Learning analytics
See where your course needs help.
Learning analytics surface difficult topics while learning is still happening. Educators see aggregated patterns from exercises, tutor conversations, and activity, without exposing private messages or any individual's performance.
Learning analytics
Three views of where your course stands.
Patterns, not profiles
Educators see developments and difficulties at course level. The analysis supports teaching decisions, not the surveillance of individual learners.
214 active learners · sample data
Course level · no individual profiles
Exercises reveal specific misconceptions
Answer distributions show which options learners pick most and which questions need another round of explanation.
Tutor questions become topics
Anonymized conversations are grouped into concepts, knowledge gaps, and misconceptions. Educators see frequent topics, never the wording of individual chats.
Topics, never individual messages
Closer look
Insight into learning, without surveillance.
What exercises reveal about your course
For shared exercises, acemate shows the answer distribution and highlights the questions the course finds hardest. Educators can tell whether a concept landed or whether one misconception runs through the whole group. The findings feed directly into the next session, a review, or a new follow-up exercise.
Every AI tutor chat, turned into teaching insight
acemate aggregates every conversation students have with the AI tutor into in-depth, always anonymous reports, grouped by topic. You see which concepts drive the most questions, where misconceptions keep returning, and how understanding shifts across the week. Individual messages stay private. What used to be a black box of AI use becomes a didactic signal you can act on in the next session.
One connected system
Related features
Who it serves
Who it is for
Your content. Your data. Your control.
acemate runs exclusively in EU data centers, complies with the GDPR and never uses your content to train AI models.
More on security & privacyFrequently asked questions
Depending on the course, acemate analyzes activity, completed exercises, answer distributions, learning progress, and anonymously summarized topics from the AI tutor.
The analytics described here show aggregated patterns at course level. They are not individual performance monitoring.
No. Educators see topic summaries and frequencies, never the wording of individual conversations.
That depends on group size and activity. Reliable patterns only emerge once enough learners are active, which also keeps individuals from being identifiable.
No. They provide formative orientation and help improve teaching. They do not replace formal assessment.
Aggregated usage and learning signals can complement evaluations. We define validity, methodology, and privacy together for each initiative.
See earlier what matters later.
Using a realistic course scenario, we show you how acemate surfaces difficult topics and gives educators concrete starting points.