Mariëlle Leijten

Keystroke Logging in Writing Research Using Inputlog to Analyze and Visualize Writing Processes

Keystroke logging has become instrumental in identifying writing strategies and understanding cognitive processes. Recent technological advances have refined logging efficiency and analytical outputs. While keystroke logging allows for ecological data collection, it is often difficult to connect the fine grain of logging data to the underlying cognitive processes. Multiple methodologies are useful to offset these difficulties. In this article we explore the complementarity of the keystroke logging program Inputlog with other observational techniques: thinking aloud protocols and eyetracking data. In addition, we illustrate new graphic and statistical data analysis techniques, mainly adapted from network analysis and data mining. Data extracts are drawn from a study of writing from multiple sources. In conclusion, we consider future developments for keystroke logging, in particular letter- to word-level aggregation and logging standardization.

Coordinating the cognitive processes of writing : the role of the monitor

Moment to moment, a writer faces a host of potential problems. How does the writer’s mind coordinate this problem solving? In the original Hayes and Flower model, the authors posited a distinct process to manage this coordinating—that is, the “monitor.” The monitor became responsible for executive function in writing. In two experiments, the current authors investigated monitor function by examining the coordination of two common writing tasks—editing (i.e., correcting an error) and sentence composing—in the presence or absence of an error and with a low or high memory load for the writer. In the first experiment, participants could approach the editing and composing task in either order. On most trials (88%), they finished the sentence first, and less frequently (12%), they corrected the error first. The error-first approach occurred significantly more often under the low-load condition than the high-load condition. For the second experiment, participants were asked to adopt the less-used, error-first approach. Success in completing the assigned task order was affected by both memory load and error type. These results suggest that the monitor depends on the relative availability of working memory resources and coordinates subtasks to mitigate direct competition over those resources.

Correcting text production errors: Isolating the effects of writing mode from error span, input mode, and lexicality.

Error analysis involves detecting, diagnosing, and correcting discrepancies between the text produced so far (TPSF) and the writers mental representation of what the text should be. The use of different writing modes, like keyboard-based word processing and speech recognition, causes different type of errors during text production. While many factors determine the choice of error-correction strategy, cognitive effort is a major contributor to this choice. This research shows how cognitive effort during error analysis affects strategy choice and success as measured by a series of online text production measures. Text production is shown to be influenced most by error span, that is, whether the error spans more or less than two characters. Next, it is influenced by input mode, that is, whether the error has been generated by speech recognition or keyboard, and finally by lexicality, that is, whether the error comprises an existing word. Correction of larger error spans is more successful than that of smaller errors. Writers impose a wise speed accuracy trade-off during large error spans since correction is better, but preparation times (time to first action) and production times take longer, and interference reaction times are slower. During large error spans, there is a tendency to opt for error correction first, especially when errors occurred in the condition in which the TPSF is not preceded by an auditory prompt. In general, the addition of speech frees the cognitive demands of writing. Writers also opt more often to continue text production when the TPSF is presented auditorially first.

Vlot schrijven: Een multi- dimensioneel perspectief op 'writing fluency'

AbstractsVolume 35 no. 2 2013 Tijdschrift voor Taalbeheersing - 35 (2013), nr. 2, 203-204 Peter Jan Schellens. Tone of Voice in Political Debates: A Stylistic and Ar-gumentative Analysis [This paper is a revised version of the fare-well lecture of Peter Jan Schellens as a Pro-fessor of Language and Communication at the Faculty of Arts of Radboud University Nijmegen on January 11, 2013.] The high tone of voice in Dutch public and parlia-mentary debates is frequently criticised. However, what do we mean with a high ‘tone of voice’? This contribution uses a case study on wildlife starvation from 2010 to answer this question from a stylistic and an argumentative perspective. The case re-solved around the question whether game-keepers should provide additional food to rescue starving wildlife in the Dutch nature reserve “The Oostvaardersplassen” or not. This issue was hotly debated in newspapers, on digital platforms, and in two parliamen-tary debates. The analysis of this debate re-veals that two pragmatic features contribute to a rising tone of voice. Firstly, debaters of-ten forcefully delivered their arguments by using a variety of language intensifiers, such as strong adverbs, adjectives and metaphors. Secondly, they frequently interlaced their argumentation with interactional fallacies, such as arguments

Exploring the Process of Reading During Writing Using Eye Tracking and Keystroke Logging

This study aims to explore the process of reading during writing. More specifically, it investigates whether a combination of keystroke logging data and eye tracking data yields a better understanding of cognitive processes underlying fluent and nonfluent text production. First, a technical procedure describes how writing process data from the keystroke logging program Inputlog are merged with reading process data from the Tobii TX300 eye tracker. Next, a theoretical schema on reading during writing is presented, which served as a basis for the observation context we created for our experiment. This schema was tested by observing 24 university students in professional communication (skilled writers) who typed short sentences that were manipulated to elicit fluent or nonfluent writing. The experimental sentences were organized into four different conditions, aiming at (a) fluent writing, (b) reflection about correct spelling of homophone verbs, (c) local revision, and (d) global revision. Results showed that it is possible to manipulate degrees of nonfluent writing in terms of time on task and percentage of nonfluent key transitions. However, reading behavior was affected only for the conditions that explicitly required revision. This suggests that nonfluent writing does not always affect the reading behavior, supporting the parallel and cascading processing hypothesis.

The impact of writing training on transediting in translation, analyzed from a product and process perspective

This paper reports on a quasi-experimental study of the effect of writing training on transediting in the translation product and process of undergraduate translation students. A classical pretest-posttest experimental design was used, in which the experimental group was trained in writing instructive texts in their mother tongue (Dutch) and the control group received a placebo training. Over the course of the experiment, both groups translated four Spanish instruction manuals into Dutch. The source texts contained a number of rich points that could not be translated literally into the target language and consequently required transediting. The product data indicated that writing training led to a higher amount and quality of transediting, specifically of macro-textual features. The process data showed that the participants of the experimental group based their decision to transedit on more diverse and precise criteria than the control group. Writing training also yielded a more detailed understanding of the acceptability norms of instruction manuals and led to a more critical stance towards the source text. Writing training did not influence the moment of transediting, which was mostly carried out as a first translation solution.

Chapter 4.00.05: Inputlog 4.0: Keystroke Logging in Writing Research

Logging programs enable researchers to accurately register and reconstruct the writing processes of writers who compose texts on the computer. The basic concept of the different logging tools that have been developed is more or less comparable. First, the keystroke logging tools register all keystrokes and mouse movements. This chapter presents the most important characteristics of Inputlog 4.0, and shortly illustrates the programs functionality. Inputlog allows researchers to record writing process data, generate various data files, integrate various types of data from other programs and playback the recorded session. The most distinguishing characteristics of Inputlog to date are its integration with Microsoft Word, the possibilities to identify and log in other Windows environments, the parsing technology, the standard XML structure of the output and the integration of speech recognition. The chapter elaborates briefly on the programs main functions. Keywords: Inputlog 4.0; keystroke logging tools; Microsoft Word; Windows environments; XML structure