Error Analysis and Artificial Intelligence: Exploring Error Monitoring and Error Treatment Possibilities in EFL

Manuel Macías Borrego

Autores/as

Manuel Macías Borrego Universidad Rey Juan Carlos

Palabras clave:

Artificial Intelligence, Error Analysis, EFL, error remediation, feedback

Resumen

This paper endeavors to investigate the potential synergy between new Artificial Intelligence (AI) tools and Error Analysis in, primarily, serving as a tool to enhance the process of error analysis aiming at error remediation (avoiding error fossilisation) while, secondly, enhancing the assessment methods employed by teachers of English as a Foreign Language (EFL) within the context of a university course targeting B2 proficiency level, as per the Common European Framework of Reference for Languages (CEFR). To gauge the efficacy of this interdisciplinary integration, a comparative corpus study was devised, wherein half of the student productions underwent assessment utilizing AI tools. The findings of this study revealed noteworthy insights, indicating that the incorporation of AI technologies offers novel perspectives that effectively facilitate EFL learners in crafting more proficient written texts. Notable observations include a significant reduction in error occurrences, evident in over 70% of cases, along with an enhanced application of grammatical rules observed in over 75% of instances.

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