Generating Contexts for ESP Vocabulary Exercises with LLMs
(2024) 13th Workshop on NLP for Computer Assisted Language Learning (NLP4CALL 2024) — Location: Rennes (25.October.2024)
Files
NLP4Call___CATS.pdf
Accepted version
Open Access - Adobe PDF
- 319.18 KB
Details
- Authors
- Abstract
- The current paper addresses the need for language students and teachers to have access to a large number of pedagogically sound contexts for vocabulary acquisition and testing. We investigate the automatic derivation of contexts for a vocabulary list of English for Specific Purposes (ESP). The contexts are generated by contemporary Large Language Models (namely, Mistral-7B-Instruct and Gemini 1.0 Pro) in zero-shot and few-shot settings, or retrieved from a web-crawled repository of domain-relevant websites. The resulting contexts are compared to a professionally crafted reference corpus based on their textual characteristics (length, morphosyntactic, lexico-semantic, and discourse-related). In addition, we annotated the automatically derived contexts regarding their direct applicability, comprehensibility, and domain relevance. The 'Gemini, zero-shot' contexts are rated most highly by human annotators in terms of pedagogical usability, while the 'Mistral, few-shot' contexts are globally closest to the reference based on textual characteristics.
- Affiliations
Citations
Nikolova, I., Bibauw, S., Dumont, A., Stas, F., Watrin, P., & François, T. (2024). Generating Contexts for ESP Vocabulary Exercises with LLMs. Proceedings of the 13th Workshop on NLP for Computer Assisted Language Learning (NLP4CALL 2024). Published. 13th Workshop on NLP for Computer Assisted Language Learning (NLP4CALL 2024), Rennes. https://hdl.handle.net/2078.5/233270