Why Do We Want Data for Learning? Learning Analytics and the Laws of Media

Abstract

With the increase of online education programs, learning analytics (LA) tools have become a popular addition to many learning management systems (LMS). As a tool for supporting learning in an educational context, LA has generated some controversy among scholars. Therefore, in this text, we aim to provide a theoretical and analytical understanding of the approach and its implications for teaching and learning. To achieve this, we apply McLuhan’s semiotic analysis of media (1988). The “Laws of Media” questions are asked about LA tools: What do they enhance, make obsolete, retrieve, and reverse into. By answering these questions, we outline which practices of teaching and learning are more likely to become common when LA tools are taken into use more widely and which others will be relegated. In the analysis, we point out that LA tools enhance prediction and personalization of learning, while they displace certain teachers’ skills, personal interaction between teachers and students, and qualitative interpretation and assessment of learning. Simultaneously, LA retrieves behaviourist views of learning and urges discussion about data literacy. Taken to the limits, LA reverses its effects and becomes a tool for supporting awareness and reflection in teaching and learning. We consider these contributions relevant for understanding and reflecting on the type of pedagogies that LA supports, the implicit values it holds, and the changes it introduces into educational practice.