Immediate feedback
Students can test ideas in real time, spot mistakes quickly, and build confidence through revision instead of waiting days to find out whether they understood.
I’m David Steckler, a 7th grade computer science teacher at Highlands Middle School in White Plains, New York. I teach coding, robotics, problem solving, and the kind of thinking that helps students become less helpless in the modern world.
My classroom is built around one simple belief: computer science matters because it trains attention, judgment, creativity, and independence. The code is real, but the deeper goal goes beyond code.
That idea has shaped the way I teach. I care deeply about technical skill, but I also care about the habits underneath it. I want students to ask sharper questions, notice assumptions faster, and become more comfortable thinking through uncertainty instead of waiting for someone else to hand them the answer.
That is why my classes often connect computer science to bigger human questions. We talk about representation, systems, choices, logic, language, identity, ethics, and the strange gap between what technology can do and what people should do with it. Sometimes those conversations come through code. Sometimes they come through a thought experiment, a paradox, or a simple question that refuses to leave the room.
I do not want students leaving class with a folder full of finished assignments and no deeper framework for seeing the world. I want them leaving with stronger judgment.
I try to build a room that feels alive. Less passive. Less worksheet driven. More discussion, more experimentation, more visible thinking. Students learn best when they can act, get feedback, revise, and immediately see the consequence of what they just did.
That is one reason computer science is such a powerful medium. You type something, run it, and the computer answers honestly. It does not flatter you. It does not guess what you meant. It gives you feedback, and that feedback becomes part of the learning.
Students can test ideas in real time, spot mistakes quickly, and build confidence through revision instead of waiting days to find out whether they understood.
I want students making decisions, not just completing procedures. They should be able to explain why they did something, not only what they clicked.
I do not remove every obstacle. Productive frustration matters. Learning gets stronger when students discover that confusion is normal and survivable.
Computer science is not just about learning a programming language. It is a way of learning how modern systems work, how instructions become outcomes, how information is represented, and how small choices can produce huge downstream effects.
When students learn to code, they are also learning precision, sequencing, pattern recognition, debugging, and patience. They are learning how to break a problem into parts. They are learning that vague thinking creates vague results. They are learning that if they want a machine to do something useful, they have to become clearer themselves.
That is why I take representation seriously. A picture on a screen, a sound in a speaker, a sentence in a chatbot, a game, a website, a robot movement, all of it comes back to information, structure, and logic. Once students really feel that, the world starts to look different to them.
Coding is valuable. But the bigger win is becoming someone who can understand systems, adapt quickly, and create instead of only consume.David Steckler
We are living through a shift that is too big for schools to ignore. AI is already changing how people write, search, plan, analyze, and create. Students need experience using these tools, but they also need judgment. They need to know when AI is helping, when it is flattening their thinking, and when they are outsourcing something they should still know how to do themselves.
I am interested in teaching students how to use AI as leverage, not as a crutch. That means prompt design, verification, revision, and knowing that a confident answer is not the same thing as a correct answer. It also means helping students understand that their own brain still matters. A lot.
The best use of AI is often acceleration. Brainstorm faster. test ideas faster. explain concepts in multiple ways. move quicker from blank page to meaningful work.
Students should learn to question outputs, compare sources, notice weak reasoning, and understand that fluency can hide errors.
I want students creating things they can point to. Not just completing invisible exercises and moving on. Depending on the course or unit, that can mean code, graphics, animations, logic puzzles, simple games, web pages, robotics challenges, collaborative problem solving, or AI driven projects that ask students to think harder about the process behind the result.
I am especially drawn to work that helps students feel the bridge between abstract ideas and concrete results. A line of code becomes a shape. A variable changes a pattern. A sequence becomes behavior. An idea becomes something real.
Middle school is one of the most important stretches in a person’s life. Students are old enough to think in interesting ways, but young enough that their habits, identity, and relationship with challenge are still highly moldable. This is where a lot of people quietly decide what kind of learner they think they are.
I take that seriously. I want students to leave my room with more confidence in their ability to figure things out. More tolerance for mistakes. More respect for their own mind. More willingness to stay with a hard problem instead of ejecting the second it gets uncomfortable.
A good class can change what a student believes about themself. That is never a small thing.
Outside the classroom, I am drawn to lifting weight. Tennis. Reading. Building projects. Training my dog Pixie. Thinking through ideas that sit at the intersection of technology, psychology, money, behavior, and meaning.
I like writers and thinkers who make complicated things clearer without draining them of depth. I like systems that reward patience, experimentation, and judgment. I like work that feels human instead of polished into emptiness.
I gravitate toward ideas about behavior, decision making, money, technology, philosophy, and the quiet forces that shape how people live.
I enjoy creating pages, tools, lessons, and digital experiences that make ideas easier to understand and more enjoyable to explore.
Whether it is the gym, tennis, or working with my dog, I enjoy the process of getting slightly better through repetition, clarity, and attention.
I care about making learning feel more real. More modern. More connected to the world students are actually entering. I want to keep building classrooms and digital tools that respect students’ intelligence while helping them become more capable, more articulate, and more self directed.
The long game is simple: help young people become harder to fool, harder to discourage, and more able to build a life with intention.
Students do not need another adult who only tells them what to finish. They need adults who help them see further, think better, and trust that they can learn things that once felt out of reach.
That is the kind of classroom I am trying to build.
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