Participatory Transformations

Learning, in its many forms, from the classroom to independent study, is being transformed by new practices emerging around Internet use. Conversation, participation and community have become watchwords for the processes of learning promised by the Internet and accomplished via technologies such as bulletin boards, wikis, blogs, social software and repositories, devices such as laptops, cell phones and digital cameras, and infrastructures of internet connection, telephone, wireless and broadband. This chapter discusses the impact of emergent, participatory trends on education. In learning and teaching participatory trends harbinge a radical transformation in who learns from whom, where, under what circumstances, and for what and whose purpose. They bring changes in where we find information, who we learn from, how learning progresses, and how we contribute to our learning and the learning of others. These trends indicate a transformation to "ubiquitous learning" ??? a continuous anytime, anywhere, anyone contribution and retrieval of learning materials and advice on and through the Internet and its technologies, niches and social spaces.not peer reviewe

The Analysis of Online Communities using Interactive Content-based Social Networks

published or submitted for publicationis peer reviewe

An Information Policy Perspective on Learning Analytics

Policy for learning analytics joins a stream of initiatives aimed at understanding the expanding world of information collection, storage, processing and dissemination that is being driven by computing technologies. This paper offers a information policy perspective on learning analytics, joining work by others on ethics and privacy in the management of learning analytics data [8], but extending to consider how issues play out across the information lifecycle and in the formation of policy. Drawing on principles from information policy both informs learning analytics and brings learning analytics into the information policy domain. The resulting combination can help inform policy development for educational institutions as they implement and manage learning analytics policy and practices. The paper begins with a brief summary of the information policy perspective, then addresses learning analytics with attention to various categories of consideration for policy development

New Metaphors for Networked Learning

As networked learning leaves designed spaces and becomes diffused and re-infused through open, online information sharing and knowledge construction, what metaphors will frame our next steps, our next inquiries? In keeping with the conference theme of ‘Looking Back – Moving Forward’, this presentation will engage with where we are in the sea of change, and how our current understanding of networks, learning and knowledge will take us forward into new areas of inquiry. Elsewhere I have been advocating for a reclamation of the term ‘e-learning’ that takes us beyond the design and use of the closed LMS and VLE systems to grapple with the open conditions of learning on and through the Internet, and the transformative effect this has on roles and relations associated with learning and knowledge practices (Haythornthwaite & Andrews, 2011; Haythornthwaite, 2015). I believe this is a necessary way forward. But, this is a wicked problem, with each change in technology, each advance in teaching practice, and each maturation of networked practice, changing the conditions of inquiry. To maintain our way forward requires keeping an eye on the horizon, and several recent papers make this point with calls for theory driven research on learning in the face of such new conditions (e.g., Rogers, Dawson & Gasevic, 2016; Eynon, Schroeder & Fry, 2016; Wise & Shaffer, 2015). Moving forward requires grappling with perpetual beta, chaordic (chaos+order) processes, emergence and social construction; assemblages, hybrids, cyborgs, post- and transhumanism; the role of the material, geographical, regional; and more. As researchers, teachers and learners, we are learning not just how to learn or effect learning in this fluid space, but rather how to navigate, to sail on the seas of information and knowledge that are beyond our control. We have indeed left the classroom, leaving the safe spaces of ‘specify, build, and use’, and the space of pre-determined questions, into the open, recursive conditions of rapidly accumulating resources, distributed and mobile knowledge, and emergent dynamics. We are leaving the world of uncertainty (in Perrow’s sense of a lack of information) to one of equivocality, where even the questions to be asked must be negotiated. In this talk I aim to stimulate the conversation I know is already ongoing about where networked learning research and practice is going next, and to introduce some play and experimentation with possible metaphors to guide us on the way forward. References •Rogers, T., Dawson, S. & Gašević, D. (2016). Learning analytics and the imperative for theory driven research. In C. Haythornthwaite, R. Andrews, J. Fransman & E. Meyers (Eds.), The SAGE Handbook of E-learning Research (pp. 232-250). London: SAGE. •Eynon, R., Schroeder, R. & Fry, J. (2016). The ethics of learning and technology research. In C. Haythornthwaite, R. Andrews, J. Fransman & E. Meyers (Eds.), The SAGE Handbook of E-learning Research (pp. 211-231). London: SAGE. •Haythornthwaite, C. (2015). Rethinking learning spaces: Networks, structures and possibilities for learning in the 21st century. Communication, Research and Practice, 1(4), 292-306. DOI: 10.1080/22041451.2015.1105773 •Haythornthwaite, C. & Andrews, R. (2011). E-learning Theory and Practice. London: Sage. •Wise, A.F. & Shaffer, D.W. (2015). Why theory matters more than ever in the age of big data. Journal of Learning Analytics, 2(2), 5-13. http://dx.doi.org/10.18608/jla.2015.22.

What Can Social Networks Tell Us About Learning Ecologies?

The ecology metaphor is drawn from the biological sciences and refers to the “scientific study of the distribution, abundance and dynamics of organisms, their interactions with other organisms and with their physical environment” (British Ecological Society, 2016). In recent decades, the metaphor has become useful for tackling the complexity of new information and learning environments, particularly as driven by the increasing quantity of information, the growing number of available media and means of communicating, the extended reach of information technologies, and the new practices arising from these configurations. This paper brings to the discussion of learning ecologies the research and perspectives of social network analysis, where we find synergies in addressing interactions, niches, species and configurations of ecosystems. This perspective opens up some new ways of looking at and understanding learning practices in both online, offline and hybrid settings, and how these create sustainable ecosystems of information exchange and knowledge construction. The ecology and network ideas are highly synergistic, and what has been found from examination of social networks, using methods of social network analysis, can help inform the practice of individual learners, as well the practice of organizing in the service of learning. This paper draws on the literature, and studies by the author to address the network ecology of learning, suggesting ways to organize and anticipate change in order to gain the best advantage from our personal and social learning networks

Beyond the backchannel: Leveraging Twitter to enact learning processes

Conferences provide opportunities for participants to learn with each other through social discovery, interaction and knowledge development. Increasingly, Twitter provides an online backchannel surrounding conference activities. This backchannel both augments in-person interactions, and provides a means for people not in attendance to follow and contribute to the dialogue. Thus, Twitter backchannels provide learning opportunities both for those in attendance, and for others in the wider Twitter-verse. Given that conferences are a forum in which interactive learning takes place, how might Twitter participation at conferences facilitate learning? This session intends to initiate a collaborative dialogue around this inquiry using Twitter as a catalyst, complementing the existing iConference Twitter backchannel. This exploration will focus on content and network analysis methods, discussions on learning networks, and ideation around Twitter as a learning tool. We invite participation both through attendance in the introductory and concluding sessions, as well as via Twitter throughout the conference.ye

Association of Gender with Clinical Expression, Quality of Life, Disability, and Depression and Anxiety in Patients with Systemic Sclerosis

OBJECTIVES: To assess the association of gender with clinical expression, health-related quality of life (HRQoL), disability, and self-reported symptoms of depression and anxiety in patients with systemic sclerosis (SSc). METHODS: SSc patients fulfilling the American College of Rheumatology and/or the Leroy and Medsger criteria were assessed for clinical symptoms, disability, HRQoL, self-reported symptoms of depression and anxiety by specific measurement scales. RESULTS: Overall, 381 SSc patients (62 males) were included. Mean age and disease duration at the time of evaluation were 55.9 (13.3) and 9.5 (7.8) years, respectively. One-hundred-and-forty-nine (40.4%) patients had diffuse cutaneous SSc (dcSSc). On bivariate analysis, differences were observed between males and females for clinical symptoms and self-reported symptoms of depression and anxiety, however without reaching statistical significance. Indeed, a trend was found for higher body mass index (BMI) (25.0 [4.1] vs 23.0 [4.5], p = 0.013), more frequent dcSSc, echocardiography systolic pulmonary artery pressure >35 mmHg and interstitial lung disease in males than females (54.8% vs 37.2%, p = 0.010; 24.2% vs 10.5%, p = 0.003; and 54.8% vs 41.2%, p = 0.048, respectively), whereas calcinosis and self-reported anxiety symptoms tended to be more frequent in females than males (36.0% vs 21.4%, p = 0.036, and 62.3% vs 43.5%, p = 0.006, respectively). On multivariate analysis, BMI, echocardiography PAP>35 mmHg, and anxiety were the variables most closely associated with gender. CONCLUSIONS: In SSc patients, male gender tends to be associated with diffuse disease and female gender with calcinosis and self-reported symptoms of anxiety. Disease-associated disability and HRQoL were similar in both groups

Online Knowledge Crowds and Communities

While much has been written about virtual knowledge communities, particularly in how to create and sustain long-term, strong-tie relationships, the connection has not been made to newer forms of online organizing such as crowdsourcing. This paper addresses the way knowledge collectives are organized online, considering the organizational and motivational structures that support these new knowledge collectives, and contrasting the social mechanisms that support crowdsourced knowledge from those that support community-based knowledge. Examination of the literature and cases of crowds and virtual communities suggest a number of important dimensions that distinguish these two forms of organizing, including contribution type and size, personal coorientation and commitment to the knowledge topic, interpersonal ties among contributors, authority and control of contributory practices, and recognition and reward systems. Exploring these different models of organizing knowledge provides insight into the ways to establish and maintain crowd- and community-based knowledge collectives, and also show why strong knowledge communities such as those found in academia come to change their knowledge distribution practices, notably from print to online publication.published or submitted for publicationnot peer reviewe

Communicating Knowledge: Articulating Divides in Distributed Knowledge Practice

Working together has always been a challenge, but recent trends in who we work with, about what, and across what regions, cultures, disciplines and time zones have conspired to increase the complexity of team work, and in particular the complexity of knowledge work and communication across knowledge divides. Over the past four years, I have been working with colleagues on examining the challenges, problems, and practice associated with distributed knowledge, with particular attention to the way distributed, multi-disciplinary teams communicate and collaborate in the co-construction of knowledge (Kanfer, et al, 2000). In coming to understand distributed knowledge practices, we have been struck by the many kinds of divides and constraints that impinge on any collaborative, multi-party endeavor. This paper explores the nature of distributed knowledge work. Borrowing the concept of asset specificity from organization theory, and affordances from the psychology and technology literature, I suggest that in order to understand work and communication problems for multi-party teams, attention needs to be paid to the knowledge-based asset specificities that can constrain work, as well as to the affordances that may expand the ability to work together across knowledge divides.unpublishedis peer reviewe

Social Informatics of Elearning

This paper presents the background, arguments and examples to support a social informatics of elearning. In more than 25 years of studies of information and communication technology, social informatics draws our attention to how technologies work in practice and in context. Extending the principles of social informatics to elearning requires attention to the history of IT implementation to identify parallels between IT and elearning development, and to use these to produce a foundation for educational informatics. These parallels suggest the usefulness of approaching elearning as an IT implementation, and learning from past experiences with large-scale IT change. Yet the case has not been made. Although a necessary and important component of elearning as a whole, as we have seen in the implementation of computer systems, lack of attention to social and technological impacts, and their co-evolution, leave us at a disadvantage for understanding organizational and institutional transformation. Thus, it is important to learn from IT development to inform elearning development.unpublishednot peer reviewe