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ABSTRACT

The relationship between people, contexts and technological tools is constantly evolving in the face of digital technologies, allowing increasing learner autonomy and opportunities to take part in networked learning.

This paper contributes to the debate about the nature of learning spaces offered through technological platforms such as Twitter and whether they allow learners to re-negotiate boundaries between different settings and encourage the creation of personal learning environments  (PLEs).

A review of relevant literature was undertaken and the theories of connectivism and activity theory, which have been used to explain human-technological interactions, are explored.

Taking an ethnographic action research approach, the Twitter interactions of a post-graduate teacher trainee cohort from a University college in the East Midlands were observed for seven months.

This study concludes that Twitter has the potential to allow a re-negotiation of boundaries between the different settings in which people learn. The affordances of Twitter  give learners the opportunity to take part in a range of discourse and be exposed to an array of resources and expertise to solve real-life problems.

Twitter does provide a space which learners can use as part of a PLE and encourages them to take an active role in their own learning. Twitter has a number of characteristics that make it a powerful networking and learning tool, which have yet to be fully exploited by the majority of those in the formal education system. However, this potential may not be realised if the role of the tutor is not satisfactorily re-negotiated and learners’ perceptions of Twitter as time-wasting, addictive and lacking in privacy are not addressed.

INTRODUCTION

The relationship between people, context and technological tools is constantly evolving, prompting a review of notions such as space and time and their effect on learning (Al Mahmood 2008, Fenwick, Edwards and Sawchuk 2011) Space has been conceptualised as the experience of ‘the relative location of objects and places’ (Tuan 2001). In online spaces, time and distance are experienced differently and this affects people’s sense of relative location or place.  According to Tuan 2001, ‘place is a type of object, it has physicality’. Dourish, 2006 defined place as ‘coming after space and being layered on top of it.’  In the disembodied, virtual context the spatial metaphor provides a means to understand and structure action, such as learning.

My research aimed to investigate the nature of the learning environment provided by the social media platform, Twitter.  Could Twitter provide a space or framework, within which a group of trainee teachers on placement might re-negotiate the boundaries between university, placement and home and create a productive learning environment?

The research group consisted of the tutor and 26 trainee teachers enrolled on the flexible route of the postgraduate certificate in education (PGCE) at a University college in the Midlands. Flexible route trainees were only required to attend the formal education establishment for one day a week with the rest of their time spent in their placement school. This resulted in limited contact between peers and with the tutor.

For such trainee teachers, it can be challenging to apply and integrate knowledge learnt in the training institution, with the practical, situated learning taking place in the busy, fast-moving environment of the primary school classroom. Irwin and Hramiak’s 2010 study confirmed the sense of isolation trainees find at the very time when support, expert knowledge and the opportunity to reflect on new learning is need.  Equally challenging for trainees is to negotiate their changing role from learner, to teacher, from expert to apprentice as they move from lecture hall, to school classroom, to online environments such as Twitter.  The formal education system does not encourage or provide a framework for learners to bring together the formal skills and knowledge they acquire with that which is gained in informal contexts such as the Internet, home and activities such as sport, part-time work and youth organisations.

As long as learning space is regarded as the equivalent of place, trainee teachers are likely to find boundaries between home, placement school and educational institution persist. Wilson, Liber et al 2009’s concept of dominant design describes the tendency for a particular system or design to gain prevalence, such as the idea of learning spaces being physical spaces. This makes it difficult to deviate from that design and thinking then tends to become confined by it. Thinking about teaching and learning in formal contexts such as universities has traditionally been confined to a face-to-face delivery model, in a specific, dedicated physical context such as classroom or lecture theatre. The learning which is valued by the current assessment regime is assumed to take place in lectures and seminars, with the lecturer’s perspective given the maximum value in the learning process.  Recent moves towards online learning, in the form of institutional virtual learning environments/VLEs such as Blackboard and Moodle) still tend to follow the dominant design, with teachers/lecturers/tutors being presumed to hold the dominant perspective in the acquisition of knowledge.  However, with technology now capable of supporting more and more sophisticated and complex ways of acquiring knowledge, supporting communication and collaboration with learners, space can no longer to be considered the equivalent of ‘place’. Consequently, according to Massey 2005, the boundaries separating traditional academic places from the work place, home and the myriad of online ‘spaces’ on the Internet, will have to be ‘dismantled’, ‘renegotiated’ and ‘recreated’.

The role of the formal education system in this new environment will need to change to produce competent, independent learners who can create their own personal learning environments to bridge the gap between their informal and formal learning. Learners will need to find ways to navigate ‘in, through and in-between’ these spaces, to inhabit liminal spaces  in which they can be transformed, to quote Cuthell, Cych et al. (2011),

‘by acquiring new knowledge, new status and a new identity in the community’.

As Tu et al (2012) point out, they will need to learn how

‘to project positive social digital identities to become network community learners’.

Could Twitter possess the attributes or ‘affordances’ as Norman 2004 called them, which would enable it to act as a bridge, ‘for mediating knowledge exchange between different cultural activity systems…’ (Mazzoni and Gaffuri 2009)? Does Twitter, as Star and Griesemer (1989)  posit, act as a ‘boundary object’, a common zone bridging the gap of knowledge between school placement, university and home and allowing boundaries to be overcome between these different systems?  Are Twitter’s affordances acting as scaffolding between the knowledge and competencies of the university environment and a new work environment such as a school placement?

THEORETICAL FRAMEWORK

My research is informed by a hybrid theoretical framework combining connectivism, a theory largely developed by George Siemens in 2005 and Stephen Downes in 2006, and activity theory as expounded by Engstrom in 1987.  The key ideas from these two theories are included in earlier entries of this blog.

However what is important about both these theories is the emphasis they place on the value and importance of diverse perspectives in the learning process. Multiple perspectives allow more actively engaged and independent learners to work through the contradictions between different identities. Inherent contradictions between perspectives lead to innovation and transformation in an activity system.

Learning happens in networks, where connection can be made between different concepts, opinions and ideas accessed from multiple sources.  Online learning communities are seen as activity systems which enable us to look at individuals in context and thereby analyse the social structures of these environments. Hash tag communities are an example of the sort of social structures which emerged in the Twitter activity system and will be discussed later in this paper. Both connectivism and activity theory also allow for changing roles and relationships in such systems. In activity theory, diversity of perspectives in networked systems is seen as a source of contradiction, which in turn, leads to transformation or learning.

Downes (2006) asserts that the term we use to describe the context of learning needs to describe the interrelations of people, groups and tools in technological environments.  Terms such as ‘social media ecosystem’ explicitly include reference to people, groups and tools (Potts and Jones, 2011). Descriptions such as ‘a common geography’ and a ‘metaphorical sense of shared space’ attempt to convey the non-physical nature of online spaces or environments (Baym and Baym 2010:75-76).

Building on the concepts referred to in the term ‘social media ecosystem’, Siemen’s (2003:3) term ‘learning ecology’  includes attributes which provide the learner with uninterrupted access to information, affords experimentation and failure and a situation in which knowledge is shared and transparent (Siemens 2004, Seely Brown 2000).  However, a learning ecology is more than a ‘set of affordances’.  It is a flexible structure which provides the conditions for learning to take place, a combination of activity systems, co-ordinated by individuals as part of their personal learning environments .  This more constructivist view of the learning process places the control of the learning situation firmly in the hands of the learner.

So what kind of learning ecology might Twitter provide for this new kind of connective learning to occur in?  Notions such as ‘in-betweeness’ have been used to describe a space which is neither wholly public nor private or what  Philo et al (2005) calls a ‘third space’, where practices cannot be neatly categorised by traditional boundaries. Indeed, Siemens’ (2005) metaphor of learning ecologies might be seen as an attempt to encompass not only this concept of liminality, but the blurring of boundaries and the possibilities of integrating understanding and knowledge from a variety of sources.

With such a variety of definitions for learning spaces , the term ‘learning ecology’ which places emphasis on the ability to ‘foster connections rather than compartmentalisation’  seems appropriate (Bickford and Wright 2006, Ch. 4) and conceptualises the ways learning takes place across a set of contexts found in physical and virtual spaces (Greenhow et al, 2009).

The concept of co-ordinating connections between people, tools and materials to create effective learning environments has been a strong theme in recent literature on learning environments (Wilson et al 2009, Tu et al 2012, Educause 2009).  How exactly do individual learners integrate technologies such as Twitter into existing personal, social and learning networks and practices?  Perhaps what might best describe this integration is the term Personal Learning Environment (PLE). Definitions range from ‘a collection of tools brought together under the conceptual notion of openness, interoperability and learner control’ (Siemens, 2007 ) to an environment where people, tools, communities and resources interact in a loose kind of way (Wilson et al 2009).  The PLE is seen not as a technological platform but a practice or process of the learner.  The advantages of these practices are that students learnt ‘to project positive social digital identities to become network community learners’ (Tu et al, 2012:17).

This perspective of learning as ‘tool-mediated, situated, object-directed and collective activity’ (Buchem, Attwell et al 2011:5)  is the basic argument of activity theory which can be used as a framework to explore innovative learning spaces (Trish and Du Toit, 2010) such as Twitter

METHODOLOGY

The guiding methodology in this study was ethnographic action research, with the data generation methods being largely qualitative, and collected through participant observation, survey and interview. Ethnographic action research encourages the collection of a ‘plurality of perspectives’ (Tacchi et al 2003) to inform the research process. In order to gain this plurality, the accounts of participants were privileged in the writing up of the research.  Different ways of observing and communicating with participants provided a kind of triangulation through which observations were cross-checked Hine (2000). In addition the reflexivity of the researcher is discussed in order to ensure the trustworthiness of the research.

As referred to earlier, the research group consisted of the tutor and 26 trainee teachers enrolled on the flexible route of the postgraduate certificate in education (PGCE) at a University college in the Midlands.

Data in the form of archived tweets was collected from the whole group.  Only 17 of the 26 participants responded to the online survey. Data for the social network analysis was based on the responses of these 17 participants, therefore providing only a partial picture of the network structure of the #bgpgt community.  A supplementary online survey was sent to a selection of 7 individuals from the group of 17 who responded to the main survey, requesting further details of their networking strategy and online identity choices.

Copies of each week’s #bgpgt Twitter feed were stored as PDFs using TweetDoc, logged on Twapperkeeper and as a visual summary on Archivist. This provided a permanent record of tweets, participants and links from which screen shots of noteworthy content were taken.

This study followed the ethical guidelines set out by the University of Edinburgh (School of Education) and the Association of Internet Researchers. There are some ethical concerns about the analysis of online discourse, issues of privacy, confidentiality, informed consent and appropriation of others’ personal stories (Sharf 1999).  Although Twitter is a public site and users’ posts are accessible by anyone on the Internet, it is not clear that participants know that their data may be archived, stored and reported on in academic reports.  As such, some may view this as a violation of privacy (Vieweg 2009).

However, all participants in this study signed a consent form which outlined how the information from their public tweets would be used (Appendix 1). They were advised about the purpose of the research in a face-to-face session with the researcher. At this session they were asked to sign up for a Twitter account, specifically for the purposes of this research. Tweets were not ‘protected’  since the observation of networking was one of the desired outcomes of the study. It was made clear that tweets would be archived and that some tweets would be quoted in the research report.  They were advised that they may be asked to complete a survey and be interviewed at a later date.  When survey data was collected participants were informed that their comments may be quoted but that these would be anonymous, where possible.

My principal method, participant observation, was of the Twitter feed on the hashtag #bgpgt, which took place over seven months from May 2011 – November 2011.

The initial core activity of this hashtag was a Twitter chat running over the course of a week, in which the discussion topic was pre-determined by the tutor. The Twitter chat was not formally moderated although it was informally moderated by me in the first few weeks.

FINDINGS

The findings in this section relate to the data obtained from archived Tweets, online surveys and a semi-structured interview with the tutor and are discussed from the perspective of activity theory using discourse and social network analysis.  The description and analysis is organised under sub-headings based on the main headings of the activity theory model

1. Tools

2. Community

3. Rules

4. Division of labour

Figure 1 shows my attempt to model this PLE, which I envisaged as a hybrid version of Engstrom’s activity theory model, shown here as a network of activity systems, each overlapping the Twitter activity system, which provides the ‘bridge’ or common learning zone.

Figure 1:Adapted Activity Theory Framework (based on Engstrom1987).

Figure 1:Adapted Activity Theory Framework (based on Engstrom1987).

The Twitter activity system

Subjects

The subjects were trainee teachers enrolled on the flexible  route of the postgraduate certificate in education (PGCE) course at a University college in the Midlands. The determined activity was to be involved in reflection on professional issues in the first term and to maintain a supportive community and network of contacts in the second term.

Object

The overall goal for the use of Twitter was to address the physical isolation of trainee teachers whilst on placement by building a supportive community online. The tutor’s more specific object for the first term was reflection on a range of key professional issues, and acquiring a professional ‘voice’ with some guidelines and structure from her. Three specific discussions revolved around a course theme: openness, accountability and professional identity. After the first term, the implicit and informal goals, to build up a network of contacts and expertise and make connections between learning done in different contexts, became more apparent in the practices and discourse of the participants.

Tools

The tool used in both terms was Twitter, with key affordances being the @reply, hash tags, shortened links, re-tweets and the ability to follow others. These affordances affected the nature of the interactions but the nature of the interactions also influenced the tools and the way they were used

Community

The community consisted of trainee teachers, their tutor and the researcher and was always open to newcomers. An undefinable proportion of the cohort were ‘lurkers’, not actively engaging in the Twitter community (in the sense of tweeting themselves).  11/26 people (42%) made less than 20 tweets in the seven month period of the research, with one participant making no tweets at all, in contrast to other members who made 200 – 300 tweets in the same period.

Outcome

  • Participants recognised that expertise was not the sole preserve of the tutor in the educational establishment. Students became more aware of other sources of ‘expertise’, even amongst their own cohort.
  • A supportive community was formed which offered support and information but, more importantly, more active individuals modelled how to develop a professional network and gave others in the community access to that network
  • Trainee teachers:

used their community as a readily accessible, constantly available
source  of information, which could be called upon at any time, from any
location.

began to construct their own personal learning environment made up
from the expertise of peers, tutor, researcher, professional bodies,
websites, library

gained the opportunity to rehearse the teacher role through use of
professional discourse and making links with fellow professionals

Sub-activity systems

The activity system has been broken down into three sub-activity systems, in order to present specific findings:

  • Subject-community-object
  • Subject-rules-object
  • Subject-division of labour-tool-object

Subject-tool-community-object

Boundary markers, filtering and professional discourse

One of the characteristics of a setting or medium which seems to recur in relation to community building is the sense of shared and psychologically ‘safe’ space. (Hill 2002). This sense of security can be helped or hindered by the ability to filter out all messages except those of the other learners in your community. Twitter, unlike other systems, does not easily allow the filtering ‘out’ of other participants, once you are ‘following’ them.

The hash tag allowed participants to filter #bgpgt  tweets to one feed where all tweets pertaining to it could be seen at once. This gave participants the illusion that they are part of a ‘bounded’ community.  The hash tag appeared to act as a boundary marker for the desired ‘safe’ space. There was a clear sense of group identification with the hash tag, but participants did not always seem to be aware of the public nature of Twitter interactions and were taken aback by apparent interlopers using the hash tag and the acquisition of unsolicited, undesired followers.  This seemed to affect their sense of a ‘shared and psychologically safe space’ (Hill 2002) with one participant tweeting (Figure 2)

Participant comment about interloper use of hash tag

Figure2: Participant comment about interloper use of hash tag

and another participant giving this lack of ‘security’ and boundary as her reason for deleting her Twitter account, six months into the research.

“I have deleted my account several weeks ago due to feeling unsure of having people follow me that I do not personally know, due to receiving strange random messages of spam.”

Interestingly anonymity, which may have added a sense of security or liberation (Kozinets 2010), was not common with only 28% of participants using pseudonyms adding to the feeling of insecurity. In most cases choice of profile details clearly identified them by their occupation as PGCE students e.g. “PGCE Lower Primary Flexi Student. Looking for others to share info with :)”. Despite the obviously permeable nature of the Twitter space, one participant still felt the necessity to ask for permission to continue contributing to it.

Figure 3:  Participant comment regarding use of hash tag

Figure 3: Participant comment regarding use of hash tag

He seemed to be questioning the ability to remain part of a ‘network’ if no longer a course member within the physical boundaries of the educational institution.  Meyrowitz (1986) raises the problem of the lack of boundary lines in new media contexts where unlike physical boundaries, there is no longer a way to define situations so that participants are excluded or included.

Ironically, the desire to be part of a ‘bounded community’ might have worked against the object of their activity to some extent since the ability of others outside their course to comment could have added valuable perspectives to their dialogue.  However, the security of the learning ecology allowed them to gain emotional support and gave them the courage to self-disclose in order to gain the support of their peers which Baym and Baym, (2010) mention as a primary motivation driving many online communities.

Subject-rules-object

In addition to the use of the hash tag, the use of professional discourse was both a boundary marker and an accepted ‘rule’ for the #bgpgt community, a sign of membership for those who use and understand it and a barrier to those who do not. The object of professional discourse was to rehearse the ‘teacher role’ and become part of the professional education community (Irwin and Hramiak 2007). A clear finding was the use of a range of professional talk in tweets – educational, academic and institutional lexis.

Table 1

Table 1: Summary of professional lexis used in sample conversations

In both Conversation 1, from early in the PGCE course, and Conversation 2, four weeks later, there is a balance between the academic lexis  used internally in the training institution and widely used professional educational lexis. Their familiarity with key educational acronyms and terms such as ‘mixed EYFS/KS  classes’ suggests that trainees saw themselves as belonging both to a community of PGCE students and a burgeoning community of ‘new’ teachers – a clear example of boundary crossing.

Research has shown the value of participation in professional talk and practice (Lave and Wenger 1998) as part of becoming a legitimate, full participant in the community of practice. Dunlap and Lowenthal (2009) reinforced the relevance of Twitter participation, in particular, in enhancing their students’ enculturation into such a community of practice. In this study several participants with large social networks commented on Twitter’s capabilities:

“It allows me to witness professional talk.” “…certainly gives me an idea of what being a qualified teacher entails”

In addition to taking part in professional talk, another significant norm or rule, observed in both conversations, was the sharing or providing of information. This accounted for a significant proportion of weekly tweets, 23% and 21% respectively.  Other purposes included seeking and providing reassurance, with status updates also being a significant factor.

Table 2: Quantitative summary illustrating purposes of communication in #bgpgt

Table 2: Quantitative summary illustrating purposes of communication in #bgpgt

Subject-division of labour-tool-object

“Those who are active within a community, in that they contribute to postings, initiate debate and synthesise the submissions of others, are increasing the sum of the cognition distributed within the artefact/environment.”  (Cuthell 2008:16)

Division of labour, in activity theory, relates to a separation of duties allowing specialisation of tasks to achieve a better outcome.  Although there were no designated roles in the community, roles were assumed in order to maintain the community and achieve the object – to exchange information, offer support, synthesise submissions etc.

Using UCINET to visualise the network connections between participants, the data collected from the online survey was used to look at key roles in the community, under the following headings (which will be explained within the analysis itself).

  • Density
  • Centrality degree
  • Centrality betweenness
  • Blocks and cutpoints
  • K-core

No data relating to the tutor or the researcher was included in the social network analysis because the object of the activity system was to develop a mutually supportive but on-going community for the trainee teachers, outwith the educational establishment.  However, this may have been a weakness in the research and is addressed in the sections on the role of tutor and researcher.

Whole network – background

A key finding emerging from participant observation was the existence of a significant core group (Shirky 2003) of ‘tweeters’  in the #bgpgt community who were responsible for most of the Twitter activity and had acquired  a sizeable professional network.

The k-core  diagram below confirmed the existence of this core group. By varying the number of ties (k) necessary to claim membership of a group, K-core enables a discussion of the cohesiveness of the group. Hanneman and Riddle (2005) suggest that if an actor has ties to enough people in a group they may feel tied to that group, even if they don’t know many of its members.

K-Core

Figure 4: K-core diagram

For the initial analysis k=3. In the diagram below, the core group (pink squares) had three or more ties to others, which suggests a high degree of cohesiveness between them. Another sub-group (green) have at least one tie to an actor in the central group and one or more ties to an actor outside the central group. There a number of actors (red) who only have one tie to one member of the central group. They are ZC, HC, LD, SC and LW.   If our value is still 3, these five actors may not feel as tied to the group as the actors in the core group, whereas NW, SA, JS and BH may feel more tied, with at least two ties.

Whole network analysis can identify both members of the group who are not well connected and those who seem to be central figures or act as bridges between different groups. A measure of this ability to act as a bridge is betweenness centrality.

Betweenness centrality is the number of times an actor connects pairs of other actors who otherwise would not be able to reach each other. It is worth pointing out that number of connections may not be any more valuable than one ‘good’ connection, as is shown in the centrality degree diagram later on.   However, an actor who is high in ‘betweenness’ is able to act as a gatekeeper controlling the flow of resources.  In this diagram the relative size of the nodes is used to show that DD (red), KB (blue) and MW (green) have the greatest degree of betweenness.

Betweenness centrality

Figure 5: Betweenness centrality diagram of #bgpgt social network

In the observation of the #bgpgt community the following was noted:

  • A large percentage of MW’s tweets were reassurance or esteem support for others.
  • DD provided a large proportion of the practical help such as locating resources and giving information.
  • KB gave status reports on her progress with tasks or on placement. Her role seemed to be to share experiences and express solidarity with others.

KB’s greater experience as a ‘tweeter’ and social networker affected her tweeting style, influenced by status style updates in Facebook.

Freeman measures centrality of actors based on their degree (or number of edges or ties). An actor with high degree centrality maintains numerous contacts with other network actors. This means that they can gain access to or have influence over others unlike a ‘peripheral actor’ (e.g. SC and LW) who maintains few contacts.  In the following table 4 it can be seen that actors DD (red), LH (pink), and KB (blue) have the greatest outdegrees (or numbers of edges/links with these actors as the starting point) and might be regarded as the most influential.  DD and KB were the most prolific tweeters in the community, in excess of 200 tweets in seven months.  They also had high numbers of followers and followed others.

Freeman's Degree Centrality Measures

Table 4 Centrality degree

From the information given in Table 5, a Pearson correlation r=0.980, n=17, p=0.001 between the total number of tweets made by an individual and the number of followers they had suggests there is a strong positive correlation between these two variables.  There is also a 0.960 correlation between the total number of tweets made by participants and the number of people being followed by that participant, suggesting again that there is a strong positive correlation between these two variables.

Table 3: Pearson correlation between total no of tweets and no. of followers/followed

Table 5: Pearson correlation between total no of tweets and no. of followers/followed

However, LH’s central position, shown in Figure 6 suggests that the correlation between the number of tweets and followers is not an accurate measure of influence. Although LH tweeted only 15 times and had a modest number of followers and contacts, she was reported as a contact by a large number of people in the #bgpgt community

Degree centrality

Figure 6: Degree centrality of #bgpgt social network

Influence and exchange of information

Social network analysis is interested in the exchanges which maintain learning and sustain social relationships.  Centrality and betweenness help predict who is in an influential position to control the flow of these resources.  The types of resources exchanged are varied, both tangible and intangible.   In the Twitter learning ecology re-tweeting is one of the tools which influential individuals can use to building a professional network and acquire social capital and ‘currency’ (Bell 2010).

  • 80% of participants claimed to understand the function of re-tweets
  • 60% claimed to re-tweet several times a month.
  • However, only 2.3% of tweets (according to Archivist statistics) in 14 week period were actually re-tweets.

The purpose of re-tweets is to extend the ‘reach’ of an individual message.  However, in the #bgpgt community many participants were followed solely by fellow trainees (giving them a median of 36 followers) making re-tweeting unnecessary as a way of extending reach or gaining influence. Although re-tweeting was largely redundant, each node was tied strongly to a number of fellow trainees but weakly to a range of professional organisations and individuals outside the immediate network. Weak ties can also be important in a network because they provide bridges to other networks and information from outside the network.

A significant finding was the extent to which a number of participants were able to create a network beyond their immediate circle.  Several participants felt this had the potential to become a powerful learning tool for them.  KB, a key actor in the #bgpgt network, had an extensive range of connections to a range of professional organisations and individuals.

KB mini

Figure 7: KB (Kelly Beeley) ego network

The network of connections shown in Figure 7 are those actors potentially having access to KB’s large network of external connections should she use  re-tweeting more extensively.

The sociogram of KB’s external network shows reciprocal links in red, giving those individuals and organisations access to her #bgpgt contacts and vice versa.

KB extended network

Figure 8: KB extended network with reciprocal ties

Role of the tutor

A depth interview, in the form of a two-way exchange of information between researcher and tutor, took place in order to elicit a range of perspectives (Tacchi et al 2003). This revealed much about the tutor’s part in the division of labour. Much research in online learning (Garrison and Anderson 2011, Moore 1993) assumes that the conditions or characteristics of a successful learning environment are created by the tutor. A similar assumption was made by the tutor in this study. She felt that Twitter might play two roles in her course – as a place for students to reflect, analyse and compare their experiences to others and as a place to form a community.

Although the initial ‘problem’, the isolation of PGCE students on placement, was recognised by both parties, due to the exploratory nature of the research, no formal protocols were established at the commencement of the study resulting in few explicit mechanisms or scaffolding for community-building.   The tutor remarked on this

“….with the benefit of hindsight I would want to put in more etiquette and shared protocols”

Mannheimer Zydneya et al (2012) found that establishing protocols in conversation significantly influenced more group cognition in asynchronous discussions.  The one specific protocol in place, the preservation of the professional  nature of the hash tag, had mixed effects.

One participant resented this injunction, seeing it as a ‘policing’ or closing down of the debate.   The tutor also saw her role as

“… a policing role …they also need directing back …I felt that they needed to feel somebody was watching.”

However, rather ambiguously she also expressed a desire not to be too ‘present’,

“I wanted them to talk to each other…wanted to be able to stand back and let it happen”

The tutor’s wish to create an independent community of learners led to greater autonomy of the learners but the direction of that learning and dialogue was not always what was desired by her. The interview revealed the obvious tension between allowing the students to create an autonomous community

“…I didn’t want…them all talking to me, I wanted them to talk to each other…”

and retaining a level of control over the direction of the interactions.

“.. they needed to feel somebody was watching. [pause] … if you didn’t have mentor input along the way I think it would degenerate.”

This autonomy has been recognised as problematic (Norris, 2001) since the critical engagement of the tutor is vital if higher order learning is to occur.

Observation revealed that the vast majority of the interaction on #bgpgt was not tutor-led. In the Twitter context, participants saw themselves on an equal footing with the tutor and were as likely to accept information from fellow students as from the tutor.  Chatti, Jarke et al. (2010) note the lack of distinction between ‘newcomers, novices or peripheral participants and old timers and masters’ in learning ecologies where knowledge is jointly created.   This lack of distinction was both a concern and a benefit for the tutor

“I wonder why they want to be knowledge providers …what makes them feel that they can be that person?”

“…the fact that they’re able to ask each other, allows me to see when they’re getting it wrong as well and I can intervene more quickly.”

Despite the apparent clash of cultures between the institutional pedagogy of transmission learning and the informal, multi-perspective culture of Twitter, the tutor did recognise the role which Twitter might play in creating a wider network of professional contacts for her students. Previous attempts had been made to create links between her students and those of another institution albeit through alternative media

“I’ve used PBWiki to link them up with Roehampton…we’ve been working with David Harmer, the poet…”

The challenge for both learners and tutor is to recognise that they are making meaning from the forming of connections, creating knowledge by the conscious use of information exchanges between their different communities, whether online or face-to-face. By consciously creating their own personal learning environment, knowledge would become something not restricted to their own intrapersonal processes but distributive, ‘consisting of a network of connections formed from experience and interactions with a knowing community’ (Downes 2006).  In order to become truly effective network learners, learners also need to recognise the importance of projecting ‘positive social digital identities. (Tu et al, 2012:17) as they were being encouraged to do by the tutor.

CONCLUSIONS

Emergent learning spaces such as Twitter, as described in theories such as connectivism, have come to incorporate both virtual and physical contexts, with learners making connections and contacts within learning networks and where overlapping activity systems all contribute to a ‘liminal’ space.

The Twitter learning ‘zone’ or activity system provides a number of affordances such as the hash tag and retweet which give learners the opportunity to take part in a range of discourse and be exposed to an array of resources and expertise to solve real-life problems. Twitter allows learners to create a personal learning environment through the creation of a network of contacts. These contacts give learners access to a range of perspectives and become part of a process of making connections between academic knowledge and day-to-day experience.   The lack of existing or defining characteristics or ‘rules’  in Twitter communication provided participants with the ability to define their own ‘context’ through dialogue and the adoption of features such as the hash tag and @reply to enable them to achieve their own purposes.  This ability to define context through dialogue was demonstrated by the redundant nature of much of the communication I observed and the rapid switches in discourse and register.  This same lack of ‘rules’ mean that roles are also up for re-negotiation as was demonstrated in my study. Learners are not only learners, they are also experts, information givers and providers of support.  The role of the traditional tutor has not been satisfactorily re-negotiated in this new learning ‘space’. This is certainly an area for future research and work.

Twitter seems to act as a ‘bridge’ or common learning zone. Boundaries between different learning contexts are re-negotiated by learners when they participate in changing roles and are given opportunities to take part in different discourse communities and activity systems which overlap and co-exist.

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