Research on Optimizing Teaching Resource Allocation Strategies with Machine Learning Models for Intelligent English Teaching Systems
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| Vydáno v: | Applied Mathematics and Nonlinear Sciences vol. 10, no. 1 (2025) |
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| Hlavní autor: | |
| Vydáno: |
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
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| Témata: | |
| On-line přístup: | Citation/Abstract Full Text - PDF |
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| 001 | 3191229649 | ||
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| 022 | |a 2444-8656 | ||
| 024 | 7 | |a 10.2478/amns-2025-0706 |2 doi | |
| 035 | |a 3191229649 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Lv, Wenjing |u Faculty of Humanities, Gansu Agricultural University, Lanzhou, Gansu, 730070, China | |
| 245 | 1 | |a Research on Optimizing Teaching Resource Allocation Strategies with Machine Learning Models for Intelligent English Teaching Systems | |
| 260 | |b De Gruyter Brill Sp. z o.o., Paradigm Publishing Services |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The arrangement of college courses and resource allocation has become a serious problem facing college teaching, and only through reasonable scheduling can the rationalization of course arrangement and the maximization of the utilization rate of educational resources be realized. In this paper, according to the principle of network teaching resource allocation, we propose network teaching resource allocation based on multi-rate cognition, calculate the user delay under different modes, and in the process of optimizing the allocation of network teaching resources, model the resource scheduling problem of network teaching resource allocation as a non-linear optimization problem, and use greedy algorithm to solve the problem in a globally optimal way. The mathematical model of automatic scheduling system is established, the backtracking algorithm is added, the automatic scheduling system is designed, and the resource allocation optimization results of the automatic scheduling system are analyzed by combining simulation experiments and case studies. The algorithm in this paper prioritizes the allocation of classrooms on the lower floors by increasing the number of time slots used in the classrooms on the lower floors. The number of time slots used in the classrooms on floors 1 and 2 changes from 3180 to 3206 before optimization, and the number of time slots used in the classrooms on floors 5 and 6 changes from 1737 to 1690 before optimization. Comparing the effects of the conventional scheduling method and this paper’s scheduling system on the English academic performance, the English academic performance pass rate of the students who used the greedy based algorithm-based English teaching resource optimization system, the passing rate of English is 90%, which is 36% higher than the conventional system. After the rational scheduling of the system and the reallocation of English teaching resources, there is a certain impact on the improvement of students’ English performance. | |
| 653 | |a Scheduling | ||
| 653 | |a Classrooms | ||
| 653 | |a Algorithms | ||
| 653 | |a Academic achievement | ||
| 653 | |a Optimization | ||
| 773 | 0 | |t Applied Mathematics and Nonlinear Sciences |g vol. 10, no. 1 (2025) | |
| 786 | 0 | |d ProQuest |t Publicly Available Content Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3191229649/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3191229649/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |