Professional Writing from Multiple Sources
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Professional Writing from Multiple Sources

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Introduction ...

Introduction
Previous writing research has lead to various well-known writing process models. However, these models are primarily based on observations made in educational environments and relate to single texts. Professional writers in the workplace on the other hand often use multiple (digital) sources to succesfully write their business texts. Writing a business text, e.g. a report for a merger, is a very complex activity during which a wide variety of sources are consulted. This project, therefore, addresses the following research question: What characterizes the writing processes of professional writers 'designing' business texts from multiple (digital) sources?
Method
In this research project (2010-2013) we describe the activities of writing professionals when writing in their organisational setting (via keystroke logging and participative observation). In this stage, we have gathered a variety of writing process data, ranging from proposals to tweets.
The writing process data are collected with Inputlog. Inputlog is a keystroke logging program that registers an identification of every activated window environment (e.g. program, document, or web page) which is very important for the source analysis.

Results
During the presentation we describe the main concepts of this research project via case studies: the use of multiple sources, the implications of sources on the fragmentation and fluency of the writing process, and we will end with an example of a linguistic analysis of the data.
To show the complexity of professional writing we have, for instance, transferred the Inputlog data to a network analysis program (Pajek). A network analysis shows the relative time spent reading/writing the different sources and the direction/quantity of the transitions between the sources when producing a text. In one of our cases (a project proposal that took 10 hours to producs), we observed that this writer on average switches 5 times per minute between documents and programs and that he spends about 75% of the time consulting other (re)sources while writing.
The conclusions will be related to the excisting writing models. Especially the decision process a writer needs to make to either retrieve information from the long term memory or consult an external (re)source seems to be an important aspect that influences the organisation of the writing process.

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Professional Writing from Multiple Sources Professional Writing from Multiple Sources Document Transcript

  • The 13th International Conference of the EARLI Special Interest Group on Writing Wednesday July 11, Porto, Portugal Presentation Professional Writing from Multiple Sources www.ua.ac.be/marielle.leijtenLeijten, M., & Van Waes, L. (2012). Professional writing from multiple sources. Paper presented at the The 13th International Conference of the EARLI Special Interest Group on Writing, Porto.   Mariëlle Leijten Flanders Research Foundation University of Antwerp marielle.leijten@ua.ac.be Luuk Van Waes University of Antwerp luuk.vanwaes@ua.ac.be
  • Professional writing from multiple sources Mariëlle Leijten & Luuk Van Waes 
  • Program introduction method case reflections
  • Introduction1980’s I think I  will start writing a ... I will change the  formulation of  this sentence  into...  Flower & Hayes, 1981
  • Introduction1996 Hayes, 1996
  • ??
  • Long term memory: Task schemas Topic knowledge Audience knowledge Linguistic knowledge Genre knowledge External digital sources:  Task schemas  Topic knowledge  Audience knowledge  Linguistic knowledge  Genre knowledge
  • Method Observations (participative & Inputlog) Interviews Versions of documents (Logbooks)
  • Inputlog 5.0.* Beta Record  Logging of sources: focus events  Procedures for professional writing   create new   open existing  continue previous
  • Case Study Midsized Design Consulting Agency in Brussels Experience in engineering, cognitive ergonomics,  visual design & social sciences Professional: Aiden   45 years old  Background in Economics and Management  No background in technical or professional writing
  • Case study Proposal for Flemish Government In cooperation with contractor Duration 8:37:54 17 pages 55.000 lines of logging dataSession Date Duration % Sessionssession 1 4/04/2011 5:32:41 64,24%session 2 4/04/2011 0:19:20 3,73%session 3 5/04/2011 1:29:59 17,37%session 4 7/04/2011 0:34:45 6,71%session 5 7/04/2011 0:41:09 7,95%
  • Data preparation  Merging  Filtering  Coding sources
  • Graph of writing process Percentage of time spend in Proposal: 26% Sources: 74% Type of text production Copied: 75% New: 25%
  • template constructing searching re‐reading constructingsearching inserting/rewriting distraction searching connectingmeeting contextualizing re‐reading constructing deletingcommenting
  • Aiden says:"I usually start working from a template‐based document. ... In this case I have used Google Docs also quite a lot. I made a distinction between Google Docs and our company Wiki. The Wiki holds more general company information and Google Docs contains more specific information that relates to a project. Because we have worked with this contractor before, we have a document that is constantly updated and shared. It contains all the agreements with contractor A and the information that needs to be included in the project proposal." 
  • Aiden says:"Ideally, we take a comparable proprosal based on our proposal template, or a comparable project that contains a lot of standard wordings. ... Sometimes the data is a bit what outdated. ... Standard tekst kan be retrieved from the Wiki or from previous texts. However, nowadays the previous texts are more recent than the Wiki. Then I choose a recent project proposal. It is a pragmatic decision." 
  • Aiden says:"I use a different document in which I save separate cases. It is just a large Word‐document in which I include all the case studies that I have ever written (e.g. case on usability of Sony webpages).  Just, so I know they wont get lost. This could also be done in the Wiki, but to save images in a Wiki is terrible.”
  • Text construction
  • Network analyses (step 1) Number of switches Total: 2759
  • Network analyses (step 2) Number of switches Without transitions: 1118
  • Network analyses (step 3) Relative time spent in: Proposal: 29 % Other documents: 24 % Mail: 18 % Other: 13 % Projectmanagement: 9 % Internet: 4% Remainder: 3 %
  • Reflections on writing models Expertise in professional writing digital sources Schriver, 2012 search for re‐sources Hayes, 1996
  • Reflections: new features of Inputlog Filters  Time Filter  Event type Filter  Window Filter Focus analyses
  • New feature of Inputlog 5.1 Focus analyses 227 60% 148 39%
  • New feature of Inputlog 5.1 Implementation of focus analyses
  • Thank you Eric Van Horenbeeck (technical coordinator Inputlog) Tom Pauwaert (programmer Inputlog) Aiden S. 
  • More informationMariëlle Leijten, Flanders Research Foundation, Belgiummarielle.leijten@ua.ac.be ~ www.ua.ac.be/marielle.leijtenLuuk Van Waes, University of Antwerp, Belgiumluuk.vanwaes@ua.ac.be ~ www.ua.ac.be/luuk.vanwaes www.writingpro.eu www.inputlog.net Inputlog 5.1 available www.jowr.org