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Titlebook: Intelligent Tutoring Systems; 11th International C Stefano A. Cerri,William J. Clancey,Kitty Panourgi Conference proceedings 2012 Springer-

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發(fā)表于 2025-3-25 04:19:32 | 只看該作者
22#
發(fā)表于 2025-3-25 09:33:10 | 只看該作者
Implicit Strategies for Intelligent Tutoring Systemsstructional strategies addressing both learners’ cognitive and affective dimensions and rely, for most of them, on explicit strategies and direct interventions. In this paper we propose a new approach to augment these tutors with new implicit strategies relying on indirect interventions. We show the
23#
發(fā)表于 2025-3-25 15:04:00 | 只看該作者
24#
發(fā)表于 2025-3-25 19:22:43 | 只看該作者
25#
發(fā)表于 2025-3-25 23:02:38 | 只看該作者
Exploration of Affect Detection Using Semantic Cues in Virtual Improvisationrucial for the appropriate interpretation of emotions implied in an individual input embedded in such online social interactions. In this paper, we discuss how context is used to interpret affect implied in conversational inputs with weak affect indicators embedded in multithreaded social interactio
26#
發(fā)表于 2025-3-26 01:51:18 | 只看該作者
Measuring Learners’ Co-Occurring Emotional Responses during Their Interaction with a Pedagogical Ageeriences by examining co-occurring emotions (COEs) (e.g., Conati) through a novel methodological approach. In this paper we examined the occurrence of students’ embodiment of basic single discrete emotions (SDEs) and COEs (in addition to neutral) using an automatic facial expression recognition prog
27#
發(fā)表于 2025-3-26 08:07:40 | 只看該作者
Visualization of Student Activity Patterns within Intelligent Tutoring Systemstudents. The Many Eyes Word Tree graphics is used to understand and analyze sequential patterns of student states, categorizing raw quantitative indicators into a limited number of discrete sates. Used in combination with sensor predictors, we demonstrate that a combination of features, automatic pa
28#
發(fā)表于 2025-3-26 12:06:58 | 只看該作者
29#
發(fā)表于 2025-3-26 13:06:15 | 只看該作者
Mental Workload, Engagement and Emotions: An Exploratory Study for Intelligent Tutoring Systemsctive of learner emotional modeling according to two fundamental dimensions, namely mental workload and engagement. We hypothesize that analyzing results from learners’ workload and engagement evolution can help Intelligent Tutoring Systems diagnose learners’ emotional states and understand the lear
30#
發(fā)表于 2025-3-26 18:56:20 | 只看該作者
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