A focused review of artificial intelligence in education: Evolution and challenges
Erkan Acar, Youmna Deiri, Fatih Yigit
Abstract
The given systematic analysis reviews 40 articles published in 2015-2025 to discuss the examine the evolution, applications, and challenges of artificial intelligence (AI) in education, specifically in the bi/multilingual learning settings. The review relies on empirical and theoretical study and provides identification of the three major domains, including personalized learning, intelligent tutoring systems and chatbots, and automated assessment. The research results demonstrate that AI improves student engagement and learning performance and teaching efficiency due to the adaptive feedback and real-time analytics, particularly when used to support multiliteracy language learning practices. There are, however, major issues of concern that data privacy, algorithmic bias, unequal access, and the disappearance of relational and cultural facets of teaching and learning. The review highlights the empathy gap in the AI tools and demands the incorporation of AI into the mainstream in an inclusive, ethically based and linguistically responsive manner. It promotes the change in automation to intelligence augmentation and places AI at the service of educators offloading them with fair, human-centered, and AI assistive tools in multilingual learning students in English-dominant settings. The implications refer to the imperative to provide strong governance structures, human centered training of teachers in which AI serves as an addition to intelligence and not intelligence, and inclusive design to provide equitable and effective AI integration and to provide a balanced innovation with a focus on human-centered learning.