2022
Conijn, Rianne; Speltz, Emily Dux; van Zaanen, Menno; Waes, Luuk Van; Chukharev-Hudilainen, Evgeny
A Product- and Process-Oriented Tagset for Revisions in Writing Tijdschriftartikel
In: WRITTEN COMMUNICATION, vol. 39, nr. 1, pp. 97-128, 2022, ISSN: 0741-0883.
Abstract | Links | BibTeX | Tags: writing analytics; writing process; revision processes; keystroke logging; eye tracking; annotation
@article{WOS:000713603000001,
title = {A Product- and Process-Oriented Tagset for Revisions in Writing},
author = {Rianne Conijn and Emily Dux Speltz and Menno van Zaanen and Luuk Van Waes and Evgeny Chukharev-Hudilainen},
doi = {10.1177/07410883211052104},
issn = {0741-0883},
year = {2022},
date = {2022-01-01},
journal = {WRITTEN COMMUNICATION},
volume = {39},
number = {1},
pages = {97-128},
publisher = {SAGE PUBLICATIONS INC},
address = {2455 TELLER RD, THOUSAND OAKS, CA 91320 USA},
abstract = {The study of revision has been a topic of interest in writing research
over the past decades. Numerous studies have, for instance, shown that
learning-to-revise is one of the key competences in writing development.
Moreover, several models of revision have been developed, and a variety
of taxonomies have been used to measure revision in empirical studies.
Current advances in data collection and analysis have made it possible
to study revision in increasingly precise detail. The present study
aimed to combine previous models and current advances by providing a
comprehensive product- and process-oriented tagset of revision. The
presented tagset includes properties of external revisions: trigger,
orientation, evaluation, action, linguistic domain, spatial location,
temporal location, duration, and sequencing. We identified how keystroke
logging, screen replays, and eye tracking can be used to extract both
manually and automatically extract features related to these properties.
As a proof of concept, we demonstrate how this tagset can be used to
annotate revisions made by higher education students in various academic
tasks. To conclude, we discuss how this tagset forms a scalable basis
for studying revision in writing in depth.},
keywords = {writing analytics; writing process; revision processes; keystroke logging; eye tracking; annotation},
pubstate = {published},
tppubtype = {article}
}
The study of revision has been a topic of interest in writing research
over the past decades. Numerous studies have, for instance, shown that
learning-to-revise is one of the key competences in writing development.
Moreover, several models of revision have been developed, and a variety
of taxonomies have been used to measure revision in empirical studies.
Current advances in data collection and analysis have made it possible
to study revision in increasingly precise detail. The present study
aimed to combine previous models and current advances by providing a
comprehensive product- and process-oriented tagset of revision. The
presented tagset includes properties of external revisions: trigger,
orientation, evaluation, action, linguistic domain, spatial location,
temporal location, duration, and sequencing. We identified how keystroke
logging, screen replays, and eye tracking can be used to extract both
manually and automatically extract features related to these properties.
As a proof of concept, we demonstrate how this tagset can be used to
annotate revisions made by higher education students in various academic
tasks. To conclude, we discuss how this tagset forms a scalable basis
for studying revision in writing in depth.
over the past decades. Numerous studies have, for instance, shown that
learning-to-revise is one of the key competences in writing development.
Moreover, several models of revision have been developed, and a variety
of taxonomies have been used to measure revision in empirical studies.
Current advances in data collection and analysis have made it possible
to study revision in increasingly precise detail. The present study
aimed to combine previous models and current advances by providing a
comprehensive product- and process-oriented tagset of revision. The
presented tagset includes properties of external revisions: trigger,
orientation, evaluation, action, linguistic domain, spatial location,
temporal location, duration, and sequencing. We identified how keystroke
logging, screen replays, and eye tracking can be used to extract both
manually and automatically extract features related to these properties.
As a proof of concept, we demonstrate how this tagset can be used to
annotate revisions made by higher education students in various academic
tasks. To conclude, we discuss how this tagset forms a scalable basis
for studying revision in writing in depth.