professional writing from multiple sources

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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.

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.leijten

Leijten, 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

Introduction

I think I will start 

writing a ... I will change the formulation of this sentence 

into... 

Flower & Hayes, 1981

1980’s

1996

Introduction

Hayes, 1996

?

?

External digital sources: Task schemas Topic knowledge Audience knowledge Linguistic knowledge Genre knowledge

Long term memory: 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 BrusselsExperience 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 data

Session 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 inProposal: 26%Sources: 74%

Type of text productionCopied: 75%New: 25%

template

searching

meeting

constructing

inserting/rewriting

searching

distraction

contextualizing

commenting

re‐reading

deleting

re‐reading

searching

constructing

constructing

connecting

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 won't 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 switchesTotal: 2759

Network analyses (step 2)

Number of switchesWithout 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 modelsExpertise in professional writing

Schriver, 2012Hayes, 1996

digital sources

search for re‐sources

Reflections: new features of Inputlog

Filters Time Filter

Event type Filter

Window Filter

Focus analyses

New feature of Inputlog 5.1

Focus analyses

227

148

60%

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 information

Mariëlle Leijten, Flanders Research Foundation, Belgium

marielle.leijten@ua.ac.be ~ www.ua.ac.be/marielle.leijten

Luuk Van Waes, University of Antwerp, Belgium

luuk.vanwaes@ua.ac.be ~ www.ua.ac.be/luuk.vanwaes

www.writingpro.eu

www.inputlog.net

www.jowr.org 

Inputlog 5.1 available

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