The project Coding4Geo aims at providing an online interactive coding platform allowing automatically checking of student submissions and initially serve the students from geoinformatics related courses at the Technical University of Munich (TUM). The longer-term scope aims at a platform, which provides the opportunity to be extended and deployed for many other ESS-related disciplines.
As an NFDI4Earth-endorsed project, the project results have the potential to find widespread further development and adoption
Coding exercises are an important component of teaching data analysis in ESS today. Manually correcting assignments is often a heavy workload for exercise instructors. Students also often do not submit in time nor receive timely feedback. Therefore, automated code checking systems are promising for a wide range of teaching activities in ESS education. Several universities offer this service, based on different software architectures and infrastructures. Most of them are closed to their own students. In addition, the same basic content is often designed repeatedly at different universities, or even in different departments of a university.
Nbgrader is an existing tool that supports creating and grading assignments for Jupyter Notebooks. It can be easily deployed in a conventional server, where student users can program Python code online in a Jupyter-Notebook interface and the exercise instructors can automatically grade their submissions. The reuse of existing teaching materials is also of great importance. Within the education-oriented project ICAML - Interdisciplinary Center for Applied Machine Learning, coordinated by co-applicant Martin Werner, BMBF funded 2018-2020, numerous Jupyter Notebook tutorials for machine learning topics in geospatial data analysis were developed and introduced to the community. Still, an interactive code checking process is important to further develop these tutorials and make these contents interactive and effortless to be included in future E-Teaching activities related to geospatial data analysis.
This project is kindly supported by the DFG (German Research Foundation) funded NFDI4Earth - NFDI (German National Research Data Infrastructure) Consortium Earth System Sciences, from Oct. 2022 to Feb. 2023.