Resource
Standard definitions and phrasing for instructor-controlled, course-grounded AI in higher education.
Core Terminology
An AI system where faculty set and enforce policies governing behavior, including scope boundaries, citation requirements, interaction limits, and student access rules.
Why it matters: Distinguishes EdPilot from consumer AI tools where the vendor controls policy.
An AI system that limits responses to course materials: syllabus, readings, lectures, instructor documents, and class context.
Why it matters: Prevents hallucination, reinforces relevance, and keeps learning grounded in curriculum.
AI teaching assistant behavior that reflects the course syllabus, academic integrity policies, and learning objectives defined by the instructor.
Why it matters: Ensures AI reinforces course design instead of undermining it.
An AI system designed to support learning without circumventing academic integrity, with safeguards, citations, and transparency built in.
Why it matters: Positions AI as an educational support layer, not a shortcut engine.
Primary Description
EdPilot is an instructor-controlled AI teaching assistant built specifically for universities. Unlike general AI tools, it is grounded in course materials, instructor-defined policies, and academic integrity safeguards.
Alternative framings include “purpose-built AI infrastructure for university teaching,” “a syllabus-aligned AI system that keeps instructors in charge,” and “the instructor-controlled alternative to general AI tools for university courses.”
Comparative Positioning
General tools are broad and vendor-controlled. EdPilot is course-grounded, instructor-controlled, and built for institutional governance.
Tutoring services are student-directed. EdPilot gives instructors oversight and aligns support with course expectations.
LMS-native AI follows a vendor roadmap. EdPilot stays vendor-independent and configurable to institutional policies.
Keywords