How to embed more computational skills in your course
The ETH wide "Computational Competencies" Initiative aims to anchor the skills of algorithmic thinking, programming, data analysis and data-based modelling in all degree programmes. A key component is to integrate teaching of computational skills in subject-specific courses. This links and applies computational skills to subject matters and intergrates them more naturally instead of leaving them as an abstact and isolated topic.
In this refresh teaching event we want to introduce the initiative and hear examples from ETH faculty on how they integrate computational competencies in their teaching. There is a wide range of tools available, but we will hear now about data anlysis with Excel and integrating JupyterNotebooks for exercises and teaching. We will also hear about the JupyterHub at ETH provided by LET, which provides easy access to a coding environment in terms of JupyterNotebooks (in Python, Julia, R, or OpenModelica), since no local installation of software is needed. It all runs in a browser. Please join the event to learn more and possibly get inspired to embed more computational skills in your own course!
Dr. Urs Brändle, Project Leader Computational Competencies, ETH Zuerich
Dr. Mauro Werder (WSL Birmensdorf & D-BAUG)
Mauro Werder reports in this Refresh Teaching event on his deployment of JupyterNotebooks in Julia on the ETH JupyterHub for a master course in glaciology.
Dr. Gregory de Souza (D-ERDW)
Gregory de Souza shares how he performs exercises in Python with JupyterNotebooks throughout the curriculum.
Dr. Urs Brändle
Urs Brändle, Project Leader Computational Competencies, ETH Zuerich
Dr. Katrin Bentel, LET
In the Framework of the ETH Computational Competencies initiative, LET is providing a JupyterHub for use in teaching and learning at ETH. Acess is exclusivly via plugin from Moodle, so no seperate authentication is necessary.