Why CT Belongs at the Center of Students’ Education
Ask 10 education leaders what they think is the key to a successful educational future for our young people, and you are likely to get 10 different responses – often, each as valid and worth pursuing as the next. Between a growing, but extremely uneven, experience of AI and emerging technology in classrooms, the push for more learner-centered practices, and shifting employer demands, it’s hard to imagine how to answer such a multitude of urgent questions. Of course, when several of these questions can be addressed at once, real progress becomes possible, and one promising shift has begun to emerge as a viable path forward.
There is growing enthusiasm for durable skills – a set of aptitudes like creativity, communication, resilience, and others that are thought to be inherently relevant, no matter the shifts in technical skills as we barrel through technological revolution after technological revolution. Major industry projections highlight durable skills as areas of emphasis for workforce development now and into the future. The World Economic Forum’s 2025 Future of Jobs Report lists analytical thinking, creative thinking, resilience, flexibility, and agility alongside technological literacy and AI & big data as key skills to focus on now and into the future.
Alongside these skills, we believe that there is a gap in what most people think of as durable skills, and that gap is in the shape of computational thinking (CT). Here’s why we see CT as a critical piece of young people’s education now and into the future.
1. Computational Thinking: a “Foundational Skill” for all Students
Computational thinking (CT) is not a new concept, and is increasingly being emphasized in places like New York City, Michigan, and Pennsylvania. Despite this, it is still seemingly left out of a lot of conversations around education. Briefly put, CT refers to a set of strategic thought processes that underlie classic computing and includes concepts like decomposition, abstraction, pattern recognition, and algorithmic thinking. Taken as a whole, they represent a set of mental tools that can help us to identify, understand, and solve problems.
These skills are not losing relevance anytime soon. As mentioned, the Future of Jobs report mentions AI & big data and technological literacy as key skills. And while we believe in continued investment in CS education, even those who disagree would find plenty to like in CT. These skills not only empower students with employable skills, but skills for navigating technology of all kinds, across contexts. Ultimately, CT skills signal to employers that applicants can learn and solve problems, and that they have the context to understand how to do so in both high- and low-tech environments.
Julie Evans, the CEO of Project Tomorrow, which helps implement CT education in schools, sums up the value that CT is providing to students and teachers: “Our teachers tell us that because of emphasizing CT in their classrooms, their students are stronger critical thinkers and problem solvers and have a better understanding of their own metacognition and learning processes. And that as teachers they are more confident in their abilities to transform instruction to meet their students’ needs. I believe that CT fluency is the new foundational skill for both teachers and students.”
2. Preparing Learners to Make Sense of AI, Not Just Adapt to It
As referenced by Evans, CT also helps us to be more critical consumers of existing and emerging technologies like machine learning algorithms. For example, CT-focused grantees of the Robin Hood Learning + Tech Fund, co-founded by the Siegel Family Endowment and Overdeck Family Foundation, have consistently reported significant gains in students’ AI literacy as a result of CT skills.
The relationship between CT and AI is a particularly impactful one because when a student understands the concepts that make up CT, they can ask better questions of AI systems. Even something as simple as spending time working with AI and learning how to get the outputs you’re looking for is enhanced by a foundation in CT: algorithmic thinking and pattern recognition, for example, lend key insights into how and why a certain output may have been generated and why different approaches to prompting yield similar or different results over repeated attempts.
As Lianne Remen, the Program Officer for Computational Thinking & Learning at the Learning + Tech Fund, puts it: “As technology automates more of the way we work, the critical advantage will be in computational thinking: knowing how to form strong prompts, spot errors, and judge the quality of AI-generated work. Students need evergreen computational thinking skills to guide technology with sophistication and lead in an AI-powered world.”
3. Computational Thinking Boosts Student Performance Across Subjects
This brings us back to another important point: that CT boosts student performance across subjects. In Learning + Tech Fund reporting, over 90% of teachers also reported that CT helped improve outcomes in student learning in computer science, STEM equity, and, crucially, core school subjects. CT not being a standalone classroom subject in and of itself, it shows up across subjects by reinforcing the metacognitive processes that help students better understand how they approach their work. For this reason, support for CT does not need to be “in competition” with any other subjects or movements to boost them. Instead, it should be seen as complementary.
Indeed, it has already proven useful for many teachers, including at the primary school level where many teachers are in general education rather than subject-specific. The CUNY Computing Integrated Teacher Education (CITE) initiative, a system-wide project which aims to instruct all teaching candidates in computing education across instructional subjects, exemplifies this approach. Sara Vogel, the Director of CITE, speaks to the universality of CT for those teachers of younger students: “Early childhood education faculty…are preparing future teachers to use the language of CT to notice and support children’s problem-solving – to help learners decompose big problems into steps, to notice patterns and debug challenges. They guide teachers to create playful classrooms where learners can use CT strategies and computing tools to express themselves through digital storytelling, reinforcing early literacy and numeracy.”
Students are also recognizing for themselves the benefits: in a survey of over 1,900 Project Tomorrow students in K-8 in Michigan, 90% responded that they believe it is important for all students to learn about CT concepts in school.
Moving Computational Thinking Forward this CSEdWeek
Knowing this, we can’t afford not to invest in CT. Tunisia Mitchell, Interim Acting Executive Director of Computer Science Education in the Office of Student Pathways at NYC Public Schools, who engages regularly with employer partners, makes this clear: “Computational thinking remains one of the most durable skills we can give our students; employers tell us they are looking for people who can communicate, think critically, solve problems creatively, and learn through iteration – preparing them to lead and become producers versus only following and becoming consumers, in an AI-powered world.”
Few subjects span these goals like computational thinking, and for that reason we see it as a key durable skill that every student should develop. So, how do we meet the moment? And where can we make meaningful change while acknowledging the difficult nature of doing so amidst the critical mass of existing change efforts? As we mark #CSEdWeek and look toward 2026, here are several considerations for the field:
- Support the gaps in the infrastructure. Widespread adoption requires addressing real challenges: sustained professional learning and funding for it; limited instructional time; the need to build administrator, SEA, and LEA buy-in; and the reality that educators are experiencing unprecedented levels of burnout. Any meaningful shift must account for these pressures.
- Integrate the movements. Siegel’s vision for the future of education is one in which learner-centered education, responsible edtech research & development, and computing education all work together to ensure that young people have everything they need to durably navigate their education. Further attention can be paid to how to increase collaboration amongst complementary movements that have previously been treated as parallel at best.
- Use influence to institutionalize CT. We and other funders and influential voices should support projects that help institutionalize CT, for example NYC Public Schools’ CS4All program, with its explicit callout of CT exemplifying the melding of CT and CS, and the vision for CS4All 2.0; the CUNY CITE program, preparing future teachers to understand and implement CT concepts; or Project Tomorrow, integrating CT through state- and district-level partnerships.
By making a clear case for why this matters to the broader durable skills and learner-centered movements, we will be ensuring that our young people are set up to critically understand and shape emerging tech for a long time to come.
This piece was authored by Evan Trout, Grantmaking Manager at Siegel Family Endowment.
