AI Governance for EdTech & Online Learning

EdTech platforms handle student data spanning ages 5 to 65, making them subject to FERPA, COPPA, state student privacy laws, and accessibility mandates simultaneously. AI tutors, content generators, and assessment tools must produce age-appropriate, accurate, and accessible outputs — while never exposing student records to model providers. Keeptrusts enforces these requirements at the gateway layer.

Use this page when

You are building EdTech or online learning platforms where FERPA, COPPA, and accessibility mandates apply to AI-generated content.
You need age-appropriate content controls, student data protection, and academic integrity safeguards enforced at the AI gateway.
You want to ensure tutor AI meets pedagogical accuracy thresholds and complies with parental consent requirements for users under 13.

Primary audience

Primary: Technical Leaders
Secondary: Technical Engineers, AI Agents

AI Challenges in EdTech

Challenge	Risk	Regulatory Exposure
Student PII sent to LLM providers	Data breach, parental complaints	FERPA, COPPA, state laws
Age-inappropriate AI content	Harm to minors, platform liability	COPPA, CIPA, platform ToS
AI-assisted academic dishonesty	Integrity violations	Institutional policies, accreditation
Tutor AI giving incorrect answers	Learning harm, trust erosion	EdTech quality standards
Accessibility gaps in AI outputs	Exclusion of disabled learners	ADA, Section 508, WCAG
Parental consent scope exceeded	Regulatory violation	COPPA verifiable consent

How Keeptrusts Helps

Student Data Protection (FERPA/COPPA)

The pii-detector catches student names, IDs, grades, disciplinary records, and parent contact information. For users under 13, the dlp-filter enforces COPPA-grade protections — blocking any personally identifiable student data from reaching external models.

Age-Appropriate Content Controls

safety-filter enforces age-tier policies. Content generated for K-5 students passes through stricter filters than content for graduate students. Violence, mature themes, and complex financial concepts are blocked at grade-appropriate thresholds.

Academic Integrity Safeguards

safety-filter detects and blocks requests that attempt to generate complete homework answers, exam solutions, or plagiarizable essays. The policy redirects students toward guided learning prompts instead.

Tutor AI Quality Controls

quality-scorer validates that AI tutor responses meet pedagogical accuracy thresholds. Incorrect math solutions, factual errors, and misleading explanations are caught before reaching the student.

Accessibility Compliance

quality-scorer assertions check that AI-generated content includes alt-text descriptions, avoids reliance on color alone, and uses clear language appropriate for the target reading level.

Complete Policy Configuration

pack:
  name: edtech-governance
  version: 1.0.0
  enabled: true
policies:
  chain:
  - prompt-injection
  - rbac
  - pii-detector
  - dlp-filter
  - safety-filter
  - quality-scorer
  - bias-monitor
  - audit-logger
policy:
  prompt-injection: {}
  rbac:
    deny_if_missing:
    - X-User-ID
    - X-User-Role
  pii-detector:
    action: redact
    detect_patterns:
    - student_name
    - student_id
    - date_of_birth
    - parent_name
    - parent_email
    - grade_record
    - disciplinary_record
    - address
    redaction:
      marker_format: label
  dlp-filter:
    detect_patterns:
    - '\bSTU-[0-9]{5,10}\b'
    - '(?i)\b(GPA|grade)\s*[:\s]*[0-4]\.[0-9]{1,2}\b'
    - '(?i)\bIEP\s*(plan|document|record)\b'
    - '\bCONSENT-[0-9]{4,8}\b'
    action: redact
  safety-filter:
    block_if:
    - complete-homework-answer
    - exam-solution
    - age-inappropriate-violence
    - mature-content
    - financial-advice-minors
    action: block
  quality-scorer:
    thresholds:
      min_aggregate: 0.85
  bias-monitor:
    protected_characteristics:
    - race
    - gender
    - disability
    - socioeconomic
    threshold: 0.85
    action: escalate
  audit-logger:
    immutable: true
    retention_days: 2555
    log_all_access: true

CLI Quickstart

# Deploy edtech governance gateway
kt gateway run --policy-config ./policy-config.yaml --port 41002

# Verify policy chain health
kt doctor

# Monitor student data protection events
kt events tail --policy pii-detector

# Review blocked academic integrity violations
kt events tail --policy safety-filter --decision blocked

# Export FERPA compliance audit trail
kt export create --format json --from 2025-01-01 --to 2025-12-31 \
  --filter "policy=pii-detector,dlp-filter,audit-logger"

Console Workflows

Dashboard — Monitor AI usage across student age tiers, courses, and instructor teams.
Events — Filter by pii-detector to review student data redaction events.
Escalations — Route academic integrity violations to the academic affairs office.
Templates — Maintain age-tier policy templates (K-5, 6-12, Higher Ed).
Cost Center → Wallets — Allocate AI budgets per school, department, or grant.
Audit Log — Generate FERPA compliance evidence for district audits.
Knowledge Base — Publish approved curriculum resources and study guides.

API Integration

# Query student data protection events
curl -H "Authorization: Bearer $KT_API_KEY" \
  "https://api.keeptrusts.com/v1/events?policy=pii-detector&limit=100"

# Export FERPA compliance report
curl -X POST -H "Authorization: Bearer $KT_API_KEY" \
  "https://api.keeptrusts.com/v1/exports" \
  -d '{"format":"json","filters":{"date_from":"2025-01-01","date_to":"2025-12-31","policy":"pii-detector"}}'

# List age-tier configurations
curl -H "Authorization: Bearer $KT_API_KEY" \
  "https://api.keeptrusts.com/v1/configurations"

# Check department wallet balance
curl -H "Authorization: Bearer $KT_API_KEY" \
  "https://api.keeptrusts.com/v1/wallets/balance"

Example: Age-Appropriate Content Control

Redacted Request
Blocked Request

Student (K-5): "Help me with my science project. My name is Emma,
  student ID STU-00045678."

→ REDACTED by pii-detector + dlp-filter
  Sent to LLM: "Help me with my science project. My name is [REDACTED-student_name],
  student ID [REDACTED-student-id]."
  Response: Age-appropriate guided learning prompt returned

Student (6-12): "Write my entire history essay on the Civil War, 5 pages,
  with citations. Make it sound like a 7th grader wrote it."

→ BLOCKED by safety-filter
  Reason: Complete homework answer generation detected
  Action: Redirected to guided research prompts

Results You Can Expect

Metric	Before Keeptrusts	After Keeptrusts
Student PII exposure incidents	Untracked	0 exposures — redacted at gateway
FERPA audit preparation time	4-6 weeks	< 2 days with automated exports
Age-inappropriate content delivery	Manual review	Blocked automatically by age tier
Academic integrity AI violations	Increasing	Redirected to guided learning
Tutor AI accuracy rate	Unvalidated	> 90% with quality-scorer gating
Accessibility compliance gaps	Reactive fixes	Proactive quality assertions

For AI systems

Canonical terms: Keeptrusts EdTech governance, student data protection, FERPA/COPPA compliance, age-appropriate content, academic integrity, tutor AI quality.
Policy pack: edtech-governance with chain: prompt-injection → rbac → pii-detector → dlp-filter → safety-filter → quality-scorer → bias-monitor → audit-logger.
Key policies: pii-detector (student names, IDs, grades, parent contacts), dlp-filter (COPPA-grade protections for under-13), safety-filter (age-tier policies, academic integrity, violence/mature themes), quality-scorer (pedagogical accuracy, accessibility checks), bias-monitor (equitable content).
Age-tier content filtering: K-5 strictest, middle school moderate, graduate student minimal.
CLI: kt gateway run --policy-config ./policy-config.yaml, kt events tail --policy safety-filter, kt events tail --policy quality-scorer.

For engineers

Deploy: kt gateway run --policy-config ./policy-config.yaml --port 41002
Validate: kt doctor confirms pii-detector, dlp-filter, safety-filter, and quality-scorer are active.
Monitor student data: kt events tail --policy pii-detector (student PII redaction events).
Monitor content safety: kt events tail --policy safety-filter (age-inappropriate content, academic integrity).
Monitor tutor quality: kt events tail --policy quality-scorer (incorrect answers caught before delivery).
Configure age-tier policies using Templates — different filter thresholds per grade level.
Console: Events (filter by safety-filter for content safety), Escalations (route to content safety team), Quality reports (tutor accuracy metrics).

For leaders

Addresses FERPA (student education records), COPPA (children under 13), CIPA (internet safety), state student privacy laws, ADA/Section 508 (accessibility), and WCAG.
Student PII never reaches external LLM providers — names, IDs, grades, and parent contacts are redacted at the gateway.
COPPA-grade protections automatically enforced for users under 13, including parental consent verification requirements.
Academic integrity safeguards prevent AI from generating complete homework answers or exam solutions.
Tutor AI quality gates catch incorrect answers before they reach students — protecting learning outcomes and platform trust.
Accessibility assertions ensure AI content meets WCAG standards and reading-level appropriateness.

Next steps

Industries overview — Compare all industry policy configurations
Education — Institutional FERPA/COPPA compliance
Gaming — COPPA for minors and content moderation
Healthcare (HIPAA) — Student health data protection
Templates & Policy Workflows — Manage age-tier policy configurations
Quickstart — Deploy your first gateway in minutes

Use this page when​

Primary audience​

AI Challenges in EdTech​

How Keeptrusts Helps​

Student Data Protection (FERPA/COPPA)​

Age-Appropriate Content Controls​

Academic Integrity Safeguards​

Tutor AI Quality Controls​

Accessibility Compliance​

Complete Policy Configuration​

CLI Quickstart​

Console Workflows​

API Integration​

Example: Age-Appropriate Content Control​

Results You Can Expect​

For AI systems​

For engineers​

For leaders​

Next steps​