K-12 AI Literacy Curriculum
A District-Ready Curriculum for Responsible AI Leadership
Embedded Files
Vision of the Graduate in the Agentic Era
Vision of the Graduate in the Agentic Era
Our vision of the graduate is a student who leaves high school prepared to lead and direct artificial intelligence. In the Agentic Era, graduates will work alongside multiple AI systems at once—tools that assist with work, but never replace human judgment or responsibility.
Archive AI prepares students to coordinate those systems with intention, evaluate their output critically, and remain fully accountable for decisions made with AI assistance. These graduates understand that AI provides leverage, not authority. They know when to accept machine support, when to reject it, and how to act ethically and responsibly in real academic, civic, and professional environments where human judgment remains essential.
How This Curriculum Is Different
How This Curriculum Is Different
Most AI curricula focus on exposure to tools or basic understanding of how AI works.
Archive AI focuses on leadership, judgment, and responsibility.
Students learn how to:
Evaluate AI output rather than accept it
Decide when AI should or should not be used
Remain accountable for work completed with AI assistance
The curriculum reflects real-world expectations, where individuals work alongside multiple AI systems and are responsible for the outcomes those systems help produce.
AI is treated as leverage—not authority—and human judgment remains central.
A Structured Framework for Learning With AI
A Structured Framework for Learning With AI
Archive AI’s curriculum is built on a clear developmental framework designed specifically for education.
Three Developmental Tiers
Three Developmental Tiers
Apprentice
Apprentice
Awareness & Discernment
Students learn to recognize when AI is being used and understand that its output is not automatically correct.
The focus is on questioning results, identifying errors, and avoiding uncritical acceptance.
This tier builds foundational awareness and healthy skepticism.
Sculptor
Sculptor
Ownership & Refinement
Students learn to work with AI without surrendering ownership of their thinking.
They practice refining AI-assisted work, improving clarity and accuracy, and explaining how decisions were made.
The focus is on shaping work intentionally and taking responsibility for outcomes.
Architect
Architect
Leadership & Accountability
Students learn to lead AI systems toward a goal rather than respond to them passively.
They coordinate multiple systems, set boundaries, reject inappropriate output, and defend their decisions.
The focus is on judgment, accountability, and real-world responsibility.
The Assessment & Accountability Framework
The Assessment & Accountability Framework
The Human Delta
The Human Delta
As AI becomes a required part of learning, a critical problem emerges for schools: how do educators evaluate student understanding when AI is involved in the work?
AI can generate drafts, explanations, and solutions, but it cannot show what a student understands, why choices were made, or how decisions were evaluated. Without a clear human contribution, student work becomes difficult — and often impossible — to assess fairly.
Human Delta solves this problem.
Human Delta is the visible evidence of a student’s judgment: how they frame a task, apply context, evaluate AI output, make decisions, and take responsibility for the final result. It allows educators to see where understanding resides, even when AI assistance is present or expected.
Archive AI’s curriculum is designed to deliberately build and surface this Human Delta, so student work remains assessable, accountable, and meaningful in an AI-enabled classroom.
Cointelligence Quotient (CQ)
Cointelligence Quotient (CQ)
As AI becomes embedded in everyday work, the question is no longer whether students use AI — but how well they work with it.
The Cointelligence Quotient (CQ) is Archive AI’s framework for measuring a student’s ability to coordinate multiple AI systems while maintaining judgment, intent, and academic integrity. While Human Delta captures what the student adds, CQ captures how effectively they work within an AI-supported environment.
CQ focuses on behaviors educators can observe and assess:
How students select and guide AI tools for a task
How they manage boundaries between human decisions and machine assistance
How they refine, validate, and take responsibility for final outcomes
Rather than grading AI output, CQ allows educators to evaluate AI-mediated thinking, strategy, and ownership — skills that increasingly define readiness for higher education and the modern workforce.
The Integrity Portfolio
The Integrity Portfolio
When AI use is expected, traditional plagiarism checks no longer work.
The Integrity Portfolio replaces detection with documentation. It provides a structured record of how a student worked with AI — what was delegated to the system, what decisions were made by the student, and how the final work was shaped through human judgment.
The portfolio makes student thinking visible by capturing:
The evolution from initial AI-assisted drafts to final human-refined work
Evidence of decision-making, revision, and critical evaluation
Clear ownership of the finished product, even when AI was used throughout
This allows educators to assess learning without banning AI, and students to demonstrate intellectual ownership in environments where AI assistance is not only allowed, but required.
The Integrity Portfolio creates transparency, protects academic integrity, and gives schools a defensible way to evaluate student work in the Agentic Era.
Together, Human Delta, the Cointelligence Quotient (CQ), and the Integrity Portfolio form Archive AI’s Assessment & Accountability Framework for AI-enabled learning.
Page updated
Report abuse