Archive for category SocialLearn
Over on Tumblr I have been running a screenshot-a-day project for a couple of years. I layer screenshots upon each other, with an image to represent each day, placed on top of previous images. This functions as a semi-public (open, but not publicised) diary. It also, consciously, forms a record of the online tools I use, and of my digital experience. Sometimes I include a whole-screen shot, showing my applications bar and all open windows, at other times I go for a single image.
This week, I have been looking at the text from 2011, pulling it together in diary format. Wordle revealed my top ten tools, as mentioned in my text, for 2011 (As I was working on SocialLearn, I have excluded it from the list – it would have come in at number 6). The majority are social media, others I use as social media by sharing them via Slideshare (PowerPoints) and Tumblr (screenshots):
I have a new article out in the journal of Educational Technology and Society, focused on social learning analytics. These analytics use data generated by learners’ online activity in order to identify behaviours and patterns within the learning environment that signify effective process. The intention is to make these visible to learners, to learning groups and to teachers, together with recommendations with the potential to spark and support learning.
Buckingham Shum, S., & Ferguson, R. (2012). Social Learning Analytics. Educational Technology & Society, 15 (3), 3–26.
We propose that the design and implementation of effective Social Learning Analytics (SLA) present significant challenges and opportunities for both research and enterprise, in three important respects. The first is that the learning landscape is extraordinarily turbulent at present, in no small part due to technological drivers. Online social learning is emerging as a significant phenomenon for a variety of reasons, which we review, in order to motivate the concept of social learning. The second challenge is to identify different types of SLA and their associated technologies and uses. We discuss five categories of analytic in relation to online social learning; these analytics are either inherently social or can be socialised. This sets the scene for a third challenge, that of implementing analytics that have pedagogical and ethical integrity in a context where power and control over data are now of primary importance. We consider some of the concerns that learning analytics provoke, and suggest that Social Learning Analytics may provide ways forward. We conclude by revisiting the drivers and trends, and consider future scenarios that we may see unfold as SLA tools and services mature.
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.
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.
This provides a context for the learning analytics research and development work that we are currently carrying out on SocialLearn.
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.
In Vancouver for LAK 2012, the second Learning Analytics and Knowledge conference. Lots of good representation from the Open University: Simon Buckingham Shum taking the lead as one of the programme chairs, Doug Clow joining the panel on building a data governance model for learning analytics, Fenella Galpin and Sharon Slade leading a workshop on the ethics of labelling students.
On 1 May I presented ‘Exploring Qualitative Analytics for E-Mentoring Relationships Building in an Online Social Learning Environment’ I was third author on this paper, with the lead taken by Haiming Liu and Ronald Macintyre.
The language of mentoring has become established within the workplace and has gained ground within education. As work-based education moves online, we see an increased use of what is termed ‘e-mentoring’. In this paper we identify some of the challenges of forming and supporting mentoring relationships virtually, and explore the solutions afforded by online social learning and Web 2.0. Based on a conceptualisation of learning network theory derived from the literature and from qualitative learning analytics, we propose that an e-mentoring relationships is mediated by a connection with or through a person or learning objects. We provide an example to illustrate how this might work.
In November 2010, Simon Buckingham Shum travelled to Barcelona to present our jointly authored paper at OpenED2010. That presentation evolved into a chapter for Collaborative Learning 2.0: Open Educational Resources, ‘a collection of the latest research, trends, future development and case studies within the field’.
Ferguson, R. & Buckingham Shum, S. (2012), Towards a social learning space for open educational resources. In: Okada, A., Connolly, T. & Scott, P. (eds.) Collaborative Learning 2.0: Open Educational Resources. IGI.
This chapter examines the meaning of “open” in terms of tools, resources, and education, and goes on to explore the association between open approaches to education and the development of online social learning. It considers why this form of learning is emerging so strongly at this point, what its underlying principles are, and how it can be defined. Openness is identified as one of the motivating rationales for a social media space tuned for learning, called SocialLearn, which is currently being trialed at The Open University in the UK. SocialLearn has been designed to support online social learning by helping users to clarify their intention, ground their learning and engage in learning conversations. The emerging design concept and implementation are described here, with a focus on what personalization means in this context, and on how learning analytics could be used to provide different types of recommendation that support learning.
In September 2011, I travelled to the University of Wales to attend Creating Second Lives 2011: Blurring Boundaries.
FERGUSON, R. Death of an avatar: presence and learning in virtual worlds. Creating Second Lives 2011: Blurring Boundaries, 2011 (8-9 September) Bangor, Wales.
Death is a common feature of online environments. Comically or tragically, predictably or unexpectedly, our characters and those around us are destroyed. In most cases there is the option to rebirth, reboot or respawn at the cost of power, position or points. Reincarnation is the norm, death is rarely terminal.
A price we pay for inhabiting and committing to long-term engagement with virtual worlds is the introduction of deeply felt deaths that can end and overshadow our lives.
This ethnographic account of Teen Second Life considers the implications of the boundary between life and non-life becoming less permeable. Pseudonym, one of the author’s avatars, is currently a shadowy figure who has survived the destruction of her world but has not yet been admitted to the next. Over the past years, she has joined her community in mourning real-world losses and in-world losses, and in memorializing the real, the unreal and the virtual.
This account draws on three intertwined elements: reactions to the permanent loss of an avatar, reactions to the permanent loss of a community member, and reactions to the real-world death of a community member. Pseudonym – or her ratava – felt these losses deeply. She draws on her personal responses, and on the accounts of other community members, to develop an understanding of what it means to introduce death to a world whose inhabitants have believed themselves unlimited by physical constraints. She considers the ethics of comparing the death of a human being with the non-appearance of a certain combination of pixels. She reflects on realism, identity and community – and on whether these are trivial, or even possible, in the absence of death.
In June 2011, I gave a presentation about SocialLearn at a technology coffee morning organised by The Open University’s Institute of Education (IET).
View the podcast.
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.
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.
At the CAL Conference 2011 in Manchester, I set up and ran a symposium on learning analytics.
‘Learning analytics is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning’ (Siemens, 2010). Educators have a long history of using data to examine, analyse and evaluate teaching and learning. The recent increase both in the number of students engaged in online learning and in the variety of tools available to support this activity can mean that the amount of data and resources available proves confusing and overwhelming. Educators and learners urgently need analytics that will help them to evaluate and use these new tools and resources effectively to support teaching and learning.
This symposium presents research carried out at The Open University, the UK’s largest provider of online education with over 180,000 students currently registered, and many thousands more accessing its learning materials through open learning programmes such as Open Learn, iTunesU and iSpot. The OU has been producing wholly online undergraduate courses since 1999 and has, since its foundation, made use of learning analytics to support its students and tutors.
The four papers in this symposium deal with issues that have prompted the current worldwide interest in learning analytics: the need to improve learners’ experience, the emergence of new tools to support data analysis, the overwhelming increase in online resources, and the development of new tools for learning and teaching.
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