Students’ Adoption of Learner Analytics

Abstract

Learner analytics is an emerging learning and teaching tool which visualises individualised learning data to student users typically via a dashboard or similar platform. In a learner analytics model data are communicated to students directly and often without tutor contact; sense-making is assumed to occur through digital and algorithmic intermediation. Through the collection and analysis of qualitative and quantitative student data, this chapter argues that students' propensity to adopt analytics is influenced by their existing relationship with data, their discipline, their perception of self and the connections between these factors and the following four benefits: analytics for orientating oneself academically; analytics for improved organization and management; analytics for signposting to support; analytics for fun.