Why Untrained Control Groups Provide Invalid Baselines: A Reply to Dienes and Altmann
Dienes and Altmann argue that an untrained control group provides a reliable baseline to measure artificial grammar learning. In this reply, we first provide a fictitious example to demonstrate that this assessment is faulty. We then analyse why this assessment is wrong, and we reiterate the solution proposed in Reber and Perruchet (this issue) for a proper control. Finally, we point out the importance of these methodological principles in the context of implicit learning studies. In their comment, Dienes and Altmann (this issue) raise two main concerns. First, they argue that any difference in classification between an experimental group and an untrained control group reflects the fact tha…
The use of control groups in artificial grammar learning.
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 1 and 2) depended on non-specific features. T…