Análisis comparativo de las estrategias de retroalimentación de docentes y de ChatGPT en la enseñanza de la escritura en español como lengua extranjera

• Luan, Yun ^[1]
  1. [1] Departamento de Español, Universidad Nanjing Tech
• Localización: RILCE: Revista de filología hispánica, ISSN 0213-2370, Vol. 42, Nº 2, 2026, págs. 589-614
• Idioma: español
• DOI: 10.15581/008.42.2.588-614
• Títulos paralelos:
  • A Comparative Analysis of Feedback Strategies by Instructors and ChatGPT in Teaching Writing in Spanish as a Second or Foreign Language
• Enlaces
  • Texto completo
• Resumen
  • español

    Este estudio analiza comparativamente las estrategias de retroalimentación escrita empleadas por docentes y ChatGPT en la enseñanza de la escritura en español como lengua extranjera (ELE). Basándose en marcos teóricos como la teoría sociocultural y la hipótesis de percepción consciente, analiza 35 composiciones de estudiantes de nivel b2, clasificadas según categorías de estructura, contenido y lenguaje. La investigación combina un análisis cuantitativo con uno cualitativo mediante Teoría Fundamentada y NVIVO 14. Los resultados muestran que ChatGPT genera un mayor número de comentarios, especialmente correcciones explícitas y observaciones estructurales, destacando por su eficiencia técnica. Los docentes, en cambio, ofrecen retroalimentación equilibrada, priorizando aspectos lingüísticos, integrando matices culturales para contextos hispanohablantes y estrategias afectivas/formativas que fomentan autonomía y motivación. Se concluye que un modelo híbrido, combinando la eficiencia de ChatGPT en tareas preliminares con la profundidad contextual de los docentes, optimizará el aprendizaje de la escritura.

  • English

    This study conducts a comparative analysis of the written feedback strategies employed by teachers and ChatGPT in the teaching of writing in Spanish as a foreign language (SFL). Drawing on theoretical frameworks such as sociocultural theory and the noticing hypothesis, it examines 35 compositions from B2-level students, classified according to categories of structure, content, and language. The research combines quantitative analysis with qualitative analysis using Grounded Theory and NVIVO 14. The results show that ChatGPT generates a greater number of comments, particularly explicit corrections and structural observations, standing out for its technical efficiency. Teachers, in contrast, provide more balanced feedback, prioritizing linguistic aspects, integrating cultural nuances essential for Spanish-speaking contexts, and employing affective/formative strategies that foster student autonomy and motivation. It is concluded that a hybrid model, combining ChatGPT’s efficiency in preliminary tasks with teachers’ contextual depth, will optimize writing learning.

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