讲座通过聚焦教学活动样态的历史变迁，考察中国基础外语教育在改革进程中教学知识体系的重建路径。从“操练型”到“输入型”再到“建构型”的三类活动样态，折射出教学知识从依赖外部范式到本土自主发展的演进趋势。当下，在“核心素养”引领下，教学知识体系已呈现出更强的整合性、开放性与系统性的内生能力，标志着一个以课程实践为基础的自主知识体系正在逐步形成。这一转变不仅回应了本土教育语境的需要，也为全球外语教学知识的重建提供了经验启示。

获取更多与本讲座相关的详细信息，敬请关注中国外语战略研究中心公众号“语言与未来”（ID: SISU_CCLPPS）的微信推送。

讲座报告拓展了外部经贸冲击的经济效应，将其从传统的贸易视角延展至微观企业的财务行为，通过利用2011-2020年全国税收调查数据，探究其对企业纳税遵从的影响。研究发现，外部经贸冲击加剧了市场竞争企业现金流压力，导致企业通过避税方式进行代偿，且“冲击—响应”模式在征管力度、所有制形式、企业规模、企业类型等方面表现出异质性。进一步研究发现，关税冲击的上下游传导路径具有非对称性，上游行业受到外部冲击后，会正向地提升下游企业的纳税遵从度，而下游行业则无法将外部冲击的价格压力传递至上游行业；减税降费政策可以降低企业的税收负担，缓解外部经贸冲击对企业纳税遵从度的负溢出效应。对此，应警惕外部经贸环境变化对微观主体的影响，建立防范和及时响应机制；继续实施结构性减税降费政策，挖掘其缓冲外部经贸冲击，提升企业纳税遵从度的潜力。

The emergence of big data has enabled the creation of significant models by allowing the storage of large data volumes. Transfer learning is a machine learning technique that transfers knowledge between different domains by utilizing pretrained models from the source domain to optimize the target domain. In contrast, inductive matrix completion is a method that leverages side information from multiple sources to improve task performance. This paper explores inductive matrix completion within the transfer learning framework, with our proposed approach assuming group sparsity for the difference between the core matrices of the target and source domains. Theoretical guarantees of our method are investigated to demonstrate the gains achieved through transfer learning compared with standard inductive matrix completion. Several synthetic experiments are conducted to evaluate the performance of the proposed approach and existing methods, demonstrating that our method outperforms others.