This practical lab is the continuation of Computing for Social Good. It is open only to students who have successfully completed that course and developed a minimal loveable prototype (MLP) in their teams.
In this lab, students take their existing prototype to the next level by implementing a working software project. Teams are self-organising and follow agile development practices. Each team selects its own programming language, frameworks, and tools. Students are encouraged to integrate AI-assisted development tools (e.g. for coding, testing, or documentation) to support collaboration and lower entry barriers for those with limited coding experience.
The course combines technical software engineering skills with the social and ethical mission of Computing for Social Good. Students will learn how to:
- apply agile teamwork practices in a real project,
- implement and iterate on their prototype,
- collaborate with AI coding assistants,
- critically reflect on team processes, AI usage, and software quality.
Assessment is based on the quality of the implemented system, the team’s agile development process, documentation, and a final presentation.
- Dozent*in: Isabella Graßl