智能导师模仿专家人类导师，显著提升生物学习效果。
Efficacy of a Computer Tutor that Models Expert Human Tutors
- 用智能系统模拟专家人类导师的教学方式。
- 即时测试中效应量达d=.71，延迟测试仍保持d=.36。
- 适合教育科技研究者与智能辅导系统开发者。
辅导对促进学习非常有效，但专家能力在其中的作用尚不明确且存在争议。我们开展了一项为期9周的学习效果研究，评估了一个基于专家人类导师设计的智能辅导系统（ITS）在生物学教学中的表现，并设置了两种对照条件：领域专家但非辅导专家的人类导师，以及无导师对照组。所有条件均作为课堂教学的补充，学生在辅导前后立即进行测试，并在1-2周后进行延迟测试。使用逻辑混合效应模型分析显示，ITS在即时后测中具有显著正向效果（d = .71），人类导师亦然（d = .66），二者均位于元分析效应量的第99百分位；在延迟后测中，ITS（d = .36）和人类导师（d = .39）同样表现出显著正向效果。研究讨论了专家能力在辅导中的作用及未来研究的设计启示。
原文摘要 · Abstract (English)
Tutoring is highly effective for promoting learning. However, the contribution of expertise to tutoring effectiveness is unclear and continues to be debated. We conducted a 9-week learning efficacy study of an intelligent tutoring system (ITS) for biology modeled on expert human tutors with two control conditions: human tutors who were experts in the domain but not in tutoring and a no-tutoring condition. All conditions were supplemental to classroom instruction, and students took learning tests immediately before and after tutoring sessions as well as delayed tests 1-2 weeks later. Analysis using logistic mixed-effects modeling indicates significant positive effects on the immediate post-test for the ITS (d =.71) and human tutors (d =.66) which are in the 99th percentile of meta-analytic effects, as well as significant positive effects on the delayed post-test for the ITS (d =.36) and human tutors (d =.39). We discuss implications for the role of expertise in tutoring and the design of future studies.
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