This paper examines the integration of data-driven and professionally oriented methods into economicseducation in Uzbekistan. It highlights the importance of analytical, predictive, and English-language competencies inpreparing students for the digital economy. The study combines big data analysis, reality mining, and ESP (Englishfor Specific Purposes) to improve learning outcomes. Experimental group results demonstrated higher performancecompared to control groups, confirming the effectiveness of the proposed approach. The methodology also supportsscalability across other disciplines, promoting broader implementation of differentiated, data-oriented education
| Mualliflar | Rakhimova , Shirin |
|---|---|
| Jurnal | Innovation science and technologiy |
| Nashr sanasi | 2025-11-01 |
| Jild | 1 |
| Son | 11 |
| Til | Ingliz |
| DOI | 10.5281/zenodo.17697034 |
DOI: 10.5281/zenodo.17697034 · Maqolaning asl sahifasi
data collection, deep learning, reality mining, prediction methods, economics education, differentiated learning, ESP (English for Specific Purposes), vocational training
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