Social Learning Analytics Monitor (University of Paderborn)

Abstract
With the rise of Social Media in various educational contexts, the monitoring of students' activities in these tools becomes increasingly important. In this contribution we are sketching a tool (SCALAR, Social Learning Analytics Monitor) that is currently under development at the University of Paderborn and that monitors and analyses students activities and visualizes metrics of their performance.

Introduction
Networked learning has become mainstream in the last decade. The rise of the Internet, the WWW and lately Social Media have fundamentally reshaped the way education can be carried out. Educational courses are increasingly becoming open. The current discussion around MOOCs [1,2] and PLEs reflect this changed attitude. Awareness and reflection support in large technology enhanced learning settings are a challenging task are not well supported by tools so far. Nevertheless are both students and supervisor in the urgent need for monitoring facilities that help them assess the (user-generated) content shared and discussed in those Learning Networks. Recently, the term of learning analytics has emerged that describes the application of well-known techniques from information retrieval, business intelligence and web analytics to the domain of learning and education. A recent study even provides a structured framework of Social Learning Analytics that proposes a 5-element-taxonomy containing 1. social learning network analysis, 2. social learning discourse analysis, 3. social learning content analysis, 4. social learning dispositions analysis, 5. social learning context analysis.

Goal of the tool
The goal of our development is to develop and open access a tool that supports supervisors of educational courses (and broader: any groups that make extensive use of Social Media for communication and co-operation) in monitoring the activities of the enrolled participants. The monitoring of Social Media activities is important for the participants' awareness about content that is created, shared and discussed within the course, as well as for their awareness of opinion leaders and the overall structure of the group. Access to such aggregated monitoring results also serve as trigger for students' reflection, self-awareness and improved assessment of their own activities.

Moreover SCALAR aims at supporting the supervisor(s) of a course with an easy-to-use tool for assessing the students' engagement, motivation and quality of their contributions. Therefore, peer reviews of UGC where peers have to access the information quality of the UGC are a core concept of

Features
Here we list features that are planned for the first open access prototype to be evaluated in the context of a cooperative seminar in the winter term 2011/12 at the University of Paderborn (Germany) and the Levinsky Teacher College (Israel):


 * 1) create new groups to monitor
 * 2) join groups (by name, hashtag, affiliation ...)
 * 3) edit your profile (name, gender, social media handles, interests ...)
 * 4) monitor content created in social media (Twitter, Facebook, Delicious, Blogs, Slideshare ...) via the groups' hashtag
 * 5) receive daily, weekly, monthly summaries of the activities in the group
 * 6) perform SNA analyses on the data
 * 7) export data for detailed inspection in tools like Gephi
 * 8) rate and comment content created in the group (star-based rating, assessment of information quality etc.)
 * 9) set the frequency, artefact types and amount of artefacts for peer review
 * 10) perform peer reviews

The list of potential features is long and will be extended in close negotiations with prospective users. We'd be happy to discuss such enhancements and show a first prototype at the conference.

Open Access strategy
SCALAR will be developed for free usage by anyone interested in using it. We will not charge any fees for its application to educational settings and hope to see active discussion about future enhancements and applications to domains we do not foresee today.