AI-Driven Personalized Instruction and Competency Development in Bilingual Accounting A Practice-Based Study
Abstract
an AI-personalized framework with four modules: profiling, tiering, recommendation, evaluation. A one-semester quasi-experiment with 92
majors shows the AI group significantly outperformed controls in pre-class completion (82% vs. 56%), bilingual accuracy (85.2% vs. 76.3%),
and case quality, while reducing grading load. Grounded in Vygotsky's ZPD and self-regulated learning theory, the model balances knowledge
delivery and competency cultivation. Barriers and enablers are discussed, offering an evidence-based upgrade pathway for bilingual accounting education.
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DOI: http://dx.doi.org/10.70711/wef.v4i4.9902
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