Background and general information
Students in AI and robotics courses often face significant challenges when setting up their programming and software development environments. Differences in operating systems, software versions, and dependencies can cause teaching examples to fail and student submissions to malfunction, leading to wasted time and unnecessary frustration. These setup issues are particularly disruptive in programming-intensive courses like Robot Motion Planning and Control (4TM00) and Networked Dynamical Systems (4DM70), where students are expected to collaborate on complex assignments under time constraints.
To address this, the EduDock project introduces containerized software development environments for education using Docker. This technology allows all students and instructors to work within identical, modular, and reproducible setups regardless of their personal hardware or operating systems. By providing plug-and-play digital environments, EduDock aims to simplify the technical setup process, reduce instructor workload, and enable fair and scalable assessment. The project builds on earlier educational innovations and responds to recurring difficulties identified in prior teaching experiences at TU/e. EduDock will also integrate automated grading tools and support teamwork through container-based assignment submissions. This approach is expected to enhance learning efficiency, promote collaborative development, and align with TU/e’s educational vision of flexibility, authenticity, and digital innovation.
Objective of the project
The EduDock project aims to design, implement, and evaluate a Docker-based digital education platform for AI and robotics that improves flexibility, modularity, and reproducibility in teaching and learning. The platform will include three main digital containerized components: a standardized modular software development environment, a collaborative development and submission system for student teams, and an automated grading infrastructure for instructors. These tools will allow students to begin working immediately without time-consuming installation setup, collaborate more effectively and reliability, and receive fair, consistent feedback on their submissions.
From the instructor's perspective, EduDock reduces time spent on troubleshooting and enables automated testing of assignments in a shared uniform environment. This leads to more transparent and scalable assessment practices, especially important in large courses with around 80 students annually. The system will be piloted in 4TM00 and 4DM70 and evaluated through comparisons of student experience and submission quality with and without containerization. Feedback will be gathered through interviews, surveys, and assignment data.
The ultimate goal is to enhance the quality and efficiency of programming education in robotics and AI, while creating a platform that can be adopted in other TU/e courses and departments. EduDock supports the university’s broader goals of flexible learning, challenge-based education, and the use of advanced digital tools to empower students and educators alike.
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