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Instructor ability to detect machine translation in L2 Spanish writing
Datos Bibliográficos
| ID | 8936293 |
|---|---|
| Autores | Luciane Maimone (0000-0003-0762-8450, Missouri State University Springfield Missouri USA, autor de correspondencia), Jason Jolley (0009-0003-7584-5016, Missouri State University Springfield Missouri USA) |
| Año | 2023 |
| Volumen | 56 |
| Número | 3 |
| Páginas | 627-644 |
| Fecha de publicación | 2023-05-09 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Foreign Language Annals (JOURNAL) |
| Identificadores de la revista | ISSN: 0015-718X • E-ISSN: 1944-9720 |
| Editorial | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/flan.12690 |
| OpenAlex | W4376114917 |
| Idioma | EN |
| Citas recibidas | 3 |
| Referencias citadas | 31 |
This article reports the results of an empirical study designed to determine the degree to which college instructors of Spanish can distinguish between machine translation (MT) and non‐MT writing samples produced by second language (L2) learners of Spanish in an intermediate‐level writing course. We also investigated relationships between detection accuracy rates, instructor teaching experience, and text type (narrative or argumentative), as well as signs instructors consider indicators of both kinds of writing. Results demonstrated that instructors were able to distinguish MT from non‐MT writing with a high degree of accuracy by relying on a broad array of indicators. However, neither text type difference nor instructor experience related significantly to detection ability. These findings have practical implications for the L2 classroom with regard to instructor response to MT use and the integration of MT tools to support L2 writing development
Argumentative · Empirical research · Linguistics · Machine translation · Mathematics education · Narrative · Natural language processing · Second language · Second language writing · Computer Science · Discourse Analysis in Language Studies · Mathematics · Psychology · Second Language Acquisition and Learning · Text Readability and Simplification
| Obras citantes distintas | 3 |
|---|---|
| Citas por año | 1,5 |
| Intervalo de citas | 2024 - 2026 (3) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 3 |