The use of control groups in artificial grammar learning
The use of control groups in artificial grammar learning
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DOI：
10.1080/02724980244000297
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发表时间：
2003-01-01
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影响因子：
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通讯作者：
Perruchet, P
中科院分区：
文献类型：
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作者：
Reber, R;Perruchet, P
实验者假设，如果实验组的参与者对测试项目进行分类的准确性明显高于未经训练的控制组，则他们已经学会了人工语法。然而，这种比较的有效性取决于一个可加性假设：学习是叠加在非特定变量的作用上的，例如，字母的重复，这在相同程度上调节了实验组和控制组的表现。在两个实验中，我们能够证明这种可加性假设不成立。在没有训练的对照组（实验I和2）的语法分类依赖于非特异性功能。在实验组中没有这样的偏见。随机字符串训练的对照组（实验2）比没有训练的对照组表现出更少的偏见。此外，我们重新分析了已发表的研究，并证明了早期使用未经训练的对照组的实验在对照组表现中产生了类似的偏差，支持了使用未经训练的对照组在方法上不合理的发现。
Experimenters assume that participants of an experimental group have learned an artificial grammar if they classify test items with significantly higher accuracy than does a control group without training. The validity of such a comparison, however, depends on an additivity assumption: Learning is superimposed on the action of non-specific variables-for example, repetitions of letters, which modulate the performance of the experimental group and the control group to the same extent. In two experiments we were able to show that this additivity assumption does not hold. Grammaticality classifications in control groups without training (Experiments I and 2) depended on non-specific features. There were no such biases in the experimental groups. Control groups with training on randomized strings (Experiment 2) showed fewer biases than did control groups without training. Furthermore, we reanalysed published research and demonstrated that earlier experiments using control groups without training had produced similar biases in control group performances, bolstering the finding that using control groups without training is methodologically unsound.