An Investigation Into Learners’ Cognitive Processes in Data-Driven Learning: Case Studies of Six Learners of Chinese

Author:

Liu Tanjun1,Chen Meilin2

Affiliation:

1. Xi’an Jiaotong-Liverpool University Suzhou China

2. Hong Kong Baptist University , Kowloon Hong Kong

Abstract

Abstract Data-driven learning (DDL), the direct use of corpus by learners in the second language classroom, has been shown to be effective in improving learners’ acquisition of various English linguistic items (Boulton & Cobb, 2017). However, it is still limited to our knowledge regarding how learners interact with DDL-related materials or tools and how DDL works in the learning/teaching of languages other than English. This study aims to closely examine the cognitive processes of six learners of Chinese in using printed concordance-based materials to learn Chinese resultative constructions. These materials contained adapted complete concordance sentences drawn from the Lancaster Corpus for Mandarin Chinese (McEnery & Xiao, 2004). The results show that in general, learners employed various strategies when scrutinising the concordance lines, particularly cognitive strategies such as summarising and grouping. Differences among individual learners were also found: learners who used more diverse strategies with higher frequencies could successfully infer the regularities, which led to learning gains. The study provides some implications for effective teacher guidance in DDL.

Publisher

Walter de Gruyter GmbH

Reference47 articles.

1. Anthony, L. (2016). Introducing corpora and corpus tools into the technical writing classroom through Data-Driven Learning. In J. Flowerdew, & T. Costley (Eds.), Discipline Specific Writing (pp. 162-180). Abingdon, UK: Routledge.

2. Benavides, C. (2015). Using a corpus in a 300-level Spanish grammar course. Foreign Language Annals, 48 (2), 218-235.

3. Boulton, A. (2010). Data-driven learning: Taking the computer out of the equation. Language Learning, 60 (3), 534-572.

4. Boulton, A., & Cobb, T. (2017). Corpus use in language learning: A meta-analysis. Language Learning, 67 (2), 348-93.

5. Boulton, A., & Vyatkina, N. (2021). Thirty years of data-driven learning: Taking stock and charting new directions over time. Language Learning & Technology, 25(3), 66-89. http://hdl.handle.net/10125/73450

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