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This practical project explores the use of JupyterLab as an Intelligent Learning Environment (ILE) for teaching and learning Python programming. The goal is to enhance the traditional JupyterLab environment with educational extensions that support students throughout their learning process. As part of the project, students will work in groups to design and develop different JupyterLab extensions. These extensions may provide features such as interactive feedback, programming exercises, learning support, code analysis, or other tools that facilitate the acquisition of Python programming skills. The project combines software development with educational design, allowing students to gain practical experience in developing learning technologies while addressing concrete challenges in programming education. The resulting extensions will contribute to transforming JupyterLab into a more supportive and interactive environment for learning Python. |
- verantwortliche Lehrperson: Irene-Angelica Chounta
- verantwortliche Lehrperson: Kaimao Sheng