A Corpus Perspective on the Development of Verb Constructions in Second Language Learners

• In Event: Constructions in Applied Linguistics: Innovation and Application of Corpus-based Construction Grammar

Summary

This paper uses data from L2 learners at different proficiency levels (CEFR A1 to C1) in a large-scale investigation of verb construction emergence. It reports findings on construction development (in terms of types, tokens, complexity, and formulaicity), dominant verb-VAC associations, and correlations between verbs/VACs produced by learners at different levels.

Abstract

This paper presents findings from a large-scale corpus study on the development of verb patterns in second language (L2) learners of English. It follows the lead of existing usage-based studies of L2 construction acquisition while considerably expanding their scope to hundreds of constructions and over 700,000 verb tokens. Using methods from Corpus Linguistics and Natural Language Processing, the study focuses on verb-argument constructions (VACs, e.g. the ‘V n n’ or ditransitive construction) and addresses the following research questions:
1. What are the first VACs acquired by beginning L2 learners of English?
2. How does the VAC repertoire of learners develop across proficiency levels?
3. How does the distribution of verbs in VACs in learner production develop across proficiency levels?
4. What role do formulaic sequences play in the L2 acquisition of VACs?
To address these questions, data on verbs and the constructions they occur in was exhaustively extracted from a dependency-parsed cross-sectional corpus of L2 writing. The corpus is a 6-million word subset of EFCAMDAT, the Education First-Cambridge Open Language Database, consisting of over 68,000 texts produced by L1 German and L1 Spanish learners at CEFR levels A1 through C1. Using a customized Python script, we generated frequency-sorted VAC and verb-VAC lists for each level and L1 (e.g., German_A1). We also extracted recurring multi-word clusters (spans 3, 4, and 5) around the 50 most frequent verbs in EFCAMDAT, together with information on frequency and cluster association strength (Mutual Information).
We will share selected results on verb construction development across learner proficiency levels. We expect to find an increase in VAC types, growth in VAC productivity and complexity, and a development from predominantly fixed sequences to more flexible and productive ones. The resulting findings help to expand our understanding of the processes that underlie construction acquisition in an L2 context.

Author

• Ute Roemer, Georgia State University