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Handbook of Learning Analytics

Chapter 14

Professional Learning Analytics

Allison Littlejohn

Abstract

Professional learning is an important component of productivity in contemporary work environments characterised by continual change. Learning for work takes various forms, from formal training to informal learning through work activities. In many work settings professionals collaborate via networked environments leaving various forms of digital traces and ‘clickstream’ data. These data can be exploited through learning analytics to make both formal and informal learning processes traceable and visible to support professionals with their learning. This chapter examines the state-of-the-art in professional learning analytics by considering the different ways professionals learn. As learning analytics techniques advance, the modelling techniques that underpin these methods become increasingly complex and the assumptions that underpin the analytics become ever-more embedded within the system. This chapter questions these assumptions and calls for a new, refreshed vision of professional learning analytics for the future which is based on how professionals learn. There is a need to broaden our thinking about the purpose of learning analytics build systems that effectively to address affective and motivational learning issues as well as technical and practical expertise; intelligently align individual learning activities with organisational learning goals and to be wary of attempts to embed professional expertise in code written by software developers, rather than by the professionals themselves. There are also ethical concerns about the degree of surveillance on learners as they work and learn with anxieties about whether people understand the (potentially serious) consequences. Finally, learning analytics generally are developed for formal learning contexts, in schools, colleges and universities, missing opportunities to provide the support professionals need as they learn through everyday work.

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