{"title":"人工智能技术助力高校英语精准教学改革研究","authors":"Lirong Wang, Junli Yu","doi":"10.2478/amns-2024-0627","DOIUrl":null,"url":null,"abstract":"\n The article analyzes the precise teaching reform by applying artificial intelligence technology in English teaching in colleges and universities to improve teaching efficiency and student learning effect. The study establishes an English teaching model based on learner profiling, using artificial intelligence technology for student data analysis to achieve personalized customization of teaching content. Through empirical analysis, this study found that the experimental class adopting this teaching model significantly improved classroom interaction, learner class profile, and English performance. The average score of English assessment of students in the practical class increased from 55.5465 to 78.7267, and the passing rate also increased significantly. In addition, the teaching mode can effectively reduce the degree of dispersion of students’ performance and reduce the performance differences among students. The application of artificial intelligence technology in English teaching in colleges and universities can effectively promote students’ learning interest and performance improvement, providing a new direction for reforming English teaching in colleges and universities.","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":"139 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on the Reform of English Precision Teaching in Colleges and Universities Facilitated by Artificial Intelligence Technology\",\"authors\":\"Lirong Wang, Junli Yu\",\"doi\":\"10.2478/amns-2024-0627\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n The article analyzes the precise teaching reform by applying artificial intelligence technology in English teaching in colleges and universities to improve teaching efficiency and student learning effect. The study establishes an English teaching model based on learner profiling, using artificial intelligence technology for student data analysis to achieve personalized customization of teaching content. Through empirical analysis, this study found that the experimental class adopting this teaching model significantly improved classroom interaction, learner class profile, and English performance. The average score of English assessment of students in the practical class increased from 55.5465 to 78.7267, and the passing rate also increased significantly. In addition, the teaching mode can effectively reduce the degree of dispersion of students’ performance and reduce the performance differences among students. The application of artificial intelligence technology in English teaching in colleges and universities can effectively promote students’ learning interest and performance improvement, providing a new direction for reforming English teaching in colleges and universities.\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":\"139 1\",\"pages\":\"\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/amns-2024-0627\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/amns-2024-0627","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Research on the Reform of English Precision Teaching in Colleges and Universities Facilitated by Artificial Intelligence Technology
The article analyzes the precise teaching reform by applying artificial intelligence technology in English teaching in colleges and universities to improve teaching efficiency and student learning effect. The study establishes an English teaching model based on learner profiling, using artificial intelligence technology for student data analysis to achieve personalized customization of teaching content. Through empirical analysis, this study found that the experimental class adopting this teaching model significantly improved classroom interaction, learner class profile, and English performance. The average score of English assessment of students in the practical class increased from 55.5465 to 78.7267, and the passing rate also increased significantly. In addition, the teaching mode can effectively reduce the degree of dispersion of students’ performance and reduce the performance differences among students. The application of artificial intelligence technology in English teaching in colleges and universities can effectively promote students’ learning interest and performance improvement, providing a new direction for reforming English teaching in colleges and universities.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
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