Linggle 2.0: A Collocation Retrieval System with Quality Example Sentences [Konferenzbericht] Paper presented at the EUROCALL 2022 Conference (30th, Reykjavik, Iceland, Aug 17-19, 2022).

Autor/inn/en	Lai, Shu-Li; Chang, Jason; Lee, Kuan-Lin; Huang, Wei-Chung
Titel	Linggle 2.0: A Collocation Retrieval System with Quality Example Sentences [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 (Lai, Shu-Li) ORCID (Chang, Jason) ORCID (Lee, Kuan-Lin) ORCID (Huang, Wei-Chung)
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Phrase Structure; Second Language Learning; Second Language Instruction; English (Second Language); Computer Assisted Instruction; Computer Software; Sentence Structure; Databases; Electronic Publishing; Books; Undergraduate Students; Student Attitudes; Teaching Methods; Writing (Composition); Likert Scales; Dictionaries + Suchen Sie Ihr Suchwort? Phrasenstruktur; Zweitsprachenerwerb; Fremdsprachenunterricht; English as second language; English; Second Language; Englisch als Zweitsprache; Computer based training; Computerunterstützter Unterricht; Satzbau; Satzstruktur; Datenbank; Elektronisches Publizieren; Book; Buch; Monographie; Monografie; Schülerverhalten; Teaching method; Lehrmethode; Unterrichtsmethode; Schreibübung; Likert-Skala; Dictionary; Wörterbuch
Abstract	Linggle is a pattern-based referencing tool that assists in collocation learning. In this ongoing project, we aimed to improve its performance further. First, many of the example sentences are long and difficult for students to understand, so we used a machine learning method and trained a classifier to help select dictionarylike example sentences. Second, we created a database of 60,270,000 sentences from 4C, S2ORC, and VOA Learning English. We also included Google books for real-time supplements. Then, we applied the classifier to select good example sentences from the database for display. We also limited the number of example sentences displayed for search results to improve users' experiences. Two classes of English as a Foreign Language (EFL) college students (N=51) were invited to use the enhanced tool and filled out a questionnaire. The results showed that the students were positive about Linggle's new interface and the quality of the example sentences. We expect that more EFL learners will benefit from the tool. [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