Analysis of Lexical Competence in Spanish as a Foreign Language (ELE) with Gemini
AI-Based Automated Feedback
DOI:
https://doi.org/10.1590/1983-3652.2026.64168Keywords:
Spanish as a foreign language, Written expression, Vocabulary, Natural language processing, Artificial intelligenceAbstract
Vocabulary is an essential component in the development of written proficiency in foreign languages. This study examines the lexical ability of a group of students learning Spanish as a Foreign Language (ELE) at a language centre within a Spanish university. The aim of the study is to determine whether lexical knowledge enables students to be assessed according to the CEFR. To this end, the Gemini language model is used; it is asked to assess the students’ proficiency levels after being provided with lexical information from their texts extracted using the Textflow tool, and is also asked to provide feedback, with the aim of guiding students towards reaching the next level. Finally, Gemini’s ability to level students correctly is evaluated, and the educational quality of its feedback is analysed. In short, this study aims to assess the potential of large language models (LLMs) as a support for teaching and self-directed learning.
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