Abstract
In this study we investigated the role of reading, how writers coordinate editing with other writing processes. In particular, the experiment examines how the cognitive demands of sentence composing and the type of error influence the reading and writing performance. We devised an experimental writing task in which participants corrected an embedded error (orthographic near-neighbors or far-neighbors) and completed a sentence (using 1 or 3 context words)—in either order. Data were collected by logging keystrokes and recording eye-movements. The results revealed that both error and sentence complexity influenced the approach to error-correcting. Participants generally completed the partial sentence first, and then corrected the error (approximately 90% of the items). Task complexity reinforced this tendency. Moreover, in most of these cases, the error was fixated at least once prior to sentence completion. This suggests that the error was detected (at least partially), but the correction response was inhibited. The differences in cognitive load also affect the reading activity during planning. This investigation illustrates how the interplay of two task factors, error and sentence complexity, appears to influence how writers coordinate error-correcting with sentence composing.
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Notes
Recently, however, a software program has been developed, called EyeWrite (Simpson & Torrance, 2007). This system allows researchers to study writers composing by keyboarding. It makes it possible to collect precise timings for the creation of each character and to combine this logging information post hoc with information about the writers’ eye movements. In other words the program creates a synchronized log of both keyboard and eye activity. Researchers in Poitiers developed a comparable research tool, called Eye & Pen, to study handwriting (Alamargot, Chesnet, Dansac, & Ros, 2006).
The linear representation of the fragment generated by Inputlog looks like this (pauses in milleseconds between brackets): [Movement][LeftButton][Movement][LeftButton](1082)[Movement](531)lussen [Movement] [LeftButton][Movement]er•zater•op•te•(811)gooire[BS2]en:•(872)[Movement][LeftButton].
The pause is shown in the linear output of Inputlog: [Movement][LeftButton](2364)ripe(731)[BS2](741)r(1062)[BS](501)ep·haar·moeder.(851)[Movement] [LeftButton](1121)[Movement](701)nufe(811)[BS]fel(681)[Movement] [LeftButton].
For a comprehensive guide to multilevel analysis we would like to refer to a tutorial by Quené and Van den Bergh (2004). Another researcher, Barr (2008), applied the MLR framework in the context of a reading study in which also eye-tracking data were analyzed. This article also contains a mini-manual for researchers who want to apply multilevel analyses to their own data sets.
Although the number and type of sentences is strictly controlled in this experiment—as opposed to more ecologically valid observations of writing processes—a few sentences could not be added to the data set for technical reasons (e.g. because of a calibration problem). The results for the variables related to these sentences were coded as missing values, which resulted in a data set with slightly deviating total numbers of scores.
We grouped the participants on the basis of their preference to either delay the error correction or not. For instance, when participants delayed error correction in less than half of the items, we grouped them in the first group (0–50%). Some of the participants were very consistent in their approach: they delayed the correction of all the errors till after they had completed the sentence. Those writers were categorized under group 4 (100%).
This percentage is calculated on the basis of the odds ratios derived from the binominal interaction model of Cursor Position preference related to Context words and Error type.
In this experiment we used a temporal threshold of 200 ms in order to capture the majority of reading fixations and to exclude noise. Rayner (1978) found the mean fixation duration during reading to be 250 ms, which has since been replicated by others. Other studies have shown somewhat shorter fixation, between 200 and 250 ms, for other types of visual behavior (see also Manor & Gordon, 2003). Because reading during writing might also relate to these other types of visual behavior (e.g., identification of objects) we opted for a 200 ms threshold.
Of course, we have to take into account that some of the words in the TPSF were, for instance, articles. We know from reading research that this kind of short and high frequent words are often only parafoveally fixated (see, for instance, Drieghe, Rayner & Pollatsek, 2005; Inhoff, Eiter, Radach & Juhasz, 2003). The manipulated errors in the TPSF were all longer words (nouns) of at least two syllables.
Note that we should take into account that the participants had to include three context words, they needed more time to complete the task (Table 2). Therefore, the (re)reading behavior and the total number of fixations is to a certain extent confounded by time on-task.
Note that the total Production time was also affect by the number of Context words. Therefore, cautiousness is recommended when interpreting this measure of duration between first and last fixation in the error zone.
This process of rereading triggered by the possibility of having made a typing mistake is probably also different for touch typists, because they follow the emerging text more constantly on the screen (see also Johansson et al., 2009, this issue).
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Acknowledgments
We would like to thank dr. Sven De Maeyer who assisted us patiently in building the multilevel models. Maaike Loncke cooperated with us in preparing the materials for the experiment and Bart Van de Velde did a wonderful job in programming the experiment. We would also like to thank David Galbraith and the other reviewers for their helpful comments on an earlier draft of this article.
The experiment was conducted in the eye-tracking lab of the University of Tilburg, The Netherlands. We would like to thank prof. A. Maes and his team for hosting us and giving us the opportunity to use their lab. The project was partly funded as a BOF/NOI (New Research Initiatives) project by the University of Antwerp (2005–2007).
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Appendix
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Van Waes, L., Leijten, M. & Quinlan, T. Reading during sentence composing and error correction: A multilevel analysis of the influences of task complexity. Read Writ 23, 803–834 (2010). https://doi.org/10.1007/s11145-009-9190-x
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DOI: https://doi.org/10.1007/s11145-009-9190-x