The integration of Natural Language Processing (NLP) technologies can support and advance second language acquisition pedagogies by enabling personalized feedback, automating error correction, enhancing pronunciation through speech analysis, and facilitating real-time language interaction. These tools promote learner autonomy, increase engagement, and provide data-driven insights for teachers to tailor instruction effectively.

Hello, there is a host of research papers in this respect. As Muhammad Amjad Bashir states, scholars claim that teaching can be personalised and instructors can dedicate more time to student-teacher relationship, as AI can perform routine tasks (such as admin tasks); knowledge and materials sharedness among teachers. Additionally, students can learn at their own pace and monitor their progress. However, there are also several drawbacks: inequal access to technologies (either country- or region-based); biases, confidentiality and privacy issues (names and details of students are inputted in AI platforms, for example); dependency (either from students or from teachers); reduced creativity. Some scholars also say that AI does not help memorising things. Scholars also claim that there has been a shift in teaching, where educators have become coaches or mediators and lost their role as pure instructors. Also, relationships have changed into a teacher-AI-student than teacher-student paradigm.

NLP supports second language learning by providing instant feedback, personalized instruction, and interactive language practice. I believe it can assist individual learners and guide them through the learning process. However, it cannot replace the benefits of a classroom environment or fully substitute for teachers.