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Jupyter notebooks have become an essential tool used in data science, scientific computing, and machine learning in both industry and academia. Cloud based platforms like Google Colab and JupyterHub bring the power of Jupyter notebooks into the cloud and make it easier to share and collaborate. At EPFL and other universities, these cloud-based Jupyter notebooks are used as interactive textbooks, platforms for distributing and grading homework, and as simulation environments.
These notebooks produce rich logs of interaction data, but there is currently no easy way for teachers and students to view and make sense of this data. This data could provide a valuable source of feedback that both teachers and students could use to improve their teaching and learning. This way of using data is called learning analytics, and we have designed and develped a system that brings the power of learning analytics directly into cloud-based Jupyter notebooks.
The goal of this project is to augment the existing system by implementing new features that are useful to teachers, or to build a complementary extension specially for students, based on the data we are currently able to collect.
We are looking for students to join in the development of this tool with any of the following interests: data visualization, full-stack web development, UX research, learning analytics.
Required knowledge: Javascript/Typescript, Python, React, PostgreSQL, docker
Contact: zhenyu.cai@epfl.ch
We have developed a system that handles data collection, data storage, and data visualization on JupyterLab. However, sometimes it is not very convenient for teachers to check the information through the Jupyter platform using their laptops, especially when they are moving around in the classroom. The goal of this project is to build an alternative solution to address this practical problem, for example, by developing a mobile-friendly website that is accessible across different platforms.
We are looking for students to join in the development of this tool with any of the following interests: data visualization, front-end web development, UX research, learning analytics.
Required knowledge: React, Python, Javascript/Typescript
Contact: zhenyu.cai@epfl.ch