A Scalable Blockchain Framework for ELA Assessment

As a popular technology in the information age, blockchain is having a profound impact on various industries, including the field of education. Blockchain technology can accelerate the modernization of education in China, adapt to the new situation of epidemic prevention and control needs, and promo...

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Main Author: Chunxia Tian
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Advances in Multimedia
Online Access:http://dx.doi.org/10.1155/2022/4452393
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author Chunxia Tian
author_facet Chunxia Tian
author_sort Chunxia Tian
collection DOAJ
description As a popular technology in the information age, blockchain is having a profound impact on various industries, including the field of education. Blockchain technology can accelerate the modernization of education in China, adapt to the new situation of epidemic prevention and control needs, and promote the renewal of the management and training modes of college students. Blockchain technology is decentralized, tamper-proof, traceable, trackable, open and transparent, which is conducive to the realization of individual student-centered teaching and learning, as well as an open, and transparent teaching process, which can motivate the learning motivation of English majors and improve the effectiveness of the student management and training models. To address the problem of low accuracy of the traditional English proficiency classification methods, this article aims to explore the application of blockchain technology in the management and training model of English majors and its feasibility. We propose a proficiency evaluation model based on a Discrete Hopfield Neural Network (DHNN). Firstly, the hierarchical analysis method is used to construct the evaluation index system of students’ English ability, and then the ability classification indexes are divided into 5 levels.The network achieves the classification of students’ English proficiency through the associative memory of the classification criteria, and the classification results are compared with those of the BPNN model. The simulation results show that the classification accuracy of the BPNN model is 80.0% and that of the DHNN model is 100.0%. The DHNN model has improved the classification accuracy and generalization ability, and the model establishment process is simple and the results are intuitive, which verifies the effectiveness of the proposed model
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spelling doaj-art-054ece8b71fa449aa2d051db89ac9eb42025-02-03T01:20:35ZengWileyAdvances in Multimedia1687-56992022-01-01202210.1155/2022/4452393A Scalable Blockchain Framework for ELA AssessmentChunxia Tian0School of Foreign LanguagesAs a popular technology in the information age, blockchain is having a profound impact on various industries, including the field of education. Blockchain technology can accelerate the modernization of education in China, adapt to the new situation of epidemic prevention and control needs, and promote the renewal of the management and training modes of college students. Blockchain technology is decentralized, tamper-proof, traceable, trackable, open and transparent, which is conducive to the realization of individual student-centered teaching and learning, as well as an open, and transparent teaching process, which can motivate the learning motivation of English majors and improve the effectiveness of the student management and training models. To address the problem of low accuracy of the traditional English proficiency classification methods, this article aims to explore the application of blockchain technology in the management and training model of English majors and its feasibility. We propose a proficiency evaluation model based on a Discrete Hopfield Neural Network (DHNN). Firstly, the hierarchical analysis method is used to construct the evaluation index system of students’ English ability, and then the ability classification indexes are divided into 5 levels.The network achieves the classification of students’ English proficiency through the associative memory of the classification criteria, and the classification results are compared with those of the BPNN model. The simulation results show that the classification accuracy of the BPNN model is 80.0% and that of the DHNN model is 100.0%. The DHNN model has improved the classification accuracy and generalization ability, and the model establishment process is simple and the results are intuitive, which verifies the effectiveness of the proposed modelhttp://dx.doi.org/10.1155/2022/4452393
spellingShingle Chunxia Tian
A Scalable Blockchain Framework for ELA Assessment
Advances in Multimedia
title A Scalable Blockchain Framework for ELA Assessment
title_full A Scalable Blockchain Framework for ELA Assessment
title_fullStr A Scalable Blockchain Framework for ELA Assessment
title_full_unstemmed A Scalable Blockchain Framework for ELA Assessment
title_short A Scalable Blockchain Framework for ELA Assessment
title_sort scalable blockchain framework for ela assessment
url http://dx.doi.org/10.1155/2022/4452393
work_keys_str_mv AT chunxiatian ascalableblockchainframeworkforelaassessment
AT chunxiatian scalableblockchainframeworkforelaassessment