The Construction and Exploration of University English Translation Teaching Mode Based on the Integration of Multimedia Network Technology

Amidst the swift advancements in information technology, university-level English education encounters both challenges and opportunities for innovation. This study is dedicated to the development of a system tailored for precise teaching strategies in college English, employing students from M-school as the primary research subjects. Subsequently, the relationship between various teaching strategies and the outcomes of precision teaching was investigated through correlation analysis using SPSS. Furthermore, the factors influencing English performance were analyzed using Pearson’s correlation coefficient and grey correlation analysis within multiple regression analyses. The results show that the overall mean score for English precision teaching is 3.5162, which is in the middle of the teaching level. Furthermore, the significant (two-sided) p-values of the factors affecting the level of English precision teaching and English achievement are less than 0.05, which is significantly correlated with English achievement. College students’ English achievement = 0.534+0.142*Teaching objectives+0.195*Learning situation analysis+0.238*Teaching content+0.271* Teaching methods+0.187*Teaching organization+0.185*Teaching evaluation. The study shows that the precise teaching of English in colleges and universities can be optimized in terms of teaching objectives, learning situation analysis, teaching content, teaching methods, teaching organization form, and teaching evaluation.

Section: Introductionmentioning

confidence: 99%

The Application of SPSS Correlation Analysis in the Study of Precision Teaching of English in Universities

2024

“…At the same time, purpose theory and behavior theory are its core theories [11][12][13]. Functional translation theory emphasizes the purpose and function of translation and regards translation as an active behavior aimed at meeting specific communicative needs [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Characteristics and Optimization of University English Translation from a Cross-cultural Perspective-Based on Functional Translation Theory

Zhou

2024

Drawing on the theoretical framework of functional translation, this study presents a multifaceted exploration of university English translation through functional, constructive, evolutionary, and cultural lenses. Positioned within a cross-cultural context, the paper categorizes university English translation into three primary attributes: the frontier nature of translation, linguistic and cultural divergences, and the professionalism required in translation activities. Utilizing Super Decision software, these attributes serve as input variables to construct a Network Hierarchical Analysis model. This model is further integrated with the Interpretive Structural Modeling (ISM) recursive structure to assess the influence of various factors on translation quality. The study employs a multidimensional approach to dissect the impact of cultural and professional variances on the quality of university English translation. The results reveal that 54 out of 65 cultural dimensions (83.08%) significantly affect translation quality. In the realm of professional characteristics, four out of six dimensions (66.67%) are found to have a considerable influence on translation quality. Based on these comprehensive findings, the paper proposes four strategic optimizations aimed at enhancing the quality of university English translation, thereby offering valuable insights and practical recommendations for the field.

“…Sun, H demonstrated through teaching experiments that the combination of the WeChat online platform and multimedia intelligent teaching methods has improved the teaching effect of English translation courses to a certain extent [10]. Yuan, L. designed a perturbation period division method constructed with the underlying logic of the motion time window theory to predict the development of English interpretation teaching in the future [11]. Li, L. explored and summarized the inadequacies of the English translation classroom and attempted to incorporate Internet technology and cultural background into the teaching of translation to strengthen the effectiveness of teaching.…”

Section: Introductionmentioning

confidence: 99%

Research on the Construction of Translation Path of College English Teaching Based on Deep Learning Strategy

Liu,

Li,

Huang

2024

Based on deep learning, this study explores a teaching model to promote college students’ English translation ability with the support of information technology. It mainly adopts the neural machine translation algorithm to make the training samples constitute data nodes with semantic feature-carrying properties through the profound training of semantic feature quantity. It then gets the best English translation utterance that recognizes the translated information. Using a combination of quantitative and qualitative methods, we explored the impact of deep learning strategies on English translation teaching in colleges and universities, as well as the evaluation of practical effects. The results of the study show that under the deep learning teaching mode, the English translation scores of college students are improved by 9.085 points, which is a significant difference (P=0.018) compared to the traditional teaching mode, indicating the excellent performance of the strategy in English translation teaching.