Jupyter Notebooks in teaching
Triggered by the pandemic-related "emergency remote teaching", digital university teaching has developed massively, especially in recent years, and is becoming increasingly dynamic for both students and lecturers. This is also accompanied by the increased use of digital tools - from collaborative online learning environments and virtual platforms with integrated chat and video conferencing functions to interactive documentation formats.
What are Jupyter Notebooks?
As an open source tool, Jupyter Notebooks play a central role in data literacy education. These are interactive documents that combine source code, equations, visualizations and text. They are versatile and flexible and enable users to develop virtual demonstrations, exercises or multimedia handouts. Due to the wide range of possible applications, the integration of different programming languages and the accessibility, Jupyter notebooks have proven themselves in various disciplines for expanding existing or developing new teaching concepts that deal with data in a narrower or broader sense.
A special feature of Jupyter Notebooks is that no additional software is required; instead, all operations are carried out via conventional web browsers. This means that users can interact universally and independently of the operating system at a low threshold.
Jupyter in data-based teaching
A wide range of didactic examples and incentives are available in a freely available digital manual on the use of Jupyter notebooks for data-based teaching.
JupyterHub at the University of Hamburg
We recommend the use of Jupyter notebooks for the funded teaching lab and student projects within the framework of the DDLitLab. For this purpose, the DL office of the MIN faculty provides a JupyterHub for all teachers and students of the University of Hamburg. This is a server on which members of the UHH can access Jupyter after logging in with their B-ID.
Self-study materials
To facilitate the first contact with Python as a programming language in connection with Jupyter notebooks, a workshop was organized by the DDLitLab on 27.09.2022. From this workshop, self-learning materials have been created, which can be downloaded as a ZIP archive via the following link. The archive also contains instructions on how to work through the workshop content independently and at your own pace. The materials also contain a number of suggestions for using Jupyter notebooks in teaching, as well as a variety of further links if there is a need for more in-depth details and further examples.