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DTEND;VALUE=DATE-TIME:20210925T111000Z
DTSTART;VALUE=DATE-TIME:20210925T103000Z
DTSTAMP;VALUE=DATE-TIME:20210918T170604Z
UID:f2dc5933-d373-438a-9b45-f023d0dde050@talks.stuts.de
DESCRIPTION:Learning how to write effectively has always been a challengi
 ng task. Not only because "good writing" involves a tremendous amount of
  practice but also because of the contextual factors influencing the pro
 cess. With the most influential cognitive writing model\, Flowers and Ha
 yes (Flower & Hayes\, 1981) successfully captured composing as an activi
 ty affected by the environment of its occurrence. Workplace writing has 
 changed dramatically\, however\, as new contextual circumstances emerged
 . These have virtually changed how experts and non-experts write in real
  life. They include\, most notably\, the shift to online writing and the
  resulting use of multiple digital and non-digital media. For instance\,
  Leijten et al. (Leijten et al.\, 2013)\, by analyzing proposal writing\
 , made exciting additions to Hayes's (Hayes & Berninger\, 2014) model. T
 hey unraveled how an expert writer searches for information and motivate
 s himself in a "downtime" period.\n\nOur study examines how the fragment
 ation and distribution of writing activity in a workplace influence the 
 technical writer\, the writing process\, and the resulting texts. As one
  may expect\, such an undertaking posits a great methodological challeng
 e. It involves visualizing the processes as they occur in a specific\, h
 ighly complex environment. The techniques of screen capturing\, think-al
 oud protocols\, video recording\, or diary interviews (Slattery\, 2007) 
 have long been the 'go to' methods in writing research. However\, they t
 end to be highly time-consuming for the researcher and taxing for the pa
 rticipants. To gain access to measurable and quantifiable data\, researc
 hers started to apply key-logging and eye-tracking tools. Although extre
 mely useful for conducting writing research\, key-logging and eye-tracki
 ng produce a high amount of highly granular data\, difficult to analyze 
 and operationalize by the researcher.\n\nIn this presentation\, we would
  like to present our preliminary results of a screen capturing\, think-a
 loud protocol from a writing experiment conducted on a technical writer 
 in her working space. We will share the primary difficulties we faced wh
 en visualizing an analyzing writing activity.
URL:https://talks.stuts.de/en/18staps/public/events/608
SUMMARY:The Challenges of Visualizing and Analyzing Workplace Technical W
 riting
ORGANIZER:18staps
LOCATION:18staps - Don Giovanni
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