Student feedback made smart takes student evaluations to the next level

Meet Hubert, a chatbot for teachers

Here's how he will help you

Upload your students' email addresses and press 'Send'.

Hubert contacts every student individually through digital platforms.

Hubert uses AI and machine learning to interpret the feedback.

The results arrive in your inbox, complete with a compiled highlight summary.

From surveys to conversations

Almost a hundred years have passed since student evaluations of teaching first emerged. Other than moving from paper surveys to online quivalents, there hasn't been much change.

Engaging students in conversations rather than asking them to fill out forms is both natural and more fun. That means higher response rates and more qualitative data from your students.


Your data is automatically collected, analyzed and compiled to a few highlighted points that most students agree upon.


After you click ‘Send’ Hubert takes care of the rest. Students are engaged in a brief chat-session where valuable feedback to the teacher is obtained.


To both Hubert and us, student anonymity is vital. We want your students to be open and feel safe, and at the same time always offer you good and factual feedback. We make sure Hubert filters the results so that they are healthy and usable.

What students have to say about using Hubert

Features coming up

Feedback is crucial for a focused development and we want to remove as many hurdles as possible to receive and act upon it. Here's what we're working on right now:

Hubert will soon take care of all your feedback needs, from end-course evaluations to class-specific feedback that can be tracked over time.

Wouldn't it be great if evaluation results came with recommendations on best teaching practices, tips on pedagogic approaces, and brainy blackboard examples? Yes, we think so too. That's why Hubert is currently collecting data about teaching tactics, and soon he'll be ready to provide even more substantial insights.

Keeping track of student interests, previously taken classes, current class size, and other factors allows Hubert to compensate for certain biases like gender bias, interest bias, and class size bias.

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