Hour of Code Is Now Hour of AI. Does That Mean Coding Is Outdated?
AI can write code in seconds. So why should we still teach elementary students how to code?
If you’ve been teaching technology for a while, you’re probably familiar with the Hour of Code. For more than a decade, it has been one of the most recognizable events in computer science education. Teachers could choose an activity, set aside an hour, and introduce students to the idea that anyone can learn to code.
Now, the Hour of Code has evolved into the Hour of AI, reflecting the growing importance of artificial intelligence in education and everyday life.
I understand why this change happened. AI is rapidly becoming part of how we work, learn, and create. Students absolutely need opportunities to understand what AI is, how it works, and how to use it responsibly.
But I have one big concern about the messaging surrounding this shift.
Will teachers start to interpret coding as an outdated skill that no longer deserves a place in elementary technology education?
I hope not! Because while AI is changing how we interact with computers, I would argue that a strong foundation in computer science is becoming more important, not less.
Let’s talk about why.
Why Did Hour of Code Become Hour of AI?
First, a little background.
The original Hour of Code launched in 2013 with a mission to make computer science accessible to everyone. Students didn’t need prior coding experience, and teachers didn’t need to be programming experts. The goal was to remove some of the mystery surrounding computer science and help students see themselves as capable of learning it.
The new Hour of AI initiative builds on that mission by introducing AI literacy to students and educators.
According to the official Hour of AI FAQ, the change is intended to expand foundational AI literacy alongside computer science, not eliminate coding instruction. Popular Hour of Code activities are still available.
That’s an important distinction.
The organization isn’t saying that coding is obsolete. It’s responding to a changing technological landscape and trying to make AI education more accessible.
I support that goal! I just don’t want the excitement surrounding AI to overshadow the value of the foundational computer science skills we’ve spent years advocating for in elementary schools.
And I especially don’t want teachers feeling like they need to abandon their coding lessons to make room for something newer.
If AI Can Write Code, Why Should Kids Learn Coding?
This is probably the biggest question we need to address.
After all, AI tools can now generate working programs from natural-language instructions. You can describe what you want a program to do, and AI can write much of the code for you.
I’ve experienced this firsthand. I’ve been using AI to create custom digital learning activities, and it has opened up possibilities that would have required significantly more traditional programming knowledge just a few years ago.
It’s exciting! But it hasn’t made me think that coding instruction is unnecessary.
Quite the opposite.
The purpose of teaching elementary students to code has never been to turn every child into a professional programmer.
Think about it this way: We don’t teach multiplication because we expect every student to become a mathematician. We teach it because understanding numbers, operations, and mathematical relationships is foundational knowledge.
Calculators can solve multiplication problems instantly, but we still want children to understand what multiplication means.
Coding serves a similar purpose in computer science education.
When students learn to code, they’re learning much more than how to make a character move across a screen.
They’re learning to:
- Break a big problem into smaller, manageable steps.
- Recognize patterns and use those patterns to solve problems.
- Create logical sequences of instructions.
- Predict what will happen when instructions are followed.
- Identify errors and figure out how to correct them.
- Test their ideas and make improvements.
These are computational thinking skills, and they’re valuable whether students eventually write code themselves or use AI tools to help them create.
An AI system might be able to produce the finished program, but that doesn’t mean students understand how the program works.
And in elementary education, the learning process is often much more important than the finished product.
Coding Teaches Students How to Think Through Problems
One of my favorite things about teaching coding is watching students figure out why something isn’t working.
Maybe they’re using Scratch and their character is moving in the wrong direction. Maybe they’ve programmed a robot to navigate a maze, but it keeps turning one square too early.
Their first reaction might be frustration.
But then they start investigating.
Which instruction caused the problem? Did they put the blocks in the wrong order? Are they missing a step? What happens if they change one instruction and try again?
They’re debugging!
And debugging is one of the most valuable experiences students can have in a computer science lesson.
A student who is simply given the correct answer doesn’t necessarily develop the same understanding as a student who works through the problem.
That’s one reason I love activities that have students create and analyze algorithms before they ever open a coding program.
For example, in my Robot Code Builders activities, students follow algorithms to assemble a robot and then work backward by examining a completed robot and writing the instructions needed to recreate it.
It seems simple, but students are practicing sequencing, decomposition, and logical reasoning.
My Algorithm Activities take these concepts further. Students order instructions, find errors or unnecessary steps, and write their own algorithms.
These aren’t lessons about memorizing programming commands. They’re lessons about understanding how a computer follows instructions and how we can communicate a process clearly enough for a computer to carry it out.
That’s knowledge I want every student to have.
AI Makes Understanding How Computers Work Even More Important
Here’s something I’ve been thinking about as AI tools become more powerful.
Technology is getting easier to use while becoming increasingly complicated behind the scenes.
A student can click a button and generate an image, write a story, or create a simple game without having the slightest idea how the technology produces the result.
Of course, ease of use is a good thing in many situations. We don’t need to understand every technical detail of a computer to benefit from it.
But I do think there’s a danger in teaching students only how to operate tools without helping them understand the systems behind those tools.
I don’t want students to see computers as magical boxes that somehow know what to do.
I want them to understand that computers process information, follow programmed instructions, represent data, and perform calculations. I want them to recognize that AI systems are built by people, trained using data, and capable of producing incorrect or biased results.
Computer science gives us a foundation for exploring those concepts.
For example, students who understand traditional conditional statements can begin comparing a rule-based program with an AI system.
In a traditional program, we might write instructions that say, “If the character touches the wall, stop moving.”
With machine learning, a system might instead learn to recognize walls by analyzing examples during training.
Those are different approaches to computing, and understanding the difference is part of AI literacy.
Students don’t need to master advanced programming to explore these ideas. They do need opportunities to build their understanding gradually.
Even something as simple as exploring how computers represent information using binary can help students recognize that digital content isn’t magic.
My Crack the Code Puzzles introduce binary, hexadecimal, and Morse code through encoded-message challenges. These activities provide a starting point for discussing how information can be represented using different systems.
And my Pixel Art Coding lessons connect coding concepts with art, math, and patterns through unplugged activities.
The more students understand these foundational concepts, the better equipped they are to ask meaningful questions about the technologies they use.
Elementary Computer Science Is About More Than Coding
I also think this conversation gives us a great opportunity to clarify what computer science education actually includes.
Coding is an important part of computer science, but it’s certainly not the entire subject.
A comprehensive elementary computer science education introduces students to concepts such as:
- Computing systems: Understanding hardware, software, input, output, and how computers process information.
- Networks and the internet: Exploring how computers connect and how information travels between devices.
- Data: Learning how information is collected, organized, represented, and interpreted.
- Algorithms and programming: Creating instructions, using logic, and developing programs to solve problems.
- Impacts of computing: Considering privacy, security, ethics, and the ways technology affects individuals and communities.
- Artificial intelligence: Understanding how AI systems use data, recognize patterns, and generate outputs, along with their limitations.
Notice how much overlap there is between these areas!
When students learn about data, they’re building background knowledge that supports future AI lessons.
When students learn how algorithms work, they’re better prepared to compare traditional programs with machine learning systems.
When students practice digital citizenship, they’re building the habits they need to make responsible decisions about AI-generated content.
These topics complement one another.
We don’t need to choose between computer science and AI literacy. AI literacy belongs within a well-rounded computer science education.
This is also why I’ve always advocated for teaching students how computers work, not just how to use specific software programs.
Software changes. Apps come and go. The tools students use today might look completely different by the time they graduate.
Foundational computing concepts give students knowledge they can carry with them as those tools evolve.
Why Start Teaching Computer Science in Elementary School?
Sometimes I think elementary computer science gets underestimated because people associate coding with complicated programming languages and lines of text on a screen.
But young students don’t need to write Python or JavaScript to begin learning computer science.
Kindergarten students can practice creating algorithms by giving step-by-step directions.
First graders can explore sequencing and cause and effect.
Second graders can create simple animations using visual coding blocks.
Third graders can begin debugging programs and explaining why an algorithm isn’t producing the expected result.
Fourth and fifth graders can build increasingly complex projects using loops, conditionals, variables, and events.
The concepts grow with the students.
And we can introduce many of them through playful, hands-on activities that don’t feel intimidating.
One of my favorite ways to approach coding with younger students is to connect it to something they’re already familiar with.
My ScratchJr & a Story activities combine picture books with beginner coding projects. Students listen to a story and then use ScratchJr to create an animated scene inspired by it.
They’re practicing sequencing, timing, events, and debugging while making something meaningful.
The literacy connection makes the activity approachable, and students have a reason to make their code work beyond simply completing a coding puzzle.
For students who aren’t ready to work in a coding app, unplugged activities can be just as valuable.
My Coding Quests Directional Coding Board Game has students use directional coding to navigate a pirate-themed board, plan routes, and work through obstacles.
No advanced programming skills required.
We’re introducing computer science concepts in developmentally appropriate ways while giving students opportunities to practice problem-solving.
And honestly, that’s what I want to see more of in elementary technology classrooms!
So Where Does AI Fit Into Elementary Computer Science?
I absolutely believe AI literacy belongs in elementary education.
Students are growing up in a world where AI is already embedded in many of the technologies around them. They need to understand what it is, what it can do, and why they shouldn’t automatically trust everything it produces.
But I think it’s important to distinguish between teaching students about AI and teaching students to use generative AI tools.
Those are not the same thing.
A kindergarten student can explore the idea of training data by sorting objects into categories and discussing how examples help a computer recognize patterns.
A second grader can investigate why an AI image recognition system might make mistakes.
A fourth grader can compare a traditional algorithm with a machine learning system and discuss the differences.
None of these lessons require students to create accounts on generative AI platforms or enter personal information into a chatbot.
We can teach age-appropriate AI concepts without rushing students into tools they may not be developmentally ready to use independently.
And we can connect AI concepts directly to lessons we’re already teaching.
For example, after completing a Sorting Matrix Coding activity, students could discuss the difference between following an explicitly programmed sorting rule and learning to categorize objects from examples.
After completing an algorithm activity, students could explore why an AI-generated answer still needs to be checked.
After a coding project, students could discuss which decisions they made themselves and which parts of a similar project an AI tool might be able to help create.
These connections help students build a more complete understanding of computer science rather than treating AI as an isolated topic.
What Should Teachers Do for Computer Science Education Week Now?
If you’ve traditionally celebrated Computer Science Education Week with Hour of Code activities, you don’t need to throw out your plans!
In fact, I would encourage you to keep the coding activities your students love and look for meaningful opportunities to introduce AI concepts alongside them.
Here are a few ways to approach it.
Start with algorithms and unplugged coding
Before students begin programming, give them opportunities to work with sequencing, directions, and logic.
Try my Cupcake Code Builders or Robot Code Builders activities for a fun way to introduce algorithms.
Give students time to create with code
Let students experience the satisfaction of making something work through their own instructions.
ScratchJr, Scratch, and other block-based coding tools are excellent options for elementary students.
If you want a little more structure for your younger students, the ScratchJr & a Story Spring Bundle includes guided projects connected to picture books.
Explore how computers represent information
Introduce students to binary, pixel art, or other ways computers represent data.
My Pixel Art Coding lessons work well for combining computational thinking with creative, hands-on learning.
Introduce an age-appropriate AI concept
Choose an activity that helps students investigate pattern recognition, training data, or the limitations of AI.
The official Hour of AI website includes activities for different ages and experience levels, including unplugged options.
Leave room for student reflection
Ask students questions such as:
- What instructions did you give the computer?
- What happened when your instructions didn’t work?
- How did you figure out what needed to change?
- How is a traditional computer program different from an AI system?
- Why is it important for people to understand technology instead of just using it?
These conversations help students connect what they’ve learned to the bigger picture.
And if you only see your students once a week for 45 minutes, remember that you don’t have to squeeze everything into one lesson!
Computer Science Education Week can be a celebration of concepts you’re teaching throughout the school year, not the only time students experience them.
If you’re looking for more lesson options, you can browse all of my coding and computer science resources here.
The Future of Coding Education Isn’t About Memorizing Syntax
I think we need to acknowledge that AI really is changing programming.
The ability to describe an idea and have AI generate functional code is a significant development. It’s changing who can create software and how quickly projects can move from idea to reality.
I don’t think we should ignore that.
But I also don’t think the appropriate response is to stop teaching children the fundamentals.
Instead, we should think carefully about what students need to understand in a world where AI can do more of the technical work.
Students still need to recognize problems worth solving.
They need to understand cause and effect, logic, and how digital systems operate.
They need to evaluate results, recognize mistakes, and make informed decisions.
And they need opportunities to develop confidence in their own abilities rather than immediately turning to a tool to complete every challenging task.
There’s a time and place for using AI to make a process faster or more efficient.
There’s also tremendous value in letting a student struggle productively with a coding challenge, test different solutions, and finally get that character to move exactly where they intended.
We shouldn’t remove those learning opportunities simply because a faster solution exists.
AI Is Changing the Tools, Not the Need for Computer Science Education
I’m genuinely excited about what AI makes possible for educators and students. I’ve been exploring its capabilities in my own work, and I see enormous potential for creating customized learning experiences.
I’m also a huge advocate for introducing AI literacy in age-appropriate ways.
But I don’t want us to lose sight of why we fought to bring computer science into elementary classrooms in the first place.
It was never just about preparing students for programming jobs.
It was about giving them a better understanding of the technology shaping their world and helping them become confident, capable problem-solvers.
That’s still worth teaching.
So whether your school celebrates the Hour of Code, participates in the Hour of AI, or creates its own Computer Science Education Week activities, I hope you’ll continue making room for foundational computer science instruction.
Let students write algorithms. Let them debug programs. Let them experiment, create, and figure things out for themselves.
Then help them connect that knowledge to the exciting new technologies they’re encountering.
AI may be changing how we write code, but it hasn’t changed why children deserve to understand how computers work.
And that’s exactly why I’ll continue advocating for computer science education in every elementary school.
Looking for ready-to-teach computer science activities?
I’ve created a collection of coding lessons, unplugged activities, algorithm challenges, and beginner programming projects designed specifically for elementary students. Whether you’re planning Computer Science Education Week or building coding into your yearlong curriculum, you’ll find activities that help students learn the concepts behind the technology they use every day.
Tech Smarts Start Here!
By Brittany Washburn
