Effects of Parental Education on Children's Academic Achievement

This report investigates the impact of parental education on children's academic achievement using data from the National Center for Education Statistics (NCES). The analysis involves data selection, filtering, and transformation in SPSS to extract relevant information. Descriptive statistics are presented for scale variables, and frequency analysis is conducted for categorical variables to determine the association between parental education and various factors, including student behavior, absenteeism, and grade performance. Correlation matrices and Eta correlations are employed to assess the relationships between continuous and nominal variables. The findings reveal a positive correlation between parental education and children's academic success, indicating that children with parents possessing higher academic qualifications tend to achieve better outcomes. The report concludes that the education level of the parent is a determinant of a student's future academic accomplishments.

S T U D E N T ’ S N A M E
P R O F E S S O R ’ S N A M E
A F F I L I AT I O N
D AT E
Parental Education Level's Effect
on Children's Achievement

Data Selection
“Parent and Family Involvement in Education”
data was utilized in this analysis. This data was
retrieved from the National Center for
Education Statistics (NCSE). The data relates
to the data product compilation for the year
2016 made by the NHES.
The data was filtered and transformed in SPSS
to get the necessary information. Majority of
the variables were removed to ensure that only
the most important were utilized in the
Assessment.

Data Description
There are 20 dummy variables in the SPSS
dataset and the remaining 5 are scale
variables for different factors associated with
the academic wellbeing of the student. The
descriptive statistics for these scale variables
are presented Table 1.
It is important to note that students who
were absent 364 days in a year from school,
attended home-schools taught by their
parents or guardians.

Descriptive Analysis
We can find the descriptive statistics for each
of the five variables with regard to the parents
education (first guardian’s results were
utilized). The results are presented in the
excel worksheet “Behavior and Absence”
(Kemp, et. al., 2018).
We are able to conclude from the results that
children with parents who have high academic
achievements are better behaved in school and
register fewer absentee days at school.

Table 1: Descriptive Analysis for the Five Continuous
Variables
N Range Minimum Maximum Sum Mean Std. Deviation
E15. Times contacted about behavior problems 13523 75 0 75 6925 0.51 2.098
E15. Times contacted about problems with school work 13523 97 0 97 8276 0.61 2.362
E15. Times contacted about very good behavior 13523 99 0 99 16498 1.22 3.61
E15. Times contacted about very good school work 13523 99 0 99 16262 1.2 3.373
E16. Days absent 13523 364 0 364 56982 4.21 6.882
Descriptive Statistics

Frequency Assessment
The 20 categorical variables cannot be assessed with
regard to descriptive statistics as the information would
be misleading. The frequencies for each of the variables
were obtained relative to parent’s education. Using the
frequencies percentages we are able to tell the
association between parent’s education and the
achievements of the children.
The SPSS results are found in the excel worksheet titled
“Frequencies”. Paying attention to grade performance
we are able to see that children with well educated
parents recorded better grades compared to students
with less academically decorated guardians/parents.

Frequency Assessment
In addition, the higher the parent’s education
achievement, the less likely that student will be
suspended or expelled from school (Kemp,
et.al., 2018). With regard to parent’s
involvement in school affairs, it is clear that the
degree of involvement increases as the level of
education held by the parent increases.
 Also, we can see that parents with higher
academic achievements are more likely to
assist their children with homework compared
to parents with lower academic achievements.

Frequency Assessment
Lastly, will regard to the advancement
placement classes we can see that children
who belong to a household where the parents
have higher academic qualifications are more
likely to be enrolled into this program.
The relationships established above are
important because we cannot calculate
correlation between two categorical variables.
Chart 1 below demonstrates this fact because
the two variables used are both categorical in
nature.

Chart 1: Scatter Plot between Parent Education and
Child’s Grade

Correlation
We can therefore create a correlation matrix
to evaluate the correlation between the 5
continuous variables. The correlation matrix
in Table 2 shows that there is a moderate
positive correlation between problematic
behavior and poor school work.
On the other hand, there is a strong positive
correlation between good behavior and good
school work.

Table 2: Correlation Matrix for the Five Continuous
Variables
E15. Times
contacted
about
behavior
problems
E15. Times
contacted
about
problems
with school
work
E15. Times
contacted
about very
good behavior
E15. Times
contacted about very
good school work E16. Days absent
Pearson Correlation1 .450 .161 .137 .065
Sig. (2-tailed) .000 .000 .000 .000
N 13523 13523 13523 13523 13523
Pearson Correlation.450 1 .157 .136 .069
Sig. (2-tailed) .000 .000 .000 .000
N 13523 13523 13523 13523 13523
Pearson Correlation.161 .157 1 .770 -.007
Sig. (2-tailed) .000 .000 .000 .438
N 13523 13523 13523 13523 13523
Pearson Correlation.137 .136 .770 1 -.007
Sig. (2-tailed) .000 .000 .000 .416
N 13523 13523 13523 13523 13523
Pearson Correlation.065 .069 -.007 -.007 1
Sig. (2-tailed) .000 .000 .438 .416
N 13523 13523 13523 13523 13523
E16. Days absent
Correlations
E15. Times contacted
about behavior problems
E15. Times contacted
about problems with
school work
E15. Times contacted
about very good
behavior
E15. Times contacted
about very good school
work

Correlation Analysis for the 20 Dummy/categorical
Variables
 We cannot use Pearson correlation to assess
the association between parent’s education
and the 20 categorical variables because they
are all nominal in nature. Instead the
relationships established through the
frequency analysis are used to summarize the
association between these 20 variables and
parental education levels.