Keystroke Logging in Writing Research: Using Inputlog to Analyze and Visualize Writing Processes
Abstract
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.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Keystroke logging is a prevalent method for examining the writing process in educational settings, involving recording and timestamping keystroke actions to reconstruct the writing process.
“Keystroke logging is a prevalent method for examining the writing process in educational settings, involving the recording and timestamping of keystroke actions to reconstruct the writing process (Leijten & Van Waes, 2013).”
From Ink and algorithm: Exploring temporal dynamics in generative <scp>AI</scp> ‐assisted writing (2026) · cites this paper as Leijten & Van Waes, 2013
No citation lists for this paper
No citation lists for this paper yet — checked again daily.
References 67 · Cited by 513
- Authors
- Leijten, M., & Van Waes, L.
- Affiliations
- University of Antwerp (BE)
- University of Antwerp, Antwerp, Belgium
- ORCID
- Leijten, Mariëlle
- Venue
- Written Communication
- Publisher
- SAGE Publications
- Published
- 2013-06-29
- Volume
- 30
- Issue
- 3
- Pages
- 358-392
- ISSN
- 0741-0883 (ISSN-L)
- 1552-8472
- OpenAlex
- W2125732627
- Cited by
- 513
- References
- 67
- Citations by year
- 2026: 53 · 2025: 40 · 2024: 30 · 2023: 51 · 2022: 76 · 2021: 50 · 2020: 35 · 2019: 34 · 2018: 58 · 2017: 24 · 2016: 21 · 2015: 27 · 2014: 12 · 2013: 1
- FWCI
- 97.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Written Communication (publishedVersion)
- Topics
- Social Sciences › Education › Writing and Handwriting Education
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Keywords
- keystroke logging, writing strategies, cognitive processes in writing, think-aloud, eye tracking, network analysis, data mining, multimodal data integration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
