Year: 2024
Type: conference-paper
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.
Institutions: King's College London, King's College School, University of Cambridge, University at Buffalo, State University of New York, Université Paris Cité, Approches Linguistiques Théoriques, Appliquées et Expérimentales : langues et cultures connectées, University of Richmond, Université Rennes 2
Language: English
Subfield: Language and Linguistics
Field: Arts and Humanities
Domain: Social Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W7131874906