The Relative Strengths of Relationships Between Fine Motor Skills, Working Memory, Processing Speed and Fluid Intelligence in Early Elementary School Children.

The goal in the present paper was to examine the combined and relative impact of fine motor ability, auditory working memory, and processing speed on fluid intelligence in a sample of early elementary school students. Our participant sample was 145 children (Mage = 9.1 years, SD = 1.1; 80 boys, 65 girls). We used the Raven's Colored Progressive Matrices Test as a measure of fluid intelligence and five other measures to represent the three predictor variables: the Grooved Pegboard Test as a measure of fine motor skills, Digit Span Forwards and Digit Span Backwards tests as measures of working memory, and Rapid Automatized Naming and Letter-Digit Substitution tasks as measures of processing speed. Regression analyses indicated that only two of these measures had a statistically significant association with the fluid intelligence test scores, namely, scores on the Grooved Pegboard (fine motor skills) and Digit Span Backwards (working memory) tests, with these two measures explaining 35% of the variance in the fluid intelligence test scores. Thus, fine motor skills and working memory were correlated with fluid intelligence in early elementary-grade students. Until the directions of these relationships are better understood, we might assume that interventions aiming to increase young children's fluid intelligence, or at least their intelligence scores, might partly target working memory and fine motor skills.

Identifying predictors of reading speed and reading comprehension in Bosnian.

The goal of the present study was to examine the predictors of reading speed and reading comprehension in third-grade students from Bosnia and Herzegovina (BIH). The sample consisted of 168 third-grade students (86 boys, 82 girls) attending regular schools in Canton Sarajevo, BIH. We examined the effects of phonological awareness (phoneme deletion and rhyming), rapid automatized naming (RAN) of letters and objects, semantic fluency, working memory, and processing speed, on three reading speed tasks and a reading comprehension task. For the reading speed tasks, total amount of explained variance was 33% for reading a text passage, 40% for word reading and 36% for pseudoword reading. The most important predictors of reading speed tasks were phoneme deletion task and RAN: Letters. On the other hand, the model explaining reading comprehension was much less predictive and explained about 11% of variance. Significant predictors of reading comprehension were working memory and processing speed. The results of this study are very informative in creating better models of reading. This in turn will help create better reading intervention programs and potentially reduce the number of children with reading disabilities.