Alps records how each student’s code took shape. Then it points you to the few moments that matter.
See where a student got stuck, what they kept reworking, and whether they worked steadily or in one late sitting.
Replay one student’s afternoon, see what Alps flagged, and compare any two moments.
A scripted walkthrough with sample data. The panels are the ones teachers use.
You’ve asked these about a submission. Alps answers them in about a minute.
Alps shows which lines a student kept coming back to across the whole session.1 Now you can see what to reteach.
Point to something specific: the moment the work turned, and what the student did next.
Alps groups work into sittings, so a steady week looks different from one long evening. Use it to start a conversation.
Alps won’t guess. It shows what was recorded, like a block pasted in all at once. You make the call.
You don’t have time to read a chart for every student. Alps points out a few key moments and stays quiet the rest of the time.
The same error came back run after run. That’s a well-known sign a student is stuck.2
Code that ran earlier broke after a later change and stayed broken. That’s usually where a student got lost.
A large block arrived in one paste from outside Alps. The observation records only how it entered the editor. It doesn’t say who wrote it.
Copying from the Alps textbook is normal work and is never flagged. A dash means nothing stood out, which is the usual case. During class, Live Activity shows who has stopped working, so you know who to visit first.
Detectors guess, and that can get students in trouble. Alps shows you what was recorded and lets you decide.
| Feature | Alps Process Insights | A typical AI detector |
|---|---|---|
| Verdict on the student | None. You decide | An accusation |
| What it reports | What was recorded | A probability it guessed |
| Risk to a student who did nothing wrong | No guesses to get wrong | False positives |
| Effect on grading | None | Often flags or blocks |
| Copying from your own course material | Treated as normal work | Often flagged |
| Time it didn’t record | Shown as gaps | Filled in by the model |
Computing education researchers have recorded how new programmers work for years.3 Alps puts that record in front of you while you grade. Pair it with semantic checks on how Python and Java code was written, and the help each student used in Adaptive Coding.
On any coding activity, students can watch their solution take shape, any time they like. That helps when code worked an hour ago and doesn’t now.
“It worked before I changed something.”
Every teacher has heard it. Now students can find that moment themselves, and so can you.
Some of the research this feature builds on. Alps isn’t affiliated with the authors or projects cited.
See where each student got stuck and what they reworked, without a chart to read for each one. Start with the free Educator Basic plan.