AI-Powered Degree Audit System with Google Sheets and GPT-5

Nodes

Who's it for

Registrars & advisors who need fast, consistent degree checks
Student success teams building prototype dashboards
SIS/EdTech builders exploring AI-assisted auditing

How it works

Read seniors from Google Sheets (Senior_data) with: StudentID, Name, Program, Year, CompletedCourses.
AI Agent compares CompletedCourses to built-in requirements (per program) and computes Missing items + a short Summary.
Write back to the same sheet using "Append or update" by StudentID (updates AI Degree Summary; you can also map the raw Missing array to a column if desired).

Example JSON (for one student):
{
"StudentID": "S001",
"Program": "Computer Science BS",
"Missing": [
"GEN-REMAIN | General Education credits remaining | 6",
"CS-EL-REM | CS Major Electives (200+ level) | 6",
"UPPER-DIV | Additional Upper-Division (200+ level) credits needed | 18",
"FREE-EL | Free Electives to reach 120 total credits | 54"
],
"Summary": "All core CS courses are complete. Still need 6 Gen Ed credits, 6 CS electives, and 66 total credits overall, including 18 upper-division credits — prioritize 200/300-level CS electives."
}

Setup (2 steps)

1) Connect Google Sheets (OAuth2)

In n8n → Credentials → New → Google Sheets (OAuth2) and sign in.

In the Google Sheets nodes, select your spreadsheet and the Senior_data tab.

Ensure your input sheet has at least: StudentID, Name, Program, Year, CompletedCourses.

2) Connect OpenAI (API Key)

In n8n → Credentials → New → OpenAI API, paste your key.

In the OpenAI Chat Model node, select that credential and a model (e.g., gpt-4o or gpt-5).

Requirements

Sheet columns: StudentID, Name, Program, Year, CompletedCourses
CompletedCourses format: pipe-separated IDs (e.g., GEN-101|GEN-103|CS-101).
Program labels: should match the built-in list (e.g., Computer Science BS).
Credits/levels: Template assumes upper-division ≥ 200-level (adjust the prompt if your policy differs).

Customization

Change requirements: Edit the Agent's system message to update totals, core lists, elective credit rules, or level thresholds.
Store more output: Map Missing to a new column (e.g., AI Missing List) or write rows to a separate sheet for dashboards.
Distribute results: Email summaries to advisors/students (Gmail/Outlook), or generate PDFs for advising folders.
Add guardrails: Extend the prompt to enforce residency, capstone, minor/cognate constraints, or per-college Gen Ed variations.

Best practices (per n8n guidelines)

Sticky notes are mandatory: Include a yellow sticky note that contains this description and quick setup steps; add neutral sticky notes for per-step tips.
Rename nodes clearly: e.g., "Get Seniors," "Degree Audit Agent," "Update Summary."
No hardcoded secrets: Use credentials—not inline keys in HTTP or Code nodes.
Sanitize identifiers: Don't ship personal spreadsheet IDs or private links in the published version.
Use a Set node for config: Centralize user-tunable values (e.g., column names, tab names).

Troubleshooting

OpenAI 401/429: Verify API key/billing; slow concurrency if rate-limited.
Empty summaries: Check column names and that CompletedCourses uses |.
Program mismatch: Align Program labels to those in the prompt (exact naming recommended).
Sheets auth errors: Reconnect Google Sheets OAuth2 and re-select spreadsheet/tab.

Limitations

Not an official audit: It infers gaps from the listed completions; registrar rules can be more nuanced.
Catalog drift: Requirements are hard-coded in the prompt—update them each term/year.
Upper-division heuristic: Adjust the level threshold if your institution defines it differently.

Tags & category

Category: Education / Student Information Systems
Tags: degree-audit, registrar, google-sheets, openai, electives, upper-division, graduation-readiness