Beyond poverty
Engaging with input in generative SLA
Bibliographic Data
| ID | 11655728 |
|---|---|
| Authors | Tom Rankin (0000-0001-5372-8773, Vienna University of Economics and Business, corresponding author), Sharon Unsworth (0000-0002-0946-2362, Radboud University, Netherlands) |
| Year | 2016 |
| Volume | 32 |
| Issue | 4 |
| Pages | 563-572 |
| Publication date | 2016-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Second language Research (JOURNAL) |
| Journal identifiers | ISSN: 0267-6583 • E-ISSN: 1477-0326 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/0267658316648732 |
| OpenAlex | W2473326316 |
| Language | EN |
| Citations received | 9 |
| References cited | 30 |
A generative approach to language acquisition is no different from any other in assuming that target language input is crucial for language acquisition. This discussion note addresses the place of input in generative second language acquisition (SLA) research and the perception in the wider field of SLA research that generative SLA ‘ignores’ the input. This impression may have arisen because generative SLA researchers have tended not to systematically study quantitative distribution of input properties, nor qualitative properties of the input available to learners. We argue that precisely these sorts of studies would be at least beneficial, if not indispensable, to the development of a comprehensive (generative) theory of SLA. Furthermore, a welcome side-effect of more systematic engagement with input would be potential for greater accessibility for generative SLA in the wider field of second language (L2) studies
Field (mathematics · Generative grammar · Language acquisition · Linguistics · Perception · Second-language acquisition · Theoretical linguistics · Computer Science · EFL/ESL Teaching and Learning · Mathematics · Multilingual Education and Policy · Psychology · Second Language Learning and Teaching · Artificial Intelligence
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| Unique citing works | 9 |
|---|---|
| Citations per year | 1,13 |
| Citation span | 2018 - 2025 (8) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 9 |