AI Agent for Special Education: IEP Tracking, Accommodation Management, and Parent Updates
Build an AI agent that tracks Individualized Education Program goals, manages accommodation compliance, generates progress reports, and coordinates the special education team.
The Special Education Coordination Challenge
Special education is one of the most documentation-intensive areas of education. Each student with an Individualized Education Program (IEP) has specific goals, accommodations, service minutes, and progress benchmarks that must be tracked, reported, and coordinated across a team of teachers, specialists, and parents. Missing a compliance deadline or failing to implement an accommodation can have legal consequences. An AI agent can track these obligations systematically and ensure nothing falls through the cracks.
IEP Data Model
The IEP data model must capture goals, accommodations, service delivery, and team membership with precision.
from dataclasses import dataclass, field
from enum import Enum
from datetime import date, datetime
from typing import Optional
class GoalStatus(Enum):
NOT_STARTED = "not_started"
IN_PROGRESS = "in_progress"
MEETING_BENCHMARK = "meeting_benchmark"
MASTERED = "mastered"
NOT_MAKING_PROGRESS = "not_making_progress"
MODIFIED = "modified"
class AccommodationType(Enum):
TESTING = "testing"
CLASSROOM = "classroom"
BEHAVIORAL = "behavioral"
PHYSICAL = "physical"
TECHNOLOGY = "technology"
COMMUNICATION = "communication"
class ServiceType(Enum):
SPEECH_THERAPY = "speech_therapy"
OCCUPATIONAL_THERAPY = "occupational_therapy"
PHYSICAL_THERAPY = "physical_therapy"
COUNSELING = "counseling"
BEHAVIOR_SUPPORT = "behavior_support"
READING_SPECIALIST = "reading_specialist"
RESOURCE_ROOM = "resource_room"
class ComplianceStatus(Enum):
COMPLIANT = "compliant"
AT_RISK = "at_risk"
NON_COMPLIANT = "non_compliant"
@dataclass
class IEPGoal:
goal_id: str
area: str # reading, math, behavior, social, motor
description: str
baseline: str
target: str
measurement_method: str
status: GoalStatus = GoalStatus.NOT_STARTED
progress_notes: list[dict] = field(default_factory=list)
target_date: Optional[date] = None
@dataclass
class Accommodation:
accommodation_id: str
description: str
accommodation_type: AccommodationType
applies_to: list[str] = field(default_factory=list)
implementation_notes: str = ""
is_active: bool = True
@dataclass
class ServiceDelivery:
service_type: ServiceType
provider_name: str
minutes_per_week: int
location: str # general ed, resource room, therapy room
actual_minutes_delivered: list[dict] = field(
default_factory=list
)
@dataclass
class IEP:
student_id: str
student_name: str
grade_level: int
disability_category: str
case_manager: str
start_date: date
annual_review_date: date
triennial_review_date: date
goals: list[IEPGoal] = field(default_factory=list)
accommodations: list[Accommodation] = field(default_factory=list)
services: list[ServiceDelivery] = field(default_factory=list)
team_members: list[dict] = field(default_factory=list)
parent_contacts: list[dict] = field(default_factory=list)
@dataclass
class ProgressReport:
student_id: str
reporting_period: str
generated_at: datetime
goal_updates: list[dict] = field(default_factory=list)
service_delivery_summary: list[dict] = field(
default_factory=list
)
accommodation_compliance: list[dict] = field(
default_factory=list
)
recommendations: list[str] = field(default_factory=list)
Compliance Monitoring Engine
The compliance engine checks that all required services are being delivered and accommodations are being implemented.
IEPS: dict[str, IEP] = {}
def check_service_compliance(student_id: str) -> list[dict]:
iep = IEPS.get(student_id)
if not iep:
return []
compliance_issues = []
for service in iep.services:
if not service.actual_minutes_delivered:
compliance_issues.append({
"service": service.service_type.value,
"provider": service.provider_name,
"required_minutes": service.minutes_per_week,
"delivered_minutes": 0,
"status": ComplianceStatus.NON_COMPLIANT.value,
"action": "No service delivery logged this period.",
})
continue
recent_entries = service.actual_minutes_delivered[-4:]
avg_minutes = sum(
e.get("minutes", 0) for e in recent_entries
) / len(recent_entries)
if avg_minutes < service.minutes_per_week * 0.8:
status = ComplianceStatus.NON_COMPLIANT
action = (
f"Average {avg_minutes:.0f} min/week vs "
f"required {service.minutes_per_week}. "
f"Schedule make-up sessions."
)
elif avg_minutes < service.minutes_per_week:
status = ComplianceStatus.AT_RISK
action = "Slightly below target. Monitor closely."
else:
status = ComplianceStatus.COMPLIANT
action = "On track."
compliance_issues.append({
"service": service.service_type.value,
"provider": service.provider_name,
"required_minutes": service.minutes_per_week,
"avg_delivered_minutes": round(avg_minutes),
"status": status.value,
"action": action,
})
return compliance_issues
def generate_progress_report(student_id: str) -> dict:
iep = IEPS.get(student_id)
if not iep:
return {"error": "IEP not found"}
goal_updates = []
for goal in iep.goals:
latest_note = (
goal.progress_notes[-1] if goal.progress_notes else {}
)
goal_updates.append({
"area": goal.area,
"goal": goal.description,
"status": goal.status.value,
"baseline": goal.baseline,
"target": goal.target,
"current_performance": latest_note.get(
"performance", "No data"
),
"on_track": goal.status in (
GoalStatus.IN_PROGRESS,
GoalStatus.MEETING_BENCHMARK,
GoalStatus.MASTERED,
),
})
service_summary = check_service_compliance(student_id)
# Check accommodation implementation
accommodation_status = []
for acc in iep.accommodations:
if acc.is_active:
accommodation_status.append({
"accommodation": acc.description,
"type": acc.accommodation_type.value,
"applies_to": acc.applies_to,
})
days_to_annual = (iep.annual_review_date - date.today()).days
recommendations = []
if days_to_annual <= 60:
recommendations.append(
f"Annual IEP review due in {days_to_annual} days. "
f"Schedule team meeting."
)
goals_not_progressing = [
g for g in iep.goals
if g.status == GoalStatus.NOT_MAKING_PROGRESS
]
if goals_not_progressing:
recommendations.append(
f"{len(goals_not_progressing)} goal(s) not making "
f"progress. Consider modifying goals or strategies."
)
return {
"student": iep.student_name,
"grade": iep.grade_level,
"case_manager": iep.case_manager,
"goals": goal_updates,
"services": service_summary,
"accommodations": accommodation_status,
"recommendations": recommendations,
"annual_review_date": iep.annual_review_date.isoformat(),
"days_to_annual_review": days_to_annual,
}
Agent Tools and Assembly
from agents import Agent, function_tool, Runner
import json
@function_tool
def get_iep_summary(student_id: str) -> str:
"""Get a summary of a student IEP including goals and services."""
report = generate_progress_report(student_id)
return json.dumps(report)
@function_tool
def check_compliance(student_id: str) -> str:
"""Check service delivery compliance for a student."""
issues = check_service_compliance(student_id)
return json.dumps(issues) if issues else "No compliance data."
@function_tool
def log_goal_progress(
student_id: str,
goal_id: str,
performance: str,
notes: str,
) -> str:
"""Log progress toward an IEP goal."""
iep = IEPS.get(student_id)
if not iep:
return "IEP not found."
for goal in iep.goals:
if goal.goal_id == goal_id:
goal.progress_notes.append({
"date": date.today().isoformat(),
"performance": performance,
"notes": notes,
"logged_by": "agent",
})
return json.dumps({
"status": "Progress logged",
"goal": goal.description,
"total_entries": len(goal.progress_notes),
})
return "Goal not found."
@function_tool
def get_upcoming_reviews() -> str:
"""Get all IEPs with upcoming annual or triennial reviews."""
today = date.today()
upcoming = []
for student_id, iep in IEPS.items():
days_annual = (iep.annual_review_date - today).days
days_triennial = (iep.triennial_review_date - today).days
if days_annual <= 90 or days_triennial <= 90:
upcoming.append({
"student": iep.student_name,
"student_id": student_id,
"case_manager": iep.case_manager,
"annual_review": iep.annual_review_date.isoformat(),
"days_to_annual": days_annual,
"triennial_review": (
iep.triennial_review_date.isoformat()
),
"days_to_triennial": days_triennial,
})
upcoming.sort(key=lambda u: min(
u["days_to_annual"], u["days_to_triennial"]
))
return json.dumps(upcoming) if upcoming else "No upcoming reviews."
sped_agent = Agent(
name="Special Education Coordinator",
instructions="""You are a special education coordination agent.
Help case managers track IEP goals, monitor service delivery
compliance, log progress data, and prepare for reviews. Be
precise with compliance data — this has legal implications.
When service minutes are below required levels, flag it
immediately with specific remediation steps. Never make
clinical or diagnostic judgments. Always recommend involving
the full IEP team for significant changes.""",
tools=[
get_iep_summary,
check_compliance,
log_goal_progress,
get_upcoming_reviews,
],
)
Compliance Dashboard Pattern
For case managers overseeing multiple students, a dashboard view is essential.
See AI Voice Agents Handle Real Calls
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def generate_caseload_dashboard(case_manager: str) -> dict:
students = [
iep for iep in IEPS.values()
if iep.case_manager == case_manager
]
dashboard = {
"case_manager": case_manager,
"total_students": len(students),
"compliance_summary": {
"compliant": 0,
"at_risk": 0,
"non_compliant": 0,
},
"upcoming_reviews": [],
"goals_needing_attention": [],
}
today = date.today()
for iep in students:
# Service compliance
issues = check_service_compliance(iep.student_id)
for issue in issues:
status = issue["status"]
if status in dashboard["compliance_summary"]:
dashboard["compliance_summary"][status] += 1
# Upcoming reviews
days_to_review = (iep.annual_review_date - today).days
if days_to_review <= 60:
dashboard["upcoming_reviews"].append({
"student": iep.student_name,
"review_date": iep.annual_review_date.isoformat(),
"days_remaining": days_to_review,
})
# Goals needing attention
for goal in iep.goals:
if goal.status == GoalStatus.NOT_MAKING_PROGRESS:
dashboard["goals_needing_attention"].append({
"student": iep.student_name,
"goal_area": goal.area,
"goal": goal.description[:80],
})
return dashboard
FAQ
How does the agent ensure IDEA compliance for service delivery tracking?
The agent tracks actual minutes delivered against the IEP-mandated minutes for each service type. When delivery falls below 80% of the required amount, it flags the case as non-compliant and recommends make-up sessions. All service delivery data is timestamped and attributed to the provider for audit purposes. The system generates the documentation trail required by IDEA regulations.
Can the agent help prepare for IEP meetings?
Yes. Before an annual review, the agent compiles a comprehensive report including goal progress data across all reporting periods, service delivery compliance percentages, accommodation implementation status, and data-driven recommendations for goal modification. This report gives the IEP team concrete data to inform decisions rather than relying on subjective impressions.
How does the agent handle confidentiality of special education records?
Special education records are protected under FERPA and IDEA with even stricter requirements than general education records. The agent enforces role-based access — only IEP team members listed in the student record can access data. All queries are logged with the requesting user identity and timestamp. The agent never includes student names in error messages or logs, using only student IDs for system-level operations.
#AIAgents #EdTech #SpecialEducation #Python #IEPManagement #AgenticAI #LearnAI #AIEngineering
CallSphere Team
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