Influence of Age on Second Language Acquisition: A Big Data Analysis in English Teaching
Guardado en:
| Publicado en: | International Journal of Web-Based Learning and Teaching Technologies vol. 20, no. 1 (2025), p. 1-25 |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Publicado: |
IGI Global
|
| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text - PDF |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3164854869 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1548-1093 | ||
| 022 | |a 1548-1107 | ||
| 024 | 7 | |a 10.4018/IJWLTT.368222 |2 doi | |
| 035 | |a 3164854869 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Liu, Wei |u Sichuan College of Architectural Technology, China | |
| 245 | 1 | |a Influence of Age on Second Language Acquisition: A Big Data Analysis in English Teaching | |
| 260 | |b IGI Global |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Age is one of the important factors affecting individual differences in second language acquisition. The development of cognitive ability also has certain influence on second language acquisition, depending on whether this influence is positive or negative. This paper discusses the educational significance of the age factor in English teaching language learning to second language learners based on BD(big data) environment, optimizes the teaching mode of English wisdom class and designs it in detail according to different classes, combining with the related theories of wisdom class and its teaching mode research. Parallelize the improved KNN(k nearest neighbour) algorithm, so that the algorithm can well adapt to the data processing model of cloud computing platform. After parallelization, the improved KNN algorithm runs on the Spark cloud platform, which can quickly improve the efficiency of the algorithm by about 10.3%. The improved KNN algorithm greatly improves the efficiency of the algorithm on the premise of ensuring the classification accuracy of the algorithm. | |
| 653 | |a Age | ||
| 653 | |a Algorithms | ||
| 653 | |a Classification | ||
| 653 | |a Cognitive development | ||
| 653 | |a Data analysis | ||
| 653 | |a Big Data | ||
| 653 | |a Data processing | ||
| 653 | |a Teaching | ||
| 653 | |a Language acquisition | ||
| 653 | |a K-nearest neighbors algorithm | ||
| 653 | |a Parallel processing | ||
| 653 | |a Individual differences | ||
| 653 | |a Age factors | ||
| 653 | |a English language | ||
| 653 | |a English as a second language learning | ||
| 653 | |a Acquisition | ||
| 653 | |a Wisdom | ||
| 653 | |a Cognitive functioning | ||
| 653 | |a Second language learning | ||
| 653 | |a Cloud computing | ||
| 653 | |a Cognitive ability | ||
| 653 | |a Medium of instruction | ||
| 653 | |a Language | ||
| 653 | |a Efficiency | ||
| 653 | |a Language of Instruction | ||
| 700 | 1 | |a Wang, Yingxue |u Weifang University, China | |
| 773 | 0 | |t International Journal of Web-Based Learning and Teaching Technologies |g vol. 20, no. 1 (2025), p. 1-25 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3164854869/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3164854869/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |