Title: Teaching Large Computer Network Class With Automated Marking
Stream: Teaching Experiences, Pedagogy, Practice & Praxis
Presentation Type: Oral Presentation
Shao Ying Zhu, Birmingham City University, United Kingdom
The Internet has become an indispensable part of daily life, particularly during the Covid-19 pandemic. Since the core of the Internet is computer networks, this has become a core module in many computing departments on various computing and cyber security-related courses. It is usually taught in large classes with hundreds of students. For assessment, students are often asked to calculate subnets using the provided IP addresses, while to avoid students copying answers from each other, they are given different IP addresses to work with. This creates a large amount of workload for the marking tutor. Since there is no standard answer for checking, they will need to work out the answer for each individual student first and then compare it with the student's answer. For feedback, they will then need to fill in the standard template with marks for each step. This generates a large amount of work, and manual marking is thus time-consuming, cumbersome and prone to errors. In this study, we propose to use a python program to automate the marking process. The program will open a student's submitted coursework, retrieve the allocated IP address and required information to calculate the correct answer. It will then automatically compare this with the submitted answer, give the relevant marks for each step, and save them into the correct positions in the feedback template. By automating the marking process, the tutor's workload is thus reduced significantly.
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