Introduction
STEM—science, technology, engineering, and math—is more than a set of school subjects. For children and teens across the U.S., it’s a pathway to understanding how the world works—and how to change it. In our previous blog, we explored how the U.K. is approaching STEM education for learners aged 3 to 18 (link: https://www.whalesbot.ai/blog/stem-in-uk-schools-are-we-giving-kids-what-they-need). This time, we turn to the United States—a country where education is shaped not by one national curriculum, but by fifty different state systems. Despite this complexity, one thing is clear: STEM is a national priority.
From early math games in preschool to learning how to code robots using real tools, American students are being introduced to STEM earlier than ever. Today, for some children as young as five, pathways into STEM begin with exploring block coding websites and coding robots at home, in clubs, or in afterschool programs. These aren’t just toys—they’re tools that help kids build logic, problem-solving skills, and confidence. This blog explores how learners aged 3–18 engage with STEM across the U.S.—highlighting state-level differences, the rise of AI in education, and the role of hands-on tools. We’ll also look at how families, educators, and companies like WhalesBot are helping shape a new generation of tech-savvy problem solvers.
Why Early STEM Matters
Research shows that early exposure to STEM builds creativity, critical thinking, and long-term academic success. Even simple activities—like stacking blocks, pouring water, or measuring flour—help young children develop logic, observation, and spatial awareness.
For learners aged 3 to 5, STEM often begins with sensory play and guided discovery. In some preschools and home settings, children interact with screen-free coding robots, explore basic shapes and patterns, and experiment with simple cause-and-effect tasks. These aren’t just games—they’re early steps in learning to think logically. Between ages 5 and 11, during elementary school, students begin to engage with more structured STEM learning. In states that follow the Next Generation Science Standards (NGSS), children are encouraged to investigate questions, design small experiments, and build basic models. Additionally, some integrate block coding websites and beginner robotics kits to introduce sequencing, algorithms, and digital logic. These tools lay the foundation for deeper exploration later on. From ages 11 to 18, students encounter more advanced STEM content—including algebra, general science, computing, and engineering principles. Some states require computer science in middle or high school, while others offer it as an elective. Students might join robotics clubs, build with programmable kits, or explore beginner-level AI using tools like gesture sensors, voice control, or vision-based robots. These experiences teach students not only how to code a robot, but how smart systems interact with the world.
As robotics and programming become more common in classrooms, many educators are beginning to take the next step: introducing artificial intelligence into student learning.
The Rise of AI in U.S. Classrooms: Early Steps and Real Potential
As artificial intelligence becomes a central part of modern life, educators across the U.S. are taking early steps to introduce AI concepts into student learning. While there is no national curriculum, many states and districts have begun experimenting with AI instruction through electives and enrichment programs.
In states like California, Virginia, and Massachusetts, pilot programs are embedding AI into technology and data science classes. Students explore tools like Teachable Machine to train image or sound classifiers, or design basic chatbots using voice inputs. In some classrooms, AI is integrated into robotics, allowing students to build systems that respond to sensor data, gestures, or visual recognition.
To support this movement, national initiatives such as AI4K12 have outlined key learning goals—covering perception, representation & reasoning, learning, interaction, and societal impact. These frameworks help educators adapt AI content to different age groups and teaching contexts.
While still in its early stages, AI education is gaining traction. Across classrooms, afterschool labs, and informal programs, students are beginning to engage with machine learning, data-driven thinking, and the ethical questions behind smart technology. These early explorations are building the foundation for a more AI-literate generation. But as AI and robotics become more integrated into classrooms, the question of who actually gets to participate becomes even more urgent.
Equity Gaps in STEM: Who Gets to Learn and Who’s Left Out
Access to STEM education in the U.S. is highly uneven. A student’s opportunities often depend on where they live, what school they attend, and whether their district can afford resources like robotics kits, lab space, or qualified teachers. Because each U.S. state sets its own curriculum standards and graduation requirements, there’s no national guarantee of exposure to science, technology, engineering, or math. Some students begin robotics and coding by grade 3. Others may not see a programmable robot—or a coding class—until high school, if ever. This fragmented structure leads to major gaps in opportunity that hinge on location, funding, and teacher availability.
Girls, Black, Latino, and Indigenous students remain underrepresented in key STEM subjects like physics, computer science, and robotics. For example, a study of the World Robot Olympiad finals between 2015 and 2019 found that only 17.3% of participants were girls. That means even in competitions aimed at younger learners, girls are significantly underrepresented. In many underserved or rural communities, students don’t lack curiosity—they lack access. Many never get the chance to code a robot, explore a STEM lab, or join a tech competition—not because they aren’t interested, but because no one offers it to them.
Teacher shortages only widen the divide. In many districts, especially in math-heavy or tech-focused subjects like computing and engineering, schools struggle to recruit and retain certified educators. When that happens, STEM learning becomes textbook-driven, low on experiments, and light on engagement.
For many students—especially those in under-resourced schools—afterschool clubs, weekend programs, and home robotics kits are more than enrichment. They’re essential entry points into STEM. These informal learning spaces allow students to explore at their own pace, in ways that feel personal and hands-on. They bridge the gap between theory and practice—between what’s taught in class and what can be built at the kitchen table. This is also where informal learning environments—and the tools that support them—can play a transformative role.
Where STEM Learning Really Happens and How WhalesBot Supports It
While access to in-school STEM programs varies widely, many students first encounter STEM through informal learning at home. Families often turn to block coding websites (like Scratch and Tynker) or app robotica kits to supplement classroom learning. With the rise of online STEM stores, it’s now easy to buy robots designed specifically for young learners—compact, programmable, and ready to use out of the box. These kits help children learn how to build a robot at home, experiment freely, and begin developing essential problem-solving skills.
As students grow, community-based STEM organizations play a larger role in deepening their engagement. Across the U.S., national initiatives like:
VEX Robotics and FIRST LEGO League – competitive programs where students design, build, and program robots to complete engineering challenges under timed conditions. These events promote teamwork, problem-solving, and fast-paced, hands-on learning.
Girls Who Code and TechBridge Girls – inclusive programs that empower girls from underrepresented communities through project-based STEM learning, mentorship, and confidence-building. These initiatives help young learners see themselves as future engineers, coders, and creators.
These programs go beyond theory: students code robots, test sensors, build prototypes, and learn through iteration. Whether in a well-funded district or an underserved neighborhood, hands-on STEM learning thrives when students have access to the right tools and environments.
That’s where WhalesBot comes in.
Organizations like Leducate LLC, Eyes4Learning, IN3LEARNING, and STEAMwhiz use WhalesBot products to support a variety of extracurricular STEM learning experiences. These may include robotics activities, coding workshops, and age-appropriate engineering challenges designed to build real-world tech skills.
In our previous article on STEM education in the U.K., we introduced tools like Eagle 1003, Rocky, and the AI Module 1S. This time, we’re spotlighting several additional kits that U.S. partners are using to engage learners at every level:
U20 Pro – This kit is designed for learners aged 4 and up and uses pen-and-card programming to teach early robotics concepts without screens. It includes basic sensors, motors, and sound features, allowing young children to experiment with motion, sequencing, and simple interactions.
U30 Pro – A modular robotics kit designed for intermediate learners. It includes magnetic coding cards, sensors, and a smart control panel. Students can use it to explore sequencing, motion control, and multi-sensor input through progressively more advanced robotics projects.
AI Module 5 – The AI Module 5 is intended for students aged 8 and up. It combines mechanical components with programmable sensors to introduce AI-related concepts such as object recognition, real-time feedback, and gesture control. It supports multiple programming languages—including Scratch, Python, and C—and can be used in both classroom and competition settings.
For students without access to formal STEM classes, these tools bring engineering and innovation directly into community spaces. And for all learners, they offer something essential: the chance to build, break, fix, and try again—turning passive tech consumption into active creation. Because when students start to see STEM as something they can do, touch, and shape themselves, the future becomes something they don’t just imagine—but actually begin to build. That future, however, takes shape differently depending on where students live—and how their country’s education system is structured.
How U.S. STEM Differs from the U.K.
While the U.S. and U.K. share many goals around STEM education—early exposure, hands-on learning, and future career readiness—their systems differ significantly in structure, curriculum design, and policy implementation.
In the U.K., STEM education is shaped by a centralized national curriculum. Subjects like science, computing, and maths follow government-issued guidelines across the country. Computer science is offered as a GCSE elective, and only in recent years has it been introduced at the primary level. National initiatives often prioritize teacher training (through CPD programs), industry alignment, and systemic reforms—such as the "Maths to 18" policy or investment in career pathways. Academic milestones are sharply defined by national exams at ages 16 (GCSEs) and 18 (A-Levels), which place strong emphasis on testing and subject depth.
By contrast, the U.S. system is decentralized. Each state sets its own curriculum standards, graduation requirements, and elective offerings. In some states, computer science is required for high school graduation; in others, it remains optional—or absent altogether. This flexibility allows for rapid innovation but also leads to wide variation in access and quality. Rather than top-down policy, many U.S. STEM efforts emerge from nonprofits, private initiatives, and grassroots movements. Organizations like Code.org, Girls Who Code, and local robotics leagues play a central role. Students choose from multiple academic paths—Advanced Placement (AP), dual enrollment with colleges, or career and technical education (CTE)—depending on school and district offerings.
This structural difference has real implications. In the U.K., reform is often slow but consistent. In the U.S., programs can scale quickly, but equity varies widely between ZIP codes. Understanding these contrasts helps explain why STEM opportunities—and challenges—look so different from one country to another.
Conclusion
From early childhood through adolescence, STEM education helps students develop essential skills—logic, creativity, persistence, and collaboration. Whether they’re experimenting with simple materials, exploring block coding websites, or learning how to code a robot using sensors and logic, they’re learning how to ask questions, test ideas, and apply what they know to solve real-world problems.
As technology evolves, access to high-quality STEM learning should evolve with it. But not all students have the same opportunities. That’s why community programs, family support, and tools like robotics kits and AI modules are playing an increasingly important role—especially outside the traditional classroom. These resources allow learners to engage with STEM in tangible, age-appropriate ways, no matter where they are or what their schools provide.
AI and robotics are no longer distant concepts—they’re part of how young people interact with the world. Giving students the chance to experiment, build, and debug their ideas isn’t just about preparing them for future careers—it’s about helping them understand and shape the systems around them today. The future of STEM education lies in making these experiences widely available, deeply engaging, and rooted in real thinking—not just memorization. With the right support, every student can participate in building that future.
In upcoming posts, we’ll continue exploring how STEM education is evolving around the world. Stay tuned for country-by-country insights into what’s working—and what’s next.
