Webinar: “Tools to Teach Math Online”

Dear Math and Stats Teachers,

You are invited to join our webinar on “Tools to Teach Math Online”. 


  • When: Monday, November 23rd, 2020 from 12:00 to 13:00
  • Where:   on Zoom (link on request)
  • We would be grateful if you can let us know if you can join us at: henrietta.carbonel@unidistance.ch

This webinar is part of a series of events to prepare for the opening of our new Bachelor of Mathematics in Spring 2021. Our first webinar on “Productive Failure in Mathematics Teaching” was a success, with a lively discussion about the pedagogy of mathematics in higher ed. This second webinar focuses on tools to support online teaching and learning.

Three UniDistance teachers will be sharing their experience:

  • will give us a demonstration of how he uses JupyterHub and nbgrader. JupyterHub is a shared platform which provides environments and resources to the teachers and the students without burdening the users with the installation process of libraries. With the tool “nbgrader” added to JupyterHub, the process of releasing, collecting, and grading assignments is facilitated for the teachers, and provides the students with a centralized platform.
  • will be presenting how he uses and makes videos for his mathematic modules in the Bachelor of Economics. When are videos useful? What is particularly important when planning them? And on the practical side: how do you make videos? where do you start? what technology? how long? Etc. Martin Schön has been using videos since 2014 with very positive feedback from his students.
  • will discuss the social and interaction side of online learning. In his module, the teaching team has managed to develop a high level of trust, leading to stimulating interactions both online and in class. Jean-Christian Tisserand will share some tips and tricks on how they created an engaged and motivated class.

More about our speakers

Olivier Canévet is a senior research and development engineer at the Idiap Research Institute. He teaches machine learning, computer vision, and deep learning for the Master AI.

Martin Schön studied physics at the Universities of Heidelberg, Göttingen, Zürich and Konstanz, finishing his PhD at the University of Bern.  He then worked in the Czech Republic, while studying economics at the Fernuniversität Hagen. He taught economics at “Studienzentrum Schwenningen” and “Studienzentrum Pfäffikon”. Since 2008, Martin teaches mathematics for economists and foundations of economy (Microeconomics, Macroeconomics) at FernUni Schweiz.

Jean-Christian Tisserand holds a PhD in economics from the University of Bourgogne Franche-Comté. He has been teaching at UniDistance since 2016. His areas of research include experimental and applied economics, econometrics and the economics of wines and spirits.


If you have any questions, please do not hesitate to contact me: henrietta.carbonel@unidistance.ch

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