WeChat-Based Interactive Translation Mobile Teaching Model

Wang, Fachang; Wang, Qingling; Du, Cuifang

doi:10.1155/2021/7054016

Cited by 25 publications

(8 citation statements)

References 23 publications

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“…Rapid technological changes also push higher education to well-prepare IS students with training in critical thinking, problem identification, and problem-solving skills [53,54]. Systems requirement analysis is a core process for developing BIS applications [55,56].…”

Section: Implications For Is Educationmentioning

confidence: 99%

Using multi-focus group method as an effective tool for eliciting business system requirements: Verified by a case study

Wang²,

Shafiabady³

et al. 2023

PLoS ONE

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This research aims to explore the multi-focus group method as an effective tool for systematically eliciting business requirements for business information system (BIS) projects. During the COVID-19 crisis, many businesses plan to transform their businesses into digital businesses. Business managers face a critical challenge: they do not know much about detailed system requirements and what they want for digital transformation requirements. Among many approaches used for understanding business requirements, the focus group method has been used to help elicit BIS needs over the past 30 years. However, most focus group studies about research practices mainly focus on a particular disciplinary field, such as social, biomedical, and health research. Limited research reported using the multi-focus group method to elicit business system requirements. There is a need to fill this research gap. A case study is conducted to verify that the multi-focus group method might effectively explore detailed system requirements to cover the Case Study business’s needs from transforming the existing systems into a visual warning system. The research outcomes verify that the multi-focus group method might effectively explore the detailed system requirements to cover the business’s needs. This research identifies that the multi-focus group method is especially suitable for investigating less well-studied, no previous evidence, or unstudied research topics. As a result, an innovative visual warning system was successfully deployed based on the multi-focus studies for user acceptance testing in the Case Study mine in Feb 2022. The main contribution is that this research verifies the multi-focus group method might be an effective tool for systematically eliciting business requirements. Another contribution is to develop a flowchart for adding to Systems Analysis & Design course in information system education, which may guide BIS students step by step on using the multi-focus group method to explore business system requirements in practice.

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Section: Implications For Is Educationmentioning

confidence: 99%

Using multi-focus group method as an effective tool for eliciting business system requirements: Verified by a case study

Wang²,

Shafiabady³

et al. 2023

PLoS ONE

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“…Wang, F. et al noted that for China's education system to continue developing, a significant number of talents with a worldwide viewpoint must be developed, and the growth of internationalized talents must improve English communication skills. And the research shows that the current English education goal in the basic education stage can not meet this requirement, and needs to be further accomplished in the university English education [11].…”

Section: Introductionmentioning

confidence: 98%

Innovative Research on the Quality Evaluation Method of English Translation Teaching in Colleges and Universities Based on Neural Network Modeling

Dou,

Yang

2024

Applied Mathematics and Nonlinear Sciences

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This paper presents BP neural network as an evaluation tool for English translation instruction in colleges and universities. It does this by analyzing and combing the structure of BP neural networks, combining the five first-level indices with the assessment of indexes data preprocessing method, and building an evaluation system based on BP neural networks. We get sample data for the teaching quality assessment indexes based on the example teaching, evaluate it, and confirm that the BP neural network is feasible to use in the evaluation model. Two randomly selected college English language teaching classrooms are used as an example for the class, and the teaching quality rating method is utilized and analyzed. The teaching quality evaluation system’s findings are used to investigate the influencing factors that affect the quality of English translation teaching in higher education institutions. The teaching effect is also discussed about the impact of course time and content arrangements. According to the analysis, the English translation teaching evaluation index system built around the BP neural network model has a substantial amount of credibility because Kendall’s harmony coefficient W = 0.756 χ 2 = 7.687 χ 2 (p − 0.025) = 7.249 indicates that the consistency credibility of the instructional quality evaluation system goes to the test at a significant level of P = 0.025 and the opinions are very uniform.

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“…At present, the Internet has brought new experiences in English translation teaching in Chinese colleges and universities [7]. Colleges and universities have proposed the teaching method of interactive English translation to address some of the current problems in the teaching of translation English, which provides a good learning platform for students and enhances their learning ability [8]. Through the enhanced implementation of the quality education policy, innovation and exploration of English teaching methods and learning tools are needed in order to effectively improve students' comprehensive quality level and subjective initiative [9].…”

Section: Introductionmentioning

confidence: 99%

The Construction of “Interactive” English Translation Teaching Mode in the Background of Internet

2024

Applied Mathematics and Nonlinear Sciences

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This paper discusses the construction of “interactive” English translation teaching mode in the background of the Internet, and analyzes the application of neural machine translation model in improving the effect of translation teaching. The research adopts Word2vec algorithm to train word vectors, combines neural network language model and encoder-decoder structure, and constructs Transformer model and CNN+Transformer model to improve translation efficiency and quality. The translation experiments on sentences of different lengths show that the models perform better in short sentence translation. The experimental results show that the proposed model outperforms the traditional model in terms of BLEU value, and the best translation effect is found in test set 1, where the BLEU value is improved by 10.6 and 11.7 compared with that of the baseline model and the CNN model, respectively. The “interactive” teaching mode designed with POA theory significantly outperforms the traditional teaching mode regarding students’ lexical, grammatical and semantic translation quality. The “interactive” English translation teaching with neural translation model can effectively improve the quality of translation teaching and students’ learning effect.

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WeChat-Based Interactive Translation Mobile Teaching Model

Cited by 25 publications

References 23 publications

Using multi-focus group method as an effective tool for eliciting business system requirements: Verified by a case study

Using multi-focus group method as an effective tool for eliciting business system requirements: Verified by a case study

Innovative Research on the Quality Evaluation Method of English Translation Teaching in Colleges and Universities Based on Neural Network Modeling

The Construction of “Interactive” English Translation Teaching Mode in the Background of Internet

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