Projects per year
Abstract
Despite a considerable amount of research conducted on the development of tense/aspect (TA) usage in English by second language (L2) learners, nuances in uses of TAs remain elusive to many L2 learners of English: the grammatical accounts proposed appear difficult to apply as they are either too general or too specific and fail to provide learners with a conceptual understanding of the system. Merging insights from psychological models of learning, corpus-based, and cognitive linguistics approaches to second language acquisition we use the results of computational simulations of learning of the TA system conducted by Romain et al. (2022) and propose an approach to TA teaching that focuses on the cues that have been identified as crucial for accurate TA use. Our pedagogical approach draws learners’ attention not so much to the cues themselves but to the type of cues that are the most reliable in the choice of different TA combinations. This approach allows teachers to equip learners with a long-term learning strategy that will help them focus on the most useful type of information, and thus gradually build up a bank of knowledge specific to each TA combination.
Original language | English |
---|---|
Number of pages | 25 |
Journal | Pedagogical Linguistics |
Early online date | 11 Jan 2024 |
DOIs | |
Publication status | E-pub ahead of print - 11 Jan 2024 |
Bibliographical note
Funding:This work was funded by a Leverhulme Trust Research Leadership Award (RL-2016-001) that funded both authors.
Open Access publication of this article was funded through a Transformative Agreement with University of Birmingham.
Keywords
- tense/aspect
- EFL/ESL
- associative learning
- cognitive linguistics
- usage-based theories
Fingerprint
Dive into the research topics of 'The types of cues that help you learn: Pedagogical implications of a computational simulation on learning the English tense/aspect system from exposure'. Together they form a unique fingerprint.Projects
- 1 Finished
-
Out of our minds: Optimizing language learning with discriminative algorithms
1/01/19 → 31/12/23
Project: Research