Establishment of a Fuzzy Comprehensive Evaluation Random Matrix Model for the Assessment of Foreign Language Translation Level in Universities

Xie, Li; Wu, Jin

doi:10.1155/2022/4313549

Cited by 3 publications

(1 citation statement)

References 22 publications

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“…Xie and Wu [21] have suggested that in-depth research and an examination of the standards for translating foreign languages in universities be done using the fuzzy comprehensive evaluation approach of random matrix, and that a corresponding model be developed for the automatic assessment of university education 's translation proficiency. The geometric properties of the deep neural network's loss plane were investigated using the second-order optimization method's Hessian matrix.…”

Section: Methodsmentioning

confidence: 99%

Classroom Management Effectiveness Assessment Model of English Teaching Based on Gustafson-Kessel Clustering Based Takagi-Sugeno Fuzzy Model with Wild Geese Algorithm

Jing Tang

2024

jes

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The classroom's evaluation of the teaching effect English has a demanding workload, complex statistics, among other factors. The assessment of classroom instruction quality plays a crucial role in creating a supportive environment that encourages and guides the improvement of university administration and services, as well as in igniting teacher enthusiasm, boosting their efficacy as teachers, and raising the standard of talent development. Strong ambiguity, fuzziness, and inexactness are the main questions that come up while thinking about the case of teaching quality evaluation. The Gustafson - Kessel Clustering Based Takagi-Sugeno Fuzzy (GK-TSF) model along with wild geese algorithm (GKTSF-WGA) method is proposed for classify the skills, attitudes, and verbal, classifications to improve the above issues. Initially, the data’s are gathered via the dataset of teaching assistant evaluation dataset. Afterward, the data’s are fed to pre-processing. In pre-processing segment; it removes the noise and enhances the input data’s utilizing adaptive robust cubature kalman filtering. The feature extraction section receives the output of the preprocessing. Fluency is extracted as a feature using the One - dimensional quantum integer wavelet S-transform in this case. After that, the extracted features are given to the GK-TSF model with wild geese algorithm for effectively classify skills, attitudes, and verbal. The proposed ET-GKTSF-WGA approach is implemented in MATLAB. The proposed ET-GKTSF-WGA method attains 23.05%, 28.95%, and 26.56% higher accuracy for skills; 23.12%, 25.43%, and 27.45%, higher accuracy for attitudes; 25.86%, 27.73%, and 21.04%, higher accuracy for verbal. The computational time performance of the proposed method attains 70.85%, 45.7%, 60.12%, and 35.34%, lower computation. The proposed ET-GKTSF-WGA method is in contrast to the current techniques like ET-FCE, ET-q-ROFs, and ET-K-MC, respectively.

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Section: Methodsmentioning

confidence: 99%

Classroom Management Effectiveness Assessment Model of English Teaching Based on Gustafson-Kessel Clustering Based Takagi-Sugeno Fuzzy Model with Wild Geese Algorithm

Jing Tang

2024

jes

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Translation quality assessment practices of faculty members of colleges of languages and translation in Arab countries: an exploratory study

Abanomey,

Almossa

2023

Humanit Soc Sci Commun

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The investigation and understanding of the process of assessing translation quality in translation courses have attracted some attention. However, only a few studies have explored general assessment (GA) and specialised Translation Quality Assessment (TQA) practices used by different translation instructors. This study explores the assessment practices of 98 faculty members of the translation departments of various universities in Arab countries. In this exploratory study, data were collected using an adapted version of the Approaches to Classroom Assessment Inventory instrument. In addition, the authors designed a Translation Quality Assessment Practices Inventory aimed specifically for the investigation of TQA practices adopted by the faculty members. Data collected from the three-part survey were subjected to descriptive statistics, exploratory factor analysis, one-way analysis of variance, an independent samples t-test, and the chi-square test. The study reveals that the participants highly endorsed GA and TQA practices equally. The results indicate that three major TQA themes are particularly prioritised: the significance of errors; the use of particular assessment methods; and the primacy of objectivity. This research shows that there is an urgent need for more training aimed at improving TQA literacy among faculty members teaching translation courses. It contributes to the efforts to improve translation training and to design more effective curricula.

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Developing a fuzzy comprehensive assessment model for English translation for college studentso

Huang

2024

JCM

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College students are learning a foreign language must know how to translate the spoken or written content from the respective language into English. These approaches do not help the college students to develop the capacity for rational thinking and adequate the motivation for the English translation. The educational principles are not in line with the qualities of the students in the typical English translation classroom teaching, and the teaching methods are out-dated. In the older process of the teaching English translation, many unreliable, vague aspects need to be considered, such as recognizing students’ fundamental English knowledge, unique circumstances, language proficiency, cultural differences, and the ambiguity of the source language. The main issue with the current English translation evaluation methodology is that it cannot be easily to deal with thecomplex fuzzy indices when judging the accuracy of the student translations. An algorithm named FCAM-AHP-ANFIS is proposed to provide an effective and accurate method for evaluating and predicting students’ English translation outcomes to overcome the traditional shortcomings. According to the proposed approach, students can learn about passive translation, but they may struggle to actively improve their translation skills. College students can benefit from the decision-making aid provided by the extensive evaluation technique due to its high availability and precision. The fundamental benefit of the fuzzy technique over more traditional forms of the assessment is that it accounts for the ambiguity and uncertainty of the making judgments at the human level and provides a coherent framework that includes the indistinct findings of the several steps in evaluating an English translation. The Fuzzy Comprehensive Assessment Model (FCAM) is a decision-making method that uses the fuzzy logic to assess the quality of English translations among the college students. The Analytic Hierarchy Process (AHP) is employed to calculate each criterion’s relative importance and determine the optimal weighting for each criterion utilized in the assessment model. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to analyze the translated data and generate predictions for the students’ translation outcomes. The experimental outcomes show the accuracy of the English translation assessment scores are 95.6% with 97% precision, 96% recall, and 96.5% of f1-score metric in addition to Root Mean Square (RMSE) and Mean Absolute Error (MAE).

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Establishment of a Fuzzy Comprehensive Evaluation Random Matrix Model for the Assessment of Foreign Language Translation Level in Universities

Cited by 3 publications

References 22 publications

Classroom Management Effectiveness Assessment Model of English Teaching Based on Gustafson-Kessel Clustering Based Takagi-Sugeno Fuzzy Model with Wild Geese Algorithm

Classroom Management Effectiveness Assessment Model of English Teaching Based on Gustafson-Kessel Clustering Based Takagi-Sugeno Fuzzy Model with Wild Geese Algorithm

Translation quality assessment practices of faculty members of colleges of languages and translation in Arab countries: an exploratory study

Developing a fuzzy comprehensive assessment model for English translation for college studentso

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