Effectiveness of Cognitive Processing Assessments and Interventions

Effectiveness of Cognitive Processing Assessments and Interventions on Academic Outcomes: Can 200 Studies be Wrong? (part 1 of a 3 part series)

As an educational psychologist working in Hong Kong parents and school staff often seek information on what sort of interventions may be helpful for their children or students academic difficulties. This includes children with ADHD, Dyslexia and Autism Spectrum Disorders (including Aspergers Syndrome). Schools in particular look for guidance in implementing Multi tiered support systems that involve various interventions and are part of a response to intervention (RTI) process. The use of research based interventions with some validity is an important part of the RTI process. In this series of three weekly blogs I will analyse and summarize a number of pieces of current research on cognitive processing assessments and interventions to help children develop academic skills. The first part will be an introduction, the second a look at the data and the third blog will explore the implications of this research.

The current national implementation of response-to-intervention frameworks in the USA has intensified the debate regarding underlying causes of student deficits and how to best assess and intervene for them. Several scholars have advocated for using measures of cognitive processing to analyse academic difficulties and design individualized interventions(e.g., Feifer, 2008; Fiorello, Hale & Synder, 2006; Floyd, Evans, & McGrew, 2003; Hale, Fiorello, Bertin, & Sherman, 2003; Hale, Fiorello, Kavanagh, Hoeppner, & Gaither, 2001). Feifer (2008) proposed using measures of underlying cognitive abilities for the purpose of selecting interventions and recommended several contemporary tests of intelligence, memory, and executive functioning to do so. There are also multiple resources available to school psychologists that describe interventions based on remediating underlying cognitive deficits. For example, there are books that list general reading interventions based on neuropsychology (Feifer & De Fina, 2007) and interventions for specific cognitive processes such as working memory (Dehn, 2008). Moreover, there were five mini-skills and documented sessions at the 2015 National Association of School Psychologists annual convention that provided free guidance on using data from cognitive measures to remediate reading difficulties, and multiple paid workshops at both the national and summer conferences with similar foci.

Meta analyses were proposed by Gene Class (1976) as a way to synthesize a research literature to better understand its findings. He proposed use of standardized mean differences in which the results of the study would be reported in standard deviation units that represented the difference between the treatment and control group. Cohen (1988) proposed the now famous d statistic, which is the difference of the two group means (control and experimental) divided by the pool standard deviation, and indicated that a d of 0.20 was a small effect, 0.50 was a moderate effect, and 0.80 was a large effect. Other metrics are also used, such as r and r2, but all approaches can be converted to each other for common comparisons.

If cognitive measures are useful to intervention planning, then experimental research should be able to demonstrate that use of cognitively focused interventions generate academic performance gains better than standard instructional practices that can be used in the absence of cognitive processing data (e.g., increasing corrective feedback, improving teacher clarity). Fortunately, there have been several recent meta-analyses regarding the role of cognitive measures to inform academic interventions. Next week a look at the data from these studies.