算法驱动的脑与认知科学基础课程思政改革实践

Algorithm-Driven Reform Practice of Curriculum Ideological and Political Education in the Brain and Cognitive Science Foundation Course

摘要: 脑与认知科学基础课程兼具理论抽象性、学科交叉性和实践应用性，教学中存在知识理解与算法实践衔接不够紧密、价值引导融入不够深入等问题。围绕课程思政建设要求，文章对教学目标、内容组织、实验任务、过程管理与评价方式进行了改革，形成了算法驱动的教学实施路径。课程实施结果表明，学生的课堂参与、作业完成和综合实践表现较为稳定，对合作意识、辩证思维、技术应用和社会责任的认识有所提升。该改革对智能类课程的课程思政建设具有一定参考价值。

Abstract: The Brain and Cognitive Science Foundation course is characterized by theoretical abstraction, interdisciplinary integration, and practical applicability. In the teaching process, some problems remain, including insufficient linkage between knowledge understanding and algorithm practice, as well as inadequate integration of value guidance. In response to the requirements of curriculum-based ideological and political education, this study reforms the teaching objectives, content organization, experimental tasks, process management, and evaluation methods, and develops an algorithm-driven teaching implementation pathway. The teaching results show that students maintained stable performance in classroom participation, assignment completion, and comprehensive practice, and demonstrated improvement in cooperation awareness, dialectical thinking, understanding of technological application, and sense of social responsibility. The reform provides a useful reference for the development of curriculum-based ideological and political education in intelligent science and related courses.