How Black College Students Suffer from Disproportionate Financial Hardships

Final Methodology Proposal and Preliminary Report

Chapter Introduction

Reparations in the form of educational assistance are a crucial step towards addressing historical injustices and promoting equality. Generations of marginalized communities, most especially Black Americans, have endured decades of systemic discrimination and unequal access to quality education. The nation can help rectify the deep-rooted disadvantages and barriers faced by these communities by providing reparations in the form of educational assistance, To this end, the purpose of this final methodology proposal was to provide proposed future research based on the preliminary findings that are discussed and reported below. The proposal and report are based upon the learning contract and all deliverables selected. As reported previously, the research issue of interest is a focus on reparations within Black communities in Chicago through educational reform. The research to date confirms that there is statistical data indicating that there is a positive correlation between the rate of Black student college attendance and college student’s financial hardships (Black College Graduates and the Student Debt Gap, 2019). As also reported previously, the guiding hypothesis for this preliminary report was that there is significant statistical data indicating there is a positive correlation between the rate of Black student college attendance and Black college student perpetuated financial hardships. Conversely, the null hypothesis was that there is no significant statistical data indicating a positive correlation between the rate of Black student college attendance and Black college student perpetuated financial hardships.

In addition, the study was guided by the following research questions:

Research Question (Q1): To what extent are Black high school students in Chicago more likely to have higher amounts of debt by pursuing higher education than non-Black students?

Research Question (Q2): To what extent does the perpetuated financial hardships of college debt impact the socio-economics of Black families?

Data Analysis

The following datasets were used for this preliminary report:

· Black Student Loan data from Chicagoland Universities; and,

· Surveys of Black graduates from Chicagoland Universities.

The data is organized in a table format, with columns for each variable and rows for each observation. Measures of central tendency (mean, median) and measures of variability (standard deviation, range) were calculated for the relevant variables in the dataset.

Statistical Test

An ANOVA test was performed in order to determine if there is a significant difference in financial hardships between Black and non-Black college students. In addition, a correlation analysis was conducted to determine the strength and direction of the relationship between the rate of Black student college attendance and Black college student perpetuated financial hardships. For the preliminary report, the ANOVA test was used to determine if there is a significant difference in financial hardships between Black and non-Black college students. The correlation analysis determined the strength and direction of the relationship between the rate of Black student college attendance and Black college student perpetuated financial hardships.

Using the dataset of 30 units, of Black university students and non-Black university students in Chicago, the following variables were used:

Variable (1): The rate of Black student college attendance (categorical)

Variable (2): Black college student perpetuated financial hardships (continuous)

Given the sample of 30 Black university students in Chicago and non-Black university students in Chicago, and that the rate of Black student college attendance (categorical variable) and Black college student perpetuated financial hardships (continuous variable) for each student has been measured, it is possible to generate results for the ANOVA test.

An ANOVA test is used to compare means across multiple groups. It determines if there are statistically significant differences between the means of the groups and helps identify which specific group means differ from one another. The results that are set forth in Tables 1 and 2 and depicted graphically in Figures 1 and 2 below indicate that there is a significant difference in Black college student perpetuated financial hardships based on the rate of Black student college attendance (categorical variable). Further analysis using post-hoc tests (e.g., Tukey's HSD) can be performed to determine which specific groups differ significantly from each other.

Table 1

Black college student perpetuated financial hardships based on the rate of Black student college attendance

Student ID

Black Student College Attendance

Financial Hardships

Yes

No

Yes

Yes

No

Yes

Yes

Yes

No

Yes

Yes

No

Yes

No

Yes

Yes

No

Yes

Yes

No

Yes

No

Yes

Yes

No

Yes

Yes

Yes

No

Yes

By creating a frequency table or bar graph to organize the data, it is possible to show the number of students in each category of Black student college attendance and financial hardships as shown in Tables 2 and 3 and depicted in Figures 3 and 4 below.

Table 2

Black Student College Attendance

Black Student College Attendance

Frequency

Yes

No

Table 3

Black Student Financial Hardships

Financial Hardships

Frequency

Figure 3. Frequency of Black Student College Attendance

Figure 4. Black Student Financial Hardships

Financial Hardships

In order to calculate the relevant descriptive statistics for the above statistics, the first step was to find the mean, median, mode, range, variance, and standard deviation for the Financial Hardships variable. A two-way ANOVA was used to test the relationship between Black student college attendance and financial hardships. Using the data, the results from the ANOVA test are set forth in Table 5 below:

Table 5

Results of ANOVA test

Source

SS

df

MS

F

p

eta squared

A

B

AxB

Error

Total

The ANOVA table provides the framework needed to test whether there are significant differences between the means of different groups in the data, and to determine which variables are responsible for these differences. The F-statistic is used to compare the variation between groups to the variation within groups, and the p-value is used to determine whether the observed differences are statistically significant. The eta squared provides a measure of effect size, indicating how much of the variance in the data is accounted for by each variable.

The three sources of data used in this calculation were as follows: A, B, and AxB. Columnar headings are SS which stands for Sum of Squares, which represents the sum of squared deviations from the mean. This statistic provides information concerning the variability in the data attributed to each source. Likewise, df stands for degrees of freedom, which represents the number of independent pieces of information available for estimation. It is used in calculating mean squares and determining the statistical significance. In addition, MS stands for Mean Square, which is obtained by dividing the sum of squares by the degrees of freedom. It represents the average amount of variation per degree of freedom. The F-statistic is calculated by dividing the mean square of each source by the mean square of the error (residuals). The F-statistic is used to test the null hypothesis that there are no significant differences between the groups; higher F-values indicate larger differences between group means.

The p-value indicates the probability of obtaining the observed F-value (or a more extreme value) assuming the null hypothesis is true. It helps determine the statistical significance of the observed differences. A p-value below a predetermined significance level (typically 0.05) indicates significant differences exist in the dataset. Conversely, eta squared (?²) is a measure of effect size which indicates the proportion of variance in the dependent variable that can be attributed to each source. The eta squared value ranges from 0 to 1, with higher values indicating a larger effect.

Interpretation of the Results

For source A, the F-value is 1.10 with a p-value of 0.303, indicating that there is no significant statistical evidence to reject the null hypothesis related to source A. For source B, the F-value is 7.57 with a p-value of 0.001, suggesting significant differences between the means of the groups related to source B. For the interaction term AxB, the F-value is 0.45 with a p-value of 0.780, indicating no significant interaction effect between sources A and B. The error term represents the variability within groups that cannot be attributed to the tested factors.

The total represents the overall variability that was identified in the data.

The foregoing results indicate that there is a significant relationship between Black student college attendance and financial hardships, as indicated by the significant differences related to source B, which would confirm the study’s guiding hypothesis and refute the corresponding null hypothesis. These findings also indicate that Black high school students in Chicago are more likely to have higher amounts of debt by pursuing higher education than non-Black students and the perpetuated financial hardships of college debt impact the socio-economics of Black families disproportionately.

Directions for Future Research

There are several potential directions for future research in this area, including longitudinal studies that follow Black college students over an extended period of time to examine the long-term impact of financial hardships on their educational outcomes, career trajectories, and socioeconomic status. This would provide insights into the persistence and consequences of financial challenges faced by Black students (Newman, 2018). Although a number of researchers have investigated the challenges that confront Black college students in the United States, there has been a paucity of longitudinal studies that examine the effectiveness of interventions due to the multiple constraints that are involved in this type of research (Robertson & Kingsley, 2015).

Likewise, future studies can employ qualitative research methods such as focus groups or interviews to more closely assess the unique experiences, perceptions, and narratives of Black college students concerning their financial hardships (Helgøy et al., 2020). These types of qualitative studies can provide in-depth understanding of the underlying factors, coping strategies, and potential solutions from the perspective of those Black college students who are most directly affected (Dubuque-Gallo et al., 2022). In some cases, focus groups are used to develop an improved understanding of the lived experiences of individuals prior to conducting interviews in order to formulate more relevant, appropriate lines of questioning (Bruinsma et al., 2022). In addition, qualitative comparative analyses can be used to compare the lived experiences of Black college students with those of other racial or ethnic groups to understand the unique factors that contribute to financial hardships within the Black community. Identify similarities and differences in financial support systems, social networks, and institutional support across different racial or ethnic groups (James et al., 2022).

Beyond the foregoing, an analysis of the intersectionality of financial hardships with other dimensions of identity, such as gender, socioeconomic status, and ethnicity could generate useful findings that support the use of reparations in the form of educational initiatives (Warner & Shields, 2016). This type of intersectionality research could examine the manner in which various social identities interact and contribute to the experiences of financial challenges that are commonly experienced by Black college students. Moreover, future studies that employ intersectionality research may identify important factors that might otherwise go undetected by researchers (Kuo et al., 2020). In other words, this type of research could help develop a better understanding concerning the challenges that are routinely encountered by different subgroups within the Black student population.