Tag Archives: ANT

Network Learning Conference

More from the Network Learning Conference with Peter Jandric on Research Methods & the post-disciplinary challenge of network learning. Good research has an ‘itch to scratch’. In the case of network learning, there is a range of different methodological approaches. Raises the question on how to compare and synthesise different approaches in network learning?
The Rise of Disciplinarity: Ancient Greece had no discplinary borders but as knowledge became more complex so disciplines began to emerge eg, the seven liberal arts identified in the 7th century that still form the structure of humanities disciplines in western HE to the present day. The liberal arts articulated as the education of a gentleman by C19th (Parker 1890) implying other educations suitable for others, eg, vocational. So disciplinarity became linked to issues of class and culture.
Linking disciplinarity and technique – as human techniques develop, there is increased complexity and so we need more disciplines to cope. But this leads to fragmentation between disciplines as the restrictions of specialisation missing the bigger picture. But also disciplines must therefore, shape how we perceive the future possibilities.
Disciplinarity and the network: radical changes in science occurs through ‘blue skies research’ led by superstar scientists that is formally recognised. But what gets funded is applied research (STEM etc.).
New fields of research such as environmental science and network learning that is postdisciplinarity (see Buckler 2004). The diversity of the field requires diverse knowledge. This opens up large opportunities for forming connections between disciplines and research methods but faces large epistemological challenges.
Four postdisciplinary approaches:
1. multi-disciplinary learning, eg, through technology studies, through learning theory
2. interdisciplinarity seeks integrative results through different methods
3. transdisciplinarity seeks to inform and transform research through integrating disciplines
4. antidisciplinarity where disciplines abandoned entirely.
All these approaches opens up questions on the nature of inquiry on network learning. Points to the importance of being critically conscious of the way we inquire in to network learning.

Q. is antidisciplinarity feasible given strengths of disciplines but also if no disciplinary boundaries that is an interesting space to be in?
A. cites example of HIV AIDs as educationallisation of medicine eg, through preventative awareness raising.

Point made that network learning is a field which people bring their disciplines to.

Cathy Adams and Terrie-Lynn Thompson on materialities of posthuman inquiry. Have you considered the tools used in research may also shape that practice? These can be positive and negative on the research process. But academic expertise is bound up with technologies used daily and shapes that practice and their performative outcomes. Digital technologies are the encoded materialities of academic practice. Looking at the insights provided from Actor Network Theory and from phenomenology. Ingold explores the link between materiality and phenomena in correspondence. ANT subject-object separation are undermined through symmetry while in phenomenology, subject-object division becomes translucent.
Research practice assemblages of long lists of tools for diffusion, search engines, storage tools, visualisation software, etc… Enrolled in the research practice through digital traces including digital artefacts. So digital devices may participate and co-research in research storing, sharing and extending data. This deccentres the human expert in elicit and generate data and can be dynamic leading to movement and slippage. So the researcher is deskilled as research outsourced to digital tools and upskilled eg, in research data curation.
NViVo presented by QSR as a solution to the ‘problem’ of qualitative research but the software may configure and surcumscribe research practice (see Introna 2012). Research found NViVo enhanced the quality of data while reducing the tactility of research and enhancing the position of the technologist. Researchers found that demands of NVivo overtook the intent of the research. Researchers must subscribe to the methodological assumptions and structures of the software.
What are the implications of encoded research practices for researching networked learning. That the non-human actors should be treated as part of the research team – their views taken in to account.
Fluencies can be seen in
1. Agency as researchers is shared with encoded actors as entanglements
2. Research practices undergoing deskilling and upskilling including through the attraction of delegation
3. New enactments of data
4. Scale, mobility and scale of data reconfigured.

Points of friction: research defined by technologies; perceived as less objective is less techie; attraction of exotic tech; outsourcing of research tasks; increase in expectations of speed of research.

Q. push back on issue of symmetry and there is a qualitative difference between human and non-human in the research assemblage. That a telescope allows us to see the moon but is not a co-researcher
A. argues that the non-human component enhances the researcher. In the case of encoded technologies, the algorithm is too often black-boxed but its impact on the research process needs to be opened up.

And running out of steam now but worth following the tweets here

 

Digital Scholarship: day of ideas 2

I’m listening now to Tara McPherson on humanities research in a networked world as the opening session of the Digital Scholarship day of ideas. (I’ve started late due to a change in the start-time).

Discussing how large data sets can be presented in a variety of interfaces: for schools; researchers; publishers and only now beginning to realise the variety of modes of presenting information across all discipline areas. But humanities scholars are not trained in tool building but should engage in that tool building drawing on their historic work on text, embodiment etc. and points to working with artistis on such interpretive tool building – see Mukurtu an archive platform design by an anthropogist based on work with indigenous people in Australia. Tools allow indigenous people to control access to knowledge according to their knowledge exchange protocols.

Open ended group create immersive 3D spaces but is not designed to be realistic but engaging. More usually found in an experimental art gallery. Also showing an example of a project of audio recordings of interviews with drug users at a needle exchanges.

Vectors is a journal examining these sorts of interactive and immersive experiences and research. Involves ‘papers’ that interact, mutate and change which challenges the notion of scholarship as stable. Interactive experiences are developed in collaboration with scholars in  a long iterative process that is not particularly scaleable.

The develop of a tool-building process was a reaction on problematising interaction with data-sets. Example of HyperCities extending google maps across space and time.

The Alliance for networking Visual Culture including universities and publishers working together, reconsider scales of scholarship and using material from visual archives. Process starts with the development of prototypes. Scalar emerged from Vectors work as a publishing platform for scholars using visual materials. Allows scholars to explore multiple views of visual materials linked to archives and associated online materials linked to critical commons (under US ‘fair use’ allowing legal use of commercial material). Scalar allows a high level of interactivity with the material of (virtual) books and learning materials.

Aim to expand proces of scholarly production and to rethink education. For example, USC has a new PhD programme in media studies in which PhD students make (rather than write) a dissertation- see Take Action Games as an example.

Thinking about scholarly practice in an era of big data and archives: valuing openness; thinking of users as co-creators; assume multiple front-ends/ interfaces; scales scholarship from micro to macro; learning from experiment and artistic practices; engaging designers and information architects; value and reward collaboration acros skills sets.

Scalar treats all items in a data-set as at the same ‘level’ so affording alternative and different ways of examining and interacting with the data.

USC School of Cinematic Arts has a long history of the use of multi-media in assessment practices and the development of criteria. Have also developed guidance on the evaluation of digital scholarship for appointment and tenure. The key issue here has been in dealing with issues of attribution in collaborative production.

…………..

Now moved on to the next sessions of the day with Jeremy Knox who is research open education and questioning the current calls for restructuring higher education about autonomous learning  and developing a critique of the open education movement. He is discussing data collection on MOOCS in terms of

  • Space
  • Objectives of education
  • Bodies and how the human body might be involved in online education

Starts with discussing what a MOOC is as free; delivered online and massive. Delivered via universities on platforms provided through main players such as Udacity, Coursera and edX.

Most MOOCs involved video lectures and quizes supported by discussion forum and assessed through an automatic process (often multi-choice quizes) due to the number of students.

Data collection in MOOCs as example of big data in education allowing learning analytics to optimise the educational experience including through personalisation of the educational experience.

Data collected specifically from the MOOC platforms. edX claiming to use data to inform both their MOOC delivery but also to inform development of the campus based progress at MIT

Space – where is the MOOC? edX website includes images of campus students congregating around the bricks and mortar of the university. Coursera makes use of many images of physical campus buildings. Also many images of where students are from through images of the globe – see here

Metaphor of the space of the MOOc is both local and global.

Taught on one of the six MOOCs delivered by University of Edinburgh. Students often used visual metaphors of space in their experience fo the MOOC – network spaces, flows and spaces of confusion. Also the space metaphor used by instructors in delivering MOOCs such as in video tours of spaces. The instructors seeking to project the campus building as the ‘space of the MOOC’ and this impacts on the student experience of the MOOC. The buildings may have agency

What else might have agency in the experience of education? For example, book as a key ‘tool’ of education. Developed a RFID system so that tagged books send a Tweet with a random sentence from the book when placed on a book-stand/ sensor as a playful way of collecting data. So twitter streams include tweets from students/ people and books.

Another example is of YouTube recommended videos recontextualises video with other videos as a mesh of videos and algorithms.

The body in the MOOCs? Is taken in to account through Signature Track that uses the body to tract the individual student.  Now showing a Kinect sensor to analyse how body position changes interaction with a MOOC course which allows the body to intervene and impact on the course space.

How does the body of the teacher be other than the body of external gaze?

……….

Now moving to a Skyped session with Sophia Lycouris Reader in Digital Choreography at Edinburgh College of Art and is working on research in using haptic technologies to enable people with impaired sight to experience live dance performance – see here. A prototype has been developed to allow users to experience some movements of the dance through vibrations. Again, uses a Kinect.

The project explores the relationship between arts and humanities and innovations in digital technology as trans-disciplinary alongside accessing and experiencing forms of performing arts. In particular, interested in how technologies changes the practice itself and how arts practice can drive technological change (not just respond to it).

The Kinect senses movement which is transformed in to vibrations in a pad held by the participant.

Discussing some problems as Microsoft now limiting code changes needed for the project.

The device does not translate dance but does provide an alternative experience equivalent to seeing the dance. The haptic device becomes a performance space in its own right that is not necessarily similar to a visual experience. So the visual landscape of a performance becomes a haptic landscape to be explored by the wandering fingers of blind users.

The project is part of a number of projects around the world looking at kinesthetic empathy.

Question on what models are being used to investigate the intersection of the human and the digital? Sophia focuses on using the technology as a choreographic medium and away from the dancing body. Jeremy’s research underpinned by theories of post-humanism that decentres the human: socio-materialism; Actor Network Theory and spacial theory.

…………

Now on to Mariza Dima on design-led knowledge exchange with creative industries in the Moving Targets project. Focusing today on the methodological approach to knowledge exchange.

Moving targets is a three year project funded by SFc for creative industries in Scotland including sector intermediaries and universities to involve audiences in collaboration and co-design. INterdisciplinary research team including design, games, management. The project targets SMEs as well as working with BBC Scotland.

Knowledge exchange as alternative to transfer model. Exchange model emphasises interaction between all participants to develop new knowledge and experiences. Used design as a methodological approach in the co-design of problem identification and problem-solving.

Used experiential design which is design as experience – the designer is not an expert but supports collaboration; transdisciplinary; experience and knowledge is closely related and interactional working in context of complexity.

Process stages of research; design and innovation. Innovation tending to incremental improvement that returns to research. Knowledge is developed as a concept through research and as an experience through design and innovation.  Phases:

Research involves secondments in to companies as immersion researching areas for improvement, gain and share knowledge and undertaking tasks/ activities. Example of working with CulturalSparks on community consultation related to cultural programme of Commonwealth Games 2014. Research workshops were also held on a quarterly basis.

Design of interventions with companies and audiences using e business voucher scheme. Ran a number of proto-typing projects including looking at pre-consumption theatre audience engagement.

Innovation based on two streams: (a) application of knowledge within the company and (b) identifying transferable knowledge. Have developed new processes, digital tools and products with an aim of creating longer-term impact of process improvements and tacit understandings by both the companies and by the universities/ intermediaries.

Experience of the clients very variable. Agencies much more receptive to working with higher education while micro-enterprises were more cautious as have limited resources. So with company, took a more business-like approach focused on outcomes and have gained positive impact.

The focus project is on supporting creative industries companies to engage with rapid changes in audiences driven by technological changes.

 

Now onto looking at invisible work in software development; data curatorship and invisible data consumption in industry, government and research. Research framework is base don the social shaping of technology; infrastructure studies and the sociology of business knowledge.

Focused on climate science due the importance of the interface between data and modelling projections through software; also in modelling data in manufacturing. In manufacturing is a question of generic software vs localisation via specific vagueness where metadata is under-emphasised and developed. While sharing data in government involved a more specific focus on curation of data and sharing data without affecting data ownership. Discourse on disintermediation tends to downplay costs of co-ordination particularly in respect of trust relations.

Data consumption linked to issues in data visualisation that aggregates and simplifies data presentation with careless consumption of data. Consumers have preference for simplified visualisations such as the two-by-two matrix to aid prioritisation. Such matrices become the shared language for users and the market or are amended as different simplified visualisation such as waves or landscapes.

The specific vagueness of the software ontologies makes comparability across platforms and contexts of the data becomes impossible.

Study on ERP involved videoed observation; situational analysis used in study on government softwares to generate grounded data analysis and study on data visualisation involved direct interviews of providers and users of data.

Ontologies discovered as useless – a life changing discovery!

Twitter and micro-blogging notes on day 2

These are notes from the Twitter and Micro-blogging conference at Lancaster University for day 2.  The full programme can be found on Lanyard.The Twitter hastag is #LUTwit

Conceptualising Twitter as a discourse system by @mdanganh

Looked at the Function of the # – lead to theory of contextualisation based on John J Gumperz conversational inference and contextualisation cues as surface feature that are verbal and non-verbal. So can be used to understand and analyse #

Cues reconfigure conversational contexts that presuppose and create context as social ordering (Bruns & Burgess 2011).

Key part of Twitter as a discourse system. Identifies four functional operators in Twitter: the RT; the @; the # and the link That have technical and communicative function as well as positioning Twitter as intertextual and interdiscursive

For data drawn from Federal State elections 2010 – 2013 over a four week period each year from parties, media, politicians, public interactions, #. Analysis uses

– profile analysis (quant)

– speech act analysis (qual and quant) (Searle), eg, inform, state, assert, announce, request etc……. Found predominately speech acts concerned with exchanging information, especially from the institutional accounts

– discourse analysis (quant informed qualitative analysis

Use case of Conservative candidate #Rottgen. But lost NRW State election and subsequntly also dismissed as Federal minister by Angela Merkel (as a ‘mother’ figure). Discourse developed as mother metaphor

# frames Tweets in to a story narrative frame that is emergent and the co-construction of meaning.

 

Now on to the plenary session with @GregMyers on Working and Playing on Science Twitter

First Tweet on an April Fools as example of different types of Twitter streams – such as different communities  or genres. @GregMyers on writing on blogging realised that there is not one ‘thing’ of a blog – share a media but are very different. Are we talking about one genre or not? Looking at the different papers at the conference it is clear that there is not a single genre or function.

How do different Twitter communities use Twitter? Are there genre differences. Focus here on science Twitter of research scientists.

Networking is a part of any science project from the 16 century onwards. But as a community, depend for reward on the production of a very different text object, the published paper which is very unlike Twitter. So science community is a network of texts but also involving equipment, people, methods, money (ANT).

Identified two themes of sociology of science:

1. heterogeneirty of scientific networks: ANT. You become powerful in science by maintaining a network

2. rhetorical tension between empiricist repertoire as timeless claims in the formal literature and a contingent repertoire and time bound and contingent activities.

Cites letter from C19 that is very Twitter like albeit as provate letter rather than a public Tweet.

More information on Greg’s blog: http://thelanguageofblogs.typepad.com

Corpus analysis based on keywords eg, paper, scientist, research, etc… but more interesting keywords such as: over use of “i” (compared to other Tweets) as a sign of formality; use of “of” as signifier of more complex; “but” as academic signifier and a negative keyword of “love” as evaluation.

Gives ground to identify scientists as a distinct community on Twitter.

Gives an example of phatic communication – communication for the sake of contact (“who is still working” at 3 am). Problematises the use of the term “here” as “a lab” rather than a geographic co-location. Solidarity building?

Particular interest in references to time: current time – what I’m doing now; temporal cycles of, eg, work , publications, terms; future time (what will be happening); and chunking time eg, pleistocene.

Gives example of scientific criticism and never-ending use of citations and references but also criticism of socio-thermodynamics using LOLcats

Scientific criticism involves personal stance; impersonal references to shared norms and hierarchies of authority for presentational purposes. Found many Tweets involve boundary work, sealing off science and non-science while at the same time concerned with outreach and public engagement with science.

Good set of question of a Twitter community:

  • present self as a community?
  • make a distinct genre – eg, use of RT, links etc…?
  • use the same genre / register?
  • how Twitter practices relate to other practices?
  • what specific kinds of performance are valued?
  • how permeable are the boundaries of the community? How many Tweets get RT from outside the community?

Permeability of the science community enhanced as scientist may be member of other communities that may cross-overs of their specific Tweets (hip hop, feminism/ women in science). But not seeing non-scientists coming back and commenting on scientific discussions.

 

The afternoon session is about to kick-off with Noreen Dunnett on The Tweeting Zone with Twitter providing a mechanism for renegotiating boundaries between Activity Systems. Looking also at how Twitter allows renegotiation of identities and roles of learners and teachers in formal learning spaces.

Referes to liminal spaces as a rite of passage in which a person moves from one state of being to another. Could Twitter affordances at act bridge between Activity Systemas a a boundary zone between different systems and spaces? Does Twitter provide scaffolding between learning and working definitions.

Affordances (actionable properties …. user perceives some action is possible. Gibson 1977, 1979 and Norman 2004). The paper uses Connectivism and Activity Theory examining a teacher training course and the student use of Twitter ordered around a given #

Frames Twitter in terms of a Personal Learning Environment (PLE) as allowing learners to coordinate arrangements between people, materials and technology so the PLE is not a platform but is rather a process that requires agency from the learner [as actor].

Uses ethnographic action research including participant observation, interview and survey. Observation of a Twitter chat over a seven month period with researcher moderating initial discussion. Spaces of learning in, eg, Twitter, enacted in to being – emerge rather that design/ predetermined (Al Mahmood 2008).

Screen shot 2013-04-11 at 13.54.07

Cited example of student who left the course asking for permission to continue to use the hashtag.

Trainee teachers participate in a range of discourse communities simultaneously, spanning formal and informal learning environment. The course tutor conflicted about Twitter and the degree of control and policing role.

Useful Tweet here:

Screen shot 2013-04-11 at 13.45.30

Twitter bridge Activity Systems as discourse communities.

Role of tutor not clear: has emergent and non-emergent elements as the Twitter space was formally set up to support students in placement but tutor also wanted to use it for learning tasks by setting up a series of tasks Tutor was concerned that the students controlled by eg, GTC notions of professional conversation.

References from the presentation can be found here

 

Now out of power and seeking a plug point ……

 

Now at An analysis of professional exchange and community dynamics of Twitter from Nicola Osborne and Clare Llewellyn from Edinburgh

Used Martin Hawksey’s TAGs for grabbing #feeds into Google Docs.

Social media collaboration group came into being to analyse Tweets on London riots using manual analysis and wanted to use more automation in the analysis. Clare developed a prototype as the JISC Twitter Workbench initially for analysis of Olympics on Twitter  but extended in to more general academic use. Currently working on developing the Workbench to work with smaller, discreet data including elimination of direct (unchanged) RTs. Testing Workbench for use at a conference (done aferwards but could be done in real time).

Used algorithm  for LDA clustering but found it no more accurate than incremental clustering 

At the conference, was a lot of interest in, for example, PechaKucha and specific talks that gained a lot of interest.

Found different algorithms appropriate for different size of event/ Twitter hashtags. Clusters confirmed some hunches about the conference.

Noted that clustering does not analyse influence of a Tweet. Confirmed participant feedback on conference sessions. Did identify what was popular (not influential?) and ‘hot topics’ etc which could have been very useful for real time use eg, in back channel. Could imply unpopular sessions not Tweeted but this is not clear.

Very clear decline in volume of Tweets after conference – often sharing links.

Analysis was about the content of Tweets and not about connections between Tweets…

Balance to be developed between clustering duplication versus clustering granularity.

Q of why JISC funded this given the existence of NodeXL

Now time for a break….

Fell behind on the blogging – lack of power, fat fingers etc….

Now at the plenary Professional Twitter Panel which can be followed at #lutwitrc

Discussing finding the time for Twitter and intensity, @johnnyunger very variable in intensity of Tweeting. Mentions that avoiding marking leads to increase in Twitter use.

A number of comments in Tweeting in between times

Screen shot 2013-04-11 at 16.25.01

Tweet when we’re doing other things or when can’t do other things

But also comments about the rhythms of the day – energy, roles etc…

Screen shot 2013-04-11 at 16.28.00

… and in relation to activities in “real life” (sitting on the bus) as well as on other SoMe.

Discussion on whether Twitter is distracting or takes time [but avoids issues of cognitive-shifting]

Moving to ethics, eg, is it OK to be anonymous on Twitter and issue of institutional constraints. Also scales of anonymity, eg, less easy to identify the individual rather than anonymous per se.

Comment on analysis of HE SoMe policies that are very constraining requiring various disclaimers for staff. HE senior management prickliness on potential reputation harm from ‘rogue staff’.

Comment that first rule of the internet that there is no such thing as anonymity – don’t say something online you wouldn’t say elsewhere (from @pennyb).

Moved on to impact – beyond simply number of followers but also who follows.

Discussion on ethics and the nature of public domain with good understanding of the nuances around anonymising Tweets. Also refering to Twitter TOS in tension with research ethics, eg, on anonymity.

Web 2.0 and actor network theory

Web 2.0 has emerged as a label for the culmination of incremental developments in software and network technologies over the last twenty years or so that focus on user-generated content and interaction around that content. Whether Web 2.0 represents a paradigm shift in the World Wide Web or the outcomes of various incremental changes remains a point of contention that may be being repeated with the labelling of the semantic web as Web 3.0. Either way, Depauw (2008) makes the case that ANT is an appropriate approach to the study of Web 2.0 phenomena. For example, social software has been described as employing Web 2.0 technologies in “digital social networks” that support interactions between “social entities” (Kieslinger & Hofer 2007, p7). McAfee (2009) discusses what he terms “emergent social software platforms (ESSPs)” (2009, p69) within which content and interactions are made visible and permanent, and the structure and organisation of content and community develops over time and through interaction. McAfee (2009, p73) then defines the term “Enterprise 2.0” as the use of ESSPs by organisations to assist those organisations to be more effective. McAfee’s ESSPs suggest a perspective on social software technologies that sees such technologies as either intermediaries within fairly stable and “unproblematised” organisational networks, or as mediators that assist in the stabilisation of those networks by making permanent and visible that network as an organisational entity.

Others suggest that Web 2.0 technologies undermine distinctions between information producers, distributors and consumers, so making networks inherently less stable (Androutsopoulos 2008; Pata 2009). Within this understanding, it becomes problematic to see them as simply assisting in organisational goal achievement. This study will focus on what may be perceived as a less stable network of a Twitter based chat event and then will seek to engage with other more stable spaces of interaction such as blogs. Both such ESSPs provide data that is mainly but not exclusively text based.

Texts provide a focus on online content but such technical artefacts also act as intermediaries that coordinate networks, suggesting that the target platforms can be seen as intermediary non-human actors (Depauw 2008). The interactional bases of these social software platforms generate and reinforce the practices of social networks, so contributing to the durability of those network effects (Waldron 2010) – the sociality of such environments (Young 2006) underpins and normalises practices of digital interactions. In discussing activities in wider Web 2.0 environments, Bruns and Humphreys (2007) suggest that knowledge and content artefacts are constantly being developed and refined through social interactions and so are dynamic and fluid rather than static and solid. Furthermore, Pachler & Daly (2009) point to Web 2.0 in learning contexts in terms of “narrative trails” (p7) of social and individual sense-making activities. Narrative trails such as the tagging of virtual spaces and flows are part of the emergent and user-centric organising of ESSPs including Twitter and blogs.

Tagging in the context of folksonomies make visible patterns of interactions (Alexander 2006) between actors as “taggers” and actants as data objects that may include both the main text and the tags used to describe and classify that text. From an ANT perspective, tagging and metadata (data about data) provides an important mediating effect on network evolution in social digital learning environments. This notion of metadata linking networks and flows of people, artefacts and traces of activities through social technologies provides a basis for a common ecological metaphor of Web 2.0 learning environments (Siemens 2006; Brown 2002; Pata 2009). The emphasis on metadata can also be found in the emerging label of “activity streams” (Boyd 2010). In both cases, the effects of tagging and metadata as being used to identify specific spaces, flows and content as well as being potentially mobilised to direct those flows is recognised.

In summary, existing literatures suggest that what is currently labelled as Web 2.0 in general but more specifically Twitter and related social platforms is an appropriate and “rich” site for a research perspective based on the sociology of translation, ANT.

References
Alexander, B. (2006). Web 2.0: A new wave of innovation for teaching and learning? EDUCAUSE review. 41 (2): 32-44.Available at: http://www.educause.edu/ir/library/pdf/ERM0621.pdf
Last accessed: 16 February 2011
Androutsopoulos, J. (2008) Potentials and Limitations of Discourse-Centred Online Ethnology. language@internet, vol 5. Available at: http://www.languageatinternet.de/articles/2008/1610/index_html/?searchterm=None
Last accessed: 22 November 2010
Boyd, D. (2010) Streams of Content, Limited Attention: The Flow of Information through Social Media. EDUCAUSE Review, vol. 45, no. 5 (September/October), 26–36
Brown, J. S. (2002). Learning, Working & Playing in the Digital Age. Available at: http://serendip.brynmawr.edu/sci_edu/seelybrown/seelybrown.html
Last accessed: 20 April 2010
Bruns, A. and Humphreys, S. (2007) Building collaborative capacities in learners: the M/cyclopedia project revisited. In Proceedings of the 2007 International Symposium on Wikis, WikiSym. Available at: http://snurb.info/node/753
Last accessed: 25 May 2010
Depauw, J. (2008a). Web 2.0 under the Actor-Network Theory point-of-view: Conceptualization and definitions analysis. Dans Proceedings of Politics: Web 2.0 – An international Conference. Royal Holloway University of London: New Political Communication Unit. Availlable: http://newpolcom.rhul.ac.uk/politics-web-2-0-conference/.
Kieslinger, B. & Hofer, M. (2007) Case study on social software use in distributed working environments. ProLearn, 22 May
McAfee, A. (2009) Enterprise 2.0: new collaborative tools for your organization’s toughest challenges. Boston, MA: Harvard Business Press
Pachler N. & Daly C. (2009) Narrative and learning with Web 2.0 technologies: towards a research agenda. Journal of Computer Assisted Learning 25, 6–18.
Pata, K. (2009) Revising the framework of knowledge ecologies: how activity patterns define learning spaces? in N.Lambropoulos & M. Romero (Eds.) Educational Social Software for Context-Aware Learning: Collaborative Methods & Human Interaction. Information Science Reference. Hershey. New York, 2009, 241-267
Siemens, G. (2006) Knowing knowledge. Available at: http://www.knowingknowledge.com/2006/10/knowing_knowledge_pdf_files.php
Last accessed: 11 November 2009
Waldron, R. (2010) ANT – a natural theory for ICT teachers. 8 March. Available at: http://russellwaldron.edublogs.org/2010/03/08/ant-a-natural-theory-for-ict-teachers/
Last accessed: 23 November 2010