Perspective on Code Submission and Automated Evaluation Platforms for University Teaching
This addresses the need for efficient and scalable teaching tools in computer science education, particularly for remote learning, but is incremental as it builds on existing platform concepts.
The paper examines platforms for code submission and automated evaluation in university teaching, highlighting their importance for remote courses and scalability with large student numbers, and finds they reduce teacher workload and improve evaluation transparency.
We present a perspective on platforms for code submission and automated evaluation in the context of university teaching. Due to the COVID-19 pandemic, such platforms have become an essential asset for remote courses and a reasonable standard for structured code submission concerning increasing numbers of students in computer sciences. Utilizing automated code evaluation techniques exhibits notable positive impacts for both students and teachers in terms of quality and scalability. We identified relevant technical and non-technical requirements for such platforms in terms of practical applicability and secure code submission environments. Furthermore, a survey among students was conducted to obtain empirical data on general perception. We conclude that submission and automated evaluation involves continuous maintenance yet lowers the required workload for teachers and provides better evaluation transparency for students.