Learning Potential in high IQ children: The contribution of dynamic assessment to the identification of gifted children

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Abstract

In recent years, models of giftedness have incorporated personal and social variables which influence IQ, rather than taking IQ into account exclusively. Among the various options presented in this context, authors have proposed dynamic assessment techniques as a method for revealing the potential capacity in different groups, independently of the IQ they present. The aim of the present study was to investigate, in two samples of Spanish children from the urban middle class previously identified as gifted and of normal intelligence, three basic assumptions common to studies in this line of research: (1) that there are significant differences in Learning Potential between gifted children and children with average IQ; (2) that the differences are apparent in diverse tasks, and (3) that Learning Potential significantly predicts the high/average status of the subjects. 127 children from 6 to 11 years old (64 high-IQ and 63 average-IQ) were evaluated using different dynamic tests. Significant intergroup differences were obtained and the tests were shown to have high predictive power.

Research Highlights

► The Learning Potential Assessment has been used to identify children with high ability in population Disadvantaged. ► This application is based on the assumption that children with high ability are more L P regardless of their IQ. ► These assumptions have not been proven in not-disadvantaged populations. ► This work shows that children with high IQ have a greater potential for learning that children of normal intelligence. ► Moreover, this potential is shown in different tasks. ► These results validate the initial use of these techniques.

Introduction

When Terman introduced the concept of giftedness in 1916 (Terman, 1925), the criterion for its definition was purely normative (IQ score), and this shaped the reductionist concept of high capacities which, in practice, is still prevalent today (Borland, 2005). With Sternberg and Gardner's contributions (Gardner, 1983, Sternberg, 1985), the most recent models of giftedness establish a network of interrelations between different types of construct and modulating variables (Coleman, 1995, Mönks and Katzko, 2005). Thus, Gagné (2003), Sternberg's WICS model (Sternberg, 2005, Sternberg and Grigorenko, 2002) and the MMG Munich Model of Giftedness (Heller, Perleth, & Lim, 2005) conceive giftedness as a multifactor construct of abilities with social and meta-cognitive modulating parameters, as well as “luck”.

Most of these approaches support the view that giftedness involves the existence of aptitudes which, in conjunction with certain personality characteristics and a favourable environment, induce in individuals the need and capacity to learn rapidly and efficiently by themselves in different fields (Calero, García-Martín and Gómez, 2007, Coleman and Cross, 2001, Freeman, 2005, Jeltova and Grigorenko, 2005).

Underlying these new conceptualizations is a paradigm of identification of gifted children in which high capacity is acknowledged to show in different ways and to require more varied and reliable forms of assessment (Van Tassel-Baska, Feng, & Evans, 2007). This view also derives from the perception that diverse minorities are underrepresented in giftedness programs in countries of the developed world. According to such authors, actual and potential execution should be distinguished (Cross & Coleman, 2005) and attention should be paid to concepts such as ‘emergent giftedness’ (Rea, 2001), potential giftedness (Babayeva and Voiskunovsky, 2003, Leitis, 2000), or high-potential children (Lohman, 2005). The implication of this approach is that intelligence and/or creativity are regulated by other abilities, such as flexibility and self-regulation, and/or by specific socio-environmental variables which may help to optimize these qualities or conversely, maintain them at normal or low levels of functioning. While some authors have developed performance-based instruments (Van Tassel-Baska, 2005, Van Tassel-Baska, Feng and de Brux, 2007), others defend the use of dynamic assessment to identify children with high capacities in underrepresented communities. This is based on the assumption that individuals who show poor performance for cultural or environmental reasons may be detected if their performance is shown to improve significantly after intensive training on the task concerned (Joseph and Ford, 2006, Laing and Kahmi, 2002, Naglieri and Ford, 2005, Noel and Edmunds, 2007, Peña et al., 2006, Stormont et al., 2001, Strong and Delgado, 2005, Swanson, 2006).

Although several dynamic tests focus on specific aspects, particularly of the educational curriculum, the techniques used in this context generally involve non-verbal tasks based on inductive reasoning, probably with the aim of establishing cognitive modifiability as a general capacity that each person possesses, as claimed by Feuerstein (Feuerstein et al., 2002, Feuerstein et al., 1979). The standard methodological procedure is pre-test–training–post-test. Training uses feedback about implementation, contingent reinforcement and verbal signs, and effects of the training have been shown to be task-specific (Brown and Campione, 1984, Fernández-Ballesteros and Calero, 2001). It should be noted that while some studies show that pretest scores correlate with IQ, gain scores (measure of Learning Potential) in some samples (low performance) do not correlate with IQ (Lidz and Van der Aalsvoort, 2005, Resing et al., 2009).

Two types of analyses may be carried out on the results of these tests: quantitative (gain or transfer score), basically consisting of the difference between post-test and pre-test, or a typological approach (Budoff, 1987). This involves classifying participants as Non-gainers, Gainers and High Scorers, thus differentiating between significant and non-significant gains. This type of statistical calculation has been used frequently (see Budoff, 1987, Scöttke et al., 1993) to establish prognostic groups in populations with learning difficulties, and has been shown to be effective and reliable in other groups, such as old people and patients with schizophrenia (Waldorf, Wiedl, & Schöttke, 2009).

The use of dynamic assessment in the context of giftedness originates with studies by Boling and Day, 1993, Passow and Frasier, 1996. Their approach was based on the fact that dynamic tests had proved to be valid for the identification of children of low intellectual level and/or with learning difficulties, and for planning subsequent intervention (Strong and Delgado, 2005, Swanson, 1995). Studies also indicated that training considerably improved the performance levels of different groups of subjects (e.g. Hickson & Skuy, 1990; for a review see the meta-analysis by Swanson & Lussier, 2001). As a result, the methodology is increasingly applied in countries with established attention programs for gifted children (e.g. the USA). For instance, Borland and Wright, 1994, Calvo, 2004, Stanley, 1995, Lidz and Macrine, 2001, Matthews and Foster, 2005 used dynamic assessment to identify gifted children (from minority groups) for participation in gifted programs. The published research is scarce and focuses on traditionally underrepresented populations (primarily ethnic minorities). However, the results show that the methodology was successful at identifying children who passed unnoticed through traditional intelligence tests.

Kanevsky's (2000) study of pre-school children with an IQ between 110 and 150 demonstrated that gifted children possessed a broader ZPD1 as well as faster learning capacity and higher generalization from such learning. Moreover, the learning demonstrated by the children was associated with high levels of motivation, meta-cognition, self-regulation and flexibility, a finding which has been confirmed in other studies (Calero, García-Martín, Jiménez, Kazén, & Araque, 2007). Subsequently, Kanevsky and Geake (2004) found significant qualitative and quantitative differences in Learning Potential between gifted and non-gifted children. However, these results were not very conclusive due to the small sample size (5 gifted/20 non-gifted). Other authors have proposed applying performance tests involving problem-solving processes or based on learning acquisition, but always as a method for detecting children with high potential in disadvantaged groups (Van Tassel-Baska, 2005, Van Tassel-Baska, Feng and de Brux, 2007, Van Tassel-Baska, Feng and Evans, 2007).

Two assumptions underlie the dynamic assessment studies to date: first, gifted children are those who obtain the highest gain as a result of the training, independently of their IQ. Second, the potential “learning capacity” measured by the studies is a global capacity (manifested in different tasks) and may subsequently be used as a global indicator of high capacity. The aim of the present study was to investigate the validity of both these assumptions in a sample of Spanish children. The children, who were not socially disadvantaged, had been previously identified as gifted, and were compared with children of average intelligence.

Working hypotheses were as follows:

  • (1)

    Children with high IQ will present a significantly higher pre-test score than those of average intelligence in each and all of the dynamic tests used.

  • (2)

    Children with high IQ will present a significantly higher Learning Potential, measured through gain scores (post/pre-test difference) in each and all of the dynamic tests used.

  • (3)

    The gain scores obtained in the different Learning Potential tests employed will be significantly predictive of the established classification status (high IQ vs. average IQ).

Section snippets

Participants

The sample comprised of 127 Spanish middle-class urban-dwelling children divided into two groups (high-IQ vs. average IQ). In the high-IQ group, N = 64 (41 female and 23 male, M age = 8.18 years (SD = 1.859); age range: 7–11 years). IQ scores range from 136 to 160 (M IQ = 144.59; SD = 8.01) measured by the K-BIT test (Kaufman & Kaufman, 1997). In the average IQ group, N = 63 (34 female and 29 male, M age = 8.25 years (SD = 1.859); age range: 7–11 years). IQ scores range from 90 to 120 (M IQ = 101.96, SD = 9.29).

Materials

The

Results

As stated earlier, the objective of the study was to establish differences in the Learning Potential between high-IQ children and those of average intelligence in the three different L. P. tests. Accordingly, we initially carried out an independent group mean comparison using the t- test analysis. Fig. 1 shows pre and post-test scores obtained by each group. As may be seen, the high-IQ children present a significantly higher initial score (pre-test) and final score (post-test) in each and all

Discussion

As specified earlier, in addition to determining if there are significant differences between high and average IQ subjects in gain scores in Dynamic tests, the study aimed to establish if such differences occurred in diverse types of tasks and if the tests discriminate between the Gifted and Non-gifted status.

Regarding the first objective, the high-IQ children started with a significantly higher performance level in each of the tests. Additionally, they showed a significantly higher improvement

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