DEVELOPING AI THAT DYNAMICALLY TRANSLATES AND LOCALIZES CONTENT TO SUPPORT MULTICULTURAL LEARNING

Abstract

Globalized education increasingly requires culturally sensitive and multilingual instructional materials to support diverse learners. This study examines the effectiveness of a dynamic AI-based translation and localization system in enhancing multicultural learning experiences. Using a quantitative research design, 200 university students and educators participated in a study evaluating AI-translated content across multiple languages and cultural contexts. Data were collected via surveys measuring perceived content accessibility, learning satisfaction, and cognitive engagement. Multiple regression analysis indicated that perceived accuracy of AI translations (β = .48, p < .001) and cultural appropriateness of localized content (β = .42, p < .001) significantly predicted improvements in learner engagement and satisfaction (R² = .51). The findings suggest that AI systems capable of real-time translation and localization can effectively support multicultural learning and inclusive pedagogy.