Your instructor teaches the class. We build what students do between sessions.
Alma's learning engineers build the practice, the AI teaching assistant and the feedback around your live sessions, from the instructor's own material. Class time goes to what only the instructor can do.
- Mon
- TueLive session
- Wed
- ThuLive session
- Fri
- Who teaches
- Your instructor, live
- Where it runs
- Any LTI-compliant LMS
- Start with
- One module
- Your team's time
- About a day of decisions
Six additions around the sessions, each built from the instructor’s own material.
A lecture students can stop and question, before class
Material the instructor chooses to move out of class time becomes a video lecture, with an AI teaching assistant that answers from the course itself.
An AI tutor on each reading
A one-to-one chat that answers from the reading the instructor assigned, there when the student asks.
Practice out loud with an AI character
Each role-play is built from one of the instructor's cases. The AI character pushes back on anything vague.
Feedback that says why points were lost
Graded work comes back quoting the student's own words and naming what is missing.
A considered reply to every discussion post
From the course's AI teaching assistant, labeled as AI in the thread, and from classmates.
The instructor sees who prepared
Who did the preparation, who is flagged at risk, and where students stop, in time for the next session.
One class meeting, with the work before and after it.
In the hours between sessions, many students say they are teaching themselves. Here is one meeting of a negotiation course, with those hours built.
Before class
Video lectureStop at a slide and askReadingTalk it through with an AI tutorStudents watch a short lecture on the framework, stopping to ask about any slide, then talk the case reading through with an AI tutor, so they arrive ready to negotiate.
In class
LiveThe instructorNothing we build is in the roomThe instructor runs the case as a live negotiation between students.
After class
Practice conversationAI character, then feedbackLearning gameA graded checkEach student negotiates again, out loud, with an AI character built from the same case, and gets feedback on what they said. A learning game checks what stuck.
What the instructor sees
- Did the preparation21 of 24
- Flagged at risk2
- Most questions onSlide 14
Who did the preparation, who is flagged at risk, and where the class got stuck, in time for the next session.
The instructor stays the teacher, and decides which roles stay human.
The live sessions
What happens in the room, or on the call, is the instructor's. So is the interaction with students that accreditors look for, in the sessions, in feedback and in office hours. The AI teaching assistant supports that teaching and does not replace it.
Office hours and every other human role
You decide role by role. The AI teaching assistant, tutor and characters are each labeled as AI wherever a student meets them.
The grade
You choose how work is graded: AI-graded and human-confirmed, fully by your instructors, or fully by AI. The instructor named on the course stays responsible for the grade.
The learning outcomes approved for the course
Every activity we add is traced to them and carries a time estimate your team can check against your credit-hour policy.
The instructor's face and voice
A video lecture shows your faculty in their own face and voice, with their written agreement. An instructor can keep every lecture live and take the other additions.
The instructor chooses from a short menu. We do the production.
A pilot on one module takes a few weeks to build, and the decisions take about a day of your team's time. If an instructor wants a tool to make activities alone this afternoon, we are the wrong choice: Alma is a service, and its learning engineers do the building.
Before you commit
Free example
Alma's learning engineers
We build an example around one of your sessions, from your own material, at no cost.
Your people
Nothing committed yet
Send the material for one session and judge the example before you commit.
Step 1
Send what you teach from
Alma's learning engineers
We read the syllabus, slides, readings, cases and class schedule.
Your people
Conversation 1 of 3
The instructor sends them as they are. Nothing needs tidying first.
Step 2
We propose
Alma's learning engineers
We propose what goes before and after each session.
Your people
Conversation 2 of 3
The instructor and your learning designers approve the design before anything is produced.
Step 3
We build it in your LMS
Alma's learning engineers
Alma's learning engineers build it. You pay a fee for the work, with no share of tuition, and own what is built.
Your people
Conversation 3 of 3
Every module is open to review, including against your accessibility guidance, before a student sees it.
More ways to support live teaching.
Course refresh & redesign
When the course is already online and recorded, and nobody teaches it live.
See adding AIFull course development
When the course does not exist yet beyond slides and a syllabus.
See new coursesLearning analytics and outcomes
Who is flagged at risk and where students stop, in every course we build.
See learning analyticsBring the syllabus of a course you teach live.
Book a demo and we will walk through what would go before and after one of your sessions.