PERSONALIZED LEARNING THROUGH AI: GLOBAL EXPERIENCES AND STUDENT-CENTERED INNOVATIONS

The thought of tailoring education to each learner’s needs has always intrigued us, but recent advancements in AI have taken that concept to new heights. Between 2019 and 2025, researchers working in Canada, the USA, Japan, and Ukraine have tried different versions of AI-powered personalization. Their findings suggest that new paths are opening up, but I also sense caution in how they address ethics and equitable access. Canada’s initiatives stand out for linking AI with multicultural education. Henry Johnston, in his research, proposes that AI can promote what he calls “dynamic multiculturalism,” ensuring that cultural and linguistic nuances don’t get overlooked in standardized curricula [4, pp. 34-38]. One of the more interesting parts of Johnston’s vision is the plan for AI systems to analyze cultural context before adjusting educational content. He also imagines virtual agents simulating cross-cultural encounters, which might engage students who’ve rarely seen their perspectives validated in the classroom. While I’m personally intrigued by the emphasis on equity, Johnston warns that humans must stay in the loop – no AI system can capture Canada’s diverse identities without careful oversight [4, pp. 34-38].