This spring, a few curious high schoolers gathered around Peter Magee’s computer as the AP biology teacher demonstrated what he was learning as a student in an online section of Statistical Programming in R—an introductory coding course offered to undergraduate and graduate data science students at AU.
As Magee, a 12-year veteran of Columbia Heights Education Campus and the school’s science department chair, shared a recreation of a graph from a Financial Times article and the layered lines of R code that had rendered the plot, an observant student piped up. “God bless him, [he] started pointing out the subtle variations in the axes and how they were presented in my graph versus in the Financial Times graph,” Magee says. “As a teacher, that attention to detail made me gush. Students making their own meaning of something so often helps me reshape my own understanding.”
The constructive criticism presented an early example of the value he hoped to extract from his semester at AU. Magee began the term without a background in coding and with a limited grasp of the data cleaning, modeling, and visualization capabilities of R, the open-source statistical programming language. He wrapped the class with a solid understanding of the basics and an excitement about infusing data science into his teaching and evaluation methods.
Magee is among 20 District of Columbia Public Schools (DCPS) high school STEM teachers who have taken R programming at no cost through a partnership launched in 2021 with the School of Public Affairs’ Center for Data Science. The program, which also offered its second two-week professional development workshop for DCPS educators on basic data science concepts this summer, is funded by the DC Space Grant Consortium, of which AU has been the lead institution for more than 20 years. The consortium provides funding for student research opportunities—including for 40 Eagles in the last academic year—and grants for projects at DC colleges and universities.
NASA space grant consortiums, of which there are 50 in the US, strive to provide meaningful research opportunities, prepare the future NASA workforce, and engage people in the agency’s missions, needs, and goals. With an ever-expanding pool of data to collect and analyze, data science is one of those needs, says Nate Harshman, AU physics professor and director of the DC NASA Space Grant Consortium.
“A lot of students don’t even understand that this is a career path. In the future, there is going to be even more demand for data science, including for people who don’t have advanced degrees in it,” he says. “[The partnership] can provide an advantage to students in sharing what opportunities are available, and we’re hoping it can be a big boost in establishing a pipeline from DC into these great jobs at NASA.”
Among those who’ve championed the partnership are Maria Barouti, mathematics and statistics professor and associate director of data science programs; Jeff Gill, distinguished professor in the Department of Goverment in SPA and the Department of Mathematics and Statistics in the College of Arts and Sciences and the inaugural director of the Center for Data Science; Elizabeth Malloy, mathematics and statistics professor and director of data science programs at AU; and mathematics and statistics professor James Dickens, for whom the partnership is personal.
Before he joined the CAS faculty, Dickens worked as a DCPS educator and administrator for more than 30 years—many of them at Anacostia High School in Southeast, where he taught algebra, geometry, and the school’s first-ever AP calculus class. A product of historic Spingarn High School in Northeast, which closed in 2013, Dickens called his early teaching experience a “Welcome Back, Kotter kind of thing, reaching back and giving back and being involved in a process that I was a product of, which was very exciting.”
Serving today as an instructor and point of contact for DCPS teachers learning R is another reminder of how his career has come full circle.
“Teaching at a university after having had a successful career in secondary education is an accomplishment that was afforded to me as a consequence of the help of others,” says Dickens, who was pulled into the partnership by former AU professor Jane Wall. “It is a special opportunity to then offer that same support to people who are coming behind you.”
Adapting to pandemic-fueled changes in education has presented tremendous challenges over the last two years, says Gabriel Cartagena, DCPS director of content and curriculum for secondary math. But it’s also created tremendous opportunities for new learning initiatives—data science included.
“Data is all around us, and we see data science as one of the foundational learning experiences that we want all students to see by the time they graduate high school,” he says. “Data science lends itself to our mission of making sure that students are ready to be contributing members to society, [including] being responsible consumers of data.”
The weaving of data science concepts into DCPS classes across multiple disciplines will be gradual, Cartagena says, but partnerships like AU’s will go a long way in ensuring faculty feel comfortable and confident in both teaching data science and selling it to students.
Maria McLemore, an 11th grade math and special education teacher at DC’s Cardozo Education Campus, is well versed in this pitch. She lives for moments when a student finally grasps a difficult algebra, trigonometry, or statistics concept or applies it to something in the real world, because she knows they’re a product of mutual buy-in. During her 11 years in the classroom, she’s learned that a critical barrier to mastering math is preconceived notions about it.
“If you build it up in your mind as something that’s too hard, then it’s going to be hard,” McLemore says. “I try to inspire my students to have an open mind about [math] and just let them know that, ‘If you work with me, I can help you understand. You might even like it.’”
Last fall, in an online section of Professor Malcolm Barrett’s R programming class at AU, McLemore took a page out of her own book as she waded through the error messages and syntax issues that are synonymous with learning a new programming language. She emerged with at least a few ideas about how to visualize math and statistics concepts for students—and how to continue her efforts to expose young people of color to STEM career opportunities.
“I’m driven to do that because a lot of our scholars have made up their minds that, ‘I can’t do math, and as a result, I’m not going to major or work in STEM,’” she says. “We have to break that stigma and try to encourage them and expose them so that they can know that this is both possible and accessible.”