人工智能赋能思政"金课"建设的价值、困境和出路
The Value,Dilemma and Solutions of Artificial Intelligence Enabling the Construction of Ideological and Political"Golden Courses"
樊莲花 1邓悦 1潘静1
作者信息
- 1. 西安外国语大学,陕西西安 710128
- 折叠
摘要
淘汰"水课"、打造"金课",提升教学质量已成为高等教育高质量发展的内在要求.研究发现,人工智能赋能思政"金课"建设有助于解决学生课程需求画像难题、丰富思政课程资源内容建设、改善思政课程教学质量效果.与此同时,人工智能赋能思政"金课"建设也面临着学生对智能技术过度依赖消解创造力、教师数字素养缺乏制约课程建设实效、工具理性思维导致课程人文关怀缺失等问题.为此,未来人工智能赋能思政课程建设中应厘清人机职责边界,培养学生创新创造能力;提升教师数字素养,彰显教师智能胜任水平;坚持以生为本立场,加强思政"金课"人文关怀.
Abstract
Eliminating"watered-down courses"and creating"golden courses"to improve teaching quality have become the inherent requirements for high-quality development of higher education.Research has found that artificial intelligence can empower the construction of ideological and political"golden courses"and help solve the problem of students'demand for courses,enrich the content construction of ideological and political course resources,and improve the teaching quality and effect of ideological and political courses.At the same time,the construction of ideological and political"golden courses"empowered by artificial intelligence also faces problems such as students'excessive dependence on intelligent technology that diminishes creativity,teachers'lack of digital literacy that restricts the effectiveness of course construction,and instrumental rational thinking that leads to the lack of humanistic care in courses.Therefore,in the future construction of ideolog-ical and political courses empowered by artificial intelligence,it is necessary to clarify the boundaries of hu-man-machine responsibilities,cultivate students'innovative and creative abilities;improve teachers'digital lit-eracy,highlight teachers'intelligent competency level;adhere to the student-oriented position,and strengthen the humanistic care of ideological and political"golden courses".
关键词
人工智能/赋能/数字素养/思政"金课"Key words
artificial intelligence/empower/digital literacy/ideological and political"golden courses"引用本文复制引用
基金项目
2023年度国家社会科学基金教育学西部项目(CHX230350)
陕西省社会科学基金项目(2023P009)
西安外国语大学本科教学改革研究项目(22BZWK02)
出版年
2024
NETL
NSTL
万方数据