NLP techniques have been integrated into Intelligent Tutoring Systems (ITS) to provide personalized language instruction. These systems are able to analyze learner language, identify errors, and provide targeted feedback and guidance to students. NLP helps in detecting grammatical errors, vocabulary misuse, and other language-related issues, enabling learners to receive immediate and tailored support. These systems go far beyond traditional spelling checkers, since they take into account several factors regarding the context and instructions of the task assessed. NLP models, such as language models based on deep learning architectures, are also able to provide assistance to the student. 

As a consequence, a learner centered system is created in which learners can study anytime, anywhere independently, at the same time they are guided and helped by intelligent systems. It is worth mentioning that these systems by themselves might be ineffective regarding learner’s linguistic development. Not taking into account factors such as motivation, learning methodologies, applied linguistics research or standardized systems for language assessment, the puzzle would be incomplete. That is why language and teaching specialists are joining forces with software engineers in order to build solid e-learning scenarios for students to take advantage of the expertise of teachers and linguists, and advanced AI.