed and selected from 177 submissions. The specific theme of the ITS 2014 conference is "Creating fertile soil for learning interactions". Besides that, the highly interdisciplinary ITS
30#
發(fā)表于 2025-3-26 19:24:19 | 只看該作者
Sensor-Free Affect Detection for a Simulation-Based Science Inquiry Learning Environmentarrative-based virtual environments. In this paper, we extend sensor-free affect detection to a science microworld environment, affording the possibility of more deeply studying and responding to student affect in this type of learning environment.
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