Selectively anonymous rankings: Design, analysis and impact on computer science students

This paper presents a method to deliver course rankings that maintain student confidentiality while still allowing students to selectively prove their position in a class to others if they wish. The method´s selective anonymity is implemented through a secure hashing algorithm that is designed to protect student privacy even where a student´s name, their student ID, their project teams and the student´s ranks for other work items are known. The paper includes results showing student perceptions of the approach and the impact on their performance for a second year Computer Science course at the University of Waikato in New Zealand.