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Subliminal Cues While Teaching: HCI Technique for Enhanced Learning

机译:教学中的潜意识线索:增强学习的HCI技术

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摘要

This paper presents results from an empirical study conducted with a subliminal teaching technique aimed at enhancing learner's performance in Intelligent Systems through the use of physiological sensors. This technique uses carefully designed subliminal cues (positive) and miscues (negative) and projects them under the learner's perceptual visual threshold. A positive cue, called answer cue, is a hint aiming to enhance the learner's inductive reasoning abilities and projected in a way to help them figure out the solution faster but more importantly better. A negative cue, called miscue, is also used and aims at obviously at the opposite (distract the learner or lead them to the wrong conclusion). The latest obtained results showed that only subliminal cues, not miscues, could significantly increase learner performance and intuition in a logic-based problem-solving task. Nonintrusive physiological sensors (EEG for recording brainwaves, blood volume pressure to compute heart rate and skin response to record skin conductivity) were used to record affective and cerebral responses throughout the experiment. The descriptive analysis, combined with the physiological data, provides compelling evidence for the positive impact of answer cues on reasoning and intuitive decision making in a logic-based problem-solving paradigm.
机译:本文介绍了一项采用潜意识教学技术进行的实证研究的结果,旨在通过使用生理传感器来提高学习者在智能系统中的表现。该技术使用精心设计的潜意识线索(正)和误线索(负),并将其投射到学习者的感知视觉阈值以下。积极的提示(称为答案提示)是一种旨在增强学习者的归纳推理能力的提示,并且可以帮助他们更快但更重要的是找到解决方案。消极提示也被称为错误提示,它的作用显然是相反的(分散学习者的注意力或导致他们得出错误的结论)。最新获得的结果表明,在基于逻辑的问题解决任务中,只有潜意识线索而不是错觉线索才能显着提高学习者的表现和直觉。在整个实验过程中,使用非侵入式生理传感器(用于记录脑电波的EEG,用于计算心率的血压和用于记录皮肤电导率的皮肤反应)来记录情感和大脑反应。描述性分析与生理数据相结合,为基于逻辑的问题解决范例中的答案提示对推理和直观决策的积极影响提供了令人信服的证据。

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  • 来源
    《Advances in human-computer interaction》 |2011年第1期|p.3.1-3.15|共15页
  • 作者单位

    Dipartement d'Informatique et de Recherche Operationnelle, Universiti de Montreal, Office 2194, Montreal, Quebec, Canada H3T 1J4;

    Dipartement d'Informatique et de Recherche Operationnelle, Universiti de Montreal, Office 2194, Montreal, Quebec, Canada H3T 1J4;

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