Exploring the relationship of ethics and privacy in learning analytics and design

The Springer journal Educational Technology Research and Development has published a special issue that examines the relationship of ethics and privacy in learning analytics, guest edited by Dr. Dirk Ifenthaler and Dr. Monica Tracey. The rapid growth of educational big data requires well-established data management, analysis, and regulations. "More educational data does not always make better learning environments," says Dr. Ifenthaler, a professor at the University of Mannheim in Germany.

Higher education institutions have always used a variety of data about students, such as socio-demographic information, grades on higher education entrance qualifications, or pass and fail rates, to inform their academic decision-making as well as for resource allocation. Such data can help to successfully predict dropout rates of first-year students and to enable the implementation of strategies for supporting learning and instruction as well as retaining students.

Advanced digital technologies and learning analytics systems enable higher education institutions to collect dynamic real-time data from all student activity, offering huge potential for personalized and adaptive learning experiences and support.

"Consequently, higher education institutions need to address ethics and privacy issues linked to educational data analytics. They need to define who has access to which data, where and how long the data will be stored, and which procedures and algorithms to implement for further use of the available data," suggests Dr. Ifenthaler.

To address serious concerns and challenges associated with the application of educational data analytics, Dr. Ifenthaler and Dr. Tracey, a professor at Wayne State University, Detroit, Michigan, call for international research studies expanding the perspectives of ethics and privacy by including different stakeholders, such as teachers, students, learning designers, university management, and governing authorities, conducted as mixed-methods designs, including qualitative components which may help to better understand the drivers of ethics and privacy issues.

The special issue gathers diverse perspectives and examples on learning analytics, ethics, and privacy, and expands the current understanding of how educational data will influence higher education institutions in the future. The special issue discusses ethical dilemmas of intervention strategies for at-risk students, the ethics of categorizing at-risk students, student perceptions and expectations of privacy, and ethical oversight of student data - all through the lens of learning analytics.