Data-driven learning of academic lexical bundles below the C1 level

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Volume 24 Number 3, October 2020
Lay, Keith J. Yavuz, Mehmet A.
2020-10-09T17:53:58Z
2020-10-09T17:53:58Z
2020-10-15
This study investigates the possibility and efficacy of paper-based, in-class, data-driven learning (DDL) of academic lexical bundles below the C1 level of proficiency described by the Common European Framework of Reference (CEFR; advanced high ACTFL). A two-stage experimental design involving three groups (n = 41) and 24 two-to-four word academic items was implemented. First, the question of whether this type of learning works with these items below the C1 level is addressed through a nonequivalent-groups quasi-experimental design covering a five-week period. The results indicate that this technique is effective at the B2 level, but not at the A2-B1 level. Next, an equivalent-groups experimental design compares this style of learning to conventional techniques at the B2 level. The results of this stage suggest that paper-based, in-class DDL is more effective than conventional learning with academic lexical bundles at the B2 level.
Made available in DSpace on 2020-10-09T17:53:58Z (GMT). No. of bitstreams: 1 24_03_10125-44741.pdf: 517123 bytes, checksum: 98b33bb13997bf21f19c33668de6bc27 (MD5) Previous issue date: 2020-10
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Lay, K. J., & Yavuz, M. A. (2020). Data-driven learning of academic lexical bundles below the C1 level. Language Learning & Technology, 24(3), 176–193. http://hdl.handle.net/10125/44741
1094-3501
http://hdl.handle.net/10125/44741
3
Language Learning & Technology
University of Hawaii National Foreign Language Resource Center Center for Language & Technology (co-sponsored by Center for Open Educational Resources and Language Learning, University of Texas at Austin)
/item/10125-44741/
176
Academic lexical bundles Corpus Data-driven learning (DDL) English for academic purposes (EAP)
Data-driven learning of academic lexical bundles below the C1 level
Article
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