Degree Audit Automation: Encoding Your Catalog as Rules an Agent Can Run

About this course

Degree audit software only works when the catalog behind it is encoded as rules a machine can evaluate, and most institutions never get every rule in. This course teaches the registrar-side craft of degree audit automation: how to inventory requirements, catalog years, substitutions and exceptions, model them as typed relationships rather than free text, and then run and explain audits with an AI agent that stays inside deterministic rules. You will learn why an accurate audit is worth money. Excess credits accounted for about 12 percent of all college-level credits earned by community college degree completers in the CCRC's 2012 study, and non-flagship public university graduates averaged 136.2 credits against the 120 typically required (EdInsights). You will build a requirement inventory for one program, encode it as rules, run a what-if audit, and design a stop-out audit that surfaces near-completers among the 37.6 million working-age adults with some college and no credential (National Student Clearinghouse, June 2025). The course stays on the rules side of the house; student-facing advising is covered elsewhere.

What you will be able to do

1. Inventory every requirement type in one degree program (credit totals, course lists, residency, GPA, sequencing, catalog-year applicability) and classify each as deterministic, judgment-based, or undefined.
2. Encode a program's requirements as a rule set with typed relationships (satisfies, requires, substitutes-for, excludes) that a second person can read and run without explanation.
3. Compute credits per credential and excess credits at completion for a graduating cohort using the Aspen Institute definitions, and state what a one-credit reduction is worth in institutional terms.
4. Run and explain a what-if audit on a sample catalog with an AI agent, and show that every pass/fail result traces to a rule rather than a model guess.
5. Write an access-scoping matrix for an audit agent that is consistent with FERPA's treatment of audits as education records.
6. Design a rollout and measurement plan for a degree audit automation project, including the metrics a provost will ask for.

Who this course is for

Roles: registrars and associate registrars, degree audit and catalog analysts, curriculum committee staff, academic advising directors, enterprise application analysts who maintain the student information system (SIS), and institutional research staff who report on time-to-degree.

Institutions: community colleges, regional public universities, private nonprofit colleges, and system offices that maintain audit rules for several campuses.

Before you start: familiarity with your institution's catalog and general-education structure, and basic comfort with a spreadsheet. No coding is required. The two labs use an AI agent through a browser and a supplied sample catalog.

Format

• Estimated time: 12 to 14 hours.
• Level: intermediate. Assumes you work with a catalog; assumes nothing about software.
• Hands-on: two labs on a supplied sample catalog (a 60-credit associate program and a 120-credit bachelor's program with general-education, major, residency and GPA rules), four templates you keep, two discussions, and a capstone on your own program.
• Structure: 4 sections, each ending in an AI conversation assessment, then a capstone assessment.

Self-paced. Every lesson is taught by an AI tutor that opens with a short story and works through one idea and one question at a time. Each section ends with an AI conversation assessment, and the course closes with a capstone assessment. Section assessments count for 60% and the capstone for 40%; 70% passes. There are no multiple-choice quizzes.

Currency of this course

Every source in this course was checked on 2026-09-28. Rules and guidance change; check the linked sources before relying on a date or figure.