Electrophysiological evidence for a neural substrate of morphological rule application in correct wordforms

Purpose The purpose of this study was to delineate differences between children with specific language impairment (SLI), typical age–matched (TAM) children, and typical younger (TY) children in learning and mastering an undisclosed artificial morphological rule (AMR) through exposure and usage. Method Twenty-six participants (eight 10-year-old children with SLI, 8 TAM children, and ten 8-year-old TY children) were trained to master an AMR across multiple training sessions. The AMR required a phonological transformation of verbs depending on a semantic distinction: whether the preceding noun was animate or inanimate. All participants practiced the application of the AMR to repeated and new (generalization) items, via judgment and production tasks. Results The children with SLI derived significantly less benefit from practice than their peers in learning most aspects of the AMR, even exhibiting smaller gains compared to the TY group in some aspects. Children with SLI benefited less than TAM and even TY children from training to judge and produce repeated items of the AMR. Nevertheless, despite a significant disadvantage in baseline performance, the rate at which they mastered the task-specific phonological regularities was as robust as that of their peers. On the other hand, like 8-year-olds, only half of the SLI group succeeded in uncovering the nature of the AMR and, consequently, in generalizing it to new items. Conclusions Children with SLI were able to learn language aspects that rely on implicit, procedural learning, but experienced difficulties in learning aspects that relied on the explicit uncovering of the semantic principle of the AMR. The results suggest that some of the difficulties experienced by children with SLI when learning a complex language regularity cannot be accounted for by a broad, language-related, procedural memory disability. Rather, a deficit—perhaps a developmental delay in the ability to recruit and solve language problems and establish explicit knowledge regarding a language task—can better explain their difficulties in language learning.

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The Prediction of Problem-Solving Assessed Via Microworlds

European Journal of Psychological Assessment ◽

10.1027/1015-5759/a000263 ◽

2016 ◽

Vol 32 (4) ◽

pp. 298-306 ◽

Cited By ~ 7

Author(s):

Samuel Greiff ◽

Katarina Krkovic ◽

Jarkko Hautamäki

Keyword(s):

Working Memory ◽

Problem Solving ◽

Complex Problem ◽

Two Dimensions ◽

Assessment Instruments ◽

Complex Problem Solving ◽

Visual Spatial ◽

Rule Knowledge ◽

Rule Application ◽

Fluid Reasoning

Abstract. In this study, we explored the network of relations between fluid reasoning, working memory, and the two dimensions of complex problem solving, rule knowledge and rule application. In doing so, we replicated the recent study by Bühner, Kröner, and Ziegler (2008) and the structural relations investigated therein [ Bühner, Kröner, & Ziegler, (2008) . Working memory, visual-spatial intelligence and their relationship to problem-solving. Intelligence, 36, 672–680]. However, in the present study, we used different assessment instruments by employing assessments of figural, numerical, and verbal fluid reasoning, an assessment of numerical working memory, and a complex problem solving assessment using the MicroDYN approach. In a sample of N = 2,029 Finnish sixth-grade students of which 328 students took the numerical working memory assessment, the findings diverged substantially from the results reported by Bühner et al. Importantly, in the present study, fluid reasoning was the main source of variation for rule knowledge and rule application, and working memory contributed only a little added value. Albeit generally in line with previously conducted research on the relation between complex problem solving and other cognitive abilities, these findings directly contrast the results of Bühner et al. (2008) who reported that only working memory was a source of variation in complex problem solving, whereas fluid reasoning was not. Explanations for the different patterns of results are sought, and implications for the use of assessment instruments and for research on interindividual differences in complex problem solving are discussed.

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