Purpose

The purpose of our project is to explore the quality of education as it varies by wealth and gender across the globe.

Goals

Through analyzing UNICEF datasets, we hope to bring attention toward the discrepancies in the quality of education across the globe. We hope to uncover any differences or similarities in the quality of education based on gender and wealth, as it varies across different regions. Every person is deserving of an education, and the first step toward improving education for all is to recognize places where access to a quality education is lacking. Our project attempts to take this first step, locating where education can be improved.

Data Visualizations

This visualization displays the developmental level classification that UNICEF has assigned to each country. The countries represented are the only countries that UNICEF has education data for, and therefore are the only countries that will be analyzed in this project. UNICEF classified these countries by income “measured using gross national income (GNI) per capita, in U.S. dollars, converted from local currency using the World Bank Atlas method."

Comparing Attendance, Completion, and Out-of-School Rates

The data visualizations below are created using a combination of data from three separate UNICEF datasets: one on net attendance rates per country, one on school completion rates per country, and one on out-of-school rates per country. Each dataset is also split up by grade level (Primary, Lower Secondary, and Upper Secondary). For each grade level, the data sets compare the percentage rates of female and males in each country that attend school, complete school, or are out of school. They also compare the rates for school children within five separate wealth quintiles (categorized by UNICEF as Poorest, Second, Middle, Fourth, or Richest). The visualizations plot attendance rates and completion rates against each other, differentiating between gender or wealth level in order to compare and identify disparities. The color of the points identifies which region the country is a part of, and by hovering on each point, the country name is displayed. The visualizations also allow comparisons to be made between the rates for each grade level. Following the scatterplots, further visualizations display out-of-school rates for each country on a map with the color corresponding to the percentage rate. The country name can be displayed by hovering over each country. These maps allow comparisons to be made between out of school rates for each gender, wealth level, and grade levels.

Gender

• For both genders, there is a direct correlation seen between attendance rates and completion rates, demonstrating that the countries whose students attend school the most consistently have the highest completion rates.
• There is a clear trend for both genders that the higher the grade level, the lower the attendance and completion rates.
• While there is not a drastic disparity between male and female attendance and completion rates, there is still lower rates for females than males.
• Sub-Saharan Africa (SSA) by far has the lowest attendance and completion rates in each of its countries.
• European and Central Asian (ECA) countries tend to have the consistently highest rates for all grade levels.

• Out of school rates have an inverse relationship with the attendance and completion rates from above--as the grade level gets higher, out of school rates for both genders and in every region get higher.
• Once again, while there is not a drastic disparity between female and male out of school rates, there still seems to be slightly higher rates for females than males.
• African countries tend to have the highest out of school rates while Latin American and Central Asian countries tend to have the lowest.

Wealth

• The attendance/completion rate disparity between wealth groups is significantly more drastic than the genders.
• For every grade level, the rates become significantly lower as the wealth levels decrease.
• Once again, both attendance and completion rates decrease as the grade levels rise, no matter the region or wealth level.
• Sub-Saharan African countries (SSA) have the lowest rates for each wealth level (although there is still a significant increase as wealth level increases) while European and Central Asian countries (ECA) consistently have the highest rates.

• Opposite of the completion and attendance rates, out of school rates for all countries decrease as the wealth level increases.
• The difference between the poorest and richest people for each country is quite significant with the poorest people having significantly larger out of school rates.
• Once again, the rates also rise with grade level, with the most kids out of school in Upper Secondary age.
• Sub-Saharan African countries (SSA) tend to have the highest out of school rates for any wealth level or grade level.
• Latin American and Caribbean (LAC) countries and European and Central Asian countries (ECA) tend to have the lowest out of school rates.

Comparing Foundational Learning Skills

For the dataset used to create the following visualizations, UNICEF calculated the percentage of children in two different age groups (children in Grades 2/3 and children aged 7 to 14) who demonstrated foundational reading skills and the percentage of children in the same two different age groups (children in Grades 2/3 and children aged 7 to 14) who demonstrated foundational numeracy skills. These values were collected from countries in the same regions analyzed in visualizations above. In the following visualizations, the percentage of children who demonstrated foundational reading skills is plotted against the percentage of children who demonstrated foundational numeracy skills for a given country. The plotted values are distinguished by color to signify the region the data is from. Furthermore, the name of the country corresponding to a particular datapoint is displayed when hovered over. In the first visualization, the values are separated into two scatterplots to group the data by gender (Girls and Boys). In the second visualization, the values are separated into five scatterplots to group the data by wealth quintile (categorized by UNICEF as Poorest, Second, Middle, Fourth, or Richest).

Gender

• Across all the data, there is not an extremely noticeable difference between the percentage of girls with demonstrated numeracy/reading skills and the percentage of boys with demonstrated numeracy/reading skills.
• There is a positive trend between the percentage of children with numeracy skills and the percentage of children with reading skills. (If a country has a high percentage of children who have demonstrated reading skills, then the country likely has high percentage of children who have demonstrated numeracy skills.)
• Children aged 7 to 14 have high higher percentages of children with demonstrated numeracy/reading skills than children in grade 2/3.
• The Sub-Saharan Africa (SSA) region has the lowest percentages of children with demonstrated numeracy/reading skills across gender, whereas the Europe and Central Asia (ECA) and East Asia and the Pacific (EAP) regions seem to have the highest percentages of children with demonstrated numeracy/reading skills.
• The Latin America and the Caribbean (LAC) region has the least amount of data represented in this dataset.

Wealth

• The percentages of children with demonstrated numeracy/reading skills are higher among the wealthier quintiles.
• There is a positive trend between the percentage of children with numeracy skills and the percentage of children with reading skills. (If a country has a high percentage of children who have demonstrated reading skills, then the country likely has high percentage of children who have demonstrated numeracy skills.)
• Children aged 7 to 14 have high higher percentages of children with demonstrated numeracy/reading skills than children in grade 2/3.
• The Sub-Saharan Africa (SSA) region has the lowest percentages of children with demonstrated numeracy/reading skills across all wealth quintiles, whereas the Europe and Central Asia (ECA) and East Asia and the Pacific (EAP) regions seem to have the highest percentages of children with demonstrated numeracy/reading skills.
• The Latin America and the Caribbean (LAC) region has the least amount of data represented in this dataset.

Conclusion

Since data for both genders seemed fairly similar when comparing visualizations, we did not find a significant difference between the quality of education based on gender. However, we did find a significant difference between the quality of education based on wealth. Across all visualizations, members of the wealthier quintiles tended to be more educated than members of poorer quintiles. Through our visualizations, we discovered that the Sub-Saharan Africa (SSA) region tended to have the lowest quality of education, and the Europe and Central Asia (ECA) region tended to have the highest quality of education. Analyzing data based on grade-level, we furthermore discovered that as people grow older, they are less likely to attend/complete school. Recognizing this fact, to improve education overall, further effort is necessary to ensure children continue to attend/complete school at all grade-levels.