Analyzing User Interactions to Estimate Reading Time in Web-Based L2 Reader Applications [Konferenzbericht] Paper presented at the EUROCALL 2022 Conference (30th, Reykjavik, Iceland, Aug 17-19, 2022).

Autor/inn/en	Hollenstein, Nora; Lungu, Mircea F.
Titel	Analyzing User Interactions to Estimate Reading Time in Web-Based L2 Reader Applications [Konferenzbericht] Paper presented at the EUROCALL 2022 Conference (30th, Reykjavik, Iceland, Aug 17-19, 2022).
Quelle	(2022), (7 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Hollenstein, Nora)
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Reading Rate; Reading Instruction; Vocabulary Development; Second Language Learning; Second Language Instruction; Case Studies; Web Based Instruction; Teaching Methods; Correlation; Reading Processes; High School Students; College Students; Adult Students; Foreign Countries; French; Indo European Languages; Eye Movements; Measurement Techniques; Netherlands; Denmark + Suchen Sie Ihr Suchwort? Reading readiness; Reading speed; Lesegeschwindigkeit; Leseunterricht; Wortschatzarbeit; Zweitsprachenerwerb; Fremdsprachenunterricht; Case study; Fallstudie; Case Study; Web Based Training; Teaching method; Lehrmethode; Unterrichtsmethode; Korrelation; Leseprozess; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Collegestudent; Adult; Adults; Erwachsenenalter; Ausland; Französisch; Indoeuropäisch; Augenbewegung; Messtechnik; Niederlande; Dänemark
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. [For the complete volume, "Intelligent CALL, Granular Systems and Learner Data: Short Papers from EUROCALL 2022 (30th, Reykjavik, Iceland, August 17-19, 2022)," see ED624779.] (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01