Schiff Rachel, Katan Pesia, Sasson Ayelet, Kahta Shani
Learning Disabilities Studies, School of Education, Bar-Ilan University, 52900, Ramat-Gan, Israel.
Haddad Center for Dyslexia and Learning Disabilities, Bar Ilan University, 52900, Ramat-Gan, Israel.
Ann Dyslexia. 2017 Jul;67(2):180-199. doi: 10.1007/s11881-017-0141-y. Epub 2017 Apr 13.
There's a long held view that chunks play a crucial role in artificial grammar learning performance. We compared chunk strength influences on performance, in high and low topological entropy (a measure of complexity) grammar systems, with dyslexic children, age-matched and reading-level-matched control participants. Findings show that age-matched control participants' performance reflected equivalent influence of chunk strength in the two topological entropy conditions, as typically found in artificial grammar learning experiments. By contrast, dyslexic children and reading-level-matched controls' performance reflected knowledge of chunk strength only under the low topological entropy condition. In the low topological entropy grammar system, they appeared completely unable to utilize chunk strength to make appropriate test item selections. In line with previous research, this study suggests that for typically developing children, it is the chunks that are attended during artificial grammar learning and create a foundation on which implicit associative learning mechanisms operate, and these chunks are unitized to different strengths. However, for children with dyslexia, it is complexity that may influence the subsequent memorability of chunks, independently of their strength.
长期以来，人们一直认为组块在人工语法学习表现中起着关键作用。我们将组块强度对高拓扑熵（一种复杂性度量）和低拓扑熵语法系统中表现的影响，与诵读困难儿童、年龄匹配和阅读水平匹配的对照参与者进行了比较。研究结果表明，年龄匹配的对照参与者的表现反映了组块强度在两种拓扑熵条件下的同等影响，这是人工语法学习实验中通常发现的情况。相比之下，诵读困难儿童和阅读水平匹配的对照参与者的表现仅在低拓扑熵条件下反映了对组块强度的了解。在低拓扑熵语法系统中，他们似乎完全无法利用组块强度来做出适当的测试项目选择。与先前的研究一致，本研究表明，对于发育正常的儿童来说，在人工语法学习过程中被注意到的组块为内隐联想学习机制的运作奠定了基础，并且这些组块被组合成不同的强度。然而，对于患有诵读困难的儿童来说，可能是复杂性独立于组块强度影响组块随后的可记忆性。
