Artificial Intelligence and Language Processing in EFL Learning: A Neurolinguistic Perspective

Abstract

Background: Artificial Intelligence (AI) has become increasingly integrated into language education and offers new opportunities to support language learning and cognitive development. From a neurolinguistic perspective, AI-assisted learning may influence cognitive processes involved in language comprehension and acquisition.

Aim: This study aims to investigate the effects of AI-based language learning systems on language processing among EFL learners from a neurolinguistic perspective.

Method: A quasi-experimental research design was employed involving 60 EFL university students divided into an experimental group and a control group. The experimental group utilized AI-based language learning systems for eight weeks, while the control group received conventional instruction. Data were collected through language processing tests, reading comprehension assessments, and learner perception questionnaires. Statistical analyses were conducted using descriptive statistics and independent samples t-tests.

Results: The findings revealed that learners exposed to AI-assisted language learning demonstrated significantly higher performance in language processing and reading comprehension tasks than those receiving traditional instruction. Furthermore, participants reported positive perceptions regarding the effectiveness, adaptability, and engagement provided by AI-based learning environments.

Conclusion: AI-assisted language learning contributes positively to language processing by facilitating attention, feedback, and repeated exposure to linguistic input. From a neurolinguistic perspective, AI technologies appear to support cognitive processes associated with language acquisition and comprehension, highlighting their potential role in future EFL instruction.