Meta-analysis of academic interventions derived from neuropsychological data

Autor: Amanda M. VanDerHeyden, Megan Rodriguez, John L. Hosp, Cynthia Conner, Maureen Cooper, Shannon Hutcheson, Shawna Petersen-Brown, Matthew K. Burns, Katherine M. Haegele, Kate Clayton, Braden Schmitt
Rok vydání: 2016
Předmět:
Zdroj: School Psychology Quarterly. 31:28-42
ISSN: 1939-1560
1045-3830
DOI: 10.1037/spq0000117
Popis: Several scholars have recommended using data from neuropsychological tests to develop interventions for reading and mathematics. The current study examined the effects of using neuropsychological data within the intervention process with meta-analytic procedures. A total of 1,126 articles were found from an electronic search and compared to inclusion criteria, which resulted in 37 articles that were included in the current study. Each article was coded based on how the data were used (screening-86% or designing interventions-14%), size of the group for which interventions were delivered (small group-45%, individual students-45%, or entire classroom-10%), and type of data collected (cognitive functions-24%, reading fluency-33%, phonemic/phonological awareness-35%, or mixed-8%). A corrected Hedges' g was computed for every study and reported for variables of interest. A Fail-safe N was also computed to determine how many studies with a zero effect would have to be found to change the conclusions. The data resulted in a small effect (g = 0.17) for measures of cognitive functioning, but moderate effects of g = 0.43 and g = 0.48 for measures of reading fluency and phonemic/phonological awareness. There were few studies that examined measures of cognitive functioning within the intervention process. Taken together with previous research, the data do not support the use of cognitive measures to develop interventions but instead favor more direct measures of academic skills (e.g., reading fluency) in a skill-by-treatment interaction. Implications for practice and future research are discussed.
Databáze: OpenAIRE