This paper is a preliminary study on how learning analytics can support tracking and measurement of informal learing, which represents a large part learning at the workplace.
The paper is in tight relationship with a previous evidence identified by this Hub (please , see http://evidence.laceproject.eu/?evidence=new-framework-informal-learning-workplace) about the development of Social Semantic Server (SSS). In this paper it is highlighted how SSS can generate semantically-enriched Actor-Artifact Networks (AANs) to describe the relationships among actors and artifacts in different learning contexts.
To simply determine how an AAN can be generated in SSS, a preliminary study was developed using SSS and two of its applications, Bookmarker (a Chrome extension that allows users to submit bookmarks and tags to the SSS while browsing) and Attacher (a WordPress plugin that integrates a blog editor to the SSS and displays a tagcloud that includes tags registered in the SSS). In this study, ten students of a training course for future teachers were asked to bookmark web resources they considered relevant (using Bookmarker) and to write "a blog post about their reflections of the subject using WordPress and Attacher to browse the bookmarks published in the social semantic infrastructure".
Results show that three AANs can be easily identified, helping the teacher to analyze the learning of the students and to understand their behavior. This study describes a first example on how the SSS can integrate the data from different applications and coherently combine it to support learning analytics at the workplace.