西南石油大学学报(社会科学版) ›› 2025, Vol. 27 ›› Issue (3): 20-28.

• 热点聚焦·思政前沿 • 上一篇    下一篇

DeepSeek类人工智能赋能高校思政课教学:价值、隐忧与纾解

王雅坤, 申小蓉   

  1. 电子科技大学马克思主义学院, 四川 成都 611731
  • 发布日期:2025-06-06
  • 作者简介:王雅坤,电子科技大学马克思主义学院讲师,电子科技大学i思政大模型创新实验室副研究员,研究方向:网络思想政治教育。
    申小蓉,电子科技大学马克思主义学院二级教授,博士生导师,电子科技大学i思政大模型创新实验室主任,研究方向:网络思想政治教育。
  • 基金资助:
    教育部哲学社会科学研究重大课题“网络算法分发模式与大学生价值观引导研究”(21JZD055)。

DeepSeek-like Generative Artificial Intelligence Empowering the Teaching of Ideological and Political Courses in Universities: Value, Risks and Mitigation Path

WANG Yakun, SHEN Xiaorong   

  1. School of Marxism, University of Electronic Science and Technology of China, ChengduSichuan, 611731, China
  • Published:2025-06-06

摘要: 以DeepSeek为代表的人工智能引发了新一轮对生成式人工智能的高度关注,并在教育领域掀起应用人工智能的热潮。对思政课来说,DeepSeek类人工智能可从“教”“学”“评”三个维度推动思政课创新发展。从“教”的维度看,DeepSeek类人工智能可助力教学内容系统性聚合,极大地提升教师备课效率。从“学”的维度看,DeepSeek类人工智能可有效捕捉学生需求,以个性化的方式生成教学内容。从“评”的维度看,DeepSeek类人工智能可有效提升思政课教学评价的精准性与真实性。但是,DeepSeek类人工智能赋能思政课教学亦有其限度,表现为主客体“智能依赖”易引发教育意义缺失、“知识存伪”易引发教学内容失真与意识形态风险、“数据区隔”易导致数据利用不足与信息安全风险。为此,应通过重塑“人机共进”的主客体素养、推动人工智能语料库建设、优化数据治理效能,以全局观建强人工智能赋能高校思政课教学的进路。

关键词: 大模型技术, 思政课建设, 人工智能, DeepSeek

Abstract: DeepSeek has sparked a new round of attention to generative AI, and set off a boom in the application of artificial intelligence in the field of education. For ideological and political courses, DeepSeek can promote the innovative development of ideological and political courses from three dimensions: "teaching", "learning" and "evaluation". In terms of "teaching", DeepSeek can help the systematical aggregation of teaching content, greatly improving teachers' efficiency in lesson preparation. In terms of "learning", DeepSeek can accurately recognize students' personalized needs and generate teaching content in response. Used in "evaluation", DeepSeek can effectively improve the accuracy and authenticity of ideological and political course teaching evaluations. However, DeepSeek-like generative artificial intelligence has its limitations in empowering ideological and political courses: "AI reliance" of educate participants tends to result in the loss of the meaning of education; "knowledge falsification" in the distortion of teaching content and ideological risk, and "discriminating data" in inadequacy in data utilization and risks of information security. Therefore, it is necessary to reshape the subject-object literacy of "human-AI integration", to promote the construction of artificial intelligence corpora, to optimize data governance effectiveness to enhance the practice path of DeepSeek-like generative artificial intelligence in empowering the ideological and political courses.

Key words: large model technology, artificial intelligence, ideological and political course construction, DeepSeek

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