Enhancing Translation Teaching Efficiency and Learning Experience through Mobile Technology Applications

With the advancement of globalization, the significance of English translation in cross-cultural communication has been increasingly emphasized. Traditional methods of translation teaching are becoming insufficient to meet the demands of modern learners, particularly in the context of the rapid development of mobile internet and intelligent devices. Consequently, there is an urgent need to introduce new technological approaches to improve teaching efficiency and the learner experience in translation education. The widespread use of mobile technology presents new opportunities for translation teaching, especially in the areas of real-time feedback, personalized learning, and translation aids. However, existing translation tools and models are often too complex and unsuitable for lightweight devices, and they exhibit certain limitations in enhancing learning efficiency and translation quality. Thus, the design of lightweight translation models suited for mobile devices has become a critical issue in translation education. This study aims to explore the application of optimized translation model designs on mobile devices in translation teaching. The study focuses on two core components: first, the design of a lightweight translation model based on attention mechanisms to improve computational efficiency and translation quality; second, the investigation of encoder and decoder designs suitable for mobile devices to enhance model performance. Through these optimizations, the study aims to provide a more efficient and personalized tool for translation teaching, thereby improving teaching outcomes and the learning experience, while offering theoretical support and practical guidance for the innovation of translation education models.