What it does
Four capabilities that handle the repetitive work so faculty and TAs can focus on the interactions that require a human.
Student Q&A from Course Materials
Students ask questions in natural language and the AI answers from the syllabus, lecture notes, and FAQ documents the instructor uploaded. "When is the midterm?" gets answered instantly at 11pm on a Sunday. "What citation format do we use?" pulls the answer from the assignment guidelines. The instructor never sees these questions unless the AI cannot answer them.
Objective Quiz Feedback Drafting
For multiple choice quizzes, numerical problems, fill-in-the-blank exercises, and matching questions, the AI checks each submission against the instructor's answer key and drafts a suggested score with a short explanation for each wrong answer. The instructor reviews the batch and releases results — nothing reaches a student record until a human approves it. What changes is the starting point: review-and-release instead of mark-from-scratch.
Smart Deadline Reminders
Following reminder rules the instructor configures, the AI sends personalized reminders based on each student's status. A student who already submitted does not get a nagging email. A student who opened the assignment but has not submitted gets a nudge 48 hours before the deadline. A student who has not opened it at all gets an earlier reminder with a direct link to the assignment page.
Discussion Forum Summaries
Instead of reading through every post in a 50-student discussion, the instructor gets a daily or weekly summary. The AI identifies the main topics discussed, highlights unanswered questions that need instructor attention, and flags posts with high engagement. A 10-minute scroll through 80 posts becomes a 90-second read.
How it works
Set it up once per course. The AI handles the rest for the entire semester.
Upload course materials
Drop your syllabus, assignment guidelines, FAQ document, and any reference materials into the course content area. The AI indexes everything. If a student asks a question and the answer is on page 3 of the syllabus, the AI finds it and quotes the relevant section.
Configure response rules
Set which types of questions the AI should answer directly (logistics, factual course info) and which should be routed to you (grade disputes, accommodation requests, anything subjective). Set grading rules for objective assessments. Choose reminder frequency and timing.
The assistant runs in the background
Students interact with the AI through the course page. Questions get answered from your materials. Quiz feedback drafts queue up for your review and release. Reminders go out on the rules you set. Forum summaries land in your inbox. You see a weekly digest of what the AI handled, what it escalated, and how students are engaging — and every AI action is audit-logged. If something looks off, adjust the rules.
A week in the life of the AI assistant
An illustrative weekly report for a 135-student Business Communication course, showing the kind of work the assistant handles and escalates.
BCOM 201 — Weekly AI Assistant Report (illustrative)
Sample Week
Student Questions Answered
87Top topics: citation format (23), midterm date/location (19), rubric clarification (14), submission instructions (12), office hours schedule (9), other (10)
Quiz Feedback Drafts Prepared
131Quiz 4 (multiple choice, 25 questions): suggested scores and per-question feedback drafted against the answer key, awaiting instructor review and release. AI flagged 3 questions where most students answered incorrectly.
Reminders Sent
42Essay draft deadline reminders: 28 students who had not submitted received a 48-hour reminder. 14 students who opened but did not submit received a 24-hour nudge. 93 students who already submitted received nothing.
Escalated to Instructor
52 grade dispute requests, 1 accommodation question, 1 question about content not in course materials, 1 personal situation affecting attendance
The pattern that matters: the AI drafted and routed; the instructor decided. Every Q&A response, feedback draft, and reminder in this report is captured in the audit log, and the five escalated items went straight to a human — AI advises, humans decide.
Bring Your Own Model
The virtual teaching assistant runs on the AI endpoint your institution already governs — Azure OpenAI, Google Vertex AI, AWS Bedrock, or another compatible provider. Your IT team registers the endpoint and controls which model handles student interactions. Course content and student questions go from your OpenEduCat instance to that endpoint under your own agreement and region. We never see, store, or route that data.
For institutions where student questions might contain sensitive information, guardrails, spending budgets, and audit logs apply to every interaction — under the data terms your institution already negotiated with its provider.
Frequently Asked Questions
Common questions about the AI virtual teaching assistant.
Read our honest position on AI detection and how the assistant pairs with advisory learning analytics. Or explore all 91 AI tools.
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