As a modest contribution to this event the EmployID project has produced a video on Workplace Learning Analytics. The general idea is to use Learning Analytics to to support Public Employment Services (PES) staff to develop competences that address the need for integration and activation of job seekers in fast changing labour markets. Learning Analytics has potential to supports the learning process of PES practitioners and managers in their professional identity development including through advanced coaching, reflection, networking and learning support services as well as MOOCs
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One of the aims for research and development is to introduce the use of Learning Analytics within Public Employment Services. Although there is considerable interest in Learning Analytics by L and D staff, there are few examples of how Learning Analytics might be implemented in the workplace. Indeed looking at research reported by SoLAR reveals a paucity of attention to the workplace as a learning venue.
In this video, Graham Attwell proposes an approach to Workplace Learning Analytics based on the Social Learning Platform model (see diagram) adopted by the Employ ID project. He argues that rather merely fathering together possible data and then trying to work out what to do with it, data needs to be sought which can answer well designed research questions aiming to improve the quality of learning and the learning environment.
In the case of EmployID these questions could be linked to the six different foci of the Social Learning Platform, namely:
· Support for facilitation roles
· Structuring identity transformation activities
· Supporting networking in personal networks
· Supporting organisational networks
· Supporting cross organisational dialogue
· Providing social networking facilitation
· Supporting networking in teams
For some of these activities we already have collected some “digital traces” for instance data on facilitation roles through within a pilot MOOC. In other cases we will have to think how best to develop tools and approaches to data gathering, both qualitative and quantitative.
