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Ratings of everyday academic and cognitive skills in evaluation of school learning and learning problems: initial scale development and validation

Although research supports the use of measures of typical performance for
assessing academic and cognitive skills, there are currently few such measures in
existence. Other measures have been used for research purposes, but they are not normed
on a large, nationally-representative sample. The Ratings of Everyday Academic and
Cognitive Skills (REACS) was created to address the need for a measure of typical
academic and cognitive skills. The goal of the REACS is to provide a timely, easy to
administer, and comprehensive assessment of a child's typical functioning in various
academic and cognitive domains. The purpose for this dissertation was to develop the
initial scale and conduct analyses to provide evidence of its reliability and validity.
In an attempt to provide preliminary evidence of the validity of scores from this
measure, Parent (n = 142) and Teacher (n = 109) REACS forms were collected for data
analysis. A subsample of parents and teachers completed forms to examine interrater and
test-retest reliability. A group of children (n = 32) were assessed with measures of
academic achievement, cognitive ability, and memory for comparison to the REACS. Results generally showed high internal consistency, yet less reliable test-retest
and interrater reliability. While the confirmatory factor analysis (CFA) of the parent
scale supported a factor structure that approximated the intended structure of the
REACS, a better fit was found with a simpler model for the teacher scale. Finally, both
the Parent and Teacher REACS forms were found to predict academic achievement
better than cognitive ability. The predictive ability of the REACS was enhanced when
used in conjunction with a measure of cognitive ability.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/86064
Date10 October 2008
CreatorsLamb, Gordon Dale
ContributorsReynolds, Cecil R
PublisherTexas A&M University
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
TypeBook, Thesis, Electronic Dissertation, text
Formatelectronic, born digital

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