Department of Education, University of Oxford.
Social Science and Humanities section, Netherlands eScience Center, Amsterdam.
Cogn Sci. 2024 May;48(5):e13445. doi: 10.1111/cogs.13445.
Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) showed how, consistent with the predictions of error-driven learning models, the order in which stimuli are presented in training can affect category learning. Specifically, learners exposed to artificial language input where objects preceded their labels learned the discriminating features of categories better than learners exposed to input where labels preceded objects. We sought to replicate this finding in two online experiments employing the same tests used originally: A four pictures test (match a label to one of four pictures) and a four labels test (match a picture to one of four labels). In our study, only findings from the four pictures test were consistent with the original result. Additionally, the effect sizes observed were smaller, and participants over-generalized high-frequency category labels more than in the original study. We suggest that although Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) feature-label order predictions were derived from error-driven learning, they failed to consider that this mechanism also predicts that performance in any training paradigm must inevitably be influenced by participant prior experience. We consider our findings in light of these factors, and discuss implications for the generalizability and replication of training studies.
拉姆斯卡尔、雅莱特、戴尔、丹尼和索普(2010 年)表明,与错误驱动学习模型的预测一致,训练中刺激呈现的顺序会影响类别学习。具体来说,与标签先于物体出现的输入相比,接触到物体先于标签出现的人工语言输入的学习者,能够更好地学习到类别区分特征。我们在两个在线实验中尝试了复制这一发现,实验采用了与原始研究相同的测试:四张图片测试(将一个标签与四张图片中的一张匹配)和四张标签测试(将一张图片与四张标签中的一张匹配)。在我们的研究中,只有四张图片测试的结果与原始结果一致。此外,观察到的效应量较小,参与者对高频类别标签的过度泛化程度比原始研究更严重。我们认为,尽管拉姆斯卡尔、雅莱特、戴尔、丹尼和索普(2010 年)的特征-标签顺序预测是从错误驱动学习中得出的,但他们没有考虑到这一机制还预测,任何训练范例中的表现必然会受到参与者先前经验的影响。我们考虑了这些因素对训练研究的可推广性和可复制性的影响。