Multidisciplinary education: making the case for agile regulatory frameworks on learning analytics

This position paper examines issues within the evolving landscape of learning analytics in education and its intersection with data protection and privacy laws. Learning analytics, encompassing the acquisition, representation, and processing of student data, has demonstrated substantial potential to enhance educational outcomes. However, its responsible adoption faces difficult challenges, particularly in (but not restricted to) regions governed by stringent regulations like the General Data Protection Regulation (GDPR) in Europe. This calls for a comprehensive approach to navigate these challenges, to facilitate compliance with evolving data protection laws, operationalising informed consent, and engaging transparent, yet secure, data usage practices. At present, privacy-enhancing technologies (PETs) and data protection impact assessments (DPIAs) already play an important role in identifying and mitigating risks associated with data processing. These allow the implementation of responsible data governance frameworks, complemented by ethically-driven policies, in order to ensure transparent, fair, and accountable data utilization throughout its lifecycle. However, these are not yet as widely adopted as needed, making the case for regulatory frameworks to be agile to keep up with the fast-paced technological landscape. Balancing regulatory predictability and agility is essential, as is the mitigation of the potential risks of regulatory capture. Moreover, this calls for a multidisciplinary collaboration among educators, legal experts, technologists, and ethicists in shaping the future of responsible learning analytics.Keywords: Learning Analytics, Multidisciplinarity, Agile Regulatory Frameworks