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 Assignment Grading
Multiple choice quizzes, numerical problems, fill-in-the-blank exercises, and matching questions are graded in under 10 seconds per submission. The AI checks answers against the instructor's key, calculates the score, and generates a short explanation for each wrong answer. An instructor with 135 students and a weekly 20-question quiz saves 4-5 hours every week.
Smart Deadline Reminders
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. Quizzes get graded. Reminders go out. Forum summaries land in your inbox. You see a weekly digest of what the AI handled, what it escalated, and how students are engaging. If something looks off, adjust the rules.
A week in the life of the AI assistant
Here is what the virtual teaching assistant handled for Dr. Sharma's Business Communication course (135 students) during a typical week.
BCOM 201 — Weekly AI Assistant Report
Week of March 3–7, 2025
Student Questions Answered
87Top topics: citation format (23), midterm date/location (19), rubric clarification (14), submission instructions (12), office hours schedule (9), other (10)
Assignments Graded
131Quiz 4 (multiple choice, 25 questions): graded in 14 minutes total. Average score: 78%. AI flagged 3 questions where more than 60% of 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
Time saved this week: approximately 7.5 hours of instructor time. 87 Q&A responses (est. 2 min each = 2.9 hrs), 131 quiz grades (est. 1.5 min each = 3.3 hrs), forum summary (est. 45 min), reminder management (est. 30 min).
Bring Your Own Model
The virtual teaching assistant runs on whichever AI model your institution selects. OpenAI, Anthropic, Google Gemini, or a locally-hosted model. Your IT team plugs in the API key and controls which model handles student interactions. Course content and student questions go directly from your OpenEduCat instance to the model provider. We never see, store, or route that data.
For institutions where student questions might contain sensitive information, a local model keeps everything on-premises. No data leaves your network.
Frequently Asked Questions
Common questions about the AI virtual teaching assistant.
See how the teaching assistant works with AI plagiarism detection and learning analytics. Or explore all 91 AI tools.
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