Part 2 Cognitive Interventions
The Data
Welcome to part two in a series on cognitive interventions. Increasing knowledge of these interventions is important for professionals such as educational psychologists, individual needs teachers and administrators that work in International schools in Hong Kong. Some of these interventions are being utilized to help children with dyslexia, ADHD and autism. In part two of this series on cognitive interventions for academic achievement the results of meta- analytic studies are summarized. Some of the meta-analyses used standardized mean differences such as d and some used correlations such as r. All of the effect sizes were converted to a standardized mean difference (d) in order to compare and combine the results across studies. There were 203 studies included in the seven meta-analyses. The effect sizes ranged from 0.07-0.58, with an overall average effect size of 0.26, which suggested a small effect. Three of the meta-analyses (Kearns & Fuchs, 2013; Melby-Lervag & Hulme, 2013; Schwaighofer et al., 2015) examined the effects of cognitively focused interventions on reading and mathematics, with two of them focusing on working memory training. Kearns and Fuchs (2013) found moderate effects for cognitively focused interventions (e.g., long-term memory, planning, processing, speed, working memory, visual-spatial processing) when compared to no intervention at all, but only a small effect (0.26) when compared to academic interventions. Both meta-analyses for working memory training found consistently negligible effects (0.07 and 0.09 for mathematics, 0.13 and 0.15 for reading decoding, and 0.13 and 0.21 for reading comprehension). These 55 studies consistently show that working memory training has little to no effect on reading or mathematics performance improvements (or achievement gains). The remaining four studies examined the effects of using cognitive measures in the intervention process. Burns et al.(in press) studied the effects of determining
reading and mathematics interventions from diagnostic measures of cognitive pro- cessing, which resulted in a small effect(0.17)from 37 studies. Three of the meta- analyses examined the relationship between student response to intervention and
preintervention cognitive measures such as IQ (Scholin & Burns, 2012; Stuebing etal., 2009). The relationship between student response to intervention in reading and mathematics resulted in an average effect size of 0.35, from 94individual
studies, which equals an rof.17 and suggests a negligible to weak relationship.
Some reading this article might wonder about executive functioning. Although executive functioning was addressed in some of the meta-analyses included in this review, none of the studies examined the construct differentially from other cognitive constructs. Jacob and Parkinson (in press) reviewed 67 studies and concluded that (a) most of the research occurred in 2010 or later, (b) there was a correlation between executive functioning and academic skills, (c) the correlation with executive functioning was approximately equal for reading and mathematics, and (d) changing skills in executive functioning through various interventions did not lead to increased skills in reading and mathematics. The authors concluded that there was little to no evidence thatexecutive
functioning and academic skills were causally linked. The study is not included in the data for the current review because the article is not yet available; readers are
encouraged to watch for its release.