Speaking at the American Enterprise Institute recently, former Governor Asa Hutchinson shared his experience in bringing coding skills to students throughout the state of Arkansas. Declaring “coding is basic,” Gov. Hutchinson led the charge to engage teachers throughout the state. Through those teachers, opportunities to learn coding became available to students statewide. In Gov. Hutchinson’s view, becoming a state-level champion for computer science (CS) was essential to enabling each student in Arkansas to flourish in tomorrow’s economy.
The February 2025 event was called “Securing our Competitive Edge: Education Innovation for a Stronger America” and focused on the role of research, of which Gov. Hutchinson said, “innovation and research is critically important.” I attended this event, and afterward invited my colleague Shuchi Grover to reflect on the contributions of the National Science Foundation (NSF) to enabling large-scale integration of coding, computational thinking, and computer science into K-12 education.
Together we realized that the historic role of NSF in fostering K-12 learning opportunities is also a present day issue; building on CS successes, education now needs to prepare students for an AI-powered world. Reviewing the history of NSF with respect to fostering CS can garner lessons that are essential to preparing the next generation of innovators, workers, and leaders in national security. The kinds of questions that must be answered include:
- What can and should K-12 students be taught about what AI is and how to use it at each grade level?
- What pedagogies are appropriate for different age groups?
- How can CS and AI fit into an already over-packed curriculum?
- How do we prepare teachers?
- And how can we measure student learning and show progress?
Over the last two decades, the field has grappled with similar questions in the context of developing K-12 students’ skills in computer science, coding, and computational thinking as new topics of study in recognition of the pervasiveness of computing in everyday lives and every field of human endeavor. “Computer Science for All” became a nationwide movement, supported and buffeted by several research efforts that helped guide curriculum design, pedagogy, assessments, teacher preparation, and building district and state capacity in every corner of the country.
NSF played a central role in birthing and growing an entire new field of STEM learning in K-12. In 2014, STEM-C Partnerships: Computing Education for the 21st Century (STEM-CP: CE21), a program jointly funded by the NSF’s Directorate for Computer and Information Science and Engineering (CISE) and its Directorate for STEM education (EDU, previously called EHR), was launched to address both the need for advances in K-12 STEM education generally, as well as the need to include computer science education. As described in the NSF description of the STEM-C program, “STEM-C Partnerships adds a discipline-specific focal area on the teaching and learning of computing and computational thinking, a strong commitment to broadening participation in computing, an emphasis on in-service teacher professional development, and support for the implementation of computer science courses at the high school level.”
The STEM-C program subsequently morphed into STEM+C (STEM + Computing Partnerships), with a greater focus on K-12 computing education and integration into existing STEM classrooms. The program spurred many consequential research projects at the intersection of STEM, data science, and computer science, as observed in the NSF description of the program: “One expectation of the STEM+C program is that it will prepare students to confront the emerging challenges in computational and data-enabled science and engineering. Accordingly, the solicitation broadens the definition of computing to include computational science, data science, human computer interfaces, and cybersecurity.” In 2018, CSForALL: Research Practice Partnerships was launched with the explicit goals of building capacity in K-12 schools, districts, and state departments of education to offer CS as a new subject in K-12 education.
Here are examples of research that NSF funding enabled:
At Digital Promise, Jeremy, with Quinn Burke and others, received a grant (now completed) to work with schools in Talladega, AL, Iowa City, IL, and Indian Prairie, IL. At the onset, we learned from our school partners that while there are high school offerings, high school is too late to start. By that time, most students have “tuned out” from computer science. Also, the curriculum is packed with requirements, so adding courses in K-8 is often not possible. Thus, we worked with three very different districts to develop innovative ways to integrate CS into existing K-8 lessons throughout the school year, and to measure the progress. The lessons we learned enabled students in these districts to have many more opportunities to learn CS, but also through this research we developed a toolkit that now is being used by other districts nationally.
For her part, Shuchi’s efforts in K-12 CS education research have been devoted to the design of curricular experiences, examining innovative pedagogies, and studying effective assessment strategies both in CS classrooms as well as STEM+Computing settings through several NSF-funded research projects. Her dissertation research at Stanford promulgated the idea of a “system of assessments” to provide a holistic understanding of the development of programming skills, as well students’ interests and attitudes toward CS. Her research over the last 15 years includes the design of principled assessments of computational thinking for the high school Exploring Computer Science curriculum, examining how students collaborate to construct computational models in integrated science+computing settings, developing an assessments hub, and teacher professional development models for promoting formative assessment in CS classrooms. Among her contributions to understanding pedagogies for teaching programming is the idea of introducing CS concepts that middle school students often find difficult to grasp through games and relatable non-programming activities before encountering them in coding, and (in collaboration with Digital Promise) how to integrate computational thinking in pre-K learners’ early STEM experiences through bridging home and school activities. Today, her research extends to examining how we can build on those learnings to develop curricular experiences for high school students in emerging topics in K-12 CS such as AI and machine learning, cybersecurity, Internet of Things, and distributed computing.
Building on her research and that of others, we now have AP CS Principles, a new Advanced Placement course in Computer Science (launched in 2016) aimed at attracting more high school students to computer science and related fields.
And through other funding streams from NSF and the efforts of a large and growing community of K-12 CS researchers, our nation now has well-researched curricula that are designed based on findings of how to teach computational thinking and programming at various grade levels. We have age-appropriate programming environments and tools that are used to teach these new skills. We have knowledge of pedagogies of how to develop computational thinking skills not only in CS classrooms, but also integrated with math, science, engineering, social studies and other subjects. We have models for teacher preparation. All of this educational infrastructure has been built on a foundation of research, much of it funded by the NSF.
As we stand on the precipice of a new educational need fueled by the rapid rise of AI, we look to research once again to help guide the way forward.
Jeremy Roschelle is Executive Director of Learning Sciences Research at Digital Promise and a Fellow of the International Society of the Learning Sciences.
Shuchi Grover is a computer scientist and learning scientist based in Austin, TX. She is currently Director, AI & Education Research at Looking Glass Ventures. She advises national and global efforts on AI education, as well as AI in education in K-12 schools, in addition to leading NSF-funded research efforts on these topics.