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Bursted! A tool for extracting bursts of writing from keystrokes logging "idfx" files

Keywords
cognitive processes;keystroke logging;keystroke logging data processing and analysis;writing processes
Domain
Cognitive Science

Abstract

We present Bursted!, an application that facilitates the extraction of bursts of writing from keystroke logging files when writing (Bordes, Olive & Cislaru, 2025). Keystroke recording is a widespread technique for studying computer writing and its dynamics. Keylogging applications record all keystrokes and mouse movements as well as their chronology. In addition, they often offer pre-analyses of raw data. However, few options to analyse bursts of writing are available. In this framework, Bursted! is designed to automate the extraction of bursts of writing, according to either a fixed or individualized threshold, with associated variables (pause duration before each burst, duration of burst, number of characters…) from “idfx” format keystrokes logs. The processing of a writing session log is divided into two modules: the first module cleans up and prepares the keylogs while the second aggregates the stored events into writing bursts. Each module creates a “csv” output file. Bursted! categorizes the bursts of writing according to their textual function: production bursts increment the text on its right edge, and revision bursts intervene on the text already produced. It distinguishes two types of revision bursts: immediate revision bursts that revise the latest production burst, and delayed revision bursts, which require a return to the text beyond said burst. Bursted! therefore facilitates the analysis of keystroke logging files when writing texts by providing a file of bursts and associated variables ready to be used for visualization, to calculate secondary variables, to prepare statistical processing, or for the automatic analysis of the content of text streams.

Inputlog: New perspectives on keystroke logging

Keywords
AI writing;keystroke logging;keystroke logging data processing and analysis;on-line writing and digital media
Domain
Learning and Instructional Technology

Abstract

Inputlog is a widely used keystroke logging tool for observing and analyzing writing processes. This demo introduces the major new features of Inputlog 9.6.0 and outlines planned future developments.Versioning and Diary Function A new automatic versioning option allows users to save intermediate Word document versions at fixed intervals (e.g., every three minutes). Researchers can compare these versions to track document changes throughout the writing session. An optional diary prompt in the closing wizard invites writers to comment on their session, facilitating the combination of process data and self-report.Expanded Logging Environments Because writing increasingly takes place outside MS Word, the logging environment has been expanded. Inputlog now offers dedicated logging modules for Google Docs and LibreOffice, broadening the range of authentic writing contexts that can be captured.Feedback Reports Inputlog generates student-centered feedback reports that visualize key process indicators, including process graphs and source interaction. Users may rely on the default template or customize report formats to meet instructional or research needs, such as the use of AI.Multilingual Logging New beta versions introduce preliminary support for logging Korean and Chinese script (via Pinyin). This extends Inputlog’s previous focus on Latin-based scripts and broadens its applicability in multilingual writing research. Copy-Task Dashboard Inputlog includes a standardized copy task designed to assess typing skills in thirteen languages using sentences, word triplets, and letter clusters. We also present a corpus of more than 5,000 anonymized copy-task recordings, accompanied by an interactive R-Shiny dashboard that allows researchers to explore the corpus, download data, and benchmark their own results.

Learning to write: Toy examples using the progressive graph tool.

Keywords
data visualisation;keystroke logging data processing and analysis;learning to write;writing at school
Domain
Learning and Instructional Technology

Abstract

Approaches to writing based on keystroke logging are becoming increasingly prevalent and are contributing to a more profound understanding of the writing process. A plethora of software programs facilitate the recording of keystrokes, thereby enabling the analysis of both the temporal and spatial dimensions of writing, from a recording file called a log. However, the interpretation of the information contained within these logs is challenging, due to the atypical nature of the data. The GIS representation has been utilised extensively (Becotte et al. 2019). Ggxlog is a recently developed software program that aims to combine text genetics (Leblay & Leblay 2019) and graph theory with keystroke logging (Caporossi & Leblay 2011; Doquet & Leblay 2014). This ggxlog software offers a specific feature, designated 'progressive graph', which enables researchers or educators to visualise the various stages of a writing session that has taken place (Usoof et al. 2020). This innovative feature enables the text being written to be displayed simultaneously, as in a word processor, alongside the real-time construction of the corresponding graph. The objective of this study is to collect a common pilot corpus between Finland, France and Quebec in a school context, with a focus on brief pieces of writing, referred to as 'toy examples'. This study will examine how young learners use keyboards to facilitate their acquisition of writing skills, thereby marking a pivotal transition from the conventional paper-and-pencil medium (Auriac-Slusarczyk et al., 2013; Cogis & Leblay, 2010). This would facilitate a more profound understanding of the utilisation of technological resources in the acquisition of written French and written Finnish as first languages.

THEtool: A software application for linguistic modeling of writing

Keywords
keystroke logging data processing and analysis;natural language processing (NLP);writing models;writing processes
Domain
-

Abstract

We present an open-source tool for analyzing writing process data in relation to linguistic structures: THEtool(https://github.com/mulasik/wta; Mahlow 2024; Ulasik and Miletic 2024; Ulasik et al. 2025). Although linguistic modeling of the writing process has gained importance in recent years, existing approaches, whether rooted in linguistic theory or writing research, remain insufficient to explain how writers actually produce and revise text at a linguistic level. THEtool enables writing researchers to investigate the writing process with a particular focus on sentences and their interaction with writing bursts and revisions. Because the software operates fully automatically and requires no manual intervention, it facilitates the efficient processing of large datasets. THEtool processes keystroke logging data in the XML-based IDFX format generated by Inputlog and ScriptLog, the de facto standard for storing and exchanging writing process data, thereby ensuring seamless integration with existing tools and workflows.To support a wide range of research applications, THEtool offers configurable key features, including language selection (currently German, Greek, French, and English, with straightforward extensibility to additional languages), the minimum pause duration that triggers the extraction of text and sentence versions within a writing burst, and relevance parameters for filtering text versions.THEtool is a fully functioning implementation of a model of text production based on the concept of layers: writing bursts, revisions, and sentence production are conceptualized as three distinct yet interacting layers that share a common timeline. Bursts may be interrupted by revision episodes or, in an abstract sense, by final punctuation marks signaling sentence completion. Revision processes can be interrupted by pauses or segmented by final punctuation. Likewise, sentence production may be interrupted by pauses or revisions. Projecting these layers onto one another enables new insights into the writing process from a linguistic perspective.We conducted exploratory studies in German, Greek, French, and English using THEtool. The results demonstrate both the feasibility and the analytical potential of the proposed approach.