@inproceedings{velentzas-etal-2024-logging,
    title = "Logging Keystrokes in Writing by {E}nglish Learners",
    author = "Velentzas, Georgios  and
      Caines, Andrew  and
      Borgo, Rita  and
      Pacquetet, Erin  and
      Hamilton, Clive  and
      Arnold, Taylor  and
      Nicholls, Diane  and
      Buttery, Paula  and
      Gaillat, Thomas  and
      Ballier, Nicolas  and
      Yannakoudakis, Helen",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.938",
    pages = "10725--10746",
    abstract = "Essay writing is a skill commonly taught and practised in schools. The ability to write a fluent and persuasive essay is often a major component of formal assessment. In natural language processing and education technology we may work with essays in their final form, for example to carry out automated assessment or grammatical error correction. In this work we collect and analyse data representing the essay writing process from start to finish, by recording every key stroke from multiple writers participating in our study. We describe our data collection methodology, the characteristics of the resulting dataset, and the assignment of proficiency levels to the texts. We discuss the ways the keystroke data can be used {--} for instance seeking to identify patterns in the keystrokes which might act as features in automated assessment or may enable further advancements in writing assistance {--} and the writing support technology which could be built with such information, if we can detect when writers are struggling to compose a section of their essay and offer appropriate intervention. We frame this work in the context of English language learning, but we note that keystroke logging is relevant more broadly to text authoring scenarios as well as cognitive or linguistic analyses of the writing process.",
}

Essay writing is a skill commonly taught and practised in schools. The ability to write a fluent and persuasive essay is often a major component of formal assessment. In natural language processing and education technology we may work with essays in their final form, for example to carry out automated assessment or grammatical error correction. In this work we collect and analyse data representing the essay writing process from start to finish, by recording every key stroke from multiple writers participating in our study. We describe our data collection methodology, the characteristics of the resulting dataset, and the assignment of proficiency levels to the texts. We discuss the ways the keystroke data can be used {--} for instance seeking to identify patterns in the keystrokes which might act as features in automated assessment or may enable further advancements in writing assistance {--} and the writing support technology which could be built with such information, if we can detect when writers are struggling to compose a section of their essay and offer appropriate intervention. We frame this work in the context of English language learning, but we note that keystroke logging is relevant more broadly to text authoring scenarios as well as cognitive or linguistic analyses of the writing process.
Velentzas, Georgios Caines, Andrew Borgo, Rita Pacquetet, Erin Hamilton, Clive Arnold, Taylor Nicholls, Diane Buttery, Paula Gaillat, Thomas Ballier, Nicolas Yannakoudakis, Helen
Logging Keystrokes in Writing by English Learners