"Computers can occasionally mess up.” Hearing those words from a middle schooler feels like a small victory. Today’s middle schoolers are digital natives, but that doesn’t mean that they understand the algorithms underlying the applications that they use. Most kids trust computer output without question because, most of the time, computers are efficient, helpful, and accurate… until they aren’t. That moment of doubt—of healthy skepticism—signals something powerful: a student beginning to think critically about how computational tools work and why they behave the way they do. When students pause and consider the algorithm behind the output on their screen, we know our Youth Engineering Solutions Computer Science module achieved one of its goals.
Four years ago, when we partnered with MathWorks to develop a computer science curriculum, we thought deeply about what we wanted students to learn. Our Youth Engineering Solutions (YES) curricula are built on decades of experience engaging PK-12 learners in authentic, hands-on engineering challenges. We emphasize process over product; encouraging students to brainstorm, create, test, and improve original solutions as they draw on their scientific knowledge and engage in engineering practices.
The reality is that engineers (and many other professionals) rely heavily on computational tools and computer science. Engineers use computational thinking to analyze problems, select appropriate tools, and develop or adapt algorithms as they work through the engineering design process. This approach helps them solve problems more efficiently while ensuring that solutions are accurate and valid.
YES computer science modules were created to help students do the same: to think like computer scientists within the context of the engineering problem they are solving.
Examples from YES Computer Science Modules
In Heatwave Visualizations, students look to temperature data from weather stations across the U.S. to consider which regions may benefit most from the medicine coolers they are engineering. After comparing tabular data from 2,334 weather stations and a visualization of the same information, students quickly recognize how the visualization helps them identify trends in the data more efficiently. That simple realization opens the door to deeper conversations about when and why engineers use computational tools.
In Bounce Height Measurements, 
students test how well various materials absorb the kinetic energy of a falling ping pong ball. After estimating bounce height with their eyes, they use a computer to extract more accurate data from videos of the same experiments. While building an understanding of the algorithm, they discover that something as simple as the ball’s color can influence the accuracy of their data. Here students learn that computers follow rules that humans design.
In User Reviews Analysis, after engineering eco-friendly slippers, students use machine learning to efficiently categorize large numbers of user reviews as positive or negative. When they notice the computer is using patterns a human would consider irrelevant; they adjust the features the model uses--improving accuracy and reducing bias. This module helps students see that computational tools can reflect the strengths and limitations of the data they’re built on.
YES Middle School Computer Science modules use free web-based MATLAB interactives.
The YES Computer Science Framework
The YES Computer Science Framework describes why it is important for students to learn to think in this way. 
• Increase efficiency and accuracy: Engineers use computational tools to solve engineering problems more efficiently and accurately.
• Generate and use algorithms: Engineers must understand the algorithms their tools use—and know when to design or refine those algorithms themselves.
• Recognize social context: Computational tools are created by people and used by people, which means biases can appear in both the tools and the ways their outputs are interpreted.
A Student’s Perspective
A teacher who implemented the Bounce Height Measurement computer science module shared this student reflection.
Teacher: "Why do you think it’s important that engineers understand the algorithm a computer is using before using it to extract data from a video?"
Student: "So they don’t make any mistakes. Computers also make mistakes sometimes and if an engineer doesn’t understand their algorithm, it won't be the most accurate result."
The student’s response is a simple statement, but a profound one. In a world where AI tools are becoming widely available—and widely trusted—we need to help all students develop computational thinking skills that allow them not just to use technology, but to understand and question it.
This work was generously supported by MathWorks.
