Create your own free account here. Note the user docs are outdated with respect to the screenshots showcased over there.
MaMpf is an innovative open source e-learning platform for the mathematical sciences developed at the Institute for Mathematics at Heidelberg University. It's actively used in teaching and learning; you can register for free here (no student email required). Our platform is fully available in English & German.
MaMpf aims to be a hypermedia system for mathematical content. Like moodle, it provides a platform for lecturers to upload & organize their teaching material including videos and scripts. But MaMpf goes beyond that and eases learning through interconnected contents:
- 🎞 Lecture videos can be enriched with a navigation that allows students to jump to specific parts of the video, e.g. mathematical definitions, theorems, examples etc. References to other media are also possible, e.g. to different lecture videos / quizzes / worked examples etc.
- 🏷 Any media can be tagged with keywords. This allows students to easily find content related to a specific topic and discover how items are connected in a graph view.
- 🕹 Interactive quizzes allow students to test their understanding of the material. The system can automatically evaluate the answers and provide direct feedback, e.g. explain why an answer is wrong or provide a link to the relevant part of the video or an additional "worked example" video.
- 👩🏫 Students can sign up for tutorials and form teams themselves. Tutors are then able to manage the groups and upload corrected homework assignments for their students.
- 🗨 A comment system allows students to ask questions about the material in the context of the specific video/script or in a general forum. Lecturers will get a notification when a new comment is posted (of course adjustable). Students may choose their own alias name when posting comments in order to stay anonymous.
This is just a brief overview of the feature set. You may think of MaMpf as a mix of Moodle, Khan Academy and YouTube. But it's more than that as features are tailored to the needs of the mathematical sciences and a university context. Start exploring MaMpf here.
To give you a closer look, here are some screenshots taken from our live system:
Video player
Try out the video player here (even without any account). Press i
to open the outline on the right. It can hold references to other parts of the video or other items in the whole MaMpf database. The player makes use of WebVTT and HTML5 video capabilities of modern browsers.
Graph tag search
MaMpf is equipped with a tagging system and rich visualizations for content relations, making use of cytoscape.js.
Quizzes
Users can play quizzes in MaMpf and get immediate feedback. In order to parse student's input in quizzes (e.g. when they enter a symbolic expression), MaMpf makes use of the JS based symbolic math expression evaluator nerdamer.
Lecturers can create quizzes and edit them in a graph:
MaMpf is a Ruby on Rails application with a PostgreSQL database. For our frontend styling, we rely on Bootstrap. Our website is hosted on a server at Heidelberg University. We use docker (compose) for development and deployment.
MaMpf is actively developed & maintained. If you are interested in using MaMpf at your university, please get in touch. But please note that we're a very small team and can't provide support for setting up your own instance of MaMpf at the moment. Our installation guide should be a good starting point. We have to admit, though, that getting your own instance up and running might involve quite some effort including setting up a mail server, the database, SSL certificates, an nginx web server / proxy, deploying the Ruby on Rails application, and more.
To clone the source code and build MaMpf locally with docker compose
, run these commands:
git clone -b main --recursive https://github.com/MaMpf-HD/mampf.git
cd mampf/docker/development/
docker compose up -d
See the full installation guide here. There you will also find out how to init your local database with some sample data.