✝︎
A First-of-Its-Kind Middle School Course

AI, Ethics &
The Image of God

A 7th & 8th grade elective exploring artificial intelligence through the lens of Catholic teaching, human dignity, and ethical responsibility.

24
Sessions Complete
6
Students
5
Project Pillars
▶  Interactive Demo
See the AI-Enhanced Classroom in Action
Explore personalized AI insights for students, teachers, and school leaders - realistic mock data showing the full potential of this approach.
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🎓
For Students
Student View
Personalized project feedback, pillar scores, and specific next steps each student can act on.
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For Teachers
Teacher View
Full class dashboard, individual engagement arcs, and how to unlock each learner’s best thinking.
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For Admins
Admin View
School-level trends, curriculum health, and evidence of learning outcomes for leadership reporting.
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AI-Powered
Class Assessments
After every session: star rating, what worked, what didn’t, and a concrete plan for the next class.
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Final Project Framework
The Five Pillars

Every student project is evaluated against five pillars co-designed by the class. These aren’t checkboxes - they’re a framework for thinking about what technology should do in the world.

01
Redeeming Value
Does it genuinely help someone? Name the person. Show the impact.
02
Appropriate
Is this the right tool for the right audience, in the right context?
03
Human Dignity
Could a real, vulnerable person be harmed by what you built?
04
Benefit Society
What does the world look like with this in it? Is that better or worse?
05
Explain It
Can you describe how it works and how a human stays in the loop?
Course Curriculum
24 Sessions

Built from scratch and refined in real time. The sequence reflects what was actually taught. Students consistently grasped concepts faster than anticipated.

1
Introduction & The Big Question
What is AI, and why does it matter to us specifically? Students surfaced their assumptions, separated fact from sci-fi, and began building a shared vocabulary for the rest of the course.
2
The Theological Foundation
Imago Dei — humans made in God’s image — as the lens for evaluating AI. A guest speaker grounded the course in Catholic anthropology: what makes us distinctly human, what AI can imitate, and what it categorically cannot.
Guest Speaker
3
How AI Actually Learns
The CGP Grey “teacher bot / student bot” framework demystified machine learning. Students worked through why AI that learns from data can be wrong, biased, or confidently mistaken — and why that matters for trust.
Video
4
Prompting as a Skill
Live hands-on with ChatGPT. Students discovered that AI output quality tracks directly to input quality — and that prompting is a learnable craft, not a trick. First real exposure to the tools they’d use all semester.
Demo
5
Check-In & Concerns
Post-it activity: What excites you? What worries you? What are you neutral on? Students’ honest responses — about job loss, AI sentience, and whether to say “please” to a chatbot — set the tone for everything that followed.
6–7
AI & Jobs: Economic Disruption
From the printing press to the assembly line to now. Students researched which jobs AI is already displacing, which are emerging, and what skills will matter in a world where most rote work is automated. The question underneath: what is work for?
Research
8
Rearrangement, Not Creation
The core theological and philosophical claim of the course: AI rearranges existing human knowledge and expression. It does not originate. Students stress-tested this against AI-generated art, music, and writing — and debated where the line actually falls.
9
AI & Education
Our principal joined as a guest speaker to explore what AI means for learning itself. The central tension: process vs. product. If AI can write your essay, what does writing it yourself actually give you? Students voted on whether they’d take guaranteed A’s from AI — and the split was revealing.
Guest Speaker
10
The Galveston Hurricane Exercise
Students were handed an AI-generated account of the 1900 Galveston hurricane — plausible, fluent, and riddled with fabrications. They had to find the lies. The lesson: you can only catch what you already know. AI hallucination isn’t a bug you can spot without a baseline of truth.
Experiential
11
AI vs. Human Writing
Blind comparison: AI-generated paragraphs alongside student-written ones on the same prompt. Could students tell the difference? Sometimes. Could they say why? That was harder — and more instructive. The exercise sharpened their eye for what “slop” actually looks and reads like.
Activity
12
Deepfakes & the Nixon Exercise
Students watched a convincing AI-generated video of a historical figure delivering a speech that never happened. The reveal — that it was fabricated — landed hard. When seeing is no longer sufficient evidence, how do we establish what’s real? The room got quiet in the right way.
Video
13–14
Project Design & the Five Pillars
Students co-designed the evaluation framework they’d be held to. Then they applied it to their own project ideas — naming real users, identifying dignity risks, and stress-testing whether their app actually helps anyone. AI provided live feedback on their worksheets.
Workshop
15
AI as Collaborator: Live Critique
The breakthrough session. Students presented project concepts; AI critiqued them in real time against the five pillars. Some feedback was uncomfortable. Students pushed back, defended their choices, and revised in the room. This is what the course was built toward.
Breakthrough Class
16–17
Peer Review & Product Refinement
Students presented to each other and received structured peer feedback on all five pillars. Several projects changed direction based on classmates’ challenges. The strongest peer contributions became permanent parts of other students’ products.
Peer Review
18
First Build Session — Gemini
Students moved from ideation to construction using Google Gemini. Working from prompt guides tuned to their individual projects, they proved their concepts in real time. The lesson: a concept is just an idea until AI gives it back to you as a working thing.
Build
19
Custom AI Mentor Sessions
Each student received a personalized ChatGPT instance pre-loaded with their project history and course context. The AI pushed, challenged, and named things the students hadn’t named themselves. The hardest work of the course — done with the most sophisticated tool.
Breakthrough Class
20
Build Sprint & Final Decisions
Decision day. Students continued building with AI mentors and made final commitments on product direction. All six projects are now clearly defined and in active development. Presentations approaching.
21–22
Landing Pages & Final Build
Students built public-facing landing pages for their projects using AI-generated code. From concept to deployed website in a single session — working from PRDs they helped author. Three students published live sites by the end of class.
Build
23–24
Final Presentations & Demo Day
Students presented their completed projects to classmates and the teacher, walking through product concept, design decisions, and Five Pillars reasoning. Each student narrated their own product — not just pointed to a screen. The closing session returned to where the course began: creation as a divine act, and what it means to build something good.
Demo Day
About This Course
The Methodology

This course was built in real time by someone who had never formally taught before - a COO at a Catholic school with a product background and a conviction that middle schoolers deserve to engage seriously with the most consequential technology of their lifetimes.

The methodology matters as much as the curriculum. Every class is recorded, transcribed, and analyzed by AI - not to grade students, but to surface what a single teacher with six students can't always catch in the moment. Which student's engagement has been quietly declining? Who made a brilliant observation that got talked over?

Anonymization is a core design principle, not an afterthought. Student identities and voice signatures are anonymized before any AI analysis is run. The system is designed to surface patterns - not to profile individuals. No student name, image, or identifying detail ever enters the analysis pipeline. The teacher receives insights about learning behavior; the AI never receives a name.

The AI watches. The teacher responds. The human is always in the loop. That's not just course philosophy - it's the operating model. This approach is documented and designed to scale across subjects and grade levels.

The demo section of this site shows exactly what becomes possible when AI serves the teacher - and the student - rather than replacing either of them.

“AI does not teach. AI watches, analyzes, and reports. The teacher does what no algorithm can: know a child and respond with wisdom, attention, and love.”
✝  Course Design Principle