With the globalization of social and economic development, the culture, economy, science and technology and materials of all countries in the world are communicating to varying degrees. The basic tool of communication is language. Therefore, language translation plays an important role in this process. Learning English translation is of great significance to the development and construction of our country. The establishment of English translation major in major universities is the base for cultivating English translation talents in our country. It is also the main place to improve students' English translation ability and practice. The text will focus on the existing problems and teaching practice application strategies of practical English in higher vocational education, so as to promote the development and use of English translation and improve the quality of teaching in our country.

In the wake of the COVID-19 pandemic, the prevalence of online education in primary education has exhibited an upward trajectory. Relative to traditional learning environments, online instruction has evolved into a pivotal pedagogical modality for contemporary students. Thus, to comprehensively comprehend the repercussions of environmental changes on students’ psychological well-being in the backdrop of prolonged online education, this study employs an innovative methodology. Founded upon three elemental feature sequences—images, acoustics, and text extracted from online learning data—the model ingeniously amalgamates these facets. The fusion methodology aims to synergistically harness information from diverse perceptual channels to capture the students’ psychological states more comprehensively and accurately. To discern emotional features, the model leverages support vector machines (SVM), exhibiting commendable proficiency in handling emotional information. Moreover, to enhance the efficacy of psychological well-being prediction, this study incorporates an attention mechanism into the traditional Convolutional Neural Network (CNN) architecture. By innovatively introducing this attention mechanism in CNN, the study observes a significant improvement in accuracy in identifying six psychological features, demonstrating the effectiveness of attention mechanisms in deep learning models. Finally, beyond model performance validation, this study delves into a profound analysis of the impact of environmental changes on students’ psychological well-being. This analysis furnishes valuable insights for formulating pertinent instructional strategies in the protracted context of online education, aiding educational institutions in better addressing the challenges posed to students’ psychological well-being in novel learning environments.

In the cultivation of talents in universities, in order to ensure the efficiency and scientificity of talent cultivation, the construction of an accounting professional teaching quality monitoring system based on "closed-loop control" is an effective path for universities to enhance their market core competitiveness and development power under the new curriculum reform. Under the new round of basic curriculum reform, the "Accounting Professional Teaching Quality Monitoring System Based on Closed Loop Control", as an integrated education system established from multiple dimensions, is of great significance for improving the quality and efficiency of current talent cultivation through rational application in university talent cultivation. In view of this, this article mainly systematically analyzes the significance of constructing a "Accounting Professional Teaching Quality Monitoring System" based on "closed-loop control", and conducts in-depth discussions on the current construction status and optimization path, in order to meet the national sustainable development demand for high-quality technical composite talents.

Technical Pedagogical Content Knowledge (TPACK) encompasses teachers’ understanding of the intricate interplay among technology, pedagogy, and subject matter expertise, serving as the essential knowledge base for integrating technology into subject-specific instruction. Over the decade, advancements in information technology have led to the consistent application of the TPACK framework within studies on instructional technology and technology-enhanced learning, significantly advancing the evolution of contemporary teacher education in technology integration. In this paper, we utilize the Teaching and Learning Knowledge of Subjects Based on Integrated Technology (TPACK) framework to administer a questionnaire survey to teacher trainees at Chinese colleges and universities. This survey aims to evaluate the current status of their integrated technology-based subject teaching and learning knowledge. Based on the research findings, we propose strategies aimed at enhancing the educational technology integration knowledge of students pursuing integrated technology courses in colleges and universities. Furthermore, we integrate the smart classroom setting to develop a comprehensive TPACK-integrated model teaching framework. Our final objective is to offer valuable references for the progress of modern teaching skills among education students in higher education institutions.

With the gradual penetration of artificial intelligence technology into various fields of society, it has brought many deeper and broader impacts, gradually improving the status of artificial intelligence in talent cultivation and education to adapt to the current development of social intelligence technology. Therefore, as the core course of artificial intelligence education in universities, machine learning needs to deeply analyze and explore the main factors that affect its development, in order to better mobilize students' learning enthusiasm and teachers' educational innovation, enhance the teaching and learning effectiveness of the course, and maximize the exploration of the educational achievements of artificial intelligence.

With the characteristics of resisting business cycle, mitigating cash flow, and improving portfolio resilience, special assets usually enter a highly active period in the economic downturn cycle, and gradually become an effective asset allocation means in the transition phase of the business cycle. This article aims to analyze the importance of the development of China's special asset investment industry in the context of high-quality economic development, and explore how to introduce market-oriented mechanisms to build primary and secondary markets for special assets, in order to improve the effective allocation of market resources and maximize returns.