Analyzing user interactions to estimate reading time in web-based L2 reader applications

Mircea Lungu, Nora Hollenstein

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

Abstract

We propose to use reading time as a metric to report progress in language learning applications. As a case study we use a web-based application that enables learners of a foreign language to read texts from the web and practice vocabulary with interactive exercises generated based on their past readings. The application captures generic interactions with the web page (e.g. switching to a different tab) but also interactions directly related to language learning (e.g. clicking on a word to get a translation). We propose two metrics for approximating reading times based on user interactions with the web application. We analyze the correlation between these metrics and other interaction metrics and show that active time is the best metric for estimating the user’s actual involvement with the texts and that it can be approximated from interaction metrics
OriginalsprogEngelsk
TitelIntelligent CALL, granular systems and learner data: short papers from EUROCALL 2022
Publikationsdato2022
Sider168-173
DOI
StatusUdgivet - 2022
BegivenhedEuropean Conference on Computer Supported Language Learning -
Varighed: 1 aug. 2022 → …
https://vigdis.hi.is/en/events/eurocall-2022/

Konference

KonferenceEuropean Conference on Computer Supported Language Learning
Periode01/08/2022 → …
Internetadresse

Emneord

  • reading time
  • second language learning
  • web-based learning
  • user interactions

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