An Experimental Online Judge System Based on Docker Container for Learning and Teaching Assistance

Abstract

Programming Languages are core courses in computer science and computing-related disciplines, and there are increasing demands on improving the experiences, motivation and efficiency of programming language teaching and learning. In recent decades, online judge (OJ) systems have been popularly adopted in educational environments to support real-time learning feedback, and provide interactive programming practice. However, most existing OJ systems rely on significant resource for hardware virtualization, and suffer from long development cycles and extensive maintenances. This paper proposed a course-oriented OJ system based on the Docker Container techniques to significantly reduce the cost and maintenance of deployment of existing OJ system. The proposed approach is designed in the form of an experimental system, which is effective in stimulating the students to learn programming language and assist the instant assessment of coursework. Meanwhile, our proposed system can be integrated with major massive open online course (MOOC) systems for assessment. The efficiency and performance of our proposed system has been evaluated and tested by 1460 students in Nanyang Institute of Technology during term time between 2018 and 2019.

Bo Yuan

Lecturer in (Assistant Professor) Computer Science

My research interests include Data Science, Artificial Intelligence, Machine Learning, Internet of Things, Distributed Computing, Edge Computing