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Affect Recognition and Support in Intelligent Tutoring Systems

机译:智能辅导系统中的情感识别与支持

摘要

Empirical research provides evidence of strong interaction between cognitive and affective processes in the human mind. Education research proposes a model of constructive learning that relates cognitive and affective processes in an evolving cycle of affective states. Intelligent Tutoring Systems (ITSs) are capable of providing comprehensive cognitive support. Affective support in ITSs, however, is lagging behind; the in-depth exploration of cognitive and affective processes in ITSs is yet to be seen. Our research focuses on the integration of affective support in an ITS enhanced with an affective pedagogical agent. In our work we adopt the dimensional (versus categorical) view of emotions for modelling affective states of the agent and the ITSs users. In two stages we develop and evaluate an affective pedagogical agent. The affective response of the first agent version is based on the appraisal of the interaction state; this agent's affective response is displayed as affective facial expressions. The pilot study at the end of the first stage of the project confirms the viability of our approach which combines the dimensional view of emotions with the appraisal of interaction state. In the second stage of the project we develop a facial feature tracking application for real-time emotion recognition in a video-stream. Affective awareness of the second version of the agent is based on the output from the facial feature tracking application and the appraisal of the interaction state. This agent's response takes the form of affectoriented messages designed to interrupt the state of negative flow. The evaluation of the affect-aware agent against an unemotional affect-unaware agent provides positive results, thus confirming the superiority of the affect-aware agent. Although the uptake of the agent was not unanimous, the agent established and maintained good rapport with the users in a role of a caring tutor. The results of the pilot study and the final evaluation validate our choices in the design of affective interaction. In both experiments, the participants appreciated the addition of audible feedback messages, describing it as an enhancement which helped them save time and maintain their focus. Finally, we offer directions for future research on affective support which can be conducted within the framework developed in the course of this project.
机译:实证研究提供了人类大脑中认知和情感过程之间强烈相互作用的证据。教育研究提出了一种建构性学习的模型,该模型将情感状态不断演变的认知和情感过程联系起来。智能辅导系统(ITS)能够提供全面的认知支持。但是,ITS中的情感支持仍然落后。 ITS中认知和情感过程的深入探索尚待观察。我们的研究重点是将情感支持整合到以情感教学代理增强的ITS中。在我们的工作中,我们采用情感的维度(相对于分类)视图来建模代理和ITSs用户的情感状态。在两个阶段中,我们开发和评估一种情感教学代理。第一代理人版本的情感反应基于对交互状态的评估;该代理的情感反应显示为情感面部表情。在项目第一阶段结束时的试点研究证实了我们的方法的可行性,该方法将情感的维度视图与对交互状态的评估相结合。在项目的第二阶段,我们开发了面部特征跟踪应用程序,用于视频流中的实时情感识别。对第二版代理的情感意识是基于面部特征跟踪应用程序的输出以及对交互状态的评估。该代理的响应采取面向情感的消息的形式,旨在中断负向流量的状态。对情感感知代理相对于非情绪情感感知代理的评估提供了积极的结果,从而证实了情感感知代理的优越性。尽管对代理人的吸收不是一致的,但是代理人在照顾者的指导下与用户建立并保持了良好的关系。初步研究和最终评估的结果验证了我们在情感互动设计中的选择。在这两个实验中,参与者都赞赏可听反馈消息的添加,并将其描述为一种增强功能,可以帮助他们节省时间并保持专注。最后,我们提供了有关情感支持的未来研究的方向,可以在该项目过程中开发的框架内进行。

著录项

  • 作者

    Zakharov Konstantin;

  • 作者单位
  • 年度 2007
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  • 原文格式 PDF
  • 正文语种 en
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