| Artificial intelligence (AI)-driven system for assessing impact of bilingual education on English language proficiency using natural language processing, has machine learning engine that correlates language proficiency with academic and behavioral performance | |
| 2025-03-28 | |
| 专利权人 | RAJASEKAR T (RAJA-Individual) ; ARUN G (ARUN-Individual) ; SABAREEDHARAN M (SABA-Individual) ; SUBBU N M (SUBB-Individual) ; ABIRAMI T (ABIR-Individual) ; NAIDU G T (NAID-Individual) ; JAYAKUMAR P (JAYA-Individual) ; ZABEEN F S (ZABE-Individual) ; PARAMAGURU E (PARA-Individual) ; MEENU R (MEEN-Individual) ; HARRIS M N (HARR-Individual) ; DHURESHAVAR K (DHUR-Individual) |
| 申请日期 | 2025-03-28 |
| 专利号 | IN202541029787-A |
| 成果简介 | NOVELTY - The system has a language assessment engine that analyzes written and spoken English samples to measure fluency, grammar, and vocabulary. An adaptive student profiling system incorporates demographic, academic and socio-emotional data. A real-time dashboard provides educators with individualized progress tracking and instructional recommendations. A predictive analytics module forecasts English language acquisition outcomes based on instructional model and student profile. A comparative analysis tool enables evaluation of multiple bilingual education frameworks. An automated reporting interface is used for program accountability and compliance with educational standards. A machine learning engine correlates language proficiency with academic and behavioral performance. An adaptive student profiling module tracks language development based on personal variables like primary language, years in the program and socio-emotional indicators. USE - Artificial intelligence (AI)-driven system for assessing impact of bilingual education on English language proficiency using natural language processing. ADVANTAGE - The system enables evidence-based optimization of bilingual education programs and supports policy compliance and equitable language development for diverse learners. system and method utilizing artificial intelligence and data analytics to evaluate and enhance the impact of bilingual education programs on English language proficiency. The system supports educators, researchers and policy makers in measuring and improving student outcomes in bilingual and dual-language environments across diverse linguistic backgrounds. The system creates an intelligent system that continuously evaluates the effect of bilingual education on English proficiency using multi-dimensional data analysis, enables individualized tracking of students English acquisition, incorporating factors such as age, grade level, native language, and language exposure, allows comparison across different bilingual education models and identify best practices for English language development and correlates English proficiency improvements with broader academic performance, social integration, and long-term educational outcomes. |
| IPC 分类号 | G06Q-050/20 ; G09B-017/00 ; G09B-019/06 ; G09B-005/06 ; G09B-007/02 |
| 国家 | 印度 |
| 专业领域 | 信息技术 |
| 语种 | 英语 |
| 成果类型 | 专利 |
| 文献类型 | 科技成果 |
| 条目标识符 | http://119.78.100.226:8889/handle/3KE4DYBR/13410 |
| 专题 | 中国科学院新疆生态与地理研究所 |
| 作者单位 | 1.RAJASEKAR T (RAJA-Individual) 2.ARUN G (ARUN-Individual) 3.SABAREEDHARAN M (SABA-Individual) 4.SUBBU N M (SUBB-Individual) 5.ABIRAMI T (ABIR-Individual) 6.NAIDU G T (NAID-Individual) 7.JAYAKUMAR P (JAYA-Individual) 8.ZABEEN F S (ZABE-Individual) 9.PARAMAGURU E (PARA-Individual) 10.MEENU R (MEEN-Individual) 11.HARRIS M N (HARR-Individual) 12.DHURESHAVAR K (DHUR-Individual) |
| 推荐引用方式 GB/T 7714 | RAJASEKAR T,ARUN G,SABAREEDHARAN M,et al. Artificial intelligence (AI)-driven system for assessing impact of bilingual education on English language proficiency using natural language processing, has machine learning engine that correlates language proficiency with academic and behavioral performance. IN202541029787-A[P]. 2025. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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