Tag Archives: PhD

Open online spaces of professional learning: searching for understanding  the ‘material’ of Twitter discussion events

Here are the slides from my presentation to the Social Informatics cluster group meeting of 13 June 2014.

Abstract:

Recent years have seen a growth in micro-blogging discussion events intended to support professional learning (McCulloch, et al, 2011; Bingham and Conner, 2010) communities. These events often take place on Twitter and are open to anyone using that service. The synchronous events are organised through the convention of hashtags (#) in combination with a shortened name as an explicit mechanism to aggregate contributions and enable open interactions (Bruns 2011).
This presentation will explore an initial investigation of two of these Twitter discussion event communities that both target corporate learning and development professionals. The overall study is concerned with how social discourses within a specific context emerge as sense-making and legitimation strategies around particular practices (Phillips and Hardy 2002: 25) and so will employ a multi-modal discourse analysis approach (Levine and Scullion 2004). However, the data from these Twitter discussion events does not have a transparently coherent structure as discussion sequences run coterminously and interrupt one another (Honeycutt and Herring 2009). So, with the purpose of “making sense of the data”, this presentation outlines the approaches used in identifying and analysing the key patterns of participation and structures of the Twitter discussion events. The descriptive statistical approaches suggested by Bruns (2014) are used to analyse the Twitter events and to discuss the limits of such analysis with reference to recent debates on the nature and status of ‘data’ in digital research (boyd and Crawford 2012; Baym 2013). The extent to which this kind of analysis can reveal the power and participation strategies of Twitter users in these events will be discussed.

Google Alert for the Soul

See on Scoop.itNetwork learning

Peter Evans‘s insight:

An interesting but unconvincing argument presented here. The corrupting influence of consumerism on authenticity appears to be to be based on a ‘straw man’ argument accepting identity as individual. The corruption is due to the colonisation of self-actualisation by consumerism. Yet, arguably, the idea of an authentic individual (internal) identity has always been problematic.

Secondly, the argument that individual identity is being transformed by social media to a socialised and computationalised (and networked?) identity appears to rely on technological determinism. Social media has not made “Authenticity as fidelity to an autonomous, unified a priori self” untenable. It was always untenable as humans are inherently social animals. Furthermore, the idea that the quantified self is a way of locating an authentic self seems distinctly flawed and would benefit from a more critical analysis of the ‘computational turn’ in the social sciences. Ben Williamson’s notion of the ‘data doppleganger” seems more appropriate here (http://bit.ly/1lwXlIC)

 

See on thenewinquiry.com

Digital Scholarship day of ideas: data [2]

This is the second session of the day I wanted to note in detailed (the first is here). The session it Robert Procter on Big Data and the sociological imagination, Professor of social informatics at the University of Warwick. These notes are written live from the live stream. So here we go:

The title has changed to Big Data and the Co-Production of Social Scientific Knowledge. The talk will explain a bit more on social informatics as a hybrid computer scientist and sociologist; the meaning of ‘big data’ and how academic sociology can use such data including the development of new tools and methods of inquiry – see COSMOS – and concluding with remarks how these elements may combine in an exciting understanding of how social science and technology may emerge through different stakeholders including crow-sourced approach.

Social informatics is inter-disciplinary study of factors that shape adoption of ICT and the social shaping of technology. Processes of innovation involving districted technologies are large in scale and involve diverse range of publics such as understanding social media as processes of large-scale social learning. Asking how social media works and how people can use it to further their aims. As it is public and involves social media makes it easier in many ways to see what is going on as the technology makes much of the data available (although its not entirely straightforward).

Social media is Rob’s primary area of interest. Recent research includes on the use of social media in scholarly communications to put research in the public domain. But the value of this is not entirely clear. Identified positive and negative view points. The research also looked at how academic publishers were responding to such changes in scholarly communications such as supporting the use of social media as well as developing tools to trace and aggregate the use of research data. This showed mixed results.

Another research project was on the use of Twitter use during the 2012 riots in England in conjunction with The Guardian. In particular, was social media important in spreading false information during such events. So the research looked at particular rumours identified in the corpus of Tweets. So how do rumours emerge in social media and how do people behave and respond to such rumours?

This leads to the question of how to analyse 2.5m Tweets which is qualitative data. Research needs to seek out structures and patterns to focus scarce human resources for closer analysis of the Tweets.

Savage and Burrows (2007) on empirical sociology arguing that the best sociology is being done by the commercial sector as they have access to data. Academic sociology becoming irrelevant. However, newer sources of data that provides for enhanced relevance of academic sociology and this is reinforced by the rise of open data initiatives. So we can feel more confident on the future of academic sociology.

But how this data is being used raises further issues such as linking mood in social media with stock market movements but this confuses correlation and causation. Other analysis has focused on challenges to dictatorial regimes and the promotion of democracy and political changes and for social movements to self-organise. Methodological challenges are concerned with dealing with the volume of data so combining computation tools with sociological sensitivity and understanding of the world. But many sociologists are wary of the ‘computational turn’.

Returning to the England riots looking at the rumour of rioters attacking a children’s hospital in Birmingham. This involves an interpretive piece of work focused on data that may provide useful and interesting results. So the rumour started with people reporting police congregating at the hospital and so people inferred that the hospital was under threat. The computational component was to discover a useful structure in the data using sentiment and topic analysis – divided Tweets into original and retweets that combine in to an information flows and some flows are bigger than others. Taking size of the information flow as an indicator of significance can provide an indication for where to focus the analysis. Used coding frames to capture the relevant ways people were responding to the information including accepting and challenging Tweets. This coding was used to visualise how information flows through Twitter. The rumour was initially framed as a possibility but mushroomed and different threads of the rumour emerged. The rumour initially spreads without challenge but later people began to Tweet alternative explanations for the police being her the hospital i.e., a police station is next to the hospital. So rumours do not go unchallenged and people apply common-sense reasoning to rumours. While rumours grow quickly in social media but the crowd sourcing effects of social media help in establishing what the likely truth is. This could be further enhanced through engagement from trusted sources such as news organisations or the police? This could be augmented by computational work to help address such rumour flows (see Pheme).

There is also the question of what the police were doing on Twitter at the time. In Manchester, accounts were created to disseminate what was happening and draw attention to events to the police so acting to inform public services.

This research indicates innovation as a co-production. People collective experimenting and discovering the limitations and benefits of social media. Uses of social media are emergent and shaped through exploration.

On to the development of tools for sociologists to analyse ‘big’ social data including COSMOS to help interrogate large social media data. This also involves linking social media data with other data sets [and so links to the open data]. So COSMOS assists in forging interdisciplinary working between sociologists and computing scientists, provide interoperable analysis tools and evolve capabilities for analysis. In particular, points to the issues of the black-boxing of computational analysis and COSMOS aims to make the computational processes as transparent as possible.
COSMOS tools include text analysis and social network analysis linked to other data sets. A couple of experimental tools are being developed on geolocation and on topic identification and clustering around related words. COSMOS research looking at social media and civil society; hate speech and social media, citizen science, crime sensing; suicide clusters and social media; and the BBC and tweeting the olympics. Points to an educational need for people to understand the public nature of social media especially in relation to hate speech.

Social media as digital agora, on the role of social media in developing civil society and social resilience through sharing information, holding institutions to account, inter-subjective sense-making, cohesion and so forth.

Sociology beyond the academy and the co-production of scientific knowledge. Points to examples such as the Channel 4 fact checker as an example of wider data awareness and understanding and citizen journalism mobilises people to document and disseminate what is going on in the world. Also gives the example of sousveillance of the police as a counter to the rise of the surveillance state. The Guardian’s use of volunteers to analyse MP expenses. So ‘the crowd’ is involved in social science through collecting and analysing data and so sociology is spanning the academy and so boundaries of the academy are becoming more porous. These developments create an opportunity to realise a ‘public sociology’ (Burawoy 2005) but this requires greater facilitation from the academy through engaging with diverse stakeholders, provision of tools, new forms of scholarly communication, training and capacity building and developing more open dialogues on research problems. Points to public lab and hackathons as means for people to engage with and do (social) science themselves.

Digital Scholarship day of ideas: data

Live notes from the day.

Starting the day with Dorothy Meill, Head of CHSS introducing the third annual day of ideas as a forum for those interested in digital scholarship across the University and College. Today has a mixture of internal and external speakers. Also mentions the other digital HSS activities including the website and the other events listed there.
Todays’ focus is on data as a contested but popular term. What does it mean for HSS and what traction does it have in the humanities and what currency does big data have for humanities and what are the implications for the computational turn for digital scholarship?
The event is being streamed on the website and the presentations will be posted there later.

Sian Bayne introducing Annette Markham as a theorist of the internet and is currently at Aarhus University. Her focus is on ethnographic research and the ethics of online research. She also has a good line on paper titles.

Annette Markham asking “‘Data’ what does that mean anyway?”. For the last five years or so she has been particularly pushing at thinking about method to better represent the complexities of 21st Century life. She works with STS, informatics, ethnographers, social scientists, linguists, machine learning scholars etc. The presentation is based on a series of workshops published in First Monday special issues October 2013.
Annette argues that we need to be careful about using the term data as it assumes we’re all meaning the same term. Taking a post-humanist perspective or at least non-positivist stance. It is our repsonsibility to critique the word “data”. For other researchers, data and big data are terms that seem unproblematic.

Annette is providing an overview of the debates on data and a provocation to start the day. Asking what does method mean for our forms of inquiry requires ‘method’ to be looked at sideways or from above and below ‘method’ to take account of  the epistemological and political conditions for inquiry. Such conditions include funding constraints and demands around, for example, developing evidence bases and requirements for the archiving of data. But the latter is problematic in terms of capturing and tracing ethnographic research and ‘data’. Also look below ‘method’ in terms of the practices of inquiry that involve the gathering and analysing of data as well as the practices of “writing up”.
The notion of framing inquiry (Goffman) involves drawing attention to some things and excludes others – those outside the frame. Changes the frame changes the focus of inquiry and perspective of the phenomenon. Different images such as frames, a globe/ sphere, a cluster of connected nodes (sociogram or DNA) are used to critique the notion of a ‘frame’. A frame guides our view of the world but is often invisible until it is disrupted. So it is important to make the frame visible.
The term data acts as a frame but is highly ambiguous yet is often perceived as being universally understood, eg, not visible as a framing mechanism.
How are our research sensibilities being framed? To understand the question, we need to ask how are we framing culture, objects and processes of analysis and how do we frame legitimate inquiry. Culture is framed in internet studies through the changes due to the internet, as a networked culture but also how our understanding of the internet as embodied informational spaces. Interfaces developed from an interest in architecturalised spaces towards standardised interfaces to simplification as represented by Google. This is linked to the rise of commercial interests in the internet. the frame of objects and processes of inquiries has not changed much and not changed sufficiently. Inquiry involves entangled processes of social interaction online yet methods remain largely based on 19th century practices. Research models are generally based on linear processes (deductive) which acts to value linear research over messy and complex. We are still expected to draw conclusions for example. The framing of legitimate inquiry has gone backwards from the feminist work on situated knowledge and practice in the 1960s towards evidence and solutions based practices.
So what is data? An easy term to toss around to cover a lot of stuff. It is a vague term and arguably powerful rhetorical term shaping what we see and think. The term comes from 18th century sciences and popularised via translation of scientific works. As a term, ‘data’ was used as preceding an argument or analysis so data is unarguable and pre-existing – it has an “itness”. Data cannot be falsified. Data as a term refers to what a research seeks and needs for inquiry. Yet there are alternative sociological approaches involving the collection of ‘material’ to construct ‘data’ through practices of interpretation. So a very different meaning from ‘data’ as more widely used.
Refers to boyd and Crawfords 2011 provocations on big data and Baym’s 2013 work arguing that all social metrics are partial and non-representative and thereis ambiguity involved in decontextualising material from its context.
Technology now pervasive in everyday life as repsented in a Galaxy S II advert. Experiences are flattened and equalised with everything else and than flattened again as informational bits that can be diffused shared through technology.
Humans as data argument. She has nothing against data and computational analysis as such analysis is important and powerful. But wants to critique the idea that data speaks for itself and that human interaction with technology produces just data. Not all human experience is reduceable to data points. Data is never raw, it is always filtered and framed. Data operates in a larger framework of inquiry and other frameworks of inquiry exist that do not focus on data. Rather, this is inquiry that is focused on the analysis of phenomena involving play around with understanding that phenomena (not data).
Data functions powerfully as a term and acts as a frame on inquiry and this should be subject critique. Inquiry can and should be playful and generative in its entanglements with ‘the world’.

Q: what is the alternative to data? What is human experience reducible to?
A: that’s not the key question. We don’t want to think in terms of reduction which is how data generally frames inquiry.

 

This talk was followed by a fascinating use of crowd-sourced data coding by Prof Ken Benoit. This included completing an analysis of a UKIP manifesto during the course of the talk via cloudflower.

A model of discussion events on Twitter

As previously discussed here & here, I am studying two Twitter discussion events as sites of professional identity formation and development. The broad structure of the two events is broadly similar to the research process of a Tweetstorm: “an online, open brainstorm-like session via Twitter” (Sie, Bitter-Rijpkema, and Sloep 2009: 60). A Tweetstorm was described as a six stage process involving: (i) the context established by, for example, a topic briefing; (ii) questions are presented on Twitter by the event moderator organised using the specified event hashtag; (iii) answers to the questions are given as tweets by participants; (iv) these tweets are aggregated, for example, using Tweet Archivist; (v) the aggregated tweets are analysed into categories and (vi) the categories are then analysed. The outputs from a Tweetstorm are a series of core statements drawn from the knowledge of the participating experts. As such, a Tweetstorm has similarities to the processes of Delphi studies (Nworie 2011) or collaborative concept mapping (Simone, Schmid, and McEwen 2001).

The individual discussion events broadly followed the structure of a Tweetstorm. However, in these discussion events, the Tweets are not aggregated, categorised or systematically analysed. Rather, they conclude with a call for participants to identify the key points of the discussions and any actions they may take in response to the points made.

Based on the notion of the Tweetstorm, the chat events’ structure can be summarised as follows:

Figure 1: structure of the chat events

Figure 1 Sie et al

 

References

Nworie, John. 2011. “Using the Delphi Technique in Educational Technology Research.” TechTrends 55 (5) (August 11): 24–30. doi:10.1007/s11528-011-0524-6.

Sie, Rory, Nino Pataraia, Eleni Boursinou, Kamakshi Rajagopal, Isobel Falconer, Marlies Bitter-rijpkema, Allison Littlejohn, and B Peter. 2013. “Goals , Motivation for , and Outcomes of Personal Learning through Networks: Results of a Tweetstorm.” Educational Technology & Society 16 (3): 59–75.

Simone, Christina De, Richard F. Schmid, and Laura A. McEwen. 2001. “Supporting the Learning Process with Collaborative Concept Mapping Using Computer-Based Communication Tools and Processes.” Educational Research and Evaluation 7 (2-3) (September 1): 263–283. doi:10.1076/edre.7.2.263.3870.

Freelance Film workers in Beirut: An Ethnographic Network Analysis by Arek Dakessian,

These are some rough notes on this presentation from a series of seminars run by the Social Network Analysis Group in Scotland (SNAS). The intro to the talk states:

Arek is a first year PhD student in Sociology at the University of Edinburgh, and his research mainly revolves around networks of cultural production in cities, specifically Beirut. He aims to unpack the relationship between processes of cultural production and consumption and the day-to-day political economy of his city.

His presentation titled “Freelance Film workers in Beirut: An Ethnographic Network Analysis” is the same title he gave a paper currently under review, but his presentation would focus more on doing a dual mode social network analysis based on ethnographic data and some of his dissertation findings.

This is a small informal seminar group. My notes will be very partial and live (and with poor spelling and grammer).

Announced that SNAS as received some funding to become more research-focused and link with the other universities in Scotland and to run two workshops in 2014. The workshops will be focused on what people are doing in Scotland on SNA and whether there is potential for collaborative research.

Arek’s research is on networks of cultural producers and  mainly film-makers in Beirut. He will be talking about the experience of practicing and the research experience of conducting SNA, especially shifting from ethnography and mixed method network analysis.

Narratives of Bierut dominated by bombs and nightlifes. The reality is more complex (as you’d expect). Consists of approx 18 different sects cutting across cultural and ethic boundaries; also 80k + non-national domestic staff (who are not allowed to practice their religions as not generally one of the 18 official sects; also Palestinian refugees based in camps as well as refugees from Syria. So have clear interplay between politics and culture and complex networks of cultural production.

Arek’s ethnographic research on social capital in networks of cultural production – essentially how to gain access to those networks and to “make it”.Initially completed some basic SNA involving centrality but not fully developed.

Ethnographic SNA is difficult in terms of sampling and bounding the network as well as data gathering. Using textual data such as credit lists linking people, objects and events. To ethnographically understand “what is going on” – identifies who is not included in the textual data.

Seeks to enhance SNA through using textual data, eg, the politics of network and multi-plexity and the double ’embeddedness’ of SN – networks within networks. In the case of Beirut, sect/ religious networks also very important in understanding the networks of cultural production.

Will be undertaking dual mode of network analysis and then to explore the semiotics running behind these networks. So the interaction of politics and cultural production can be explored.

UFHRD Conference 5 June 2013

This years UFHRD conference is themed on human resource development (HRD) and the challenges and opportunities in times of economic uncertainty. I’ll be life blogging the event as best I can (including a disregard for the conventions of spelling, syntax and grammer).

First up is a keynote address from Kathryn Mountford, Head of HR at the Money Advice Service on “Leadership, HRD and Organisational Change”.

To start with some background on Kathryn’s own experience across three organisations which has had the benefit for her being being able to see the results of change initiatives. Included working for Church of England especially in terms of assert management. From mid 1990s worked in transforming the Pensions Regulator and expanding its abilities in supporting development of pensions and now with Money Advice Service.

Therefore all have a strong public sector ethos but now under pressure to: deliver more for less; digital enabled and changing in customer and stakeholder expectations (and away from being producer/ provider centric to customer-centric). Much change involved bringing in private sector expertise to the public sector in, eg, asset management or business transformation.

Looking at a series of stereotypes of private sector workers in the public sector:

the maverick usually from start-up or similar environment to push through agile development, new ideas, networking and creativity. Good at engaging people in change but can be too radical for some creating tension with Boards. They tend to see HR as blocking change – the police. Also become easily bored and can get distracted by new things… need t be occupied with ‘right’ sort of work.

The aggressor: on a personal mission to transform the poor public sector and driving through massive tides of change and introducing a commercial mindset. Very good networkers and ambassador of organisation. Tell lots of ‘battle’ stories and can be keen to be seen as elite of the organisation which can create tensions. They may have come from a macho environment and can bring that with them which again can create tensions – can often include women from private sector.

The evangelist: joins the organisation as have had a bashing in the private sector and looking for some form of redemption. Can be great at moving the organisation forward with focus on the purpose of the organisation. Can be very evangelical and bringing in fresh skills and networks while reminding colleagues of what they’ve given up to join the organisation. Tend to be keen on HR as welfare provider and employee focused.

The corporate player: worked in large private institutions such as banking and insurance focused on governance and hierarchy. Very good on maintaining core activities during change but tend to have a dislike of the uncertainty and mess of change. Can also find it harder giving up their position as small fish in a big pond and becoming a bigger and accountable fish!

the consultant: used to working in uncertainty but can rely on previous approaches being applicable to public sector and also also seeking to increase their own revenues rather than  the job in hand. The best consultants seek to leave a positive legacy.

The real worlders: a great asset to the organisation coming from bigger institutions working on big ventures and now at end of their careers looking to give something back – were very valuable in the Pensions Regulator. Helped other staff in coping with the changes in the public sector and the realities of the private sector environment.

Other elements important for making the best of private sector skills in public sector organisations. There needs to be a clear organisational appetite for bringing in the private sector and this is explained to staff the benefits of a mixed workforce. The HR strategy needs to be geared to manage a mixed workforce of short-term employees, contractors and secondees and along with development of existing staff, eg, secondments to the private sector and L&D interventions.

Also important on clarifying the values of the organisation that are used to manage staff behaviours to create a longer-term stable environment. Recognition and reward balanced between existing staff rewards and needs to attract higher performers from private sector. Boards need to understand the link between salary and behaviours. Job titles are important so those from private sector do not perceive a loss of status as well as provide mentoring/ internal consulting opportunities.

Recruitment and selection becoming more aligned with private sector practices including use of head hunters and how the organisational proposition is stated. Also important to demonstrate the absence of bureaucracy in the pubic sector recruitment processes.

HR business partnering in a period of change presents opportunities and challenges of bringin in new talent but needs managing.

Bringing in private sector colleagues is common in the public sector and can provide lots of value in terms of knowledge and understanding transformational change. Modernisation is something private sector has a good deal of experience of. HR can help to facilitate the organisation to make best use of such staff and act as guardians of the values of the public sector host.

Questions: 

1. to what extent has HRD been part of the contribution of these private sector staff in public sector organisations?

Kathryn cited experience of some private sector colleagues pushing importance of progressive HRD provision but their remains a residual view of HR as an administrative function.

2. which is the hardest stereotype if the hardest to manage?

The Maverick can be the hardest as provide a lot of value as focused on driving change and innovation and leading teams but challenging as don’t take account of governance and related concerns in public sector.

3. Do you have bringing in academics to your organisations?

MAS currently working with academics on consultancy basis so can be precise on what the academics are being asked for. Tend to support change rather than lead change.

4. How do you retain the corporate players?

But need to be realistic and you shouldn’t plan to retain the corporate player – rather treat them as an interim manager and manage expectations along these lines.

5. not all private sector people will be successful in transferfing to the public sector and what is your experience of that?

Need to acknowledge that there will be failure. From my own experience, possibly roles for the mavericks could have been better design to focus on innovation rather than in combination with general management activities.

6. does working under government whim prove difficult.

MAS is independent but public sector and raises question of role of MAS as focused on government agenda or to be more citizen-centric. Also MAS bring in colleagues from central government.

7. what has been the reaction of public sector staff to private sector colleagues?

Often based on stereotypes of private sector workers that can only be dealt with by experience of private sector colleagues. HR’s role is to ensure their is a fairness and transparency in how staff are treated and that all staff describe themselves as working for XXX rather than “being on secondment from …”.

 

Moving on now to the main conference paper sessions.

I’m in the session on Innovation, Sustainability & HRD.

First paper from Chris Mabey on managing the paradoxes of staying innovative. This is based on research taking place at CERN/ ATLAS on what re strategic knowledge assets, are these being leveraged effectively and can HRD functions facilitate this? These questions are relevant to universities as sites of knowledge activists.

Three kinds of knowledge: from structured (codified/ abstract/ materialised/ formalised)  through to unstructured/ experiential and highly personalised knowledge as a single axis with narrative knowledge (stories and fables) at the mid-point. A second axis is about diffusion/ sharing of knowledge – with structured knowledge being the least problematic in terms of diffusion, eg, public knowledge. WHile widely diffused unstructured knowledge might be understood as common wisdom.

In terms of strategic management concepts, core competences might be seen as unstructured and difficult to diffuse. Patents and copyright may be more structured but still not widely diffused. Industry-wide principles might be structured and diffused. Industry wisdom is widely diffused but unstructured.

But what does this mean for HRD as all knowledge ‘types’ have benefits and challenges and attached to them. So personal/ unstructured experiential knowledge share through mentoring but often not captured by the organisation – cited Polyani stating we know more than we can say – and is fragmented. So this knowledge leaks especially with downsizing of organisations. While proprietary knowledge can be locked-in/ rigid, under exploited and perishable. Public knowledge brings challenges of being in the public arena and therefore common/ lacks differentiation and may not be validated – so downloadable competence frameworks work but provide no differentiation or specific fit. Conventional wisdom provides the challenge of how to locate and use such knowledge (boundary spanners).

ATLAS as a huge experiment involving 3,500 scientists and engineers at the large hadron collider. Scientists and engineers asked what knowledge they needed to do their jobs – requiring high structure and diffusion – while the unstructured and experiential and difficult to diffuse was also cited as important to getting the work done.

How could the tacit knowledge be understood and diffused to wider group of people given the scale of the organisation? How do we identify the core knowledge assets and leverage that including managing leakage of knowledge from the organisation where staff turnover is high (due to secondments, short-term research contracts etc.).

But …. paradoxes: (1) the more knowledge is managed the less valuable knowledge will be exchanged. For HRD need to acknowledge that the scientists/ engineers are highly motivated by the shared goals of the experiments and professional peer pressure rather than corporate compliance. Also, they are seeking long-term legacies rather than short-term benefits. So HRD might look to coaching, mentoring, apprenticeships and light-touch governance to avoid micro-management.

(2) the more democratic knowledge sharing is designed, the more intentional leadership is required –  to lead spontaneous exchanges of tacit knowledge, eg, in the importance of the cafeteria as a site of knowledge exchange. But this needs to be thought about, planned and supported. “Things work when people identify themselves with the project”, eg, place the emphasis on ethos setting but “nudge to make it happen”.

(3)  the more knowledgeable the professional the less likely they are able to lead. As there is a tension between specialists vs boundary scanners and focused on trusted sources rather than drawing in other perspectives (know what rather than how) and emphasise output rather than process and emphasise collective acknowledgement over solo success. For HRD, how can the function support boundary scanning and diffusing; developing skills in learning, diversity and emotional intelligence.

(4) the more informal knowledge sharing is, the more open to elitism it becomes: ‘the tyranny of structurelessness’.

Questions:

1. what sort of people were interviewed and to what extent the nature of the people involved in the ATLAs project have influenced findings?

59 people interviewed at CERN and so tended to be successful but also interviewed some people in China. So cannot claim representativeness but did interview a wide-range of people. But ATLAS are atypical but we can still learn from them for a knowledge-based economy. We can really learn in terms of long-term horizon and the ethos formulation.

 

Now on to Alex & Andrea  Ellinger and Scott Fitzer on Leveraging HRD to Improve Supply Chain Management (SCM) Knowledge & Skills. Looking for HRD and SCM synergy in response to the talent shortages in SCM as SCM becomes increasingly complex through globalisation. In particular, the people aspects of SCM have been de-prioritised to technology and customer-service issues.

SCM professionals manage risk, relationships and tradeoffs requiring softer people skills to harders statistical analysis and problem-solving. In addition, senior managers tend not to appreciate the complexity of the SCM roles. This is important – up to 75% of firm revenue is spent on SCM activities (Trent 2004) – purchasing, manufacturing, moving, storing, selling, servicing products, etc……[but then is there anything left?]

But SCM tend to be dominated by a ‘push’ perspective focused on cost control and specifications rather than relationship-building and customer-centric so responsive to market demand. This places the focus on process innovation rather than process improvement (six sigma etc.).

So we can see functional specialisation of organisations acts as barrier to knowledge sharing  including the lack of understanding of SCM among other and senior managers. Including making the financial-SCM connection. Gives rise to dis-functional incentives around sales and production. But also, SCM have been weak on making the business-case for SCM investments at the C-level – see R.E Slone (2004) Leading a Supply-Chain Turnaround. HBR.

The problem is the supply-demand split in organisations as the two facets of the organisation fail to communicate to one another. Demand-Supply integration requires HRD interventions. But the field of HRD little understood in the SCM domain. HRD as focused on learning, performance and change.

Both HRD and SCM are marginalised in organisations. But SCM offers an opportunity to demonstrate the strategic importance of HRD as 75% revenues tied into SCM. So what can HRD offer SCM and SC Managers? HRD may have strategic role in facilitating solutions development around the people development and change needs in SCM and developing the competences of SCManagers to respond to the challenges they are facing.

Game changing SCM trends (Sweeney): collaboration; lean & six sigma; management of complexity’ network optimisation; globalisation; sustainability; cost and working capital. Human and behavioural of SCM neglected in comparison to physical and technical components. Key areas for HRD may be in organisational development aspects of facilitating collaboration, learning supporting for six-sigma (coaching etc). SCM is foremost about people yet the people dimension in SCM is under researched (Sweeney, 2013).

HRD classified as one of the pillars of excellence in SCM and research consistently demonstrate impacts of HRD interventions on effective SCM. Senge (2010) content SCM needs to be transformed if organisations are going to be focused on sustainability and environmental issues.

Question

1. links SCM to food sector in UK that reinforces points made in the presentation.

Also the importance of collaboration and inter-organisational working is an opportunity for HRD that is being missed as HRD functions focus on learning within a single organisation.

2. what competences will not be outdated? Are they the ones identified in the presentations but can a curriculum be designed around this?

 

Just back from a break and on to the next session:

“How doe Innovations in Teaching HRD Link Theory to Practice” by Melika Shirmohammadi & Mina Beigi from Texas A&M. Presented by Mina Beigi. Started with question of whether academic teaching models innovative delivery of HRD? Questions then focused on what innovations and how delivered.

But found only 21 academic papers published on teaching HRD using database searches and snowball the references of articles found. So this is an under-researched area. From the paper found that: innovations addressed different areas but predominantly used a self-regulated pedagogy. Methods included using film excerpts and music; work-based; action learning; reflective learning; case-based; computer-based. Half the papers focused on general HRD concepts and half more specific topics but some absences such as career development. Indicates a lack of reflection on their own practices by HRD academics. While the argument that HRD should be ill-defined in terms of definition but there should be more research and publications on the teaching of HRD. But do academics want to keep their processes in some way private or do not consider their innovations worthy of publication.

 

But, is this a feature that, at least for UK, is made difficult by the setting of examination criteria by external bodies. So certain contextual conditions may be squeezing out innovation.

 

Now onto “Virtual Action Learning and HR Offshore Outsourcing” by Cheryl Brook & Vijay Pereira based on a course on current HR debates. The initial questions were on the definitions of offshore outsourcing and the context of HRM in India before looking the use of virtual action learning in a long-term research project.

Define action learning as requiring a number of essential components including questioning at the heart of the process involving a real organisational problem (not a puzzle), involving small action learning sets (up to 6 people – although this may be contested especially on top and bottom of the range of people in a set).

How can virtual action learning (VAL) be facilitated? How might VAL assist the case organisation to address a  real organisational problem? How might VAL contribute to improving and maintaining virtual team relationships and communication skills? The case organisations works almost exclusively in virtual teams in global offshore outsourcing.

The state of HRM in India: Vijay has completed extensive research into HRM in India. India started with concept of HRD and this underpins understanding of HRM. The label of HRM was only introduced as a result of liberalisation of India in 1990s and adoption of terminology from USA. So training and development is at the core of any HRM department.

Human Resource Outsourcing (HRO) niche area of outsourcing such as needs analysis, recruitment etc. and is a large and well established industry in India. So the research context is a complex industry. The case organisation chosen due to existing access and is a micro multi-national company with approx 200 employees and more then 100 clients working in recruitment and talent management.

VAL has a limited research base and is defined by a range of enabling, interactive and collaborative communication technologies – interested in the word “enabling” in the context of ICT. So issues of interest included ensuring the technologies work but also in the building up of relationships and developing high performing virtual teams. Such research requires: organisational readiness and commitment; having a real problem; access, connectivity and time zones; higher levels of listening and developing an atmosphere of inquiry in cross-cultural sets.

The case organisations is interested in dealing with attrition rates; business growth; leadership development and developing high performance work practices. So these are really important issues for the company with a high penalty for failure.

The research team have attained a small research grant and are addressing a key research gap in terms of the industry and VAL.

Question: what was the process of developing the real organisational problems?

So these emerged from previous research and they are now in the process of formulating the action learning set. So starting with a single set of senior managers possibly including the MD co facilitate by the two researchers. Initially the researchers will travel to India but the head office of the organisation is in the UK. A series of virtual set meetings will be set up using tele conferencing.

That is it for the day. Tomorrow is a full day for the conference and more blogging notes to come. 

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

PhD research

*warning* this is a long post that basically provides the theoretical foundations for my ongoing research. Its taken from a paper presented to a PhD progress board at the University of Edinburgh so its basically an edited version of a vast/ huge paper written a few months back. All questions/ comments/ suggestions/ criticisms are welcome – especially is you manage to read the whole thing!

It starts with my espoused theoretical stance (which I anticipate will change as the research progresses (I couldn’t really describe it as a learning experience if it didn’t change).

My initial research approach took an epistemological position that drew on differing strands of social constructivism. Social constructivism (Vygotsky 1978) has been cited as a dominant theoretical perspective in educational research (Phillips, 1995; Fox 2001) and has been seen to be making significant in-roads to management research (Alvesson & Skoldberg 2009; Cunliffe 2008; Samra-Fredericks, 2008).

However, I was also interested in learning and knowledge as a practical act, that is, learning to “do” something. This brought in pragmatism as an epistemology of action (Cook & Brown 2005), of knowing “how” rather than knowing “that” (Spender 2005; Kivenen & Ristela 2003). A similar combination of social constructivism with pragmatism can be seen to inform Engestrom’s use of Vygotsky’s theories in the development of activity systems theory (Young 2008) that also places an emphasis on knowledge and action together. Furthermore, Cook and Brown (2005) refer to the notion of knowing linking to the theoretical area of practice (Bourdieu 1977; Antonacopolou 2006).

So, constructivism involves understanding, knowledge development and learning as active and either intentional or unconscious and habitual, which indicated that a practice-based approach to my research might prove beneficial. Given my focus on interactive digital environments that can be labelled as Web 2.0, a practice-based approach that is concerned with the complex interrelations between people, artefacts, language, collaboration and control seemed appropriate (Nicolini et al 2003; Guzman 2009; Geiger 2009).

Based on this argument, I was initially attracted to using the social constructivist based Activity Theory (Engestrom 1987; 2001) as it allows for multiple constructions of practice. As a socio-material perspective, Activity Theory suggests an individual only becomes meaningful in a social context where knowing in practice, activities and non-human materials are intertwined in a dynamic series of interactions (Tuomi 2000). The interactions of activity systems aim to highlight the tensions and contradictions that stimulate change, development and learning (Chappell et al 2009, p179). As Piaget argues, change comes not just through exposure to a ‘better’ theory, but rather through actively applying that ‘better’ theory in the world (Ackermann 2001). In other words, to practice (with) it.

Yet the experience of attempting an earlier discourse analysis of a single Twitter chat event suggested that Activity Theory was predicated on a degree of stability that did not appear to apply to the dynamic instabilities seen in the chat event. The event appeared to exaggerate many of the key problematic features of unstructured discussions identified by Belnap & Withers (2008, p8): sequences extending over many exchanges; overlapping exchanges and sequences; short sequences tending to be cut off prior to a conclusion and sequences re-emerging later in discussions. The norms of participant interactions appeared to be under almost constant negotiation and renegotiation. Also, non-human elements appeared to have an impact that suggested more than passive mediation. For example, Twitter apps such as Tweetdeck, which aggregates and organises Twitter ‘streams’, arguably shape how Twitter chats are structured and “consumed”. This combination of inherent emergence, instability and ambiguity within a socio-material framework (Fenwick & Edwards 2010) suggested that Actor Network Theory (ANT) would provide a more appropriate perspective to the research study. Indeed, Sorenson (2007) suggests that for material to be meaningful the material object must interact with “the social”, so the material object can be seen as being itself as unstable as the social context of the interactions that make it meaningful. The material, or materiality, can only be understood in terms of patterns of relations that change over time and space and not in any notion of the independent properties of that material.

Approaches to researching networked and practice-based approaches to learning and knowledge construction include a range of theories on social learning including communities of practice, cultural historical activity theory and so on. What these approaches have in common is a rejection of the primacy of the individual person in that the individual only becomes meaningful as a member of any number of networks where knowing in practice, activities and non-human materials are intertwined in a dynamic series of interactions (Tuomi 2000).

Actor Network Theory
Actor Network Theory (ANT) can be characterised as a “perspective” or lens of loosely combined ideas and concepts rather than a theory (Bergquist et al 2008). Latour (1999, p19) argues that in the case of ANT:
It was never a theory of what the social is made of … for us, ANT was simply another way of being faithful to the insights of ethnomethodology
At its most basic, ANT seeks to “follow the actors” (Latour 1999) by the detailed tracking of specific practices as a means to see how actors influence the world (Fenwick & Edwards 2010). ANT is focused on the study of networks through actors (Miettinen 1997) and:
Although the ‘T’ of the ANT acronym stands for ‘Theory’, it is this better understood as a methodological approach. In this way, ANT can be seen as an approach to the field that offers analytical tools that can be applied to narrative knowledge, be they organizational or otherwise (Alcadipani & Hassard 2010, p423).
While there is a broad range of ANT based research approaches, they are all fundamentally socio-materialist whereby an actor pursues an interest which can be translated into both non-human and social arrangements. These arrangements can be seen as network effects and can include combinations of people, organisations, groups, equipment or objects (Law 1992). Examples of these arrangements include a professional community, an organisational routine (Bergquist et al 2008) or communities of practice (Fox 2000).

There appear to be three key elements of ANT of particular interest: symmetry of human and non-human actors; the processes of translation and network assemblages or dynamics.

Symmetry
Symmetry seeks to avoid a subject/ object dualism that defines the human and non-human worlds as distinctly and qualitively different (Mietinen 1997). ANT specifically rejects the privileging of the human as an “all powerful agent imposing an arbitrary form on shapeless matter” (Latour cited in Miettinen 1997) while at the same time rejecting technological determinism.

But in practice symmetry appears to be difficult to achieve in the research process (Fenwick & Edwards 2010). As a result, ANT research practice has been criticised for adopting a form of human asymmetry described as Machiavellian as the researcher ends up following the loudest actor (Miettinen 1997).

To some extent this Machiavellianism is difficult to avoid other than through the reflexivity of the researcher (although such reflexivity may be aided by adopting the perspective of symmetry). It should also be noted that Miettinen (1997) goes on to discuss Machiavellianism only in terms of ANT’s concern with power and thus with “the Prince” and so ANT:
ignores such phenomena as learning, development of expertise, complementarity of resources and know-how in network construction (Miettinen 1997 unpaginated).
By focusing on the interaction between power, learning and resources in the emergence of networks, this study should have a wider span of attention than solely the machinations of the loudest actor.

Fox’s (2005) analysis of the role of newspapers illustrates the role of non-human actors in the generation and maintenance of the imagined community of the nation. Specifically discussing the layout of newspaper front pages as consisting of a number of unrelated news stories, Fox asserts that (2005, p103):
The regular reader thus keeps abreast of multiple narrative threads that weave the fabric of his or her imagined world. But this is not experienced as a simulated world but as the real world … By following the threads of news over time, the reader maintains a sense of a world known in common with distant, imagined others, fellow readers, fellow citizens too numerous to know personally, participants in a regional community, with spatial as well as temporal specificity.
Fox goes on to conclude:
In terms of ‘symmetrical analysis’, the non-human elements in the networks of ‘print capitalism’ made the ‘imagined community’ of the nation … a social and cultural reality.
Similarly, in an earlier study of a Twitter based chat event undertaken as part of a research methods course, it was found that using a browser or specific applications such as Tweetdeck (http://www.tweetdeck.com/) or Twhirl (http://www.twhirl.org) around 20 tweets are co-visible to the participant. Individual tweets are made visible in a single stream in time order rather than threaded by discussion theme. A result of this is that an individual is more likely to make contributions across multiple sequences rather than stay focused on a single discussion sequence (Simpson 2005).

(Screenshot of Tweetdeck)

But it was also clear that the technology of presentation required participants to focus on a few specific threads of discussion as they came up, at least partially ignoring other threads. So to ensure participants were able to re-engage with discussion sequences that they may have been ignoring, there was frequent retweeting of key tweets as well as of the agreed event questions.

In addition, other non-human actors also influence the network: the computers that people use, the technical infrastructure of the internet and World Wide Web, the use of rss feeds and content aggregators, hyperlinks into and out of the event content, the blog site that archives the tweet chat and so on.

Translation
ANT has been described as a sociology of translation (Latour 2005). The term translation appears to be used in two key ways. Firstly, it concerns the interpretation and reinterpretation of knowledge or meaning as seen in various studies of ‘workarounds’ that emerge during the implementation of information systems or in studies of workplace safety (Gherardi & Nicolini, 2000, cited in Fenwick & Edwards 2010). For example, different actors translate changes in organisational routines in different ways. Networks evolve as actors seek the support of others by translating the interests of others and enrolling them into the network (Mitev 2009). This in turn generates ordering effects and stabilises the network (Fenwick & Edwards 2010, p9).

The processes of translation in ANT are also processes of simplification whereby an actor comes to be taken to represent a complex underlying network. This simplification is necessary to enable practical action to be taken as these translated networks become taken for granted. So translation is part of the process of generating social order and stabilising a system through ordering routines (Tuomi 2000). The process whereby the social meaning of actors becomes settled is often referred to as “black boxing”.

In the earlier study of a Twitter chat event previously mentioned, the following tweet was interpreted as an attempt to legitimate among the participants the rejection of the Kirkpatrick model of evaluation as inadequate.

8:55:29 @H Can we have another question to keep us from wasting time burying Kirkpatrick? #lrnchat

However, it could also be framed as an attempt to negotiate a stabilisation of the #LrnChat network that the critique of Kirkpatrick can be taken for granted, eg, placed within an unexamined “black box”. Similarly, notions of workplace “performance” were treated as “givens” not to be examined, while other notions such as “business” or “learning” were treated as being far-from-stable notions and central to key discussions during the event. More broadly, the use of Twitter applications (as discussed earlier) and their wider networks of development, maintenance and dissemination and how these might impact on how the individual may experience such chat events was also, unsurprisingly, “black boxed”.

Network assemblages
Networks can be seen as an:
assemblage of materials brought together and linked through processes of translation that perform a particular function (Fenwick & Edwards 2010, p12)
ANT approaches are less interested in the size of a network or networks than in the dynamics of the influence in and on networks, being concerned with the ways in which influence can expand and contract those networks (Fox 2005). So ANT has a central concern with power as enacted through processes of enrolling and translation – that power can be understood as persuasion (McLean & Hasssard 2004).

Networks are products of symmetrical actors linked by intermediaries (Callon 1991). An intermediary “is anything passing between actors, which defines the relationship between them” (Callon 1991, p134). These can include software, documents or human bodies (Depauw 2008). Raisanen and Linde (2004) focused on text as intermediary finding that text played a key role in organisations in attempting to control the environment as well as “being durable and transmittable” (2004, p117). Mitev points to textual intermediaries as “reflecting earlier translations of interests” (2009, p15). Mediators, however, can transform entities and the network and there are an endless number of potential mediators in a network. These may include a CPD plan, a strategy document, (Fenwick & Edwards (2010) or a management method (Raisanen & Linde 2004).

The process by which networks evolve, grow or contract, is proposed by Callon (1986) as starting with a problematisation of specific entities. This “problem” becomes a focal point for the identity of the network via which actors seek to translate a “set of possibilities” to enrol other actors (Toennesen, et al n.d, p7).

For example, it may be argued that the #LrnChat Twitter event network had a tendency to problematise “training”. Members of the #LrnChat community sought to enrol actors by processes of negotiated translation of the possibilities of technology enhanced informal and self-directed learning. Translation and enrolment processes may further stabilise networks and sub-networks to the point that they act as a unified entity in their own right, ie, they become “punctualised” (Tuomi 2000, p9). Punctualisation being the process whereby a network becomes stablised to the extent that it is no longer understood as a network of actors but rather is understood and “black-boxed” as a given single entity (Fox 2005, 102). In other words, the network, such as a community of practice, becomes itself a single actor in a network or collection of networks.

There is some concern among ANT scholars that the term “network” itself leads researchers towards seeking actors of authority as nodal points in the network that in turn may generate a bias towards asymmetry. Thus the language of space and flow may be adopted (Mol & Law 1994) or “action nets” (Czarniawska 2004) placing an emphasis on contextual variables and interactions of human and non-human actors. The notion of “action nets” which privileges links between actions rather than actors themselves is of particular interest if a text object is treated as an action in its own right – a speech act – as Czarniawska suggests (2004, 783):
Although actants access existing action nets, thus recreating and stabilizing these connections, they must also continually form new connections. Such connections are forged during the process of translation, in which words, numbers, objects and people are translated into one another. Like calculation, translation is dispersed: everybody translates, although some translations, like some calculations, have more currency than others.
So (2004, 782):
Action nets need therefore to be observed as they are being established and re-established, which can be done progressively, deduced speculatively or, in Foucault’s terms, studied genealogically.

ANT, knowledge and learning
From the ANT perspective, knowledge and knowing is situated, embodied and distributed in and across networks. Knowledge cannot be perceived as stable nor:
limited to subjective constructions through meaning-centred interpretations of the world, as is the case with much interpretive research (Fenwick & Edwards 2010, p24).
Learning (new ideas or changes in behaviours) can be seen as the network effects of relational interactions involving technologies, objects, people and knowledge changes occurring anywhere in a network (Fenwick & Edwards 2010, p22). Networks act to mobilise knowledge and negotiate its alignment with actor interests. Networks of actors may also operate to bound and constrain learning activities to specific sites of relational interactions; that some interactions are allowed to occur in specific spaces, flows and action nets. Certain discourses of learning may take place in informal contexts such as a Twitter chat event that would be suppressed within other networks or action nets. This would, to an extent, reflect Ashton’s (2004) findings that the mobilisation of more expansive learning opportunities in larger organisations was limited to the higher “management levels” while more restrictive and task-orientated learning opportunities were more widely available. So, such restrictive learning opportunities were arguably constrained to align to the interests of a specific group of actors while opportunities for counter-discourse development were limited to actors who had already been mobilised within those distinct management networks and their related discursive genres and reportoires.

ANT as a research method
ANT has also been described as a “hybrid theoretical blend” that is contingent and unstable (Fenwick & Edwards 2010, p2) and is often used in conjunction with other theoretical perspectives and methods. For example, in a study of higher education Fox (2005) sets out to combine ANT with Communities of Practice and Benedict Anderson’s notion of imagined communities. Mitev (2009) found that ANT alone was insufficient in researching a major information system implementation and eventually combined it with Clegg’s theory of power. Raisanen and Linde (2004) combined ANT with Critical Discourse Analysis in the study of a project management methodology in a specific firm, while Czarniawska (1997) combines an ANT approach with institutional theory in studies of municipal government. However, in a study of human resource managers, Vickers and Fox (2007) successfully used an ANT approach to challenge the notion of a unified “management” within the case organisation, and to expose management practices as sites of both conformity and subversion of official policy. ANT’s focus on the micro-levels of negotiation in network formation and development – the uses of persuasion, coercion, seduction and resistance (Fenwick & Edwards 2010) – provide a mechanism for new insights in the critical dynamics of power relations.

A number of researchers have commented on how difficult it can be to operationalise ANT as a research method (Fenwick & Edwards 2010; Mitev 2009; Raisanen & Linde 2004). Mitev (2009) in particular focuses on the difficulties of deciding where to start, how to “cut the cake” of the initial problem area and then who to include as actors (and by implication, who to exclude). Such discussions are also framed by the practical issues of handling huge volumes of data and the concomitant requirement to scope the research and to exclude various actors, networks and black boxes, with this in mind.

Web 2.0
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

week notes

keeping this series intermittent …

However, the last couple of weeks have been focused on work that can’t really be discussed – either very confidential concerning individuals or working on longer term plans that I should be discrete about. Sorry about that …

Also, I’ve been doing a fair amount of work to take forward my PhD research. It has reached that point where I need to stop wandering around a wealth of possibilities to focus on a realisable research project. My current thinking is to focus on discourses in professional and workplace learning from the perspectives of the individual and the group/ community and in the context of open learning networks and closed workplaces networks. The key issue to be decided is whether to place these subjects in a framework of Cultural Historical Activity Theory (CHAT) and/ or Actor Network Theory (ANT).