More confusion and frustration, better learning: The impact of erroneous examples
More confusion and frustration, better learning: The impact of erroneous examples
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DOI：
10.1016/j.compedu.2019.05.012
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发表时间：
2019-10-01
影响因子：
12
通讯作者：
McLaren, Bruce M.
中科院分区：
文献类型：
--
作者：
Richey, J. Elizabeth;Andres-Bray, Juan Miguel L.;McLaren, Bruce M.
先前的研究表明，与解决问题的练习或学习正确的解决方案相比，学生有时可以通过解释和纠正错误解决的示例问题来更有效地学习。然而，目前还不清楚学生的情感在从错误例子中学习的过程中可能起到什么作用。具体地说，可能是学生在学习错误的例子时经历了更多的困惑和挫折，但他们的困惑和挫折导致了更多的学习。我们分析了之前发表的一项研究中的学生日志数据，该研究比较了十进制数学的错误范例教学和基于计算机的智能教学系统中的问题解决教学。我们创建并应用了针对困惑和挫折感(“Confrustion”)组合的情绪检测器，并比较了Confrustion在不同条件下的作用。正如预测的那样，处于错误例子条件下的学生在阅读教学材料时经历了更大的混乱。然而，与预测相反的是，混淆与后测和延迟后测在不同条件下的表现呈负相关，尽管对于错误的例子条件，这一相关性较小。考虑到处于错误范例条件下的学生在延迟后测中的表现要好于处于解决问题条件下的学生，他们似乎学到了更多东西，尽管他们也经历了更多的争执，而不是因为它。结果表明，与传统的解决问题相比，从错误的例子中学习可能是一个本质上更令人困惑和沮丧的过程。更广泛地说，这项研究表明，在循序渐进的问题解决水平上记录学生的行为，并分析这些记录来推断情感，可能是调查学习的一种强有力的方式。
Prior research suggests students can sometimes learn more effectively by explaining and correcting example problems that have been solved incorrectly, compared to problem-solving practice or studying correct solutions. It remains unclear, however, what role students' affect might play in the process of learning from erroneous examples. Specifically, it may be that students experience greater confusion and frustration while studying erroneous examples, but that their confusion and frustration lead to greater learning. We analyzed student log data from previously published research comparing erroneous example instruction of decimal number mathematics to problem-solving instruction in a computer-based intelligent tutoring system. We created and applied affect detectors for a combination of confusion and frustration ("confrustion") and compared the role of confrustion across conditions. As predicted, students in the erroneous example condition experienced greater confrustion while working through the instructional materials. However, contrary to predictions, confrustion was negatively correlated with posttest and delayed posttest performance across conditions, though less so for the erroneous example condition. Given that students in the erroneous example condition performed better on the delayed posttest than students in the problem-solving condition, it appears they learned more despite also experiencing greater confrustion rather than because of it. Results suggest that learning from erroneous examples may be an inherently more confusing and frustrating process than traditional problem solving. More generally, this research demonstrates that logging student actions at a step-by-step problem-solving level and analyzing those logs to infer affect can be a powerful way to investigate learning.