Visualising Social Learning Ties by Type and Topic

On 12 April, Bieke Schreurs presented a paper I had co-authored at the annual conference on learning analytics and knowledge, LAK13, which took place in Leuven, Belgium.

Schreurs, Bieke; Teplovs, Chris; Ferguson, Rebecca; De Laat, Maarten and Buckingham Shum, Simon (2013). Visualizing social learning ties by type and topic: rationale and concept demonstrator. In: Third Conference on Learning Analytics and Knowledge (LAK 2013), 8-12 April 2013, Leuven, Belgium.

Doug Clow liveblogged the presentation.

Paper abstract:

This paper builds on the ideas of Social Learning Analytics and focuses on the question of how people develop and maintain a ‘web’ of social relations that support their learning. We describe how we visualise learning ties in SocialLearn, an online learning space in use at the UK’s Open University. To gain more insight into the networked learning processes, we constructed a theoretical framework with the intention of identifying what counts as a learning tie by classifying the online interactions that promote the learning process. Based on this model we created a plug in, based on The Network Awareness Tool (NAT), to visualise learning ties within SocialLearn. NAT visualises socio-material networks by identifying relationships between people who interact with the same learning topics. The tool serves different goals for different target groups. It has been shown to provoke learning-centric reflection by learners on how they use their peers for learning. Learners can also use it as a Social Learning Browser to locate who are dealing with the same learning topics. Educators can use it to guide the students in their networked learning competences and to gain insight into the ability of groups of students to learn collectively over time. For researchers, the analysis of learning ties and networks helps clarifies how professionals engage in learning relationships and the value of this engagement. This work informs the field of learning analytics by identifying ways on making networked learning activities more explicit and therefore more accessible for professionals to share and analyse.

Photo by gr0uch0 on Flickr.

Analytics To Identify Learning Dialogue in Online Discussions

On 11 April, I presented a full paper at the learning analytics and knowledge conference, LAK13, in Leuven, Belgium.

The paper, ‘An Evaluation of Learning Analytics To Identify Exploratory Dialogue in Online Discussions‘ was co-authored by Zhongyu Wei of the Chinese University of Hong Kong, Yulan He, now at Aston University, and Simon Buckingham Shum from The Open University.

Learning analytics to identify exploratory dialogue in online discussions from Rebecca Ferguson

Paper abstract:

Social learning analytics are concerned with the process of knowledge construction as learners build knowledge together in their social and cultural environments. One of the most important tools employed during this process is language. In this paper we take exploratory dialogue, a joint form of co-reasoning, to be an external indicator that learning is taking place. Using techniques developed within the field of computational linguistics, we build on previous work using cue phrases to identify exploratory dialogue within online discussion. Automatic detection of this type of dialogue is framed as a binary classification task that labels each contribution to an online discussion as exploratory or non-exploratory. We describe the development of a self-training framework that employs discourse features and topical features for classification by integrating both cue-phrase matching and k-nearest neighbour classification. Experiments with a corpus constructed from the archive of a two-day online conference show that our proposed framework outperforms other approaches. A classifier developed using the self-training framework is able to make useful distinctions between the learning dialogue taking place at different times within an online conference as well as between the contributions of individual participants.

Doug Clow liveblogged the presentation.

Photo from gr0uch0‘s excellent LAK13 conference set.

Discourse-Centric Learning Analytics

On 8 April I co-chaired the 1st International Workshop on Discourse-centric Learning Analytics, which took in place with the third Learning Analytics and Knowledge conference (LAK13) in Leuven, Belgium.

The workshop began with a keynote by David Williamson Shaffer on ‘How Research into Epistemics Might Inform DCLA’.

This was followed by six papers – one of which I had co-authored.

• Analysis of Discourse and the Importance of Time (Gregory Dyke, Elijah Mayfield, Iris Howley, David Adamson, Carolyn P. Rosé)
• Leveraging CSCL Research Analyzing Online Discussion to Inform DCLA (Alyssa Friend Wise)
• Discourse, Computation and Context – Sociocultural DCLA Revisited (Simon Knight and Karen Littleton)
• XIP Dashboard: Visual Analytics from Automated Rhetorical Parsing of Scientific Metadiscourse (Duygu Simsek, Simon Buckingham Shum, Ágnes Sándor, Anna De Liddo, Rebecca Ferguson)
• Virtual Communities of Practice in Academia: An Automated Discourse Analysis (Nicolae Nistor, Beate Baltes, George Smeaton, Mihai Dascalu, Dan Mihaila, & Stefan Trausan-Matu)
• OpenEssayist: Extractive Summarisation & Formative Assessment of Free-Text Essays (Nicolas Van Labeke, Denise Whitelock, Debora Field, Stephen Pulman, John Richardson)

The workshop concluded with a discussion session.

The event was liveblogged by Doug Clow.

Photograph by gr0uch0.

 

 

 

ORO downloads – most requested

Second most requested download on the university’s Open Research Online system for the last year.

Buckingham Shum, Simon and Ferguson, Rebecca (2012). Social learning analytics. Journal of Educational Technology and Society, 15(3)

Confronting Reality with Big Data & Learning Analytics

Yesterday I was at ALT-C in Manchester, as one of a group from The Open University and JISC, running the symposium, Big Data & Learning Analytics: Confronting Reality with Big Data & Learning Analytics. Sheila MacNeill has blogged about the event and responses to it.

ALT-C2012 Learning Analytics Symposium from Simon Buckingham Shum

Abstract

We are experiencing an explosion in the quantity of data available online from archives and live streams. Learning Analytics is concerned with how educational research, and learning platform design, can make more effective use of such data (Long & Siemens, 2011). Improving outcomes through the analysis of data is of interest to researchers, administrators, systems architects, social media developers, educators and learners. Analytics are being held up by some as a way to confront, and tackle, the tough new realities of less money, less attention, and higher accountability for quality of learning.

Researchers and vendors are building reporting capabilities into tools that provide unprecedented levels of data on learners. This symposium will show what is possible, and what’s coming soon. What objections could possibly be raised to such progress?

However, information infrastructure embodies and shapes worldviews: classification schemes are not only systematic ways to capture and preserve, but also to forget, by virtue of what remains invisible (Bowker & Star, 1999). Learning analytics and recommendation engines are designed with a particular conception of ‘success’, driving the patterns deemed to be evidence of progress, the interventions that are deemed appropriate, the data captured and the rules that fire in software.

This symposium will air some of the critical arguments around the limits of decontextualised data and automated analytics, which often appear reductionist in nature, failing to illuminate higher order learning. There are complex ethical issues around data fusion, and it is not clear to what extent learners are empowered, in contrast to being merely the objects of tracking technology. Educators may also find themselves at the receiving end of a new battery of institutional ‘performance indicators’ that do not reflect what they consider to be authentic learning and teaching.

This Symposium will provide the opportunity to hear a series of brief presentations introducing contrasting perspectives, before the debate is opened to all. Speakers from a cross-section of The Open University will describe how we are connecting datasets, analysing student data and prototyping next generation analytics. Complementing this, JISC will present a national capability perspective, with an update on the JISC CETIS ‘landscape analysis’ of the field, which will clarify potential benefits, issues to consider, and help institutions to assess their current capability and possible next steps.

Participants will catch up with developments in this fast moving field, through exposure to the possibilities of analytics, as well as issues to be alert to.

Visual analytics

Suzanne Little has developed our Ed-Media 2011 paper, which she presented in Lisbon in June last year, into a full-scale journal article. The article focuses on visual similarity search, which uses features of images in order to find material that is visually related, thus supporting navigation of educational materials in a variety of ways, including identifying the source of an image, finding items that offer different ways of understanding a concept, or finding other content in which a given image or video frame is used

Little, Suzanne; Ferguson, Rebecca and Rüger, Stefan (2012). Finding and reusing learning materials with multimedia similarity search and social networks. Technology, Pedagogy and Education, 21(2), pp. 255–271.

Abstract

The authors describe how content-based multimedia search technologies can be used to help learners find new materials and learning pathways by identifying semantic relationships between educational resources in a social learning network. This helps users – both learners and educators – to explore and find material to support their learning aims. Exciting new technologies are emerging for designing and deploying multi-modal, interactive educational tools such as video, 3D models, games, remote sensors or collaborative community-created resources (e.g. wikis). With the increasing availability of open educational resources in online, semantically marked-up and socially connected spaces, users are building their own learning pathways by exploring and remixing content. In this article the authors look at how the integration of multimedia search into the SocialLearn platform for shared learning spaces can contribute to this vision.

Social Learning Analytics: Five Approaches

2 May, and my main LAK12 conference paper on social learning analytics - co-authored with Simon Buckingham Shum.

This provides a context for the learning analytics research and development work that we are currently carrying out on SocialLearn.

Social learning analytics: LAK 2012

View more PowerPoint from Rebecca Ferguson

Video of the presentation.

Abstract

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.

The strength of cohesive ties

In September 2011, I presented at ReLive 2011 together with Julia Gillen, one of my co-authors. We won third prize for Best Conference Paper.

FERGUSON, R., GILLEN, J., PEACHEY, A. & TWINING, P. The strength of cohesive ties: discursive construction of an online community.  ReLIVE11: Creative Solutions for New Futures, 2011 (21-22 September) Milton Keynes, UK.

Abstract

Learning takes place in a social context and this context can offer many resources, including structure, continuity and motivation. Online, two primary learning types of context have been identified, networks and communities. While networks may offer a wealth of people and resources, communities appear to offer richer learning possibilities. It is therefore important to investigate how online learning communities can be formed from online networks, and whether such a shift benefits learners. The study reported here focuses on two groups of teenagers, one a formal learning group from the USA and the other an informal learning group from the UK. The groups were originally only weakly tied in a network, but aimed to create a single learning community through activity in an online forum, wiki and virtual world. Thematic analysis of their forum posts shows the importance of cohesive ties – grammatical devices used to construct coherent narratives – to the development of key elements of community: spirit, authority, trade and art.

Collaborating to know with Web 2.0 tools

In August 2011, Dorothy Faulkner travelled to the EARLI conference in Exeter to present a paper co-authored with me, Denise Whitelock and Kieron Sheehy.

Ferguson, R., Faulkner, D., Whitelock, D., & Sheehy, K. (2011). Knowing how to collaborate: Collaborating to know with Web 2.0 tools. Paper presented at the EARLI  2011 conference, Exeter, UK.

Abstract

This paper reports an exploratory study that draws on sociocultural accounts of learning to frame an investigation of 10 – 11 year-olds’ experience of using of Web 2.0 tools to support informal, self-directed learning activities at home and out-of school contexts. Focus group interviews and visual elicitation methods were used to support informed dialogues with 10-11 year-olds about their use the Internet and Web 2.0 applications. Fourteen children from a UK primary school’s robotics and with computer clubs participated in the study. Children were interviewed in small groups of three or four and were also invited to produce visual representations of the ICT hardware, software and Internet applications they used at home. Preliminary analyses of the drawings and interview transcripts revealed that these participants routinely engage in both face-to-face and on-line learning activities with friends and that they use a variety of instant messaging and mobile technologies to share and exchange knowledge and expertise about gaming and the Internet, the usefulness of different search engines and information and retail sites. The data also reveal that although these children enjoy an extended, global network of family and friends, the learning potential afforded by Web 2.0 tools is hampered by inefficient information search and knowledge-sharing strategies. The paper will draw on the theoretical and analytical framework of activity theory to explain these findings.

Visual Similarity Search

In June 2011, Suzanne Little travelled to Ed-Media in Lisbon to present a paper I had co-authored. In this case, I must admit, my contribution was at most 0.01% of the effort involved in writing the paper.

Little, Suzanne; Ferguson, Rebecca and Rüger, Stefan (2011). Navigating and Discovering Educational Materials through Visual Similarity Search. In: Ed-Media 2011 – World Conference on Educational Multimedia, Hypermedia & Telecommunications, June 27 – July 1 2011, Lisbon, Portugal.

Abstract

We describe the development and implementation of visual multimedia similarity search within a platform for social exchange of educational experiences and material to provide services for finding related media. The SocialLearn project develops tools to support the building and exploration of personal learning networks. With the ever-increasing volumes of educational resources being made available, it is a challenge to find new material and forge appropriate learning pathways. Visual search can help when it is difficult to describe your interests in words (“search terms”) or when you want to browse for inspiration without a specific result in mind. In this paper we present the usage scenarios for visual search within education and describe the design and implementation of visual similarity search within the SocialLearn platform. The outcomes from this work are not only directly useful for the SocialLearn project but also for others who are interested in the challenges of using multimedia for education.