Implicit (Not Explicit) Learning Aptitude Predicts the Acquisition of Difficult (Not Easy) Structure

doi:10.1017/9781009076463.020

15 - Implicit (Not Explicit) Learning Aptitude Predicts the Acquisition of Difficult (Not Easy) Structure

A Visual-World Eye-Tracking Study

from Part IV - Aptitude–Treatment Interaction (ATI)

Published online by Cambridge University Press: 27 May 2023

Yuichi Suzuki ,

Robert DeKeyser and

Yi Ting Huang

Edited by

Zhisheng (Edward) Wen ,

Peter Skehan and

Richard L. Sparks

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Zhisheng (Edward) Wen: Affiliation:
Hong Kong Shue Yan University
Peter Skehan: Affiliation:
Institute of Education, University of London
Richard L. Sparks: Affiliation:
Mount St Joseph University

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Summary

The current study investigated to what extent two aptitude components, one for explicit and the other for implicit learning, could predict the acquisition of English grammatical structures by late L2 English learners in a naturalistic acquisition context. Sixty-five L2 English learners of Chinese Mandarin, as well as a group of English native speakers, performed a visual-world eye-tracking task. This task involved real-time processing of two grammatical properties of the English nominal phrase that differ in terms of L2 psycholinguistic difficulty: (1) definiteness (a difficult structure) and (2) mass–count (an easy structure). Predictors were implicit learning aptitude, measured by the serial-reaction time (SRT) task, and explicit learning aptitude, measured by subtests of the Modern Language Aptitude Test (MLAT Part 4) and the LLAMA_F test. The overall findings suggest that explicit and implicit learning mechanisms are recruited differentially for learning different grammatical properties.

Keywords

Cognitive aptitudes visual-world task grammatical difficulty implicit knowledge explicit and implicit learning awareness naturalistic adult L2 acquisition

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Type: Chapter
Information: Language Aptitude Theory and Practice , pp. 381 - 413

DOI: https://doi.org/10.1017/9781009076463.020 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2023

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