Review of personalized language learning systems

TLDR: The authors' review led us to propose a review and classification scheme with two dimensions each with a few sub-elements: language learning dimension and technical dimension, suggesting that language personalization systems may improve by incorporating more complex adaptive learner's model and more complex contextual language learning tasks.

Abstract: This study reviews published scientific literature on personalized language learning systems. The focus is threefold: 1) present a review and categorization framework that can be used to analyze and classify personalized language learning systems, 2) analyze recent work in personalized language learning systems and organize them under the proposed framework, 3) identify current trends, challenges and open research questions in the field. Our review led us to propose a review and classification scheme with two dimensions each with a few sub-elements: language learning dimension and technical dimension. The reviewed articles indicate that recent language personalization systems increasingly introduce Artificial Intelligence and focus on cognitive-based personalization. Findings also suggest that language personalization systems may improve by incorporating more complex adaptive learner's model and more complex contextual language learning tasks.