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Research Design: Twitter and professional learning


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This is a presentation on the research design for my PhD

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Research Design: Twitter and professional learning

  1. 1. Socio-material methods & making a mess of a PhD? Pete Evans 30 August 2016
  2. 2.   Overview Introduction to the study Research site and matters of interest Paradigm in to design Methods repertiore
  3. 3.   Twitter discussion events • Hosted on Twitter • Synchronous • Organised through hashtags (#) aggregating contributions & interactions (Bruns & Stieglitz, 2013) • Approximately 750 regular leisure & professional discussion events: #imcchat (integrated marketing communication); #innochat (innovation); #lrnchat (corporate and academic learning); #PhDChat; #ECRChat (early career researchers); #talentnet (recruitment industry) (see Gnosis Media Group, n.d.).
  4. 4.   Matters of interest 1.How the common professional domain of HRD is constituted 2.How online community is enacted 3.How professional learning and knowledge sharing is performed
  5. 5.  
  6. 6.   If this is an awful mess … then would something less messy make a mess of describing it? Law (2004, p1)
  7. 7.   Doing socio-material Images: (i) froBy Credited to Francesco di Antonio del Chierico - Ptolemy's Geography (Harleian MS 7182, ff 58–59), Public Domain, Paul Randall, 2009; (ii) Rainbow brainwaves by Herman Cruz In practice research needs to be messy and heterogeneous. It needs to be mess and heterogeneous because that is the way it – research – actually is. And also, and more importantly, it needs to be messy because that is the way the largest part of the world is: messy, unknowable in a regular and routinized way. Unknowable, therefore, in ways that are definite or coherent. (Law , 2007, p596-7)
  8. 8.   Image from Paul Randall, 2009 Repertoire of methods Method assemblage …seeks to compel, relate, or explore, understanding the inherent open-endedness of this act in contextual space and time. The key would be to add transparency, acknowledging that on is engaging in sense-making rather than discovering or finding or attempting to classify in a reductionist sense (Markham 2013)
  9. 9. A repertoire of methods? Discourse Analysis Tracing the emergence of orders of discourse: styles, genres and discourses using NVivo Twitter Event data Twitter data collected using TweetArchivist and data from the event websphere captured in PDF
  10. 10.   But … As a research term, ‘data’ has been a problem for qualitative researchers for some decades now, not least because the term is — in most common usage — associated with some thing that one gathers, hence is a priori and collectable. Data are potentially informational, yes, but as operationalized in most of the social or natural sciences, function fundamentally as discrete objects that can be located in time and space. The problem with this conceptualization is that it remains categorically different from — and in a sense opposed to — the very idea of process. From a qualitative perspective, ‘data’ poorly capture the sensation of a conversation or a moment in context. (Markham 2013: 1)
  11. 11.   Matters of interest My central argument is to understand the Twitter chat events as heterotopic socio-material assemblages. So the RQs become: how are heterotopic assemblages manifested in: 1.How the common professional domain of HRD is constituted 2.How online community is enacted 3.How professional learning and knowledge sharing is performed
  12. 12. By DuMont Television/Rosen Studios, New York-photographer.Uploaded by We hope at en.wikipedia, Public Domain.
  13. 13.   References Beighton, C. (2013). Assessing the mess: challenges to assemblage theory and teacher education. International Journal of Qualitative Studies in Education, 26 (March 2015), 1293–1308. DeLanda, M. (2006). A New Philosophy of Society: Assemblage Theory and Social Complexity. London: Bloomsbury. Geiger, D. (2009), Revisiting the Concept of Practice: Toward an Argumentative Understanding of Practicing. Management Learning, 40, 129–144. Gherardi, S. (2000). Practice-based Theorizing on Learning and Knowing in Organizations. Organization, 7(2), 211–223. Latour, B. (2005). Reassembling the Social - An Introduction to Actor-Network-Theory. Oxford: Oxford University Press. Law, J. (2004). After Method: Mess in Social Science Research. Abingdon: Routledge. Markham, A. N. (2013). Undermining ‘data’: A critical examination of a core term in scientific inquiry. First Monday. 18 (10). Markham, A.N. and Lindgren, S. (2012). From Object to Flow: Network sensibility, symbolic interactionism and social media. Studies in Symbolic Interaction Miettinen, R. (1997). The Concept of Activity in the Analysis of Heterogeneous Networks in Innovation Processes. In CSST Workshop: Actor Network Theory and After. Nicolini, D., Gherardi, S., & Yanow, D. (2003). Knowing in practice. Armonk, NY: ME Sharpe. Pickering, A. (1992). Science as Practice and Culture. Chicago: University of Chicago Press. Roger, R. (ed). (2011). An introduction to critical discourse analysis in education. 2nd edition. London: Sage