Aug 2026· Review of Artificial Intelligence in Education· Vol 7, pp. e01120· 0 citations· 15 references
TL;DR
The successful integration of AI in multilingual contexts depends on a shift from content generation to pedagogical scaffolding, and designers must prioritize "Human-in-the-loop" models that balance computational efficiency with human oversight to provide the emotional engagement and cultural authenticity that AI currently lacks.
Abstract
Background: While AI is promoted as a transformative force in education through adaptive platforms and real-time feedback, its implementation for multilingual learners often risks reinforcing educational inequalities. Current scholarship cautions that automated systems still struggle with cultural nuances and idiomatic expressions, highlighting the need for design approaches that foreground equity and human agency.
Objective: This systematic review examines 10 core studies through the lens of the ISO 9241-210 Human-Centered Design framework. The objective is to analyze how AI-based educational technologies are designed and evaluated to support multilingual learners, specifically focusing on the "Context of Use," "User Requirements," "Design Solutions," and "Evaluation" phases.
Methods: Through a systematic search of four databases and subsequent snowballing, 10 core papers were selected to analyze how AI tools address linguistic and cultural diversity.
Results: Across the reviewed studies, reported improvements ranged from quantitative gains, including a 25–31% increase in literacy and vocabulary retention and a rise in academic success rates up to 77.8%. Furthermore, AI-driven systems, when aligned with HCD principles, were associated with saving educators up to 41% of their time. However, evaluations revealed critical 'socio-technical paradoxes': students faced a "trade-off" where they reverted to English-centric prompting due to algorithmic bias in low-resource languages, and risks of "metacognitive laziness" emerged from over-reliance on automated tools.
Conclusion: The successful integration of AI in multilingual contexts depends on a shift from content generation to pedagogical scaffolding. Designers must prioritize "Human-in-the-loop" models that balance computational efficiency with human oversight to provide the emotional engagement and cultural authenticity that AI currently lacks.
A conceptual framework offering AI designers, teacher educators, and policymakers a psychologically grounded, empirically mapped, and internationally contextualised basis for developing AI-supported educational systems that advance equity, learner engagement, and meaningful educational transformation is proposed.
Arpana Koul· Review of Artificial Intelli...· 0 citations
Artificial Intelligence (AI) is rapidly transforming education globally, yet its potential to foster inclusive learning in South Asia remains under-examined. This study explores how Universal Design for Learning (UDL) and Human-Centred Artificial Intelligence (HCAI) can be jointly leveraged to reduce access disparities and support learner diversity in the region. UDL promotes curricular design that anticipates learner variability, while HCAI emphasizes AI systems that are transparent, ethical, and responsive to human needs, particularly in low-resource and high-diversity settings. Using secondary data, this paper conducts a critical review of recent scholarship on inclusive pedagogy, AI in education, and South Asian educational ecosystems. The review finds that UDL-HCAI integration presents promising avenues for inclusion, including assistive technologies, multilingual interfaces, adaptive content delivery, and teacher-guided AI applications. However, persistent challenges such as infrastructure gaps, uneven digital literacy, and insufficient teacher training remain significant obstacles to equitable adoption. The study concludes that meaningful implementation requires ethical AI design, systemic support for educators, and participatory co-design with affected learner groups. It recommends piloting integrated UDL-HCAI models in real South Asian classroom contexts to assess their practical and longitudinal impact on inclusion and learning outcomes.
Yohan Perera, Sachithra Jayavindi· Sri Lanka Journal of Develop...· 0 citations
A systematic review of peer-reviewed studies published between 2015 and 2024 concludes that while tools such as generative artificial intelligence, intelligent tutoring systems, virtual and augmented reality, and predictive analytics are increasingly present, their adoption is concentrated in specific areas, particularly problem-solving, simulation, and assessment.
Firas Almasri· International journal of tec...· 0 citations
It is argued that students' needs matter on their own, the field should start from what students need when deciding how to use AI in design education, and good educational frameworks should be anchored in the learner, not driven by technology.
This study explored the emerging trends, current practices, challenges, and pedagogical implications of Artificial Intelligence in Education (AIEd) in the Division of Oroquieta City during the School Year 2025- 2026. Employing a descriptive qualitative research design, data were gathered from purposively selected public secondary school teachers through an adapted questionnaire, interviews, and document analysis. The findings revealed that AI is increasingly used as a teaching and learning support tool for lesson planning, assessment, student engagement, and administrative tasks, contributing to improved efficiency and personalized learning. However, challenges such as limited infrastructure, unequal access to technology, capacity and skills gaps, ethical and academic integrity concerns, and resistance to AI adoption persist. The study further indicated that AI integration transforms the teacher's role toward facilitation and mentoring while highlighting the need to strengthen learner-centered approaches, critical thinking, and digital literacy. Overall, the study underscores the importance of institutional readiness, professional development, and clear policy frameworks to ensure ethical, equitable, and sustainable AI integration in education.
Maria Benjie Ann M. Cabasag· Journal of Educational Resea...· 0 citations
