Reanalyzing L2 preposition learning with Bayesian mixed effects and a pretrained language model
- We use both Bayesian and neural models to dissect a data set of Chinese learners’ pre- and post-interventional responses to two tests measuring their understanding of English prepositions. The results mostly replicate previous findings from frequentist analyses and newly reveal crucial interactions between student ability, task type, and stimulus sentence. Given the sparsity of the data as well as high diversity among learners, the Bayesian method proves most useful; but we also see potential in using language model probabilities as predictors of grammaticality and learnability.
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| Author: | Jakob PrangeGND, Man Ho Ivy Wong |
|---|---|
| URN: | urn:nbn:de:bvb:384-opus4-1176624 |
| Frontdoor URL | https://opus.bibliothek.uni-augsburg.de/opus4/117662 |
| ISBN: | 978-1-959429-72-2OPAC |
| Parent Title (English): | Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (volume 1: long papers), July 9-14, 2023, Toronto, Canada |
| Publisher: | Association for Computational Linguistics (ACL) |
| Place of publication: | Stroudsburg, PA |
| Editor: | Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki |
| Type: | Conference Proceeding |
| Language: | English |
| Year of first Publication: | 2023 |
| Publishing Institution: | Universität Augsburg |
| Release Date: | 2024/12/16 |
| First Page: | 12722 |
| Last Page: | 12736 |
| DOI: | https://doi.org/10.18653/v1/2023.acl-long.712 |
| Institutes: | Fakultät für Angewandte Informatik |
| Fakultät für Angewandte Informatik / Institut für Informatik | |
| Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Computerlinguistik | |
| Dewey Decimal Classification: | 4 Sprache / 40 Sprache / 400 Sprache |
| Licence (German): |  CC-BY 4.0: Creative Commons: Namensnennung |
