scholarly journals Measuring Goal Setting in School-Aged Children: Studying the Effects of Demographic Variables in Regression-Based Norms

2020 ◽  
Vol 6 (2) ◽  
pp. 96-110
Author(s):  
A. Toornstra ◽  
P. P. M. Hurks ◽  
W. Van der Elst ◽  
K. Massar ◽  
G. Kok ◽  
...  

Abstract The aim of the study was to establish demographically representative norms for tasks measuring goal setting, and more specifically planning and reasoning in children. Three tasks were administered to n = 195 Ukrainian children aged 5.10 to 14.5 years old: the Spatial Working Memory (SWM), the Stockings of Cambridge (SOC) test, and the Naglieri Nonverbal Ability Test (NNAT). Main outcome per test was accuracy: i.e., the total number correct for the SOC and NNAT, and the total amount of incorrect responses for the SWM. Correlations among accuracy measures varied from − 0.51 to 0.60, indicating these tasks measure related but at the same time unique constructs. Higher age was associated with more accurate test performances on all outcome measures. On the NNAT, we found a curvilinear association between age and accuracy, indicating that younger children’s NNAT accuracy scores increased more with age compared with older children. We found a cubic age effect on accuracy for the SWM and SOC: i.e., test scores were relatively stable at younger and older ages, with a curvilinear increase in test scores in the other age groups. Demographically corrected norms were calculated and presented per test. These indicated that sex was not associated with accuracy scores on any of the tests. Last, a higher level of parental education (LPE) was associated with higher accuracy scores, but only on the NNAT. We conclude that demographic variables in norm analyses enhance insight in the scores and allow for application in clinical settings and research.

2018 ◽  
Author(s):  
Roxanne Connelly ◽  
Vernon Gayle

The ‘Flynn effect’ describes the substantial and long-standing increase in average cognitive ability test scores, which has been observed in numerous psychological studies. Flynn makes an appeal for researchers to move beyond psychology’s standard disciplinary boundaries and to consider sociological contexts, in order to develop a more comprehensive understanding of cognitive inequalities. In this article we respond to this appeal and investigate social class inequalities in general cognitive ability test scores over time. We analyse data from the National Child Development Study (1958) and the British Cohort Study (1970). These two British birth cohorts are suitable nationally representative large-scale data resources for studying inequalities in general cognitive ability.We observe a large parental social class effect, net of parental education and gender in both cohorts. The overall finding is that large social class divisions in cognitive ability can be observed when children are still at primary school, and similar patterns are observed in each cohort. Notably, pupils with fathers at the lower end of the class structure are at a distinct disadvantage. This is a disturbing finding and it is especially important because cognitive ability is known to influence individuals later in the lifecourse.


2020 ◽  
Vol 64 (3) ◽  
pp. 171-191
Author(s):  
Carol A. Carman ◽  
Christine A. P. Walther ◽  
Robert A. Bartsch

The two most commonly used nonverbal tests for gifted identification, the Naglieri Nonverbal Ability Test (NNAT) and the Cognitive Abilities Test (CogAT) nonverbal battery, have not been compared in their newer versions to explore the effects of their use on the identification of underserved populations. Additionally, the effects of the use of various norming groups and cutoff scores on both instruments’ identification abilities has not been compared. This study compared 15,733 CogAT7 nonverbal battery scores and 14,421 NNAT2 scores of kindergartners between 2013 and 2015 from one large urban school district to explore the differences between how each test relates to major demographic variables and examine the effects on who is selected for participation in gifted programming based on which instrument, which norming group, and which cutoff scores are used. Both instruments were less likely to identify students from demographic groups that have been traditionally underrepresented than students from traditionally overrepresented demographic groups, but identification varied based on the type of norming plan used and which instrument was taken. Suggestions are made as to the best instrument for use with various demographic groups and norming plans.


Sign in / Sign up

Export Citation Format

Share Document