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Virginia Levels Up in Data Science Education

Leaders from the industry, education, and nonprofit spheres gathered to ensure Virginia’s students develop into the innovators of tomorrow.

Dr. Michelle DeLoach presenting as part of the K-12 Data Science & Literacy Panel.

Rarely does a state build a new high school course from scratch, let alone an entire content area.

Virginia was already well on its way to becoming a national leader on Data Science and Literacy. But on December 3, the state’s K-12 leaders decided to take things a step further, collaborating with The Virginia Society for Technology in Education (VSTE) to gather K-12, higher education, and business leaders for a conversation focused on guiding Virginia’s students on their journeys from the classroom to their future careers.

The Data Science Career Pathways Summit, hosted by VSTE as a part of their Annual Conference in Roanoke, Virginia brought these leaders from many different spheres of influence together to focus on one shared goal: empowering Virginia’s students with the data literacy skills and data science education they will need to succeed in the 21st-century workforce.

New commitments to accelerate K-12 Data Science

Over 50 new commitments, suggestions and ideas were gathered at the Summit to advance statewide work in K-12 Data Science education. These commitments ranged from Laurel Ridge Community College agreeing to add Data Science to the teacher CS Generalist Certificate to the expansion of dual-credit partnerships with the community college system.

Equipping the future workforce

The summit opened with a welcome from Dr. Lisa Coons, Superintendent of Schools, Virginia Department of Education. Rod Carnill, Executive Director of VSTE, connected the purpose of the Summit to prepare the workforce needed now and in the near future to the VA 2030 Blueprint.

The workforce and industry panel then tackled the question of which knowledge, skillsets and dispositions related to data are needed for employees’ success. The workforce panel was stacked with panelists from every industry touched by data science, from IBM to NASA. Many speakers focused on the need to teach students data science in order to keep the US workforce competitive:

Ted Hallum of IBM shared, “If we talk about keeping the US competitive, for every one machine learning or data scientist the US produces, China produces nine…If we want to remain competitive over the next five, ten, 15, 20 years, we need to radically optimize our pipeline for people to learn these skills.”

Henry R. (“Speaker”) Pollard, V. moderates the Business & Industry Workforce Panel.

Several panelists pointed out that these skills must be taught long before an employee ever steps into the office, especially with the advent of AI.

Angela Rizzi of NASA shared, “We need to understand this doesn’t start in college, and it doesn’t start in high school — it starts much earlier. We need to build capacity and interest amongst our earliest learners.”
Joshua Jones, CEO of Quanthub, shared, “[AI] Prompt engineering is a data skill, and not enough folks are talking about this or are afraid to do so. You need to understand data privacy, data fluency, and how the tool works to do that well.”

Dr. Padhu Seshaiyer moderates the Higher Education panel.

Paving a data science pathway to success, no matter the method

This was followed by the higher education panel led by Dr. Padhu Seshaiyer from George Mason University, VA that included faculty from 2-year and 4-year universities (public and private) across the state including University of Virginia, Old Dominion University, Longwood University, Shenandoah University and Laurel Ridge Community College. Dr. Seshaiyer currently serves as the higher education appointee to both the VA STEM Education Advisory Board and the VA Workforce Development Board to the Office of the Governor of Virginia. The panel focused on questions surrounding higher education pathways in data science around degree programs, majors, minors, digital badging, microcredentials and dual-enrollment as well as aligning these programs to the workforce needs. The questions included:

  • What should all students know about data science by the end of high school, regardless of career or postsecondary path?

  • What prerequisite subjects will set students up for success in university data science programs?

  • What are the advantages of getting a formal data science degree?

  • How would you advise a student to choose a particular data science program or pathway?

Speakers focused on the overall necessity of data science education, for all students.

Dr. Ralph Wojtowicz, Director of the Division of Applied Technology and Associate Professor of Mathematics and Shenandoah University, shared, “Why is data science important to study at the undergraduate level? Without data, there is no science. Without data, there is no business.”
Dr. Brian Wright, Associate Professor and Director of Undergraduate Programs with UVA’s School of Data Science, shared, “We need to abandon the idea that Data Science is fundamentally derivative of other disciplines. Other disciplines do not caveat their study as being footnotes in other fields.”

Empowering tomorrow’s leaders today

Dr. Deb Crawford moderates the K-12 Data Science & Literacy Panel.

The summit closed with a panel on K-12 Data Science and Literacy led by Dr. Deb Crawford, VDOE Data Science Course Development & Implementation Lead. Panelists from school districts across the state emphasized the need to begin teaching students data literacy skills early and often, highlighting the fact that though many students might not go into STEM, all would use data.

A graph used during the K-12 Data Science & Literacy Panel highlighting the need for data literacy

Panelists also noted that data literacy and data science education are not easily taught in one singular course and need to be infused across subjects in order to reach all students at the beginning of their educational journeys. This may require changing the image most students conjure when they think of data science.

As IBM’s Ted Hallum shared, many young students count themselves out of math early on because they’re intimidated by the language of math and fail to see themselves in the unapproachable formulas and hypothetical questions. However, once they can see themselves and their lives reflected in the math, in the data, they begin to see its power:

“I listened to the lecture, I read the textbook, the concept was totally alien to me… and then when we did an applied exercise and wrote it in R, I finally understood what the formula in the textbook was trying to express….I hope you’ll entertain the idea of taking the math you’re familiar with, embracing a coding-language, and integrating those two things together — because out in the workforce, that’s how it’s going to play out in the real world. The sooner [students] can gain experiences with that, the better.”

Chris Dovi, current Virginia STEM Advisory Board Appointee and Co-Founder of CodeVA, shared during a lunch talk, “As a former journalist, I can tell you that data science education protects democracy. We need a data literate population that understands how to interpret statistics they see in the news and on social media. We need people to ask the right questions and to understand how our changing world works.”

As Executive Director of CodeVA, Chris Dovi is now helping amplify the work created by the VDOE Data Science Course Development & Implementation Taskforce and making it accessible to other states, with samples of content from Virginia’s OER portal modeled from resources created by the VDOE Data Science taskforce.

Statewide progress in Virginia outpaces the country

Few states have done as much as Virginia to ensure students are prepared for the data-driven 21st century.

A new high school course developed from scratch; statewide educator training cohorts; modernized content standards in K-12; and students placing in Ivy-league institutions with projects submitted from their new coursework. The list of achievements is long and continues to grow as Virginia K-12 Data Science sets out to scale to additional schools.

How did Virginia manage to accomplish so much so quickly?

In 2020, the Virginia Department of Education (VDOE) Mathematics leadership organized a Data Science course development team to write the Virginia Standards of Learning for a high school Data Science course. This Phase 1 team of K-12 and higher education representatives began organizing conversations to imagine a new type of high school mathematics experience for students, one which would center data analysis, technology, computing, and core mathematics learning together in one joint program — reflecting how these disciplines are utilized in the modern workforce.

“In creating the course, we have been intentional in employing project-based learning combined with an instructional philosophy that moves beyond the traditional approach of ‘here is the mathematics, statistics or computing, go solve the problem’ to ‘here is the societal problem or dataset, let us find innovative data science approaches motivated by mathematical foundations, statistical thinking or computational thinking to solve it’” — Dr. Padhu Seshaiyer, Professor of Mathematics and Director at George Mason University
“Students rarely have an opportunity to explore problems relevant to them or their communities. We are making that the norm in data science courses.” — Dr. Deborah Crawford, Mathematics Supervisor, Frederick County Public Schools

The Virginia Data Science State Standards and content unit resources were developed entirely from scratch by a diverse team, including K-12 district leaders and teachers, practicing data scientists from industry, six higher education institutions, CTE reps, and the Virginia Department of Education mathematics team. The team developed four curriculum modules in 2021 which were field tested in the Year 1 pilot in 2022–2023, following the approval of the DS state standards in April of 2022.

The Data Science Leads team revised the unit resources in 2023, based on feedback from the Year 1 pilot teachers through VDOE surveys and data science teacher focus groups. Four curricular modules, including over 310 vetted resources, video guides produced in-house, and locally sourced datasets and data talks and project guidelines and rubric for student choice in problem statements were created and shared with teachers on a Data Science Hub in a Canvas LMS through Virtual VA. Teachers drove much of this content development, working late hours and countless weekends — far beyond their normal job descriptions.

“The Data Science Standards of Learning in Virginia were developed by a diverse group consisting of Virginia educators from higher education and K-12 along with input from representatives from business and industry across the Commonwealth. The varied perspectives brought to the table by each member of this group resulted in a rich set of standards that address the future needs of students as they leave K-12 education and enter college or the workforce. The skills needed to be successful in today’s data-driven environment are different than the skills needed just ten years ago. Students must be flexible learners who can represent data and analyze information in order to recognize patterns and solve problems.” — Tina Mazzcane, fmr. Virginia Department of Education, Mathematics Coordinator

The Data Science Leads team designed two VDOE Data Science 3-day institutes in 2022 and 2023 to provide professional learning for new Data Science teachers and key insights into the data literacy skillset. Partners providing training included NASA, Amazon: AWS, CodeVA, and NC State InSTEP. Teachers from the first pilot year are now mentoring the Year 2 pilot teachers, and this network of data science high school educators is fueling the acceleration of resource creation and coaching statewide.

The Data Science Career Pathways Summit connected district leaders, teachers, community college and university professors with community partners from business and industry. The Year 2 pilot teachers are forming community partnerships where students work with a partner on a problem statement from a real data set provided by the partner. One example comes from Norfolk Airport Authority who asked students to use their data to create a cost-effective model that allocates every incoming flight at Norfolk International Airport to a specific gate. Data science students themselves are reaching out to potential community partners based on their interests.

eMediaVA Video Series on Virginia K-12 Data Science Pilot

The VA Data Science course kicked off their pilot year in the 2022–2023 school year, with nineteen high schools piloting the program statewide — and it went better than expected. Some students entered their projects in regional and state-wide science and engineering fairs with great success. Student teams from the pilot took first place in Engineering, first place in Mathematics, and third place in Computer Science at the JMU Science & Engineering Fair. Other students at Frederick County Public Schools leveraged data science and computing projects developed in the state’s pre-pilot as supplement materials on college applications, landing them coveted spots at the nation’s top universities including John Hopkins University, Dartmouth University, and the University of Virginia.

The data science pilot has since expanded to about 50 teachers from 23 school divisions and independent schools this school year and is on track to reach 75 teachers in the 2024–2025 school year.

Last August, the state capitalized on this momentum by infusing data literacy throughout their updated mathematics standards of learning for K-12 curriculum, building upon the course state standards released in April 2022. Now, students as early as K-5 will begin learning more robust foundations of data intuition and literacy — guaranteeing high school isn’t the first time these students encounter data learning.

Virginia’s work has been nothing short of heroic and has generated national interest in the subject. Many in the state were working extra hours or on volunteer basis to make 21st century mathematics opportunities that prepare students for today’s realities of career and daily life. But more action is needed nationally to ensure data literacy can be the norm, rather than the exception.

Are you an educator in Virginia eager to start a data science program in your school? Contact Keisha Tennessee, VDOE CS Coordinator,, or Dr. Deb Crawford for more information.

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