Linggle 2.0: A Collocation Retrieval System with Quality Example Sentences

التفاصيل البيبلوغرافية
العنوان: Linggle 2.0: A Collocation Retrieval System with Quality Example Sentences
اللغة: English
المؤلفون: Lai, Shu-Li (ORCID 0000-0002-9976-9279), Chang, Jason (ORCID 0000-0002-8227-7382), Lee, Kuan-Lin (ORCID 0000-0002-9819-6755), Huang, Wei-Chung (ORCID 0000-0002-5062-6429)
المصدر: Research-publishing.net. 2022.
الإتاحة: Research-publishing.net. La Grange des Noyes, 25110 Voillans, France. e-mail: info@research-publishing.net; Web site: http://research-publishing.net
Peer Reviewed: Y
Page Count: 7
تاريخ النشر: 2022
نوع الوثيقة: Speeches/Meeting Papers
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: 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
مستخلص: 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.]
Abstractor: As Provided
Entry Date: 2023
رقم الأكسشن: ED625231
قاعدة البيانات: ERIC