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

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 168-173

Publication milestones

  • Published - 2022

Publication status

Published - 2022

Host publication title

Intelligent CALL, granular systems and learner data: short papers from EUROCALL 2022

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

Publication metrics

Related Event

Title

European Conference on Computer Supported Language Learning

Event type

Conference

Date

01/08/2022