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Enhancing Collaboration in Computer-Administered Survey Interviews

机译：加强计算机管理调查访谈中的合作

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We investigated the extent to which a collaborative view of human conversation transfers directly to interaction with non-human agents, and we examined how a collaborative view can improve user interface design. In two experiments we contrasted user-initiated and system initiated clarification in computer-administered surveys. In the first (text-based) study, users who could clarify the interpretations of questions by clicking on highlighted definitions comprehended questions more accurately (in ways that more closely fit the survey designers' intentions) than users who couldn't, and thus they provided more accurate responses. They were far more likely to ask for help when they had been instructed that clarification would be essential than when they were merely told that help was available. In the second (speech based) Wizard-of-Oz study, users responded more accurately and asked more questions when they received unsolicited clarification about question meaning from the system in response to their linguistic cues of uncertainty (urns and uhs, restarts, talk other than an answer, etc.) than when they did not. The results suggest that clarification in collaborative systems will be successful only if users recognize that their own conceptions may differ from the system's, and if they are willing to take extra turns to improve their understanding.
机译：我们调查了人类交谈直接转移到与非人类代理人互动的程度的程度，我们研究了协作视图如何改善用户界面设计。在两个实验中，我们对比计算机管理调查中的用户启动和系统开始了澄清。在第一个（基于文本的）的研究中，通过点击突出显示的定义可以更准确地理解问题的解释（以更紧密地拟合调查设计师的意图），用户比不能，因此提供更准确的响应。当他们被指示澄清时，他们更有可能要求帮助，而不是仅仅被告知提供帮助。在第二个（基于语音）的巫师的研究中，当他们收到未经请求的澄清系统的问题意义时，用户响应了更多的问题，并询问了更多问题，以响应他们的不确定性的语言线索（URNS和UHS，重新启动，谈论，谈论其他而不是答案等）而不是他们没有。结果表明，只有当用户认识到他们自己的概念可能与系统不同，才能取得成功，才能取得成功，如果他们愿意努力提高他们的理解。

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