Abstract
In Second Language Acquisition (SLA), the exposure of learners to authentic material is an important learning step, but the use of raw text may pose problems, because the information that the learner should be focusing on may be overlooked. In this paper, we present SMILLE for Portuguese, a system for detecting pedagogically relevant grammatical structures in raw texts. SMILLE’s rules for recognizing grammatical structures were evaluated in random sentences from three different genres, achieving an overall precision of 84%. The automatic recognition of pedagogically relevant grammatical structures can help teachers and course coordinators to better inform the choice of texts to be used in language courses, while also allowing for the analysis of grammar profiles for SLA. As a case study, we used SMILLE to analyze pedagogical material used in a Portuguese as foreign language course and to observe how the predominance of grammatical content in the texts is related to the described grammatical focus of the language levels.
Keywords
- Second Language Acquisition
- Grammatical structures
- Natural Language Processing
- Grammatical parsing for Portuguese
Supported by the Walloon Region (Projects BEWARE 1510637 and 1610378) and Altissia International.
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Notes
- 1.
The system is available for testing at https://cental.uclouvain.be/resources/smalla_smille/smille/.
- 2.
Our grammatical structures were based on the course developed by Altissia International (www.altissia.com).
- 3.
SMILLE for Portuguese makes use of the PassPort system [21].
- 4.
We do not present here the 71 rules because many of the grammatical structures are divided along the CEFR levels, presenting some basic content in lower levels and reinforcing them in higher levels, and others are divided in different categories, such as the verb tenses, the comparative forms, the types of adverbs, etc.
- 5.
Selected romances from www.dominiopublico.gov.br.
- 6.
This corpus was compiled in the scope of the project PorPopular (www.ufrgs.br/textecc/porlexbras/porpopular/index.php).
- 7.
Sentences with more than one instance of the selected structure were evaluated only based on the first instance.
- 8.
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Zilio, L., Wilkens, R., Fairon, C. (2018). SMILLE for Portuguese: Annotation and Analysis of Grammatical Structures in a Pedagogical Context. In: , et al. Computational Processing of the Portuguese Language. PROPOR 2018. Lecture Notes in Computer Science(), vol 11122. Springer, Cham. https://doi.org/10.1007/978-3-319-99722-3_2
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