Student autonomy and Learning Analytics: Philosophical Considerations for Designing Feedback Tools

Learning Analytics (LA)-based feedback applications are becoming increasingly important in higher education institutions (HEIs). However, the impact of such systems on student autonomy is contested in parts of the research debate, where hopes and ambitions of learner autonomy and self-regulated learning are confronted with fears that learners are being reduced to mere numeric constructs and are caught up in neoliberal demands to self-optimize. We explore these challenges from the debate with a focus on automated, LA feedback systems in HEIs and their impact on student autonomy. As we show, such technologies must be seen within a field of tension between heteronomous (i.e., contextual and societal) demands and autonomous, self-organized learning. Aiming to bridge the critical parts of the debate with those that highlight the potential of such technologies, we build upon meaningful conceptions of limited, situated autonomy and explore what it would mean for such feedback systems to strengthen, not undermine student autonomy. To make the concept of student autonomy applicable, we propose a list of philosophical design considerations for LA-based feedback systems. We believe that this will offer a philosophically informed intellectual tool to address common concerns raised by parts of the debate and that it can encourage further discussion on recognizing, promoting, and preserving student autonomy in higher education.