Estudio de la influencia de la inteligencia y el género en la evaluación matemática temprana. European. Journal of Education and Psychology, 6(1), 5-18. doi: ...
ACADEMIC SKILLS PREDICTORS AND GENDER DIFFERENCES Estívaliz Aragón, Ana Isabel Navarro Universidad de Cádiz (SPAIN)
Abstract Introduction: Recently researchers have studied the relevance of domain-specific and domain-general predictors on basic academic skills development (e.g., [1]). Some data maintain that intelligence, working memory and its components as general predictors of basic school skills ([2],[3]).In addition, domain-specific predictors of academic skills as early literacy and early numeracy are also stated ([4]) Objective: This study evaluated possible gender differences in domain-general and domain-specific predictors of academic skills. Those differences could explain gender gap in early years. Methodology: Participants included 178 third year of Preschool Education from four schools students. Girls were 89, ages ranged from 59 to 71 months (M=65.53; SD=3.48), and 89 boys, whose ages ranged between 59 and 72 months (M=65.66; SD=3.64). A cognitive assessment was carried out using the Raven Coloured Progressive Matrices Test, Forward and Backward digit Test, Get Ready to Read and Early Numeracy Test. Results and Discussion: To analyse gender differences Kruskal-Wallis one-way statistical test was used. Our findings support the notion that gender differences were not significant considering the psychological variables assessed (intelligence, working memory, short-term memory, early literacy and early mathematical competence). They are also consistent with other studies reporting of no gender differences between boys and girls in domain-general and specific-predictors of academic skills ([5], [6], [7], [8]). Keywords: Gender differences, Domain-specific predictors, Domain-general predictors, Kindergarten.
1
INTRODUCTION
Domain-specific and domain-general predictors are relevant in the development basic academic skills [1]. More accurately, research supports the role of intelligence, working memory and its components as general predictors of basic school skills ([2], [3]). Moreover, domain-specific predictors of academic skills as early literacy and early numeracy are also stated ([4]). Significance of working memory in the development of basic academic skills has been studied ([9]). Research argues the importance of working memory as a predictor of mathematical learning in the first years of formal schooling ([1]). One of the most used working memory model is Baddeley & Hitch ([10]), reformulated by Baddeley ([11], [12]). Part of this multicomponent model is the central executive, responsible for the allocation of the attentional resources that underlie the processing of complex tasks ([13]). Consequently, research shows strong evidence for the involvement of the central executive in solving arithmetic problems ([14], [15], [16]). Moreover, recent literature supports the relationship between numeracy skills and executive functions in children ([17]) and Primary Education ([18], [19]). In addition, we considered fluid intelligence as a key component when studying learning processes because it contributes to the acquisition, understanding and organisation of new information. It could be a milestone in the acquisition, formation, and consolidation of concepts ([20], [21]). The definition suggests the existence of a relationship between mathematical and fluid intelligence, a point which is supported by recent research ([22], [23], [24]). There are also researches that suggest a link between emergent literacy and academic skills ([25], [26], [4]). The main goal we considered in this study was gender differences in early predictors of academic skills. In the literature we find studies in which no significant differences in math between boys and
Proceedings of ICERI2014 Conference 17th-19th November 2014, Seville, Spain
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ISBN: 978-84-617-2484-0
girls of school age ([27], [28]) and preschool age ([5], [7], [28]) were found. Furthermore, a metaanalysis by Hyde (2005) also supported the absence of significant gender differences. In summary, our study had as general objective: to analyse gender differences in cognitive causes in early age.
2
METHOD
2.1
Objective and Hypothesis
We report on study designed to evaluate possible gender differences in domain-general and domainspecific predictors of academic skills as a possibility to explain what might be generating a gender gap in early years. Our aim was to assess the early manifestation and tried to contrast the lack of possible gender differences in the levels of early maths competence, early literacy, working memory, short term memory and fluid intelligence, at five years old.
2.2 2.2.1
Instruments Early Numeracy Test (ENT- R)
The Early Numeracy Test-Revised is a task-oriented test which attempts to measure the level of early mathematical competence ([29]). Using ENT-R, the teacher or another user of the test can determine to what extent a child or the whole group of children masters early numeracy. By comparing the performance of a child with that of children in a norm group, the level of early mathematical competence can be determined. ENT-R has been developed for grade 1, and 2 of kindergarten and 1 of Primary education and special Primary education. The ENT-R consists of three parallel versions (A, B and C) of 45 items each. The items are divided into groups of five of nine parts (comparing, linking quantities, one to one correspondence, arranging, using numerals, synchronous and shortened counting, resultative counting, applying knowledge of numbers, and estimating). The ENT-R should be administered individually. Computerized version of ENT- R was used. Cronbach’s alpha is .92.
2.2.2
Get Ready to Read!
Whitehurst & Lonigan ([30]) developed this test to measure emergent literacy. Get Ready to Read is a 20-item multiple-choice measure in which children were instructed to respond by pointing to their answer choice. Firstly, it assesses phonological awareness using items related to knowledge of letter sounds, rhyming and word segmentation. Secondly, it measures knowledge of written text through activities based on understanding, and discrimination of letters and words. A computerized version of this test was used. Cronbach’s alpha is .78.
2.2.3
Raven Coloured Progressive Matrices Test (CPM)
We used this classic test to measure fluid intelligence. CPM ([31]) involves establishing logical relationships between a figure missing one part and the possible patterns that could complete the figure. This test illustrates the ability to make sense of disorganised or confusing material, handling non-verbal constructs that facilitate the understanding of a complex structure. In this way, we can measure nonverbal intelligence through reasoning ability based on figurative stimuli without cultural influence. Cronbach’s alpha is .82.
2.2.4
Forward Digits
The WISC- IV ([32]) digit test is composed of two tasks: direct and reverse digits. In this task, series of numbers must be repeated in the same order in which they were verbalized by the evaluator. It is an appropriate way to measure phonological short-term memory, as a sequence is stored without manipulation, and it is necessary to repeat the series exactly as presented. This test assesses the ability of concentration and attention necessary to follow the proposed sequence. This involves the implementation of skills involved in learning and memory processes, which we use regularly. Cronbach's alpha is .78.
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2.2.5
Backward Digits
In digits in reverse order task ([32]) participants must repeat a series of numbers in reverse order to that in which they have previously been verbally presented. In this task, unlike in the previous one, verbal working memory is evaluated. Both this task and the previous one consist of 8 elements, each providing two attempts at the same number of digits. The reverse digit task has a training element prior to undertaking the evaluation which allows the child to become familiar with the test and understand the instructions correctly before increasing the difficulty level of the items. Cronbach's alpha is .76.
2.3
Participants
The sample of students was taken from four schools in the province of Cadiz. Two of the schools were grant-aided and the other two were public schools, all with a middle class socio-economic profile. The participants were 178 pupils in their last year of Preschool Education, ages ranged from 59 to 72 months, mean of 65.60 and a standard deviation of 3.55. Of the total sample, 89 participants were girls, ages ranged from 59 to 71 months (M=65.53; SD=3.64), and 89 were boys, whose ages ranged between 59 and 72 months (M=65.66; SD=3.48). The sample excluded special educational needs. Parents gave informed written consent for their child’s participation.
2.4
Procedure
The authors conducted two assessment sessions. First one, emergent literacy and early mathematical skills were assessed. Then the cognitive tests were administered under appropriated testing assessing conditions. All the assessment tests were individually administered. Assessment sessions lasted between 30 and 35 minutes, and the tests were randomly presented, both in terms of intersession and intra-session.
3
RESULTS
Results of statistics descriptive showed boys’ scores were higher than girls’ scores in any of the predictor variables studied, except in the assessment of fluid intelligence in which girls performed better. Table 1. Table 1. Means and standard deviations of the tests to measure early math competence, emergent literacy, fluid intelligence, working memory and short-term memory according to gender. ENT-R
GRTR
Raven
Digit backward
Digit forward
Boys
M
21.79
16.85
15.63
4.06
5.76
(N=89)
SD
(6.48)
(2.27)
(3.71)
(1.41)
(1.15)
Girls
M
21.55
16.80
16.39
3.98
5.67
(N=89)
SD
(6.59)
(2.35)
(3.68)
(1.46)
(1.51)
Total
M
21.67
16.83
16.01
4.02
5.72
(N=178)
SD
(6.52)
(2.31
(3.71)
(1.43)
(1.34)
Note: GRTR = Get Ready to Read; ENT-R=Early Numeracy Test-Revised To analyse significance gender differences a Kruskal-Wallis one-way test was calculated. This method is used when data do not meet the requirements for the parametric ANOVA. Results show that gender differences were not found in all the variables studied. Early math competence, early literacy, short term memory, working memory and fluid intelligence showed also no significant differences (p > 0.05). Table 2.
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Table 2. Results of Kruskal-Wallis test ENT-R
GRTR
RAVEN
Digit backward
Digit forward
Chi-square
,270
,004
2,463
,702
,521
Sig.
,603
,951
,117
,402
,471
p
