Expert Tutors Feedback Is Immediate, Direct, and Discriminating

Expert Tutors Feedback Is Immediate, Direct, and Discriminating
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专家导师的反馈是即时、直接且有区别的

DOI:
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发表时间:
2010
期刊:
The Florida AI Research Society
影响因子:
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通讯作者:
N. Person
N. Person
中科院分区:
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文献类型:
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作者:
S. D’Mello;B. Lehman;N. Person

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反馈在人类和计算机辅导中都至关重要,因为它具有指导、促进和激励功能。对于渴望为此类导师建模的 ITS 来说,了解专家导师的反馈策略至关重要。尽管之前的研究表明专家导师会提供间接和延迟的反馈,但方法论上的担忧限制了这些研究结果的普遍性。为了缓解其中一些方法论问题,我们对 50 场会议中 10 名专家导师的反馈策略进行了细粒度分析。我们分析了在学生回答正确、部分正确、错误百出、模糊或没有答案后,导师立即提供积极、消极和中立反馈的可能性。我们的结果支持这样的结论:专家导师的反馈是直接的、即时的、有区别的,并且很大程度上独立于领域。我们讨论了我们的结果对于渴望成为专家导师模型的 ITS 开发的影响。
Feedback is critical in both human and computer tutoring because it has directive, facilitative, and motivational functions. An understanding of the feedback strategies of expert human tutors is essential for ITSs that aspire to model such tutors. Although previous research suggests that expert tutors provide indirect and delayed feedback, methodological concerns limit the generalizability of these findings. In order to alleviate some of these methodological concerns, we conducted a fine-grained analysis of the feedback strategies of 10 expert tutors across 50 sessions. We analyzed the likelihood that tutors provide positive, negative, and neutral feedback immediately following students’ correct, partially-correct, error-ridden, vague, or no answers. Our results support the conclusion that expert tutors feedback is direct, immediate, discriminating, and largely domain independent. We discuss the implication of our results for the development of an ITS that aspires to model expert tutors.