园林植物遗传育种学课程思政教学探索与实践
魏国 1曹雅铮 1冯立国1
作者信息
- 1. 扬州大学 园艺园林学院,江苏 扬州 225009
- 折叠
摘要
课程思政在高校承担着实施立德树人使命的重要任务,而园林植物遗传育种学是园林专业中不可或缺的重点课程.该文以课程和专业特点为出发点,深入研究园林植物遗传育种学课程中蕴含的思政元素.着重强调如何将思政元素贯穿于整个园林植物遗传育种学课程中,通过有机融合专业理论与实际操作,使学生在掌握专业知识的同时提升综合素质.并对思政教学提出多角度的具体措施,包括优化教学体系、强化思政元素重点、多样的教学方法,落实思政目标以及完善教学考核和评分体系,旨在提高思政工作的质量.最终,为园林专业学生在未来工作中更好地应对复杂挑战,同时拥有崇高的价值观,为园林专业学生的综合素养培养奠定坚实基础.
Abstract
Ideological and political education in all courses undertakes the important task of implementing the mission of establishing morality and cultivating people in colleges and universities,and landscape plant genetic breeding is an indispensable key course in landscape architecture major.Based on the characteristics of curriculum and specialty,this paper makes an in-depth study of the ideological and political elements contained in the course of genetic breeding of garden plants.It is emphasized that how to run through the ideological and political elements in the whole garden plant genetic breeding course,through the organic integration of professional theory and practical operation,so that students can improve their comprehensive quality while mastering professional knowledge.This paper puts forward multi-angle specific measures for ideological and political teaching,including optimizing the teaching system,strengthening the focus of ideological and political elements,a variety of teaching methods,implementing ideological and political objectives and improving the teaching assessment and scoring system,in order to improve the quality of ideological and political work.Finally,this lays a solid foundation for landscape architecture students to better deal with complex challenges in their future work and have lofty values,which lays a solid foundation for the cultivation of comprehensive literacy of landscape architecture students.
关键词
园林植物遗传育种/思政元素/课程思政/实践教学/优化教学体系Key words
garden plant genetics and breeding/ideological and political elements/ideological and politic education in all courses/practical teaching/optimization of teaching system引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据