首页> 外文期刊>Journal of educational multimedia and hypermedia >Constructing Knowledge from Dialog in an Intelligent Tutoring System: Interactive Learning, Vicarious Learning, and Pedagogical Agents
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Constructing Knowledge from Dialog in an Intelligent Tutoring System: Interactive Learning, Vicarious Learning, and Pedagogical Agents

机译:在智能辅导系统中通过对话构建知识:交互式学习,替代学习和教学代理

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College students either interacted directly with an intelligent tutoring system, called AutoTutor, by contributing to mixed initiative dialog, or they simply observed, as vicarious learners, previously recorded interactive sessions. The mean pretest to posttest effect size (Cohen's d) across two studies was 1.86 in the interactive conditions and 1.12 in standard vicarious conditions. In Experiment 1, redundant onscreen printed text produced an effect size of 0.43, but the difference was not significant. In addition, the image of a talking head presenting AutoTutor's contributions to the dialog while displaying facial expressions, gestures, and gaze did not produce learning gains beyond those produced by the voice alone. In Experiment 2, the effect size was 0.71 when interactive tutoring was contrasted with the standard vicarious condition, but only 0.38 when compared to a collaborative vicarious condition.
机译:大学生或者通过参与混合主动对话来直接与称为AutoTutor的智能辅导系统进行交互,或者作为替代学习者,他们只是观察到以前录制的交互式会话。在两项研究中,交互作用条件下的平均测试前测验到事后效果大小(Cohen d)为1.86,标准替代条件下的平均测验为1.12。在实验1中,多余的屏幕打印文本产生的效果大小为0.43,但差异不明显。此外,会说话的头像在显示面部表情,手势和注视的同时向对话框显示AutoTutor对对话框的贡献,并不会产生仅由语音产生的学习收益。在实验2中,当交互式辅导与标准替代条件相比时,效果大小为0.71,而与协作替代条件相比则仅为0.38。

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