Modeling Writing Processes and Predicting Text Quality in Technical Communication

Combining keystroke logging, screen recordings, interviews, and text quality assessment in two mixed-methods studies with technical writers, this research (1) identifies defining variables of technical writing processes and (2) examines their correlations with and predictive power for text quality. Study 1, an exploratory investigation with 10 participants, identified 22 distinct writing behaviors under six categories of information searching, information reusing, content shaping, organization structuring, language styling, and layout designing during planning, translating, and reviewing sessions. These behavioral variables, together with time-related variables, were subsequently analyzed as “process indicators” in a comparative experiment with 43 participants across experience levels. Results of Study 2 revealed significant differences among experience levels in writing speed, planning duration, pause, search, reuse, content shaping, and structuring. Detailed planning and systematic content/structure editing were strongly associated with higher-quality texts. Building on these findings, we propose a process model of technical writing, explain its correlations with writing score, and depict process profiles of different experience levels. We also highlight the importance of information processing skills in enhancing writing efficiency, offering empirical guidance for technical writing instruction and professional training.

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Publication Details

Journal
Written Communication
Published
2025-11-06
DOI
https://doi.org/10.1177/07410883251372212
Primary Topic
Writing and Handwriting Education
Type
article
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article

Modeling Writing Processes and Predicting Text Quality in Technical Communication

Zhijun Gao, Jiangying Wang, Lin Dong
Written Communication
Writing and Handwriting Education
article

Modeling Writing Processes and Predicting Text Quality in Technical Communication

Zhijun Gao, Jiangying Wang, Lin Dong
article en

Abstract

Combining keystroke logging, screen recordings, interviews, and text quality assessment in two mixed-methods studies with technical writers, this research (1) identifies defining variables of technical writing processes and (2) examines their correlations with and predictive power for text quality. Study 1, an exploratory investigation with 10 participants, identified 22 distinct writing behaviors under six categories of information searching, information reusing, content shaping, organization structuring, language styling, and layout designing during planning, translating, and reviewing sessions. These behavioral variables, together with time-related variables, were subsequently analyzed as “process indicators” in a comparative experiment with 43 participants across experience levels. Results of Study 2 revealed significant differences among experience levels in writing speed, planning duration, pause, search, reuse, content shaping, and structuring. Detailed planning and systematic content/structure editing were strongly associated with higher-quality texts. Building on these findings, we propose a process model of technical writing, explain its correlations with writing score, and depict process profiles of different experience levels. We also highlight the importance of information processing skills in enhancing writing efficiency, offering empirical guidance for technical writing instruction and professional training.

Written CommunicationVol. 43(1)
University of International Business and Economics (CN), Peking University (CN)
Openalex Percentile: Top 65%
Writing and Handwriting Education
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