Privacy Concerns of Student Data Shared with Instructors in an Online Learning Management System

要旨

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.

著者
Monika Blue. Kwapisz
University of Washington, Seattle, Washington, United States
Avanya Kohli
Bellevue High School, Bellevue, Washington, United States
Prashanth Rajivan
University of Washington, Seattle, Washington, United States
論文URL

doi.org/10.1145/3613904.3642914

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Learning and Teaching Technologies A

311
5 件の発表
2024-05-15 01:00:00
2024-05-15 02:20:00