本文以泰国汉语学习者为对象,以内江师范学院的教学实践为例,探讨语块习得中的学习策略体系构建及其教学应用。研究发现,语块教学通过“整体提取一即时输出”的自动化处理模式,显著提升学习者的语言流利度与表达自然性。内江师范学院结合“构式一语块”分析法与情境教学法,设计多维度互动教学模式,有效促进泰国学生对汉语语块的理解与应用。研究通过课堂观察与深度访谈发现,情景模拟与跨文化对比教学能显著增强语块记忆效率并减少母
语负迁移,但需优化技术工具的使用体验。基于泰国学生从初级到中级阶段的语块习得特点,本文提出包含输入、加工、输出及评估反馈的立体化策略体系,其中语义网络构建与错误分析档案等加工策略对提升语块深度处理能力尤为重要。案例设计显示,高频会话语块与文化特色语块的分层教学结合模态输入与语境化输入,可有效提升习得效率。最后,研究建议通过个性化AI反馈、动态评估及跨学科方法进一步优化语块教学。
This study investigates learning strategies for chunk acquisition among Thai learners of Chinese,focusing on the teaching practices at Nejiang Normal University. Findings reveal that chunk-based instruction, through an "integrated retrieval-immediate output" automated processing model, significantly enhances learners’fluency and naturalness in language production. The university's multidimensional interactive teaching model, integrating "construction-chunk" analysis with situational pedagogy. effectively improves Thai students' comprehension and application of Chinese chunks. Classroom observations and in-depth interviews indicate that situational simulations and cross-cultural comparative teaching enhance chunk memorization and reduce LI negative transfer, though technical tools require usability improvements. Based on Thai learners' developmental trajectory from beginner to intermediate levels, this study constructs a comprehensive strategy system encompassing input. processing, output, and assessment. Case studies demonstrate that tiered instruction combing high-
frequency conversational chunks and culture-specific chunks, supported by multimodal input and contextualized input, optimizes acquisition efficiency. The study proposes further refinements through the personalized AI feedback. dynamic assessment, and interdisciplinary approaches.
