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Of rhizomes and assemblages in
freelance language teachers‘
becoming(s) on…and with…and
through Twitter
Martina Emke, The Open University
Martina.Emke@open.ac.uk
Twitter: @MartinaEmke
Tweet and hashtag assemblages
Univiersity of Reading, 13 Feb 2018 2
What is this (all) about?
• Background and research questions
• A Deleuzo-Guattarian research approach
• Pathways into data enquiry (analysis)
• On data
• Situational Analysis and situational mapping
• Social Network Analysis
• Data vignettes
• Emerging lines of discussion
Univiersity of Reading, 13 Feb 2018 3
Research background & RQs
• Increase in number of Part-time language teachers (PTLTs) across
educational sectors (Beaton & Gilbert, 2013)
• Increase in professional development (PD) demands (Locke, 2014)
• Limited access to organised, formal professional development for
PTLTs (Stickler & Emke, 2015)
• RQ1: How does freelance language teachers’ professional
development on…and with…and through Twitter work?
• RQ2: What does freelance language teachers’ professional
development on…and with…and through Twitter produce?
Univiersity of Reading, 13 Feb 2018 4
A Deleuzo-Guattarian research approach
• A Thousand Plateaus (Deleuze & Guattari, 1987): a book as (a)
rhizome
• Plugging into the Deleuzo-Guattarian concepts
• non-binary, non-linear thinking, fluid concepts
• no fixed identities  subjectivities are produced through and within
assemblages
• becomings pertain to humans and non-humans
• production of new concept(s) (methodology as research assemblages, Twitter
machine)
• seeks to produce new thinking and temporal knowledge about social
phenomena
• experimentations: Situational Analysis working with Social Network Analysis
Univiersity of Reading, 13 Feb 2018 5
Key concepts: assemblage, rhizome,
becoming
• Rhizome: image of roots, multiplicity
• Assemblage: human and non-human comings-
together that are capable of producing
becomings
• Becoming(s): pertain to human and non-
humans; fluid, unpredictable, constantly
changing states
Univiersity of Reading, 13 Feb 2018 6
Source: Mackness, Bell, Funes (2016), CC-BY
On data
• data collection: 1 Sep 2016 – 15 Mar 2017
• online narrative frame questionnaire (n=14)
• 6 research participants (closer investigation)
• tweet capture:
• one month individual tweets per participant (n= 2,020)
• one month Twitter network tweets per participant
(n=13,834)
• Twitter networks deemed important for professional
development: #ELTchat, #TBLTchat, #LTHEchat
• 6 semi-structured online interviews
OU Residential weekend, 10 Feb 2018
Pathways into data enquiry (analysis)
Univiersity of Reading, 13 Feb 2018 8
cross-reading
cross-reading
Situational Analysis (Clarke, 2005)
• Grounded Theory (Glaser & Strauss, 1967) needs to be
pushed and pulled around the postmodern turn
• “[S]ituational analyses seek to analyze a particular situation
of interest through the specification, re-representation, and
subsequent examination of the most salient elements in
that situation and their relations.” (Clarke, 2005, p. 29).
• Maps as analytical tools
Univiersity of Reading, 13 Feb 2018 9
Situational mapping
Univiersity of Reading, 13 Feb 2018
• looks at salient elements and their
relational workings
• research participants’ professional
development is connected to the
ELT industry and working
conditions within complex and
dynamic relations of power and
competition
• emerging concept of Twitter
machine: algorithmic assemblages
and assemblages of practice that
constantly plug into tweet and
hashtag assemblages via
recommendations, metrics and paid
advertisement 10
Social Network Analysis (SNA)
• SNA for gaining insight into the structure of Twitter networks, e.g.
#ELTchat
• “A NETWORK is, in its simplest form, a collection of points joined
together in pairs by lines.” (Newman, 2010, p. 1)
• SNA measures and maps relationships and flows between network
actors (vertices, nodes); links (edges, ties) show relationships or
flows
• Most important types of tweet analyses
• time series  looks at peaks or low points in tweets over a period of time
• network analysis  looks at the structure of a network; measures the links
between nodes in a network and the position of nodes / group of nodes
• content analysis  looks at the most frequently used words / word pairs,
themes, hashtags, URLs
Univiersity of Reading, 13 Feb 2018 11
#ELTchat social network analysis
Univiersity of Reading, 13 Feb 2018 12
• Network structure: 273 edges, 124
vertices, 102 self-loops
• Hanna: retweeted a voting tweet
• Marc: was mentioned in #ff
• Heather: blog post on being a self-
employed language teacher (14 Jan
2016) was retweeted
• Maria: participated in one-hour chat
on how students’ English
conversational skills compared to
their L1 and wrote summary
• Martina: tweet on translation
vacancies, which included Rachel
was retweeted
#ELTchat word pairs analysis
Univiersity of Reading, 13 Feb 2018 13
• analysis of most frequently co-occurring
words in #ELTchat network (15-20 Oct
2016); numbers are treated as words;
• direct connection between Maria and Chat
Moderator (CM) who helped disseminate
and promote Maria’s chat summary 
Twitter machine
• two other chat summaries visible: “How to
help teachers become more comfortable
with teaching pronunciation? “How to
develop teachers digital literacies?” 
chats produce becomings (summaries) that
may connect with teaching practice
• Maria: “I'm happy to do the
summary.Hopefully,it will be a chance to
start my own blog :)”
Data vignette: #ELTchat situational map
Univiersity of Reading, 13 Feb 2018 14
• strong connection between
#ELTchat and #TBLTchat,
#ELTwhiteboard networks
(SNA and interviews)
• weak connection between
#ELTchat and #LTHEchat
• moderated one-hour
weekly chats + slow-burn
closely related to teaching
practice (topics are voted
on)
Data vignette: #ELTwhiteboard
Univiersity of Reading, 13 Feb 2018 15
• English language
teachers tweet
whiteboard classroom
pictures
• teaching assemblages
connect with
professional
development
assemblages on…and
with…and beyond
Twitter
• becomings are still to be
explored
Emerging lines of discussion
• re-conceptualisation of professional development as non-
linear, unpredictable moment-to-moment becomings
through and within human and non-human assemblages
• re-conceptualisation of the relationship between language
teaching and professional development as entangled,
dynamic and co-constituting
• methodology as assemblages: making Deleuzo-Guattarian
thinking and concepts work within one’s research
Univiersity of Reading, 13 Feb 2018 16
Thank you for your attention!
…. And if you would like to know more, please contact me on
@MartinaEmke
Martina.Emke@open.ac.uk
Univiersity of Reading, 13 Feb 2018 17

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2018 02-13 pathways-data enquiry_martina_emke

  • 1. Of rhizomes and assemblages in freelance language teachers‘ becoming(s) on…and with…and through Twitter Martina Emke, The Open University Martina.Emke@open.ac.uk Twitter: @MartinaEmke
  • 2. Tweet and hashtag assemblages Univiersity of Reading, 13 Feb 2018 2
  • 3. What is this (all) about? • Background and research questions • A Deleuzo-Guattarian research approach • Pathways into data enquiry (analysis) • On data • Situational Analysis and situational mapping • Social Network Analysis • Data vignettes • Emerging lines of discussion Univiersity of Reading, 13 Feb 2018 3
  • 4. Research background & RQs • Increase in number of Part-time language teachers (PTLTs) across educational sectors (Beaton & Gilbert, 2013) • Increase in professional development (PD) demands (Locke, 2014) • Limited access to organised, formal professional development for PTLTs (Stickler & Emke, 2015) • RQ1: How does freelance language teachers’ professional development on…and with…and through Twitter work? • RQ2: What does freelance language teachers’ professional development on…and with…and through Twitter produce? Univiersity of Reading, 13 Feb 2018 4
  • 5. A Deleuzo-Guattarian research approach • A Thousand Plateaus (Deleuze & Guattari, 1987): a book as (a) rhizome • Plugging into the Deleuzo-Guattarian concepts • non-binary, non-linear thinking, fluid concepts • no fixed identities  subjectivities are produced through and within assemblages • becomings pertain to humans and non-humans • production of new concept(s) (methodology as research assemblages, Twitter machine) • seeks to produce new thinking and temporal knowledge about social phenomena • experimentations: Situational Analysis working with Social Network Analysis Univiersity of Reading, 13 Feb 2018 5
  • 6. Key concepts: assemblage, rhizome, becoming • Rhizome: image of roots, multiplicity • Assemblage: human and non-human comings- together that are capable of producing becomings • Becoming(s): pertain to human and non- humans; fluid, unpredictable, constantly changing states Univiersity of Reading, 13 Feb 2018 6 Source: Mackness, Bell, Funes (2016), CC-BY
  • 7. On data • data collection: 1 Sep 2016 – 15 Mar 2017 • online narrative frame questionnaire (n=14) • 6 research participants (closer investigation) • tweet capture: • one month individual tweets per participant (n= 2,020) • one month Twitter network tweets per participant (n=13,834) • Twitter networks deemed important for professional development: #ELTchat, #TBLTchat, #LTHEchat • 6 semi-structured online interviews OU Residential weekend, 10 Feb 2018
  • 8. Pathways into data enquiry (analysis) Univiersity of Reading, 13 Feb 2018 8 cross-reading cross-reading
  • 9. Situational Analysis (Clarke, 2005) • Grounded Theory (Glaser & Strauss, 1967) needs to be pushed and pulled around the postmodern turn • “[S]ituational analyses seek to analyze a particular situation of interest through the specification, re-representation, and subsequent examination of the most salient elements in that situation and their relations.” (Clarke, 2005, p. 29). • Maps as analytical tools Univiersity of Reading, 13 Feb 2018 9
  • 10. Situational mapping Univiersity of Reading, 13 Feb 2018 • looks at salient elements and their relational workings • research participants’ professional development is connected to the ELT industry and working conditions within complex and dynamic relations of power and competition • emerging concept of Twitter machine: algorithmic assemblages and assemblages of practice that constantly plug into tweet and hashtag assemblages via recommendations, metrics and paid advertisement 10
  • 11. Social Network Analysis (SNA) • SNA for gaining insight into the structure of Twitter networks, e.g. #ELTchat • “A NETWORK is, in its simplest form, a collection of points joined together in pairs by lines.” (Newman, 2010, p. 1) • SNA measures and maps relationships and flows between network actors (vertices, nodes); links (edges, ties) show relationships or flows • Most important types of tweet analyses • time series  looks at peaks or low points in tweets over a period of time • network analysis  looks at the structure of a network; measures the links between nodes in a network and the position of nodes / group of nodes • content analysis  looks at the most frequently used words / word pairs, themes, hashtags, URLs Univiersity of Reading, 13 Feb 2018 11
  • 12. #ELTchat social network analysis Univiersity of Reading, 13 Feb 2018 12 • Network structure: 273 edges, 124 vertices, 102 self-loops • Hanna: retweeted a voting tweet • Marc: was mentioned in #ff • Heather: blog post on being a self- employed language teacher (14 Jan 2016) was retweeted • Maria: participated in one-hour chat on how students’ English conversational skills compared to their L1 and wrote summary • Martina: tweet on translation vacancies, which included Rachel was retweeted
  • 13. #ELTchat word pairs analysis Univiersity of Reading, 13 Feb 2018 13 • analysis of most frequently co-occurring words in #ELTchat network (15-20 Oct 2016); numbers are treated as words; • direct connection between Maria and Chat Moderator (CM) who helped disseminate and promote Maria’s chat summary  Twitter machine • two other chat summaries visible: “How to help teachers become more comfortable with teaching pronunciation? “How to develop teachers digital literacies?”  chats produce becomings (summaries) that may connect with teaching practice • Maria: “I'm happy to do the summary.Hopefully,it will be a chance to start my own blog :)”
  • 14. Data vignette: #ELTchat situational map Univiersity of Reading, 13 Feb 2018 14 • strong connection between #ELTchat and #TBLTchat, #ELTwhiteboard networks (SNA and interviews) • weak connection between #ELTchat and #LTHEchat • moderated one-hour weekly chats + slow-burn closely related to teaching practice (topics are voted on)
  • 15. Data vignette: #ELTwhiteboard Univiersity of Reading, 13 Feb 2018 15 • English language teachers tweet whiteboard classroom pictures • teaching assemblages connect with professional development assemblages on…and with…and beyond Twitter • becomings are still to be explored
  • 16. Emerging lines of discussion • re-conceptualisation of professional development as non- linear, unpredictable moment-to-moment becomings through and within human and non-human assemblages • re-conceptualisation of the relationship between language teaching and professional development as entangled, dynamic and co-constituting • methodology as assemblages: making Deleuzo-Guattarian thinking and concepts work within one’s research Univiersity of Reading, 13 Feb 2018 16
  • 17. Thank you for your attention! …. And if you would like to know more, please contact me on @MartinaEmke Martina.Emke@open.ac.uk Univiersity of Reading, 13 Feb 2018 17

Editor's Notes

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