지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.13 No.1
- 발행연도
- 2024.2
- 수록면
- 51 - 60 (10page)
- DOI
- 10.5573/IEIESPC.2024.13.1.51
이용수
초록· 키워드
오류제보하기
The “explosive” development of information technology and the acceleration of teaching reform have made it difficult to adapt the traditional “cramming” English teaching method to the development of education and affect the improvement of students’ comprehensive quality and the international innovation of teaching mode. Therefore, based on the current situation and characteristics of English teaching, the research proposes that the dynamic prediction of teaching information will be realized with the help of an improved radial basis function neural network algorithm based on mobile technology, i.e., the support and confidence in association rules will be used as the basis for RBF algorithm to select the data center, and a mobile intelligent teaching system will be built to promote the transformation of teaching mode. The results showed that the overall sample output error of the improved RBF algorithm was less than 3%. The generalization performance was good. The classification accuracy of teaching data was more than 93%, and the teaching correlation was basically more than 0.15. The system platform can effectively extract the characteristic factors of teaching importance, which makes the score of teachers’ and students’ dissatisfaction with the effect of English teaching decrease by more than 55%. The above results showed that the teaching system supported by mobile technology can effectively realize the dynamic management of English teaching activities and provide some technical and theoretical support for teachers to adjust their teaching plans.
목차
Abstract
1. Introduction
2. Related Works
3. Application of Mobile Technology in The Construction of International Model of English Teaching
4. Research on The Application Effect of Mobile Technology in The Innovation of International Mode of English Teaching
5. Conclusion
Reference
참고문헌 (18)
참고문헌 신청
S. Shahrol, et al. “A Systematic Literature Review on Teaching and Learning English Using Mobile Technology”. International Journal of Information and Education Technology, 2020, vol. 10(9), pp. 709-714. Article (CrossRef Link)
H. Meng, F. Yuan, T. H. Yan, et al. “Indoor Positioning of RBF Neural Network Based on Improved Fast Clustering Algorithm Combined with LM Algorithm”. IEEE Access, 2018, vol. 99, pp. 1-1. Article (CrossRef Link)
R. Cavoretto, and A. D. Rossi, “An Adaptive Algorithm Based on Rbf-Pu Collocation for Solving 2d Poisson Problems”. Rendiconti del Seminario Matematico, 2018, vol. 76(2), pp. 77-86. Article (CrossRef Link)
I. K. Suartama, et al. “Development of an Instructional Design Model for Mobile Blended Learning in Higher Education”. International Journal of Emerging Technologies in Learning (iJET), 2019, vol. 14(16), pp. 4-22. Article (CrossRef Link)
Y. Hao, et al. “An evaluative study of a mobile application for middle school students struggling with English vocabulary learning”. Computers in Human Behavior, 2019, vol. 95, pp. 208-216. Article (CrossRef Link)
H. Meng, F. Yuan, T. H. Yan, et al. “Indoor Positioning of RBF Neural Network Based on Improved Fast Clustering Algorithm Combined with LM Algorithm”. IEEE Access, 2018, vol. 99, pp. 1-1. Article (CrossRef Link)
R. Cavoretto, and A. D. Rossi, “An Adaptive Algorithm Based on Rbf-Pu Collocation for Solving 2d Poisson Problems”. Rendiconti del Seminario Matematico, 2018, vol. 76(2), pp. 77-86. Article (CrossRef Link)
I. K. Suartama, et al. “Development of an Instructional Design Model for Mobile Blended Learning in Higher Education”. International Journal of Emerging Technologies in Learning (iJET), 2019, vol. 14(16), pp. 4-22. Article (CrossRef Link)
Y. Hao, et al. “An evaluative study of a mobile application for middle school students struggling with English vocabulary learning”. Computers in Human Behavior, 2019, vol. 95, pp. 208-216. Article (CrossRef Link)
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