Revisiting the Explicit Learning of Vocabulary of Chinese EFL Learners
- Chen Wang
- Jingjing Yang
Abstract
This study intends to find out how the retention of new vocabulary items could be affected by the item type (collocations versus single words), association strength between collocates and the collocate-node relationship. 101 Chinese EFL learners encountered the new items in paired-associate format. Participants were assigned to three groups: learning two types of collocations with high association strength, learning two types of collocations with low association strength, and learning new items in single words. The results show that learning new items in collocations yielded better retention of receptive and productive knowledge of meaning than in single words. Collocations with greater association strength also led to better retention of meaning. Different item types and associate strength has little effect on the retention of form.
- Full Text:
PDF
- DOI:10.5539/elt.v13n2p86
Journal Metrics
Citation Metrics (for informational purposes only; sourced from Google Scholar as of May 2026):
1. Citations (May 2026): 112462
3. i10-index (February 2025): 1811
*Note: Citation metrics vary significantly across indexing platforms. These figures are provided transparently and should not be used for cross-database comparisons. For methodological details, please refer to the official Google Scholar Metrics documentation.
Index
- Academic Journals Database
- CNKI Scholar
- Elektronische Zeitschriftenbibliothek (EZB)
- EuroPub Database
- Excellence in Research for Australia (ERA)
- GETIT@YALE (Yale University Library)
- Harvard Library E-Journals
- IBZ Online
- INDEX ISLAMICUS
- JournalSeek
- JournalTOCs
- LearnTechLib
- Library and Archives Canada(LAC)
- Linguistics Abstracts Online
- LOCKSS
- MIAR
- MLA International Bibliography
- NewJour
- Open J-Gate
- PKP Open Archives Harvester
- ResearchGate
- ROAD
- SHERPA/RoMEO
- Technische Informationsbibliothek (TIB)
- The Keepers Registry
- Ulrich's
- Universe Digital Library
Contact
- Gavin YuEditorial Assistant
- elt@ccsenet.org