Construction of a Corpus for L2 Derivational Morphology: Based on Construction

This study followed the theoretical framework of Constructional Morphology and proposed a model for constructing an L2 derivational morphology corpus based on affix concordances. This model used morphological series members as keywords and provides examples containing these keywords, aiming to offer rich and systematic language materials for L2 instruction of derivational morphology. Excel and AntConc software were used to analyze the word lists of L2 English textbooks. By examining the distribution of derived words and related affixes, affix concordances that included abundant morphological and syntactic contexts were established. This study suggested that L2 learners should be exposed to more comprehensive and targeted learning resources, so as to deepen their understanding of English derivational morphology.

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Publication Details

Journal
English Language Teaching
Published
2024-08-12
DOI
https://doi.org/10.5539/elt.v17n9p26
Primary Topic
Natural Language Processing Techniques
Type
article
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article

Construction of a Corpus for L2 Derivational Morphology: Based on Construction

Xiaomei Yu
English Language Teaching
Natural Language Processing Techniques
article

Construction of a Corpus for L2 Derivational Morphology: Based on Construction

Xiaomei Yu
article en

Abstract

This study followed the theoretical framework of Constructional Morphology and proposed a model for constructing an L2 derivational morphology corpus based on affix concordances. This model used morphological series members as keywords and provides examples containing these keywords, aiming to offer rich and systematic language materials for L2 instruction of derivational morphology. Excel and AntConc software were used to analyze the word lists of L2 English textbooks. By examining the distribution of derived words and related affixes, affix concordances that included abundant morphological and syntactic contexts were established. This study suggested that L2 learners should be exposed to more comprehensive and targeted learning resources, so as to deepen their understanding of English derivational morphology.

English Language TeachingVol. 17(9)
Quality Education
Openalex Percentile: Top 89%
Natural Language Processing Techniques
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