I have taught computer science since 2014.
Since 2018, I have taught AP Computer Science Principles every year.
Before entering education, I spent more than a decade working in information technology and cybersecurity, first in the United States Army and later in the private sector with Dell Technologies, New York City law firms, and healthcare revenue organizations.
I have lived in two very different worlds.
One measures success through standardized assessments.
The other measures success by solving problems that have never been seen before that eat into profit margins.
Those experiences have shaped how I think about computer science education.
Every year, my AP Computer Science Principles students substantially exceed both New York State and global averages. With one exception during the COVID-19 pandemic, my students have consistently outperformed those benchmarks throughout my time teaching AP Computer Science Principles.
I share those results because they matter.
Not as a celebration.
As context.
Everything that follows comes from someone whose students consistently succeed on the examination. Which is precisely why I believe it is time to ask a more difficult question.
Are we measuring the right things?
When AP Computer Science Principles was introduced, it solved an important problem.
It broadened participation in computing.
It moved introductory computer science beyond memorizing syntax.
It emphasized creativity, computational thinking, abstraction, data, and the societal impact of technology.
For many students, AP Computer Science Principles became the first invitation into a discipline they wanted but lacked formal guidance on.
That achievement should not be minimized.
It transformed computer science education.
The College Board deserves enormous credit for that.
But successful courses should not become static courses.
Computer science certainly has not.
During my years working in IT and cybersecurity, I witnessed wave after wave of technological change.
Virtualization.
Cloud computing.
Automation.
Cybersecurity.
Mobile computing.
DevOps.
Artificial intelligence.
Each fundamentally changed how technology professionals approached their work. Today’s software engineers rarely solve problems alone.
They work collaboratively.
They consume APIs.
They integrate cloud services.
They review code continuously.
They write automated tests.
Increasingly, they partner with artificial intelligence throughout the software development lifecycle. AI is no longer another technology to learn. It has become another way developers think.
Students know this.
Many walk into AP Computer Science Principles having already experimented with ChatGPT, GitHub Copilot, Replit, Roblox Studio, YouTube programming tutorials, or personal coding projects.
They have already seen what modern computing looks like. They expect school to reflect that reality.
Too often, it does not.
The recently announced redesign of AP Computer Science Principles acknowledges what every computer science educator already knows.
Artificial intelligence has permanently changed computing. The redesign introduces AI concepts throughout the curriculum.
Students will complete a new AI Design Project. The examination will assess AI concepts alongside traditional computer science principles.
These are thoughtful improvements.
Ignoring artificial intelligence would have been impossible to justify. The College Board deserves credit for responding.
Unfortunately, I believe the redesign stops where the more important conversation begins.
Reading the redesign announcement, one theme appears repeatedly.
Students will learn AI. Students will complete an AI project. Students will answer AI questions.
The redesign introduces artificial intelligence as additional content.
Professional software development does not work that way.
Artificial intelligence is not another chapter in the textbook. It has become part of the workflow. Developers use AI while designing software.
While debugging.
While writing documentation.
While creating test cases.
While exploring unfamiliar frameworks.
While reviewing architecture.
While learning entirely new technologies.
Artificial intelligence has fundamentally changed how software is built. Teaching AI concepts matters. Teaching students how AI transforms development matters even more.
Those are not the same thing.
One aspect of the redesign concerns me more than any other.
The addition of a second culminating project on top of one that is already questionable.
On paper, another project sounds like progress. Projects are valuable. Students absolutely should build with artificial intelligence. But adding another assessed artifact raises an important question.
What problem are we trying to solve?
If the goal is exposing students to AI, another project may accomplish that.
If the goal is preparing students for modern development and understanding, I believe it misses the larger opportunity.
Professional software engineering and IT is not organized around isolated projects completed for assessment.
It is an iterative process of building, testing, failing, refining, documenting, collaborating, and continuously learning.
Artificial intelligence now exists throughout every one of those stages. Students should not experience AI as something they do during one project. They should experience AI the way professionals are experiencing it.
As a design partner.
As a debugging assistant.
As a code reviewer.
As a research assistant.
As another engineering tool that helps them become better problem solvers.
That requires more than another project. It requires rethinking the learning experience itself.
One sentence in the redesign announcement stood out to me.
“The course will modernize with AI while maintaining its core structure.”
I understand why that sounds reassuring. I also think it reveals the central challenge. The redesign assumes the existing structure remains fundamentally correct.
I am no longer convinced.
Artificial intelligence has not simply introduced another topic into computer science. It has transformed how software engineers learn, collaborate, and create. When a profession changes this dramatically, curriculum redesign should involve more than adding new material.
It should challenge assumptions about assessment.
About projects.
About collaboration.
About how students experience computer science from the very first day they enter the classroom.
I consistently redesign my own AP Computer Science Principles course.
Weekly formative assessments. Regular coding checkpoints. Far more AP Classroom practice. Frequent opportunities for reflection. Comprehensive review materials.
The results spoke for themselves.
Objectively, those instructional changes improve AP performance. Ironically, they also reinforced something I had already begun questioning.
Preparing students to succeed on the AP examination and inspiring students to pursue computer science are becoming increasingly different goals.
One measures achievement.
The other measures curiosity.
Only one appears on an AP score report.
Nothing in this article should be interpreted as criticism of algorithms.
Or abstraction.
Or decomposition.
Or iteration.
Or data structures.
Those concepts remain timeless.
The issue is not what students learn. The issue is how they experience those ideas.
Students remember building meaningful software. They remember solving problems that mattered. They remember creating something they once believed was impossible.
That is where passion for computer science begins.
The fundamentals become unforgettable because students needed them to accomplish something meaningful. Not because they were preparing for a multiple-choice examination.
I still believe of AP Computer Science Principles has its purpose.
I remain proud of my students.
I will continue preparing them to succeed because those opportunities matter.
But after more than a decade in IT and cybersecurity, more than a decade teaching computer science, and seven years teaching AP Computer Science Principles, I believe we should ask a larger question.
Not whether AP Computer Science Principles includes artificial intelligence. Not whether it adds another project. Not whether it updates the examination.
We should ask whether the learning experience itself reflects the reality of modern computing.
Because the future of computer science education will not be defined by how effectively we add AI to yesterday’s curriculum.
It will be defined by whether we are willing to rethink how students experience computing in a world where artificial intelligence has fundamentally changed the profession.
Our students deserve nothing less.
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