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This paper proposes that Social Learning Analytics (SLA) can be usefully thought of as a subset of learning analytics approaches. SLA focuses on how learners build knowledge together in their cultural and social settings. In the context of online social learning, it takes into account both formal and informal educational environments, including networks and communities. The paper introduces the broad rationale for SLA by reviewing some of the key drivers that make social learning so important today. Five forms of SLA are identified, including those which are inherently social, and others which have social dimensions. The paper goes on to describe early work towards implementing these analytics on SocialLearn, an online learning space in use at the UK's Open University, and the challenges that this is raising. This work takes an iterative approach to analytics, encouraging learners to respond to and help to shape not only the analytics but also their associated recommendations.

Analytics in Higher Education: Establishing a Common Language Title: Analytics in Higher Education: Establishing a Common Language (ID: ELI3026) Author(s): Angela van Barneveld (Purdue University), Kimberly Arnold (Purdue University) and John P. Campbell (Purdue University) Topics: Academic Analytics, Action Analytics, Analytics, Business Analytics, Decision Support Systems, Learning Analytics, Predictive Analytics, Scholarship of Teaching and Learning Origin: ELI White Papers, EDUCAUSE Learning Initiative (ELI) (01/24/2012) Type: Articles, Briefs, Papers, and Reports

"Introduction In this discussion paper, we define learning process analytics as a collection of methods that allow teachers and learners to understand what is going on in a' 'learning scenario, i.e. what participants work(ed) on, how they interact(ed), what they produced(ed), what tools they use(ed), in which physical and virtual location, etc. Learning analytics is most often aimed at generating predictive models of general student behavior. So-called academic analytics even aims to improve the system. We are trying to find a solution to a somewhat different problem. In this paper we will focus on improving project-oriented learner-centered designs, i.e. a family of educational designs that include any or some of knowledge-building, writing-to-learn, project-based learning, inquiry learning, problem-based learning and so forth. We will first provide a short literature review of learning process analytics and related frameworks that can help improve the quality of educational scenarios. We will then describe a few project-oriented educational scenarios that are implemented in various programs at the University of Geneva. These examples illustrate the kind of learning scenarios we have in mind and help define the different types of analytics both learners and teachers need. Finally, we present a provisional list of analytics desiderata divided into "wanted tomorrow" and "nice to have in the future"."

Flare at Purdue in October    Hi everyone. Can someone provide more information for the upcoming SoLAR FLARE event at Purdue in October? Thanks, Kelvin Bentley By Kelvin Bentley  - May 14 - 2 new of 2 messages - Report as spam     EDUCAUSE Survey on Analytics - Looking for International Input    Colleagues, EDUCAUSE is soliciting input on analytics in higher education. They have currently sent email to their current members, but are looking for additional participation from the international community. We would greatly appreciate if you could complete the survey below. -- john... more » By John Campbell - Purdue  - May 11 - 2 new of 2 messages - Report as spam     CFP: #Influence12: Symposium & Workshop on Measuring Influence on Social Media    Hi Everyone, If you are interested in Learning Analytics and Social Media, I invite you to submit a short position paper or poster to the Symposium & Workshop on Measuring Influence on Social Media. The event is set for September 28-29, 2012 in beautiful Halifax, Nova Scotia, Canada. All submissions are due *June 15, 2012*.... more » By Anatoliy Gruzd  - May 11 - 2 new of 2 messages - Report as spam     LA beginnings    Learning Analytics isn't really new, it is just getting more publicity now as a result of the buzz word name change. Institutions have been collecting data about students for a long time, but only a few people dealt with the data. Instructors kept gradebooks and many tracked student progress locally - by hand. What's new about Learning... more »

Learning networks, crowds and communities Full Text: PDF Author: Caroline Haythornthwaite University of British Columbia, Vancouver, BC Who we learn from, where and when is dramatically affected by the reach of the Internet. From learning for formal education to learning for pleasure, we look to the web early and often for our data and knowledge needs, but also for places and spaces where we can collaborate, contribute to, and create learning and knowledge communities. Based on the keynote presentation given at the first Learning Analytics and Knowledge Conference held in 2011 in Banff, Alberta, this paper explores a social network perspective on learning with reference to social network principles and studies by the author. The paper explores the ways a social network perspective can be used to examine learning, with attention to the structure and dynamics of online learning networks, and emerging configurations such as online crowds and communities.

Attention please!: learning analytics for visualization and recommendation Full Text: PDF Author: Erik Duval Katholieke Universiteit Leuven, Leuven, Belgium This paper will present the general goal of and inspiration for our work on learning analytics, that relies on attention metadata for visualization and recommendation. Through information visualization techniques, we can provide a dashboard for learners and teachers, so that they no longer need to "drive blind". Moreover, recommendation can help to deal with the "paradox of choice" and turn abundance from a problem into an asset for learning.

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From the Semantic Web to social machines: A research challenge for AI on the World Wide Web Jim Hendler, Tim Berners-Lee Abstract The advent of social computing on the Web has led to a new generation of Web applications that are powerful and world-changing. However, we argue that we are just at the beginning of this age of "social machines" and that their continued evolution and growth requires the cooperation of Web and AI researchers. In this paper, we show how the growing Semantic Web provides necessary support for these technologies, outline the challenges we see in bringing the technology to the next level, and propose some starting places for the research.