Table of Contents
Advocacy Lesson Plan A and Artifacts
Advocacy Lesson Plan B and Artifacts
My students consistently spoke, wrote, and thought about a variety of important issues, but I highlight their work speaking, writing, and thinking about educational inequality in this section. As a class, we investigated many statistical phenomena through the lens of educational inequality in DC. Since educational inequality is so stark in DC, and my students live in such a segregated community, the statistics unit seemed like a good opportunity for students to investigate this phenomena themselves. Students used statistics and graphs to examine inequality within DC and the value of a college education.
By discussing this important issue by having students analyze the data themselves, students not only learned about an important justice issue in their own community but also felt empowered to discover the evidence for themselves. Many students commented that these conversations were some of their favorite lessons because they felt like they were able to bring both their own experience and skills to the conversation in class.
We had many rigorous class discussions about the value of education and the impact of educational inequity through multiple math lessons throughout the year. Students would typically discuss their thoughts and findings in small groups, as pictured above, prior to turning to a full-class discussion. Prior to doing our investigation into educational inequity in DC, students still generally thought that education was important. Students typically cited that education helps you get a good job, helps you help out your kids, and teaches you important life-skills. Some other students came in with the preconceived notion that teachers push education a bit too much, and that the payoff of an education is not that great, as there are many wealthy people without a college education. Many students pointed out that college is very expensive, and while a high school diploma pays off, college may be a scam.
We then looked into the statistics and numbers as a class about what educational inequity looks like in DC and what the monetary value of an education is. I did not want to push my own views on the students, especially since many students had the idea that teachers specifically were biased about the value of an education. Instead, I encouraged them to use their mathematical skills to draw conclusions for themselves. As we started to do the math about how much more money people tend to make with a college education, and how much this money translates over the course of a year, more students started to argue that at least monetarily, a college education pays off. Students also were surprised to find out that educational inequity in DC was so stark, and speculated that wealthier schools are probably better at providing an education and preparing their students for college. Many students were also convinced by their classmates’ unique arguments that education helps you help your children with reading, for example, and has value beyond the monetary value of an education.
The class discussions that stemmed from the statistical investigation of education and educational inequity were very rich. They were most powerful because students felt like they were discovering the facts about educational inequity and the value of a college education themselves, and that they were given the freedom to draw their own conclusions based upon the facts. Below I have attached a few of the explicit lessons on educational inequity and the value of education, as well as some student work samples. We always had small group and full class discussions based upon what students discovered.
Lesson Plan on Educational Inequity A
The first lesson I planned to address educational inequity is linked below:
Lesson Plan Educational Inequity A (Click here to zoom in)
Handouts Educational Inequity A (Click here to zoom in)
As can be seen in the lesson plan above, the conversation about educational inequity was driven through two different lenses. At the beginning of the lesson, students will use their graph interpretation skills to analyze the differences in educational attainment among different wards in DC. This initial class-wide conversation will give students the opportunity to reflect on what inequalities they notice and if they believe these inequalities matter. In the main body of the lesson, students will learn about finding mean and median through analyzing real-world data on income by education. This allows students to use their mathematical skills to answer the question “does education matter?”. After doing this analysis, we revisit the question from the beginning of the lesson again about what the consequences of educational inequity are for a community.
Lesson Introduction: Reflections on Inequity Data
Students investigated graphs on educational inequity in DC. We discussed the implications of this inequity as a class and reflected on students’ own personal attitudes towards education.
The student above noted, for example, that Ward 7 (the ward our school is in) had higher educational attainment than Ward 8. They also noted that Ward 7 had low educational attainment compared with most of the city. By having students analyze the data themselves, they were able to pick up on nuance such as this. This student already had the opinion that education was important because it helps people get good jobs. When there was debate during class on whether or not education matters, this student was quick to point out that if fewer people in Ward 7 have bachelor’s degrees, then fewer people have good jobs.
This student also noticed that Ward 7 was low in educational attainment compared to the rest of the city. During the class discussion, they noted that the education gap not only existed for college, but also for high school degrees. They believed that education was important because it can help get you somewhere in life.
This student noticed that generally, many more people have high school degrees than college degrees. They also noticed that Ward 7 had higher education than Ward 8, wanting to return the class conversation to what Ward 7 was doing well instead of what it was doing poorly. Like many of their classmates, this student believed having a good education was essential for getting a good job. They said that getting a high school diploma let you get better jobs than dropping out of high school, as they saw with some of their older siblings. Many of their classmates agreed, and said it was annoying that many teachers focused on saying they should go to college when going to high school also helps.
This student noticed that Ward 3 had the highest educational attainment (where wealthy white people generally live in DC), and Ward 8 had the lowest educational attainment. They believed that education was the key to “everything in life”, and therefore was important. They said that an education was important for more than just getting a good job.
Students were very successful on their own noticing from the data where there were education gaps in DC. They had a robust class discussion on why exactly they thought education mattered and continuing to find new layers of where there were gaps in DC. Students built on each other by noticing the different gaps in high school versus college education and between different wards.
Mean and Median Calculations
Having previously relied on data summarized by others, students summarized their own data using median and mean. They re-discovered through their own mathematical analysis that more educated people tend to earn more than less educated people. While many students had this intuitive notion, this idea was largely based on what other adults had told them, not their own mathematical discoveries. Some students during the class discussion of the educational inequality in DC were skeptical that an education got you a much better job, but perhaps only a marginally better job.
First, as a class, I taught students how the government collects education data (random survey of 4 million Americans each year), and then told them that I picked out 5 random data points from people with a college degree and 5 random data points for people without a high school degree. We calculated the mean salary for people with a college degree as a class to provide a reference point for when students did the same calculation for those without a high school degree. These calculations are pictured above.
Students then did the calculations on their own for people without a high school degree. They were surprised that the difference was so large (over $100,000), and said that the value of an education in terms of money was very large. We then went over the “real data” on the differences in average salaries as an exercise in how a small sample can skew the results. I also then led the class into a small aside of why this means that even if people use numbers, a healthy dose of skepticism about those numbers is always useful, as people can use tricks like a small, biased sample to tell the story that they want.
Then, as pictured both above and below, students calculated the median income for both those with a college degree and those without a high school education. Students then discussed that no matter how exactly you calculated the average, people with a college education earned substantially more money than people without a high school degree.
After doing our calculations, we returned to the introductory discussion about educational inequity in DC. Students came to the consensus that there were more economic consequences to not having an education than they were initially aware, and this had an impact on the community. Students were interested in having more conversations about educational inequity in the future.
Lesson Plan on Educational Inequity B
The lesson students did the next day on educational inequity is linked below:
Lesson Plan Educational Inequity B (Click here to zoom in)
Handouts Educational Inequity B (click here to zoom in)
In this lesson, students use their mathematical knowledge to make predictions about exactly how many more people had a certain education and/or income in different wards of DC. Rather than simply look at the percentages, students calculated and discussed how many more thousands of people had more education in different wards. They compared Ward 7 (the ward Kelly Miller is in) with Ward 3 (the wealthiest ward in DC).
Students analyzed just how many more people were more educated and making more money in other parts of the city. Students were able to use their own mathematical knowledge and analysis to discover this inequity.
As pictured above, students used their knowledge of proportions and ratios in order to calculate how many more thousands of people in Ward 3 had college degrees than Ward 7. We then discussed at the class what the consequences of this may be. Some students noted that more parents would have good jobs if they had college degrees. When I challenged students with the idea that people with more education may be able to open up more businesses, students had varying levels of agreement. Initially students were split, but then some students pointed out that starting a business cost money, and if education gives you more money, education makes it easier to start a business.
The student above noted that having more education meant that people could get better jobs. The student above specifically noted that more people could be what they want to be, and speculated that more people may be happy in places with more college degrees than without because of this. This was not initially where I had predicted the conversation would go, but it added a nice layer to the class discussion that pushed many peoples’ thinking.
Students overall thought that the educational inequity gap seemed more “real”, as the consequence was thousands of more people with better-paying jobs. Students were interested in improving the education in their community in order to change these numbers.
Revisiting Educational Income Inequality
We revisted the concept of educational inequity later in a warm-up, as pictured below. Students analyzed the average weekly earnings by education. Students also calculated out for themselves what the long-term loss of earnings would be from being less educated.
The student above noted that generally, income increases as education increases. They also argued that education was important because it gives you the tools to manage money. This student, like many others, also thought that the income difference of $32,000 a year for having a college education versus no high school diploma translated to a very substantial economic consequence of education.
The student above argued that an education lets you help your kids and be a good parent, which added a unique dimension to the class discussion. Once this student brought it up, many other students agreed that being able to help your child with their homework is a great skill to have and another benefit of education that is not noted by a simple income differential.
By discovering the value of a college education through the power of mathematics, students were empowered to discover their own truth about the world. They were not simply hearing a teacher tell them the value of a college education, but they were discovering it themselves. Furthermore, students were able to have deep conversations about educational inequity in their own communities by investigating the impacts of educational inequity in DC. Students were able to apply their math skills in a meaningful, real-world way. While students may not always remember all statistics terminology, they will remember how they were able to use their own skills and knowledge to discover injustices in their own communities. As a result of these many statistical investigations into education’s value and educational inequality, my students as well equipped to speak, think, write, and listen about advocacy issues in the future.
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