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Titlebook: Artificial Intelligence in Education; 17th International C Cristina Conati,Neil Heffernan,M. Felisa Verdejo Conference proceedings 2015 Spr

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51#
發(fā)表于 2025-3-30 09:56:21 | 只看該作者
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發(fā)表于 2025-3-30 12:41:18 | 只看該作者
Moody Agents: Affect and Discourse During Learning in a Serious Gamehe discourse of the artificial pedagogical agents was manipulated to evoke student affective states. Student emotion was measured via affect grids and discourse features were measured with computational linguistics techniques. Results indicated that learner’s arousal levels impacted learning and that language use is correlated with learning.
53#
發(fā)表于 2025-3-30 20:32:35 | 只看該作者
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發(fā)表于 2025-3-30 21:19:40 | 只看該作者
55#
發(fā)表于 2025-3-31 01:08:27 | 只看該作者
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發(fā)表于 2025-3-31 06:29:33 | 只看該作者
57#
發(fā)表于 2025-3-31 12:09:17 | 只看該作者
Is a Dialogue-Based Tutoring System that Emulates Helpful Co-constructed Relations During Human Tuto students learned from both versions of the system, the experimental group outperformed the control group. A particularly interesting finding is that the experimental version was especially beneficial for female students.
58#
發(fā)表于 2025-3-31 13:58:29 | 只看該作者
Games are Better than Books: In-Situ Comparison of an Interactive Job Interview Game with Conventione days, during which we compared the technology-enhanced training with a traditional learning method usually practised in schools, i.e. reading a job interview guide. The results are promising as professional career counsellors rated the pupils who trained with the system significantly better than those who learned with the traditional method.
59#
發(fā)表于 2025-3-31 19:19:02 | 只看該作者
0302-9743 e and learning sciences, education, game design, psychology, sociology, linguistics, as well as many domain-specific areas..978-3-319-19772-2978-3-319-19773-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
60#
發(fā)表于 2025-3-31 23:16:30 | 只看該作者
Play as a Context for Early Learning,udy, and a method of improving Bing results is presented. Results provide a useful understanding of the capabilities of contemporary ASR engines in noisy classroom environments. Results also highlight a list of issues to be aware of when selecting an ASR engine for difficult speech recognition tasks.
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