Courses as pathways
Topics of lessons and practice sets, grouped into pathways and modules. A pathway can be sequential, where each step unlocks the next, or open, where students choose the order.
For teachers
Courses and AI authoring
Build your course as a pathway of lessons and practice sets. The AI assistant drafts lessons and exercises from your own material, and nothing reaches students until a teacher approves it.
A simulated walk through AdaptIQ. A teacher attaches a lecture in the AI chat and asks for a four-question quiz. The AI drafts it, including a question on an ECG with its answer key; the teacher moves one wave label the AI placed wrong and accepts the exercises.
One platform for the whole course
Courses, classes, grading and progress in one place.
The basics of a university learning platform, designed from the first line of code around how students learn and remember.
Classes
Every class has its own feed. Teachers post announcements, polls and files there and tell students what to work on next; students comment and vote.
Grading
Answers are graded on the server, and every exercise can carry an explanation. Image annotations can go to a teacher’s grading queue instead.
Progress
Each student sees their own accuracy per topic. Teachers see how the class is doing topic by topic, and a weekly league ranks the class by practice points.
AI authoring
AI authoring, with teachers in charge.
Upload what you already teach from. The assistant reads it, proposes a pathway and writes lessons and exercises step by step. Nothing reaches a student until a teacher has accepted and approved it.
- 01
Bring your material
PDF, Word, PowerPoint, Excel, CSV, Markdown or images. Materials are extracted, indexed and searchable; a vision model describes the images.
- 02
Get a proposed pathway
The AI reads a document’s outline and pages and proposes topics, lessons and practice sets — each with the page range it comes from.
- 03
Generate, step by step
“Generate content” writes every lesson in the material’s language and 3–8 exercises per practice set. A progress bar shows how far it has got and what it has cost so far. You can stop it at any time; a step already running still finishes.
- 04
Accept, change or discard
Accept one proposal, everything below it, or a whole batch. Ask for a change and compare before and after. Try any exercise in the real student player first.
- 05
Approve before students see it
Accepted AI content is marked as AI-made and waits for a teacher’s approval. Publishing is refused while unapproved AI content remains.
Also in the chat
How AI authoring works →- Type “@” to point the AI at a specific lesson, set or exercise.
- The AI asks clarifying questions, with quick-reply chips.
- It rewrites a lesson and keeps your micro questions in place.
- “How are students doing?” — answered from aggregate numbers only, never names.
- Several conversations in parallel, with unread markers.
From a PDF to a learning pathway: how AdaptIQ’s AI authoring works
A lecture PDF goes in; a proposed pathway of lessons and practice comes out. Here is how AdaptIQ’s AI authoring works, step by step — and why the teacher has the final say.
Read article →Streaks without guilt: the rules behind our motivation design
Fear of loss is an easy way to bring students back: a broken streak, a countdown, a guilt-tripping reminder. AdaptIQ’s motivation design starts from the opposite rule.
Read article →A different physics problem for every student
When every student gets the same numbers, answers travel faster than understanding. AdaptIQ’s biomechanics module generates a fresh statics problem for every student and every attempt — and checks the answer on the server.
Read article →See AdaptIQ in action.
Book a demo and we’ll walk you through the AI workspace, the student player and the review flow — on a phone and on a desktop.