Writing Process Differences in Subgroups Reflected in Keystroke Logs

Guo, Hongwen; Zhang, Mo; Deane, Paul; Bennett, Randy Elliot

doi:10.3102/1076998619856590

Cited by 16 publications

(7 citation statements)

References 25 publications

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“…Our own continuing work to advance the state of the art includes investigating the statistical properties of keystroke data (Guo, Deane, van Rijn, Zhang, & Bennett, ), trying to distinguish keyboarding skills from higher level writing skills (Deane et al., ), developing approaches to defining bursts of text personalized to the individual (as opposed to using a uniform threshold for all individuals) (Zhang, Hao, Li, & Deane, ), employing keystroke data to infer whether processes are consistent with the construct the test is designed to measure (Zhang, Zou, et al., ), and trying to model process durations and transitions (e.g., from text generation to editing) to see if they might suggest meaningful demographic group differences (Guo, Zhang, Deane, & Bennett, ). Ultimately, we and others will need to investigate and devise ways to report writing‐process information to teachers and students so that such information contributes to the development of more effective writing and writers.…”

Section: Discussionmentioning

confidence: 99%

Are There Gender Differences inHowStudents Write Their Essays? An Analysis of Writing Processes

Zhang

Bennett

Deane

et al. 2019

Educational Measurement

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This study compared gender groups on the processes used in writing essays in an online assessment. Middle‐school students from four grades responded to essays in two persuasive subgenres, argumentation and policy recommendation. Writing processes were inferred from four indicators extracted from students’ keystroke logs. In comparison to males, on average females not only obtained higher essay scores but differed from males in their writing processes. Females entered text more fluently, engaged in more macro and local editing, and showed less need to pause at locations associated with planning (e.g., between bursts of text, at sentence boundaries). That these differences were detected after controlling for essay scores suggests that they cannot be attributed solely to disparities in group writing skill.

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Section: Discussionmentioning

confidence: 99%

Are There Gender Differences inHowStudents Write Their Essays? An Analysis of Writing Processes

Zhang

Bennett

Deane

et al. 2019

Educational Measurement

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“…This study offers a perspective considerably different from the existing literature on writing processes. Previous research has found notable process differences among demographic groups and between writing proficiency levels (Bennett et al, 2021, 2020; Guo et al, 2019). The current study documents the existence of subsets of individuals at the same proficiency level who, within a subset, employ processes similar to one another yet different from other individuals at that same level.…”

Section: Discussionmentioning

confidence: 94%

Are There Distinctive Profiles in Examinee Essay‐Writing Processes?

Bennett

Zhang

Sinharay

et al. 2021

Educational Measurement

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Grouping individuals according to a set of measured characteristics, or profiling, is frequently used in describing, understanding, and acting on a phenomenon. The advent of computer‐based assessment offers new possibilities for profiling writing because aspects can be captured that were not heretofore observable. We explored whether writing processes could be profiled of over 30,000 adults taking a high‐school equivalency examination. Process features were extracted from keystroke logs, aggregated into composite indicators, and used with essay score to assign individuals to profiles. Analyses included computing the percentages of individuals that could be classified, using MANOVA to examine differences among profiles on external variables, and examining if profiles could be distinguished from one another based on patterns derived from cluster analysis. Results showed that about 30% of examinees could be classified into profiles that were largely distinct. These results contribute toward a foundation for using such profiles in describing how individuals compose and in how their writing might be improved.

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“…KL is an unobtrusive approach to get fine-grained process data on every keystroke during writing (Vandermeulen et al, 2020;Guo et al, 2019). Extensive empirical research with different orientations has been done on writing to discover the relation between KLs and underlying cognitive writing processes (Leijten & Van Waes, 2013).…”

Section: An Overview Of Kl Studiesmentioning

confidence: 99%

Clustering students’ writing behaviors using keystroke logging: a learning analytic approach in EFL writing

Talebinamvar

Zarrabi

2022

Lang Test Asia

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Feedback is an essential component of learning environments. However, providing feedback in populated classes can be challenging for teachers. On the one hand, it is unlikely that a single kind of feedback works for all students considering the heterogeneous nature of their needs. On the other hand, delivering personalized feedback is infeasible and time-consuming. Available automated feedback systems have helped solve the problem to some extent. However, they can provide personalized feedback only after a draft is submitted. To help struggling students during the writing process, we can use machine learning to cluster students who benefit the same from feedback using keystroke logs. We can apply the results in automated feedback systems that provide process feedback. In this study, we aim to find homogeneous student profiles based on their writing process indicators. We use fourteen process indicators to find clusters in the data set. We used these measures in a four-stage analysis, including (a) data preprocessing, (b) dimensionality reduction, (c) clustering, and (d) the analysis of the writing quality. Clustering techniques identified five different profiles: Strategic planners, Rapid writers, Emerging planners, Average writers, and Low-performing writers. We further validated the emerged profiles by comparing them concerning students' writing quality. The present work broadens our knowledge of how students interact with writing tasks and addresses how variations in writing behaviors lead to qualitatively different products. We discuss the theoretical underpinnings and potentials of finding profiles of students during writing in higher education.

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Writing Process Differences in Subgroups Reflected in Keystroke Logs

Cited by 16 publications

References 25 publications

Are There Gender Differences inHowStudents Write Their Essays? An Analysis of Writing Processes

Are There Gender Differences inHowStudents Write Their Essays? An Analysis of Writing Processes

Are There Distinctive Profiles in Examinee Essay‐Writing Processes?

Clustering students’ writing behaviors using keystroke logging: a learning analytic approach in EFL writing

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