A six-hour, project-based AI and 3D-printing program
Two three-hour instructional sessions, with supervised printing between sessions. Each learner finishes with a working website, its reviewed source code, a calibrated printable STL, a physical lithophane night-light, and a portfolio-ready explanation of what they built and learned.
01Two three-hour instructional sessions
02Supervised printing between sessions
03Beginner-friendly and project based
04Free, open-source curriculum
05Reusable technology stations
06Individual or small-team delivery
07Public publishing optional
Why the program is fundable
One understandable artifact connects the learning.
Learners do not merely watch a technology demonstration. They create working software, review its source code, manufacture a physical product, and document the complete idea-to-production process.
Natural program connections
STEM · Career and technical education · AI literacy · Additive manufacturing · Digital citizenship · Workforce readiness · Art and design · Entrepreneurship · Community engagement
Physical evidence of learning
What each learner produces
A reviewed source repository and Git history
A downloadable lithophane STL generated from their own site
A Base Fit Lab calibration result
A finished physical lithophane night-light
A privacy-safe project story or short reflection
A portfolio-ready explanation of the process
The school or program normally retains the reusable computer and printer station. Learners take their digital work, source code, physical light, and evidence of learning. Public deployment, personal photographs, purchases, and public gallery participation remain optional.
Adaptable delivery model
Two sessions, with printing between them.
This is a practical starting model, not a rigid requirement. Facilitators can adjust pacing, team size, and local-only milestones to fit their learners and facilities.
Build and prepare
- Introduce AI-agent use, consent, and privacy
- Open or clone the project and run it locally
- Inspect and personalize the site
- Review changes and save them with Git
- Use the Base Fit Lab
- Print and test the Fit Finder
- Select the correct adapter size
- Generate and inspect the final STL
- Prepare the print in the slicer
Supervised print period
Complete lithophanes may take longer than the instructional session. Printing occurs during an instructor-managed or otherwise appropriately supervised period. Programs follow printer, material, facility, and manufacturer policies.
Finish, inspect, and explain
- Inspect the completed print
- Troubleshoot fit or quality problems
- Test the cooled print on the unplugged light
- Complete and review the website
- Publish an approved version when appropriate
- Create a privacy-safe project story
- Explain what changed, what worked, and what was learned
- Discuss community, portfolio, or small-enterprise uses
Measurable learning outcomes
Outcomes paired with observable evidence.
By completion, learners should be able to demonstrate these skills. The program gives each learner the opportunity to create the evidence below; it does not promise identical mastery for every participant.
| Outcome | Evidence |
|---|---|
| Guide an AI coding agent and review its work | Prompt history, changed-file review, and learner explanation |
| Run and personalize a web project | Functioning local or hosted website |
| Explain Git versus GitHub | Reviewed commit and repository |
| Apply privacy and consent practices | Source-photo handling and publication checklist |
| Generate and validate an STL | STL, settings note, and automated checks |
| Apply measurement and tolerance | Labeled Fit Finder result and selected slot width |
| Inspect a 3D print safely | Completed print inspection checklist |
| Explain how software became a physical product | Short reflection, presentation, or portfolio story |
Count the work, then ask learners to explain it.
- Completion of key digital and physical artifacts
- A simple instructor rubric
- Learner reflection
- Pre/post confidence questions
- Attendance and completion counts
- Counts of functioning sites, validated STLs, Fit Finder tests, and completed prints
- Optional follow-up project or presentation
No Dark Nights has not yet published formal pilot results. Outcomes and evaluation measures on this page are proposed for a future program to validate.
Ownership of equipment is not a prerequisite.
- Learners do not need to own a computer or printer.
- Equipment can be reused by later cohorts.
- Calipers are optional.
- Neutral or permission-cleared images may replace personal photographs.
- A public website is not required for completion.
- A physical print is optional when accessibility or program circumstances prevent it.
- Meaningful local-only milestones remain available.
- Work may be completed individually or in small teams.
- Families and educators determine appropriate guidance beyond applicable service requirements.
- The curriculum and source code are open and adaptable.
Reusable equipment
Suggested learning station
Named products are examples, not requirements. Existing school, library, or makerspace equipment may be used.
- Mac mini or comparable supported computer
- Bambu Lab A1 Mini or comparable beginner-friendly 3D printer
- Codex desktop access or an approved managed Codex environment
- PLA filament
- Commercially manufactured LED night-light hardware
- Internet access
- Slicer software
- Basic finishing and safety supplies
- Calipers optional—the Base Fit Lab provides a no-caliper path
- Product links elsewhere on this site are not affiliate links
Bedrock-managed local Codex work and OpenAI-hosted Sites publishing may require separate access arrangements, as explained on Learn. Never give learners root credentials, shared permanent credentials, or unrestricted cloud spending.
Reusable budget framework
Use current quotes and local rates.
Most initial funding supports reusable equipment. Ongoing expenses are primarily managed AI access, filament, night-light hardware, replacement supplies, and program delivery.
Reusable equipment
- Computers
- 3D printers
- Storage and workstation accessories
- Optional measuring and finishing tools
- Spare parts or maintenance allowance
Per-learner or recurring costs
- Filament
- LED night-light hardware
- Replacement supplies
- Managed AI/Codex access
- Printing and finishing materials
Program delivery
- Instructor or facilitator time
- Curriculum preparation
- Technical setup and support
- Accessibility accommodations
- Shipping, tax, or institutional purchasing costs where applicable
Applicants should insert current vendor quotes, institutional pricing, and local staffing rates. This framework intentionally contains no estimated retail prices.
Safety and privacy
Build with deliberate boundaries.
- Source photos remain local in Studio.
- Private photographs should not be given to Codex.
- Contact is disabled in repository clones.
- Public publishing requires deliberate review.
- Fit tests happen only after cooling and with the light unplugged.
- Electrical components are never printed or modified.
- Programs follow applicable age, account, facility, printer, and manufacturer requirements.
Grant-writing tools
Reuse the brief.
Copy the summary into an application, or use your browser to print this page or save it as a PDF. These controls do not collect or transmit information.
Program summary
No Dark Nights is a project-based AI, web-development, and additive-manufacturing learning program. In two three-hour instructional sessions, with supervised printing between sessions, learners use Codex to inspect and personalize an open-source website, review changes with Git, generate and calibrate a printable lithophane STL, and manufacture a physical night-light. Learners finish with working software, reviewed source code, a physical artifact, and a portfolio-ready explanation of the complete idea-to-production process. Funding primarily supports reusable computer and 3D-printer stations, managed AI access, instructional delivery, and consumable printing and night-light materials.
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