Luận Văn Thạc Sĩ Using Data-Driven Learning To Improve Non-English Majors Vocabulary Learning In TOEIC Reading

Using Data-Driven Learning To Improve Non-English Majors Vocabulary Learning In TOEIC Reading : An Action Research At Nong Lam University - Ho Chi Minh City​

That language learners should have a number of encounters with words in multiple contexts in the classroom before they understand, remember, and apply them has been highlighted in previous studies in vocabulary teaching and learning. One prominent approach promoting this is data-driven learning (DDL), in which learners interact with corpora’s concordances as a kind of language data. In fact, DDL is gaining more popularity as it reflects language learning theories, such as noticing hypothesis, constructivism, and socio-cultural theory. Although researchers have called for more replication of DDL studies to validate the effects of DDL, very few studies were found in Vietnam’s context. This study is an effort to fill this gap and, through the use of DDL, to solve the problems of non-English majors’ vocabulary learning in Test of English for International Communication (TOEIC) Reading at The Center for Foreign Studies of Nong Lam University (NLU-CFS).

• Luận văn thạc sĩ ngữ văn
• Chuyên ngành Ngôn ngữ Anh
• Người hướng dẫn: TS. Nguyễn Thị Như Ngọc
• Tác giả: Phạm Quỳnh Mai
• Số trang: 214
  
• File PDF-TRUE
• Ngôn ngữ: Tiếng Anh
• Đại học Khoa học Xã hội và Nhân văn - Đại học Quốc gia TP. HCM 2021

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https://drive.google.com/file/d/1o5HBFk449QJkZ1ULkloRHDu6u_qUSF7Y
https://drive.google.com/drive/folders/1yLBzZ1rSQoNjmWeJTM6cEZ3WGQHg04L1