Research on Mobile English Learning System Based on iOS

In order to improve the use experience of mobile learning and reduce the response delay caused by the slow positioning of system resources, research on mobile English learning systems based on iOS is proposed. Firstly, the value of realizing mobile learning is objectively analyzed, and the practical...

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Autor principal: Xiaofei Zhen
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Lenguaje:EN
Publicado: Hindawi-Wiley 2021
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Acceso en línea:https://doaj.org/article/3fe00c120fe0408f97b943232fbece9a
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spelling oai:doaj.org-article:3fe00c120fe0408f97b943232fbece9a2021-11-22T01:10:38ZResearch on Mobile English Learning System Based on iOS1939-012210.1155/2021/6336565https://doaj.org/article/3fe00c120fe0408f97b943232fbece9a2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/6336565https://doaj.org/toc/1939-0122In order to improve the use experience of mobile learning and reduce the response delay caused by the slow positioning of system resources, research on mobile English learning systems based on iOS is proposed. Firstly, the value of realizing mobile learning is objectively analyzed, and the practical significance of the research is clarified from the perspectives of social development and learning conditions. On this basis, taking the intelligent client equipped with an iOS operating system as the hardware condition of the system, the system architecture, including data access layer, business logic layer, and presentation layer, is constructed by MVC. In the model module, it is divided into ten difficulty levels by using the frequency of vocabulary, the length of words, and the number of syllables of a single word. The learning resources of the reading class are uniformly represented by the vector space model, and the improved TF-IDF is used to calculate the weight of eigenvalues in the resources. According to the calculation results, the resources are also divided into ten difficulty levels, and the divided resources correspond to their respective databases and use regular expressions to find the learning resources that match the access request. Finally, with the support of the iOS protocol, the feedback mechanism between each module is constructed by Express.js. By analyzing the access requests sent and received by the view, the timely call to the target database resources is realized to improve the response rate of the system. The test results show that the function of the designed system can be realized stably, and the module response delay time is stable within 1s; under the ideal network environment, the buffer delay is in the range of 0.4–0.6 s, and the loading delay is no more than 1.8 s when the network speed is 3 Mpbs, which has a good user experience.Xiaofei ZhenHindawi-WileyarticleTechnology (General)T1-995Science (General)Q1-390ENSecurity and Communication Networks, Vol 2021 (2021)
institution DOAJ
collection DOAJ
language EN
topic Technology (General)
T1-995
Science (General)
Q1-390
spellingShingle Technology (General)
T1-995
Science (General)
Q1-390
Xiaofei Zhen
Research on Mobile English Learning System Based on iOS
description In order to improve the use experience of mobile learning and reduce the response delay caused by the slow positioning of system resources, research on mobile English learning systems based on iOS is proposed. Firstly, the value of realizing mobile learning is objectively analyzed, and the practical significance of the research is clarified from the perspectives of social development and learning conditions. On this basis, taking the intelligent client equipped with an iOS operating system as the hardware condition of the system, the system architecture, including data access layer, business logic layer, and presentation layer, is constructed by MVC. In the model module, it is divided into ten difficulty levels by using the frequency of vocabulary, the length of words, and the number of syllables of a single word. The learning resources of the reading class are uniformly represented by the vector space model, and the improved TF-IDF is used to calculate the weight of eigenvalues in the resources. According to the calculation results, the resources are also divided into ten difficulty levels, and the divided resources correspond to their respective databases and use regular expressions to find the learning resources that match the access request. Finally, with the support of the iOS protocol, the feedback mechanism between each module is constructed by Express.js. By analyzing the access requests sent and received by the view, the timely call to the target database resources is realized to improve the response rate of the system. The test results show that the function of the designed system can be realized stably, and the module response delay time is stable within 1s; under the ideal network environment, the buffer delay is in the range of 0.4–0.6 s, and the loading delay is no more than 1.8 s when the network speed is 3 Mpbs, which has a good user experience.
format article
author Xiaofei Zhen
author_facet Xiaofei Zhen
author_sort Xiaofei Zhen
title Research on Mobile English Learning System Based on iOS
title_short Research on Mobile English Learning System Based on iOS
title_full Research on Mobile English Learning System Based on iOS
title_fullStr Research on Mobile English Learning System Based on iOS
title_full_unstemmed Research on Mobile English Learning System Based on iOS
title_sort research on mobile english learning system based on ios
publisher Hindawi-Wiley
publishDate 2021
url https://doaj.org/article/3fe00c120fe0408f97b943232fbece9a
work_keys_str_mv AT xiaofeizhen researchonmobileenglishlearningsystembasedonios
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