brain
sciences
Article
The Raven’s Coloured Progressive Matrices in
Healthy Children: A Qualitative Approach
Daniela Smirni
Department of Psychology, Educational Science and Human Movement, University of Palermo,
Received: 29 September 2020; Accepted: 18 November 2020; Published: 20 November 2020
Abstract:
Studies on the structure of intelligence refer to two main theoretical models: the first
one considers intelligence as a unitary construct, the second one assumes the involvement of a plurality
of factors. Studies using Raven’s Coloured Progressive Matrices (RCPM) tasks have often highlighted
the involvement of different cognitive abilities and brain structures, but in the clinical setting,
RCPM measurement continues to be used as a single score. The current study aimed to analyse the
RCPM performance following qualitative clustering, in order to provide an interpretation of the
intelligence assessment through a factorial criterion. The RCPM have been administered to a large
group of typically developing children between 6 and 11 years of age. The sample was divided into
twelve age groups, and the performance of each age group was shown. Three qualitative item clusters
were identified through a factorial criterion. Data showed that performance on RCPM may arise from
different cognitive abilities, starting from basic attentional skills up to the more complex ones that
require perceptual or analogical reasoning. The qualitative parameters could provide more effective
diagnostic and treatment suggestions than a single total score in the clinical setting, and may be
crucial for focusing on strength and weakness in the intellectual functionality evaluation of children.
Keywords:
intelligence; RCPM qualitative parameters; attentional abilities; analogical reasoning;
concrete and abstract reasoning
1. Introduction
Most theories on the nature and the structure of intelligence can be summarised by two broad
theoretical models: the first one considers intellectual activities as the expression of a unitary construct,
and the second hypothesises a plurality of factors with different primary mental abilities that are
functionally independent [1].
In the early decades of the last century, on the basis of statistical–mathematical methods, Spearman
proved that intelligence tests scores, although different, correlate positively with each other. However,
he noted that the strength of these correlations often was not strong. Therefore, he decomposed the
variance in test scores to the part that is common with all other tests, as well as to the part that is unique
to the given test [
2
]. With this background, Spearman hypothesised that each test measures a general
ability, which he labeled as the “gfactor”, and a specific factor tapping abilities or processes unique
to the given test, which he labeled as the “sfactor” [
3
,
4
]. In this context, intelligence, as a “gfactor”,
could be mediated by a specialised region of the brain or by the whole brain being globally activated [
5
].
Subsequently, the further development of factorial analysis methods has encouraged other
structural theories of intelligence, mainly on a statistical basis. Burt [
6
], for example, hypothesised
a hierarchy of intellectual abilities, and distinguished in each individual test three orders of factors:
general, group, and specific factors. Thurstone [
7
], using factorial analysis, concluded that there is
no general factor, but many lower-order, uncorrelated modules or neural processes (so-called bonds),
while Thomson [
8
] rejected Spearman’s gbecause the positive manifold should emerge without
Brain Sci. 2020,10, 877; doi:10.3390/brainsci10110877 www.mdpi.com/journal/brainsci
