Re-imagining 'Learning Analytics' ... a case for starting again?

Abstract This brief paper develops a series of provocations against the current forms of Learning Analytics that are beginning to be implemented in higher education contexts. The paper highlights a number of ways in which Learning Analytics can be experienced as discriminatory, oppressive and ultimately disadvantaging across whole student populations, and considers the limitations of current efforts within educational data science to increase awareness of ‘ethics’ and ‘social good’. This culminates in a stark choice: is it possible to substantially improve the field of Learning Analytics as it currently stands, or should we abandon it in favour of new forms of applying data science that are aligned with the experiences of non-conforming ‘learners’ and un-categorizable forms of ‘learning’?