Industry Vocabulary Reference

Higher Education

Higher education fields describe admissions, learning activities, student support, financial aid, records, and accessibility workflows. Select the fields relevant to the decision being recorded.

Back to industry coverage library

This page shows selected examples and categories. Download the JSON for the complete vocabulary, including every field, permitted value, and policy pattern in this catalog.

How to use this reference

1. Start with the core file if you need the cross-industry governance baseline.
2. Choose an industry file for its workflow fields and permitted values.
3. Match the OTel attributes to the policy paths your rules use, then verify the recorded fields in a test session.

Catalog context

For an admissions or student-support workflow, record the decision stage and review outcome. Avoid copying student records into traces when metadata is sufficient.

Risk note: Assess privacy, accessibility, and decision-review requirements for the institution and intended use. A student's location alone does not determine every applicable obligation.

Vocabulary file

• Download filename: 07_vertical_higher_education.json
• Kind: vertical

OTel namespaces

Referenced standards

These references explain the catalog's context. A listed standard does not establish that a configured application meets its requirements.

• CEDS v12, Common Education Data Standards (US Department of Education, 2024)
• IMS Global LTI Advantage 1.3, Learning Tools Interoperability (1EdTech Consortium)
• IMS Global Assignment and Grade Services (AGS) 2.0, LTI Advantage extension
• IMS Global Caliper Analytics v1.2, Learning activity telemetry standard
• IMS Global Open Badges v3.0, Digital credential standard
• FERPA, Family Educational Rights and Privacy Act (20 USC 1232g; 34 CFR Part 99)
• COPPA, Children's Online Privacy Protection Act (13 and under; relevant for dual-enrollment)
• ADA Title II / Section 504, Accessibility obligations for higher education institutions
• WCAG 2.2, Web Content Accessibility Guidelines (applicable to AI-generated content)
• EU AI Act (2024/1689) Annex III para 3, High-risk AI in education and vocational training
• EU GDPR (2016/679), Applicable to EU student data; FERPA equivalent for EU institutions
• Uniform Guidance 2 CFR Part 200, Federal award administration (grants and contracts)
• Higher Education Act (HEA) Title IV, Federal student aid eligibility and reporting
• FSA (Federal Student Aid) COD, Common Origination and Disbursement system schemas
• IPEDS, Integrated Postsecondary Education Data System (NCES mandatory reporting)
• National Student Clearinghouse (NSC), Enrollment verification and transfer data
• PESC, Postsecondary Electronic Standards Council, EDI standards for transcripts, financial aid
• Common App, Undergraduate admissions data exchange standard
• QM (Quality Matters) Rubric v7, Online course quality standards
• HLC / SACSCOC / MSCHE / WASC / NWCCU, Regional accreditation standards (AI use disclosure)

Source references

• https://ceds.ed.gov/ 
• https://www.1edtech.org/standards/lti 
• https://www.imsglobal.org/spec/lti-ags/v2p0 
• https://www.imsglobal.org/spec/caliper/v1p2 
• https://studentprivacy.ed.gov/ferpa 
• https://www.ecfr.gov/current/title-2/subtitle-A/chapter-II/part-200 
• https://www.ed.gov/about/offices/list/fsa/ 
• https://nces.ed.gov/ipeds/ 

Subdomains

Implementation examples

• Student Success & Early Alert: Student Success Risk Level. AI student success agent computes risk level nightly from LMS engagement, grade data, and attendance. Advisors receive daily caseload sorted by risk level. OPA policy requires that 'high_risk' students cannot have their risk score used for adverse actions (e.g. scholarship removal) without human review and student notification. (Eu AI Act Annex3 3b: EU AI Act Annex III para 3(b), High-risk AI: systems that assess or evaluate students. Requires human oversight, logging, transparency disclosure to students, and conformity assessment.)
• Student Success & Early Alert: Early Alert Trigger Category. Every early alert generated by the AI student success agent is tagged with its trigger category. This enables advisors to prioritise outreach type and ensures students can request explanation of why they received an alert. (Eu AI Act Art13: EU AI Act Article 13, Transparency: students must receive meaningful information about which trigger categories drove their AI risk assessment)
• Student Success & Early Alert: Intervention Outcome. AI success agent closes the intervention loop by recording outcome when the semester ends or the student's status changes. Outcome data feeds back into the AI risk model training pipeline, subject to FERPA deidentification requirements before model training use.
• Admissions & Enrollment Management: Admission Consideration Level. AI admissions screening agent references consideration level for each factor (test scores, GPA, essays, extracurriculars) to correctly weight its evaluation. 'Required' factors cannot be waived by the AI, missing required data must trigger human review, not a default score imputation.

Control ideas

These patterns describe possible controls, not active rules. Confirm applicability, implement the control, and test its effect on the application.

Enforce before the action

Pass the request and your business action to this function. The core SDK checks policy before the action runs and again before its result is released. A deny or review decision means the action never runs.

import { Veriproof } from '@veriproof/sdk-core';
import type { GovernedResult, IndustryFact, JsonValue } from '@veriproof/sdk-core';

const veriproof = Veriproof.fromEnv();

export async function runProtectedAction<TInput extends JsonValue, TValue>(
  request: TInput,
  action: (input: TInput, signal: AbortSignal) => Promise<TValue>,
): Promise<GovernedResult<TValue, TInput>> {
  // Catalog values for this vertical. Replace them with facts from the current workflow.
  const industry: IndustryFact[] = [
    { attribute: "education.student.success_risk_level", policyInput: "education_student_success_risk_level", value: "on_track" },
    { attribute: "education.early_alert.trigger_category", policyInput: "education_early_alert_trigger_category", value: "attendance_absence_threshold" },
    { attribute: "education.intervention.outcome", policyInput: "education_intervention_outcome", value: "student_engaged_retained" },
  ];

  // Policy runs before action() and again before the result is released.
  // A deny or review decision means action() never runs.
  return veriproof.govern(
    "higher.education.evaluate",
    request,
    ({ input, signal }) => action(input, signal),
    { industry },
  );
}

• Replace the sample values with facts from the current workflow. Rules read them under input.snapshot.industry.
• Test both permitted and blocked actions. Confirm that a blocked action never reaches your business function.
• Only completed, completed_with_warning, and transformed results carry a released value.

For review decisions, follow the Human Review guide to configure continuation. Observe remains available when you need to record activity without enforcing a decision.

Set up the Higher Education example. See the API reference for TypeScript, Python, or .NET.

Selected vocabulary categories

This page uses the vocabulary JSON distributed with the documentation. Check its version when comparing it with an installed SDK.

Download the vocabulary JSON for offline review or automated comparisons.

Use the SDK reference for configuration and supported APIs. Keep vocabulary selection separate from the compliance team's assessment of applicable requirements.