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@article{194474,
        author = {Harshini V S and Lowra Vickuna A and Dr. M. Lavanya},
        title = {ARTIFICIAL INTELLIGENCE IN INCLUSIVE EDUCATION: ASSISTIVE TECHNOLOGIES AND MULTILINGUAL SUPPORT - A RESEARCH OUTLOOK WITH GAPS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {3887-3897},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194474},
        abstract = {Inclusive education seeks to create equal access to education for students with disabilities and those from diverse linguistic backgrounds by providing appropriate learning experiences for all. With improvements in technology (e.g., AI), it is now possible to create personalized learning experiences through adaptive instructional approaches, as well as using assistive technology and multilingual support systems. Presently, machine learning, natural language processing (NLP), speech recognition and neural machine translation have been used to provide assistance to learners who are experiencing sensory, cognitive or language-based challenges. Unfortunately, the majority of existing AI-enabled technologies have been shown to have limited success within low-resourced environments or those that utilize code-switching, they generally have weak multimodal integration, inadequate cultural relevance and are not fully explainable. The goal of this paper is to present the AIM-Inclusive framework, which is designed to enhance the future of inclusive education. AIM-Inclusive combines assistive and multilingual technologies via multimodal fusion, cross-lingual NLP, and culturally-aware adaptations. These technologies will be integrated into a unified framework that is able to provide improved understanding of the learner's state through the use of transformer-based models to integrate speech, text, gesture, and eye-gaze data from a multitude of sources. Another goal of AIM-Inclusive is to use transferable learning and data augmentation techniques to produce improved performance of learners in low-resourced and code-switching contexts. A culturally aware content adaptation module will be incorporated to ensure preservation of the pedagogical intent and contextual meaning, while also providing increased transparency and learner agency through the use of an explainable personalization engine. Longitudinal and mixed-methods assessment studies will be conducted to determine the effectiveness of AIM-Inclusive. Overall, AIM-Inclusive offers an innovative, scalable, and culturally responsive solution that advances the provision of inclusive education by using AI-based technologies.},
        keywords = {Artificial intelligence, Assistive technology, Inclusive education, Machine learning, Natural language processing (NLP)},
        month = {March},
        }