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Automated Working Memory Assessment (AWMA) - Theory

 

Theoretical structure | Language adaptations | Culture-fair | Genetic research | Reliability | Construct stability | Convergent validity | Divergent validity

 

Theoretical Structure

The theoretical structure of the AWMA was investigated using Structural Equation Modelling, where several models were tested. The best fitting model was a 4-component model with factors for: Verbal STM; Verbal WM; Visuo-spatial STM; and Visuo-Spatial WM.

Reference: Alloway, T.P., Gathercole, S.E., & Pickering, S.J. (2006). Verbal and visuo-spatial short-term and working memory in children: Are they separable? Child Development, 77, 1698-1716.

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The study on adults confirmed that verbal and visuo-spatial WM represent related but distinct skills.

Reference: Alloway, T.P., Kerr, I., & Langheinrich, T. (2010). The effects of articulatory suppression and manual tapping on serial recall. European Journal of Cognitive Psychology, 22, 297-305.

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This is a review paper for educational/school psychologists on the benefits of using the AWMA to screen for working memory difficulties that can impair academic success.

Reference: Alloway, T.P. (in press). The benefits of computerized working memory assessment. Educational and Child Psychology.

 

 

 

Language adaptations

Adaption into European Spanish

Reference: M. Perez, F. Santos, & L. Cobos (under review).

Adaption into European Spanish

Reference: Injoque-Ricle, I., Calero, A.D., Alloway, T.P., & Burin, D.I. (2011). Assessing Working Memory in Spanish-Speaking Children: Automated Working Memory Assessment Battery Adaptation. Learning and Individual Differences, 21, 78-84.

 

 

 

Culture-fair

The AWMA provides a measure of Working Memory that is relatively impervious to substantial differences in socio-economic background. Brazilian children from the low socio-economic group did not perform significantly differently from their higher income peers in AWMA tests, but obtained significantly lower scores on measures of expressive and receptive vocabulary.

Reference: Engel, P. M. J., Santos, F. H., & Gathercole, S. E. (2008). Are working memory measures free of socio-economic influence? Journal of Speech Language and Hearing Research. 51, 1580-1587.

 

 

 

Genetic Research

Genotype at rs363039, located in the gene coding for synaptosomal-associated protein, 25 kDa (SNAP25) was associated to WM capacity in ADHD samples.

Reference: Söderqvistab et al. (2010). The SNAP25 Gene Is Linked to Working Memory Capacity and Maturation of the Posterior Cingulate Cortex During Childhood. Biological Psychiatry, 68, 1120-1125.

 

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This study investigated the association of COMT genotype with behavioural and magnetic resonance imaging data collected during performance of a visuospatial WM task (using the AWMA). These results suggest that COMT genotype effects on WM brain activity and behaviour are not static during development.

Reference: Dumontheil et al. (in press). Influence of the COMT Genotype on Working Memory and Brain Activity Changes During Development. Biological Psychiatry.

 

 

 

 

Reliability

Test-retest

Test reliability of the AWMA was measured on128 individuals randomly selected across schools and universities aged between 4.10 years to 22.5 years. After 4 weeks, they were retested. There was a close relationship between the first and the second time of testing (rs ranged from .69 to .90).

Reference: Alloway, T.P., Gathercole, S.E., & Pickering, S.J. (2006). Verbal and visuo-spatial short-term and working memory in children: Are they separable? Child Development, 77, 1698-1716.

 

 

 

Construct stability

Students with low working memory

 

 

 

 

 

Working memory skills in children with low working memory (< 10th centile) remain relatively stable over the course of the school year. When students were retested 9 months later, there was a moderate relationship between the students’ performance at the beginning and the end of the school year.

Reference: Alloway, T.P. (2009). Working memory, but not IQ, predicts subsequent learning in children with learning difficulties. European Journal of Psychological Assessment, 25, 92-98.

 

 

 

Convergent validity

WISC-IV Working Memory Index

There is a high degree of convergence in performance between the AWMA and the WISC-IV Working Memory Index (WMI). This was established in a group of low working memory (standard scores <86) and average working memory children (standard scores >95) selected on the basis of AWMA scores. Performance on the digit span test from the WMI was able to assign correct group membership for 91% of low and average working memory children.

Reference: Alloway, T.P., Gathercole, S.E, Kirkwood, H.J., & Elliott, J.E. (2008). Evaluating the validity of the Automated Working Memory Assessment. Educational Psychology, 7, 725-734.

 

 

 

Divergent validity

WISC

A study following children from pre-school to year 2 found that Working Memory (measured by the AWMA) represented a related but separate construct from fluid intelligence in young children.

Reference: Engel de Abreu, Conway, & Gathercole. (2010); Working memory and fluid intelligence in young children; Intelligence, 38, 552-561.

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This study investigated the use of the AWMA to accurately measure Working Memory in children aged 4-6 years with low capacity (as defined by IQ scores).

Reference: Bergman et al. (2010). Measuring Working Memory Capacity With Greater Precision in the Lower Capacity Ranges. Developmental Neuropsychology, 35, 81-95.

Delis Kaplan

In a study of students with clinical ADHD, low working memory, and average working memory, AWMA scores represented a distinct but related skill from that measured by the Delis Kaplan.

Reference: Holmes, J., Gathercole, S.E., Place, M., Alloway, T.P., & Elliott, J. (2010). An assessment of the diagnostic utility of executive function assessments in the identification of ADHD in children. Child & Adolescent Mental Health, 15, 37-43.

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In a group of students with borderline intellectual functioning, visuo-spatial working memory scores (using the AWMA) and the Sorting task (Delis Kaplan) were the best single predictors that reliably classified students with low IQ.

Reference: Alloway, T.P. (2010). Working memory and executive function profiles of students with borderline intellectual functioning. Journal of Intellectual Disability Research, 54, 448-456.

Working Memory Rating Scale

We compared the relationship between the AWMA, a cognitive-based measure of working memory, and the Working Memory Rating Scale (WMRS), a behavior-based measure of working memory. A measurement model tested the relationship between the two factors: it was .52, with 27% of their variance shared. This establishes a substantial relationship between the cognitive and rating-based assessments of working memory.

Reference: Alloway, T.P., Gathercole, S.E, Kirkwood, H.J., & Elliott, J.E. (2009).The working memory rating scale: A classroom-based behavioral assessment of working memory. Learning and Individual Differences, 19, 242-245.

Conners’ Teacher Rating Scale

AWMA scores were compared with another teacher-rating measure of behaviour, Conners’ Teacher Rating Scale (CTRS; Conners, 2001) in children with low (standard scores <86) and average working memory (standard scores >95).  Students with low working memory did not display any behavioural difficulties in the Oppositional or Hyperactive subscales, although 50% of them did have atypical scores in the Cognitive Problems/Inattention subscale. In contrast, only 5% of average working memory children received atypical scores in the Conners’ subscales.

Reference: Alloway, T.P., Gathercole, S.E., Holmes, J., Place, M., & Elliott, J. (2009). The diagnostic utility of behavioral checklists in identifying children with ADHD and children with working memory deficits. Child Psychiatry & Human Development, 40, 353-366.

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Students with low scores in the AWMA also scored poorly in the Cognitive Problems/Inattention subscale of the Conners’.

Reference: Gathercole, S.E, Alloway, T.P., Kirkwood, H.J., & Elliott, J.E. (2008). Attentional and executive function behaviors in children with poor working memory. Learning and Individual Differences, 18, 214-223.

Behavior Rating Inventory of Executive Function

AWMA scores were also compated with a teacher-rating measure of behaviour, the Behavior Rating Inventory of Executive Function (BRIEF; Gioia et al., 2000) in children with low (standard scores <86) and average working memory (standard scores >95). Over 50% of the low working memory group received atypical scores characterizing a deficit in the Working memory subscales. The latter two are related to the child’s ability to plan and effectively manage information in working memory. However, they did not exhibit the difficulties in controlling behavior or emotion that characterised the ADHD children. In contrast, less than 10% of average working memory children received atypical scores in these subscales.

Reference: Alloway, T.P., Gathercole, S.E., Holmes, J., Place, M., & Elliott, J. (2009). The diagnostic utility of behavioral checklists in identifying children with ADHD and children with working memory deficits. Child Psychiatry & Human Development, 40, 353-366.

 

 

 

   

Key Information

Description

AWMA provides a practical and convenient way for teachers and psychologists to screen for significant working memory problems from childhood to early adulthood

Author(s)

Dr Tracy Packiam Alloway

Publication Year

2007

Age Range

4 to 22 years

Administration

Individual - Screener: 5 to 7 mins; Short form: 10 to 15 mins; Long form: 45 mins

Qualification Code

CL3


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