Machine Learning-Based Intelligent Scoring of College English Teaching in the Field of Natural Language Processing

Wang, Wei

doi:10.1155/2022/2754626

Cited by 2 publications

(2 citation statements)

References 28 publications

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“…Wang [21], have presented ML-depend intelligent scoring of college English teaching in the field of NLP. Here, undertakes a number of theoretical investigations, including theoretical analysis of NLP technologies, an analysis of related intelligent scoring technologies, design of a methodical procedure for intelligent scoring college English instruction, theoretical investigation of NB process in ML.…”

Section: Methodsmentioning

confidence: 99%

Assessment and Prediction of University English Teaching Effect Using Progressive Recurrent Generative Adversarial Network

Zhiyong Sun

2024

jes

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An intelligent evaluation technique of English teaching ability based on enhanced machine learning algorithm is proposed to fully explore the quality of English teaching, fully exploit the effect of intelligent evaluation of English teaching ability. It can guarantee rational allocation of English teaching resources, evaluate big data of constraint parameters of English teaching ability evaluation, attain frequent item sets of English teaching quality depend on big data mining technology. In this paper, Assessment and Prediction of University English Teaching Effect Using Progressive Recurrent Generative Adversarial Network (APETE-PRGAN-GOA) is proposed. Initially the input data is collected from fig share, it is given to preprocessing. The preprocessing, remove useless words using Learnable Edge Collaborative Filtering (LECF). Then the pre-processed output is fed to Prediction of English Teaching Effect. Here, Progressive Recurrent Generative Adversarial Network (PRGAN), is used to Predict English teaching ability. In general, PRGAN classifier does not express any optimization adaption approaches for determining optimum parameters to assure the assessment. Here Gazelle Optimization Algorithm utilized to optimize PRGAN classifier, for English Teaching Effect. The proposed technique executed in Python, performance of proposed technique is analysed with evaluation metrics likes,evaluation accuracy, correlation coefficient, mean squared error, evaluation time, occurrence (time), recall, F1-score, RoC are analyzed. The proposed APETE-PRGAN-GOA method attains 30.58%, 28.73% and 35.62%, higher evaluation accuracy, 20.48%, 24.73%, 29.32% higher RoC and 30.98%, 26.66% and 21.32% lower mean squared error analysed with existing models such as intelligent assessment method of English teaching ability depend on enhanced machine learning algorithm (ISM-ETE-CNN), application of machine learning with IoT methods in evaluation of English teaching effect in colleges (CNN-ETE-IOT),English teaching evaluation technique depend on association rule algorithm with machine learning (ETE-ARA-SCN) respectively.

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Section: Methodsmentioning

confidence: 99%

Assessment and Prediction of University English Teaching Effect Using Progressive Recurrent Generative Adversarial Network

Zhiyong Sun

2024

jes

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“…The NLP-based Artificial Intelligence Scoring System is a powerful tool that can be used in various educational settings [46]. For example, Wei Wang et al conducted experiments on intelligent English teaching assessment based on machine learning in the field of natural language processing [47]. Similarly, Nazaretsky et al explored the potential of using NLP technology to analyze the performance of teachers and simulated students' interactions in order to evaluate the performance of teachers.…”

Section: Nlp-based Artificial Intelligence Scoring Systemmentioning

confidence: 99%

Natural Language Processing in Teacher Training : a systematic review

Zhu

2023

LNEP

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In the previous decade, there has been a growing interest within the research community to apply artificial intelligence (AI), particularly natural language processing (NLP) tech-nology, across various domains such as law, medicine, and finance. More recently, the fo-cus has shifted towards exploring the potential of NLP technology in education, specifi-cally in teacher training. Thus, it becomes crucial to conduct a systematic literature review to comprehensively examine the literature on the use of NLP technology in teacher train-ing. This study concentrates on the applications and use cases of NLP technology in higher education institutions and educational research institutions. Our analysis suggests that significant NLP applications in education include Language Learning, intelligent analysis, assistive technology, automatic content analysis, and speech emotion analysis. Further examination reveals that NLP technology can be effectively utilized to improve teachers professional abilities, such as helping language teachers improve their accents, ultimately contributing to the delivery of high-quality education. Finally, this paper summarizes the critical lessons learned from the application of NLP technology in teacher training that can guide future research endeavors in this rapidly evolving field.

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Machine Learning-Based Intelligent Scoring of College English Teaching in the Field of Natural Language Processing

Cited by 2 publications

References 28 publications

Assessment and Prediction of University English Teaching Effect Using Progressive Recurrent Generative Adversarial Network

Assessment and Prediction of University English Teaching Effect Using Progressive Recurrent Generative Adversarial Network

Natural Language Processing in Teacher Training : a systematic review

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