Privacy Issues in Learning Technologies
Ying Tang
Faculty Mentor
Ying Tang (Luddy School of Informatics, Computing and Engineering)
Project Description
This project will involve research on privacy issues in learning technologies. Instructors and students are generating tremendous amount of administrative, academic, and personal data, when using technologies to support teaching and learning. However, these data are usually created in contexts where privacy issues, such as data ownership and information control, are not clearly addressed. This project aims to explore one or more of the following questions related to privacy in learning technologies; 1. Perceptions of exposing individual learning analytics data to instructors; 2. Preferences and practices related to privacy in using certain technological tools; 3. Design and develop solutions to helping learners manage their privacy in learning technologies. The student will collaborate in one or more of the following aspects: studying existing research, collecting empirical data, and analyzing the data using qualitative or quantitative methods. There is possibility of eventually designing and conducting original research in this area.
Technology or Computational Component
The project will focus on technologies that have been used to support teaching and learning, such as learning analytics, social media, cloud computing, and mobile technologies. The research activities may involve using the following technologies, such as Qualtrics for survey, R programming for data collection and processing, MaxQDA for qualitative data analysis, Overleaf/LaTeX for paper writing, Slack for communication, and Trello for project management, etc. No prior experience with these tools is required.