1 Introduction

This section introduces the characteristics of Chinese-style chunk adverbials and their significance in international communication, highlighting the neglect of their paratactic features and cognitive challenges in existing research and translation pedagogy. The article proposes that data-driven learning (DDL) and deep learning theory offer new approaches to improving translation instruction. DDL emphasizes autonomous learning through corpus resources, while deep learning focuses on critical thinking and knowledge construction. Current research lacks DDL-based translation pedagogy oriented toward deep learning, particularly for cultivating competence in translating Chinese-style chunk adverbials. Using the multilingual database platform of Xi Jinping: The Governance of China as an example, the article explores implementation pathways for DDL pedagogy grounded in deep learning.

2 Theoretical Basis for DDL-Based Deep Learning Pedagogy in Translating Chinese-Style Chunk Adverbials

This section examines the theoretical foundation for designing deep learning-oriented DDL pedagogy for translating Chinese-style chunk adverbials. The six key features of deep learning include activity and experience, association and structure, essence and variation, internalization, expression and flexibility, transfer and creation, as well as value and evaluation. These emphasize student-centeredness, knowledge framework construction, uncovering intrinsic information connections, in-depth understanding and innovative application of knowledge, knowledge transfer and real-world problem-solving, and moral education. The instructional design prioritizes student agency, employs educational philosophies and methods that foster development, adopts flexible organizational formats, encourages participation, and transcends spatiotemporal constraints. Teaching activities emphasize embodied experience, collaborative learning, task-driven approaches, and process evaluation, while situational construction motivates learning through data-driven interactive experiences. DDL translation pedagogy follows a teacher-guided, student-led "bottom-up" inductive model. The pre-class phase focuses on value evaluation and internalization, with teachers training students in corpus retrieval techniques and students internalizing research-based learning paradigms. The in-class phase fully embodies deep learning features, including pre-translation analysis, corpus exploration, classroom interaction, and formative assessment. The post-class phase strengthens transfer and creation as well as value evaluation, with teachers collecting feedback to optimize instruction and students evaluating the impact of their learning process while transferring skills to broader contexts. The design reflects active construction, collaborative interaction, process development, situational application, technology empowerment, and personalized experience, positioning teachers as designers, guides, and supporters, and students as discoverers and researchers, achieving deep learning of Chinese-style chunk adverbials.

3 Application Cases of the Integrated Platform in DDL-Based Pedagogy for Translating Chinese-Style Chunk Adverbials

This section explores how the multilingual database platform of Xi Jinping: The Governance of China (DDL) was used to design instructional plans for the "Understanding Contemporary China" course for English majors, helping students overcome challenges in translating Chinese-style chunk adverbials. The study involved second-year English majors at a university in Hubei Province, with data collected over one semester, including teaching design materials, teacher reflection logs, and student feedback. Application cases of the platform include:

1. Using the concordance line function to cultivate students' holistic extraction of Chinese chunk adverbials. By retrieving bilingual co-occurrences of typical three-character and six-character chunk adverbials, students explored translation patterns, reinforcing their awareness of the holistic nature of chunk adverbials.

2. Employing the KWIC (Key Word In Context) co-occurrence function to enhance students' attention to chunk adverbials. Multi-context co-occurrence tasks promoted deeper processing and long-term retention.

3. Utilizing the word cluster and collocation functions to improve students' collocational competence and semantic prosody awareness while fostering national sentiment. Comparative analysis of the semantic prosody of Chinese chunk adverbials and their English translations revealed attitudinal differences between source and target languages.

4. Leveraging parallel concordance lines to explore differences between Chinese and English chunk adverbials. Students independently identified disparities, focusing on the strong paratactic features of native-language chunk adverbials and accurately grasping internal morphemic relationships.

5. Applying the "Translation Strategies and Techniques" function to encourage students to observe and summarize translation principles for Chinese-style chunk adverbials, cultivating higher-order thinking skills for autonomous knowledge construction.

Through these activities, students strengthened their holistic extraction perspective, improved translation skills, and achieved integration of ideological education and chunk adverbial translation pedagogy.

4 Application Outcomes of the Integrated Platform

This section evaluates the effectiveness of the multilingual database platform of Xi Jinping: The Governance of China in deep learning-driven pedagogy for translating Chinese-style chunk adverbials. Teachers reflected on their instructional practices across six dimensions, finding that the platform facilitated collaborative exploration, uncovering translation patterns and analyzing the rationale behind translation choices, thereby addressing fragmented and superficial teaching and enabling deep learning. Student feedback indicated that DDL-based pedagogy promoted deep learning, transforming them from passive recipients into explorers, discoverers, and active constructors, enhancing engagement and classroom integration. The study demonstrates the feasibility of guided DDL pedagogy in translation classrooms, effectively improving learners' competence in translating chunk adverbials, with positive feedback from both teachers and students.

5 Conclusion

This section discusses the application of the integrated platform in chunk adverbial translation pedagogy, aiming to address fragmentation and superficiality while enhancing the systematicity and authority of translation instruction. Through platform functionalities, teachers guided students to explore Chinese-English chunk adverbial differences, analyze discourse styles, and investigate translation strategies, shifting pedagogy from teacher-centered to student-centered and from surface-level to deep learning. This fostered national sentiment and enabled personalized, adaptive learning. The article suggests future empirical and action research to further explore the effectiveness of data-driven teaching models, achieving the educational goals of foreign language instruction.