AI IN THE CLASSROOM: EVALUATING THE EFFECTIVENESS OF INTELLIGENT TUTORING SYSTEMS FOR MULTILINGUAL LEARNERS IN SECONDARY EDUCATION
DOI:
https://doi.org/10.63125/gcq1qr39Keywords:
Intelligent Tutoring Systems, multilingual learners, adaptive learning, learner modeling, cultural responsiveness, systematic literature review, multimodal instructionAbstract
This study presents a systematic literature review examining the role, design, and effectiveness of Intelligent Tutoring Systems in supporting multilingual learners in secondary education. A total of 110 peer reviewed studies were analysed to identify the key functional components, pedagogical strategies, and adaptive features that contribute to the success of these systems in linguistically diverse classrooms. The review explores four interrelated components of Intelligent Tutoring Systems including learner modelling, domain knowledge, pedagogical strategy engines, and user interaction or interface design. Particular emphasis is placed on how these components integrate adaptive personalization, multimodal instructional resources, and culturally responsive frameworks to address both content mastery and language acquisition. Findings reveal that systems which employ sophisticated learner models such as Bayesian Knowledge Tracing and Performance Factor Analysis combined with linguistically sensitive feedback and multimodal delivery significantly enhance comprehension, retention, learner confidence, and engagement. Furthermore, culturally relevant domain knowledge and inclusive interface design were found to reduce barriers caused by language differences, thereby fostering an equitable learning environment. The study underscores the importance of teacher training, infrastructure readiness, and ethical data governance to ensure effective and responsible implementation. While emerging technologies such as generative artificial intelligence present opportunities for deeper personalization and more natural interaction, careful attention must be given to preventing bias, safeguarding privacy, and preserving cultural diversity. This review contributes to academic discourse and practical application by offering a synthesized framework for designing Intelligent Tutoring Systems that are inclusive, adaptive, and pedagogically grounded, ultimately supporting both academic success and language development for multilingual learners.