Working Memory and Fluid Intelligence in Young Children by Abreau - Essay Example

?Article Analysis: de Abreau, P.M.J.E.; Conway, A.R.A. and Gathercole, S.E. (November-December . “Working Memory and Fluid Intelligence in YoungChildren.” Intelligence, Vol. 38(6): 552-561. By Student Name Course Institute Date Part I: De Abreau, Conway and Gathercole (2010) tested the hypothesis that, although separate, there is a relationship between working memory and fluid intelligence. The study was designed to “explore the development of working memory and fluid intelligence” in young children and to shed some light on the link between the two cognitive functions (de Abreau, et. al., 2010, p. 552). The study was conducted by following and testing 119 children from Kindergarten to Second grade in Luxemburg. The children were tested each year in areas that assessed their working memory, short-term memory and fluid intelligence (de Abreau, et. al., 2010). Research findings indicate that although working memory, short-term memory and fluid intelligence were significantly related, they were constructed differently in young children. Moreover, when controlling for commonalities between the short-term memory and the working memory, the latter was significantly linked to fluid intelligence and short-term memory was not. Using the Chi-square test for fitness of the model in terms of the independence of the three variables (working memory, short-term memory and fluid intelligence), a two-factor model was a better fit than a single factor model. Although the single factor model measured .96 in the CFI and IFI indices, it was low in RMSEA values. However, the three-factor model loaded the latent variables across each of the tests results for each year demonstrating that links between the variables: working memory ranged from .50-.62; fluid intelligence to short-term memory showed no significant correlations in kindergarten [.18, p=2]. Medium links were shown in 1st grade [.26, p=.12] and stronger links in 2nd grade [30, p=.01]. Therefore the data fit well since working memory, short-term memory and fluid intelligence are latent variables, and the underlying observable and measureable factors of problem solving tasks (beta values) reflect three separate but correlated factors: working memory, short-term memory and fluid intelligence in early childhood. Part II: The study proceeded on a strong hypothesis. The study hypothesized that based on the findings of several studies, there is a strong link between fluid intelligence and working memory in adults. Essentially, it is argued that working memory and fluid intelligence require attention control techniques. However the “underlying nature of” the link is not well “understood” (de Abreau, et. al., 2010, p. 553). Nevertheless, it is hypothesized that in fluid intelligence tasks, the individual is required to cognitively evaluate problems and devise a solution. Likewise, cognitive control may be required in working memory tasks to retain active memories for confronting problems. Alternatively, the short-term memory as opposed to cognitive controls explains the link between fluid intelligence and working memory. While some studies have been conducted with respect to young children, it is not clear whether or not working memory functions as either a cognitive control or short-term memory device contributes to children’s fluid intelligence (de Abreau, et. al., 2010). The study therefore set out to measure latent variables which are unobservable in a direct way (Bollen, 2002). The latent variables are short-term memory, working-memory and fluid intelligence. However, the study used tools that allow an interpretation of underlying factors that are predictors of working memory, short-term memory and fluid intelligence. In this regard a structural equation model was used. The structural equation model allows for variables to have an influence on each other in a reciprocal way. This can be accomplished in a direct way or through other variables acting as mediums (Fox, 2006). The strengths of de Abreau et. al.’s (2010) study was that it observed the influence of the latent variables through other variables acting as mediums. In this regard, the other variables were observed in the form of several tests administered strategically at each year under observation: Kindergarten, 1st and 2nd grades. Each of the tests were designed to explore the impact of working memory on the learning abilities of children. The children were tested on an individual level away from the general population. Prior to administering the tests, the tests were checked by experts for fitness by experts and were also subjected to a pilot test before using them among the sample (de Abreau, et. al., 2010). The of the tests scores were calculated using Cronbach’s alpha reliability coefficients. Cronbach’s alpha is described as among the “most popular reliability statistics” and it reliably “determines the internal consistency or average correlation of items” under investigation (Santos, 1999). Once the correlations were identified, a number of confirmatory factor analyses were conducted using several tools including Bentler’s Comparative Fix Index, Bollen’s Incremental Fit Index, Root and Square Error of Approximation, RMSEA, CFI and IFI for testing the goodness of the models for estimating how each test reflected how working memory and short term memory functioned distinctly and how both memories and fluid intelligence were linked over the years (de Abreau, et. al., 2010). Therefore the study’s strength was found in its reliability and the use of raw data. The weakness of the study however, was in its relatively small sample size. Although the study consisted of 119 children, they came from 11 public schools and while it may represent a modest sample size in Luxemburg, it represents small samples from each school. Moreover, the study does not reveal how many of the children came from each school. Therefore the reader is not sure how well the sample size represents the 11 public schools. Moreover, all of the children were white and may not represent a multicultural population. Since the tests were administered on an individual basis, the smaller sample size was a better fit as it involved administering and monitoring the test 119 times. Therefore, a larger sample size may not have been amenable to this kind of testing and would have increased the risks of error in the test results. Part III: One suggestion for further research that would improve the study would be to include practical exercises as a means of improving the variance. The study administered tests which most likely engaged working and short-term memory. Practical exercises would have tested fluid intelligence and most likely demonstrated the link between fluid intelligence, working memory and/or short-term memory. In this regard, the practical exercise could have been based on asking the child to decide what the class can do as a group to preserve the environment. This would engage and test the child’s fluid intelligence and most likely the child’s working and short-term memory. This would involve more complex thinking and doing, as opposed to the actual tests used that require a right or wrong answer. Thus practical response tests would have involved an additional dependent variable. Overall the independent variables could have been expanded on for improving the variance. For example, rather than using 11 public schools, at least 5 of the schools should have been private schools. A conscious effort should have been made for including different races and/or ethnic groups. These would have also changed the characteristics of the sample to improve the strength of the conclusion. The same hypothesis can be used in a longitudinal study as it was used in the present study. Longitudinal studies involve following the same sample over a period of time (British Medical Journal, 2013). The hypothesis cannot be used in an experimental study because experimental studies typically involve trying something out with a specific population. For example, an experimental group might be used to determine the effects of a specific drug or programme and would try it out on a sample population (British Medical Journal, 2013A). Bibliography Bollen, K. A. (2002). “Latent Variables in Psychology and the Social Sciences.” Annual Review of Psychology, Vol. 53: 605-634. British Medical Journal. (2013). “Longitudinal Studies.” BMJ. Available online: http://www.bmj.com/about-bmj/resources-readers/publications/epidemiology-uninitiated/7-longitudinal-studies (Accessed 25 April, 2013). British Medical Journal (2013A). “Experimental Studies.” BMJ. Available Online: http://www.bmj.com/about-bmj/resources-readers/publications/epidemiology-uninitiated/9-experimental-studies (Accessed 25 April, 2013). de Abreau, P.M.J.E.; Conway, A.R.A. and Gathercole, S.E. (November-December 2010). “Working Memory and Fluid Intelligence in Young Children.” Intelligence, Vol. 38(6): 552-561. Fox, J. (2006). “Structural Equation Modeling With the SEM Package in R.” Structural Equation Modeling, Vol. 13(3): 465-486. Santos, J.R. (April 1999). “Cronback’s Alpha: A Tool for Assessing the Reliability of Scales.” Extension Journal, Vol. 37(2): ISSN 1077-5315. Available online: http://www.joe.org/joe/1999april/tt3.php (Accessed 25 April, 2013). Read More