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L2 Morphological Instruction Based on Affix Index

A Constructional Approach

Bibliographic Data

ID22190409
AuthorsXiaomei Yu (0000-0002-9682-0438, Guangdong University of Foreign Studies, corresponding author)
Year2024
Volume8
Issue3
Pagesp283
Publication date2024-08-24
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueStudies in Linguistics and Literature (JOURNAL)
Journal identifiersISSN: 2573-6426 • E-ISSN: 2573-6434
PublisherScholink Co, Ltd. (PUBLISHER)
DOI10.22158/sll.v8n3p283
OpenAlexW4401854907
LanguageEN
References cited17

This study introduces a pedagogical approach based on Construction Morphology and affix index, aiming to create morphological and syntactic contexts for L2 learners and enhance the effectiveness of teaching derived words. The experiment consisted of an Experimental Group (EG) receiving 40 minutes’ morphological instruction and a Control Group (CG) without such intervention. The instructional approach focused on six polysemous affixes, utilizing six sets of affix concordances (each comprising six sentences) to assist learners in conducting morphological analyses of familiar words containing the specified affixes. Subsequently, both groups underwent an immediate post-test evaluating four dimensions of morphological knowledge of new words: relational, syntactic, distributional, and semantic knowledge. The EG engaged in a delayed post-test two weeks later, with adjusted test item sequencing. Results indicated positive short-term effects on comprehensive morphological knowledge and its constituent aspects. However, in the delayed post-test, while no significant difference was observed in relational and semantic knowledge, the EG’s mean scores for syntactic and distributional knowledge notably declined. These findings underscore the efficacy of the affix index-based teaching mode in facilitating L2 learners’ understanding of morphemic structures and subsequent acquisition of derived words

Affix · Linguistics · Morpheme · Natural language processing · Significant difference · Statistics · Computer Science · Mathematics · Psychology · Reading and Literacy Development · Second Language Acquisition and Learning · Writing and Handwriting Education · Artificial Intelligence

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