Summary
Research Question
The study aimed to identify children’s cognitive assessment scores by assessing how an individual’s minority ethnic group (MEG), home learning environment (HLE), and home languages (HL) affect his or her cognitive achievement. The study hypothesized the following: “(1) cognitive achievement scores vary by minority ethnic group, (2) more home learning environment in early childhood leads to higher cognitive development scores, and (3) English only in the home yields the highest cognitive scores while no English in the home yields the lowest” (Frumkin, 2013).
The study used MEGs, HLEs, and HLs because of their hypothesized ability to shape cognitive development. An individual’s home learning environment helps shape cognitive development. The individual’s early cognitive achievement will then predict future academic achievement. Language also plays a significant role in cognitive achievement. It was found that there was a negative correlation between children who spoke only their native language at home to their cognitive achievement (Jensen and Wuertz, 2010).
Home learning environment refers to parent-child interactions and the interactive setting in which a child can explore. It was found that if parents read to their child and encouraged the child to read individually, then there was a correlation to language and literary development (Frumkin, 2013). This would in turn increase the child’s motivation to read more in the future. It was also found that an individual’s HLE could significantly increase cognitive and academic achievement for children raised in a low socioeconomic background (Frumkin, 2013).
Methods
To select the children used for the study, a sample from the Millennium Cohort Study (MCS) was used. The MCS is a longitudinal study that followed about 19,000 babies born in the United Kingdom from 2000 – 2001. The information collected in the MCS includes family environment, child development, and socioeconomic status. The MCS collected data using from interviews and questionnaires from the children’s caregivers. A cognitive assessment would also be used during the second data collection period.
For measures, an Ordinary Least Squares (OLS) analysis was used to determine child cognitive outcomes from the two dependent variables: [1] the Bracken Basic Concept Scale-Revised (BBCS-R) and [2] the British Ability Scale-Naming Vocabulary (BAS-NV). The OLS uses a linear regression model to estimate unknown parameters by reducing differences between observed responses and predicted responses of a dataset. The BBCS-R is a test that measures children’s academic comprehension. The BAS-NV is a test that measures children’s cognitive ability and academic achievement, in particular the children’s oral and language abilities.
The OLS had two regressions for each dependent variable, the BBCS-R and the BAS-NV. The independent variables used were the ethnicities of the families, the home environment, and the home language.
The home learning environment was measured by selectively using certain MCS questions, which used a Likert scale from 1 – 7, that relate to home environment. Sample questions include: “How much television the child watches,” “How often the child is taught the alphabet at home,” and “Whether anything special was done for the child’s third birthday” (Frumkin, 2013). The study then divided the data collected into five groups that ranged from “Little home learning” to “Lots of home learning” (Frumkin, 2013).
In short, the BBCS-R and BAS-NV were tests used to determine the cognitive outcomes of children. Data about children’s ethnic groups, home learning environment, and home language were collected from the MCS. These would then be measured to determine the strength of their correlation to the cognitive outcomes of children.
Results and Conclusions
It was found that in general South Asians, particularly the Pakistani and Bangladeshi groups, performed the worst on the BBCS-R, which measured academic comprehension (Frumkin, 2013). The Black African group performed more poorly than the Black Caribbean group. The Indian group, despite being South Asian, would perform the best of all minority ethnic groups. Though, the White group would perform significantly better than all other groups.
The Pakistani and Bangladeshi group also performed the worst on the BAS-NV, which measured cognitive ability and academic achievement (Frumkin, 2013). The White group, as expected, also performed better than other groups. Surprisingly, the Indian group and the Black African group performed the same with both performing less well than the Black Caribbean group.
The home learning environment played a role cognitive achievement according the findings on the BBCS-R and the BAS-NV. In general, children generally had higher cognitive scores when there were more interactive learning items in the home (Frumkin, 2013). Ethnicity played a role in three of the five minority ethnic groups: the Black African group, the Pakistani group, and the Bangladeshi group. They all had higher cognitive achievement scores when there was a better home learning environment.
Households that spoke only English had children perform the best and households that did not speak English at all performed the worse (Frumkin, 2013). There was no significant difference if the child had two home languages or had their native home language (non-English). White children performed better than others regardless of whether or not they spoke one language or two languages.
Hypothesis 1 predicted that ethnicity affected cognitive achievement. This hypothesis was supported. White children performed better than minority children. Additionally, there were further achievement differences among the different minority groups.
Hypothesis 2 predicted that home learning environment led to increased cognitive achievement. This hypothesis was partially supported. Only three minority ethnic groups had significant difference in cognitive achievement based on their home learning environment.
Hypothesis 3 predicted that English-only homes had children with the highest cognitive achievement while no-English homes had children with lowest cognitive achievement. This hypothesis was fully supported.
Critique and Discussion
There were some drawbacks to the study. Firstly, the information gathered to determine home learning environment was greatly inadequate. It relied on responses from the MCS, which did not directly try to assess home environments, but rather gather demographic data. The researchers of the study also did not specify the reasoning and methods they used to select the specific questions to identify the home learning environment. A more direct and accurate assessment of the home learning environment should have been used instead.
Additionally, the study used a very limited range of ethnicities. Asians (with the exception of South Asians), Hispanics, and Latinos were not used in the research. By neglecting these populations, it would be hard to accurately determine the level of significance ethnicity plays in cognitive achievement.
Though, the study did raise thought to the impact home environments have on cognitive development even if Hypothesis 2 was partially supported. It could be that home learning environment only affected certain ethnic groups because of the flawed method to measure home learning environment. Because the MCS did not directly look for home learning environment data, then the researchers’ selected questions may be unknowingly geared toward specific populations. If this is the case, then their hypothesis may possibly be correct.
Another drawback of the study was that it did not focus much on how much socioeconomic status could play a role in the available options for a rich home learning environment. It raises concern that children whose parents spoke a non-English language and held lower socioeconomic status had less learning opportunities than others, which greatly hinders their cognitive achievement. For instance, children in low socioeconomic households may be less likely to go to libraries and museums as well as not have enough resources to access learning materials.
Regarding language, the tests administered are most likely in English, and for a young child who is learning two languages it may be very difficult. However, as the child has a higher cognitive capacity and learned to fluently speak one or both languages, then the cognitive achievement scores may even surpass those who only spoke English at home. Of course, this is only a speculation and will need more research.
Language can be a subset of home learning environment. For instance, if parents provide reading materials to their children at home, then the children’s learning environment is higher and they become more proficient in their language capabilities. By having reading materials at home, parents can allow the child to have increased cognitive development because they can provide more parent-child oral interactions and can cultivate language development.
The implication that can be taken from this study is that parents should be more proactive in developing a learning environment for their child because they play a very important role in fostering their child’s cognitive development. While they may not be able to control their ethnicity and socioeconomic status, they do have control over the learning environment of their children. By allowing for a more interactive learning environment, they expedite their child’s cognitive development and ultimately increase academic achievement in the future.