Learning management systems are used for facilitating communication between instructors and students, dissemination of lecture materials, and grading of assignments. They collect large amounts of student data, necessary or otherwise, with or without explicit consent from students. Furthermore, they make the data visible to instructors, which could have significant implications for students’ grades and experience in the classroom. In this study, we interviewed 31 students enrolled in a large public university about their privacy concerns towards different data sharing practices related to the learning management system used at their university – Canvas. Data from the study was analyzed by two researchers using inductive thematic analysis methods. The results show concerns about misrepresentation, the justification for information being visible, and discrimination. We present the implications of this study on instruction, design of learning management systems, and policy.
https://doi.org/10.1145/3613904.3642914
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)