赵文政. 多智能体赋能高校思想政治教育数字化转型:逻辑、问题和路径J. 内江师范学院学报, 2026, 41(1): 84-92. DOI: 10.13603/j.cnki.51-1621/z.2026.01.014
    引用本文: 赵文政. 多智能体赋能高校思想政治教育数字化转型:逻辑、问题和路径J. 内江师范学院学报, 2026, 41(1): 84-92. DOI: 10.13603/j.cnki.51-1621/z.2026.01.014
    ZHAO Wenzheng. Multi-agent Empowerment for the Digital Transformation of Moral and Core Values Education in Higher Education: The Rationale, Problems, and Practical PathsJ. Journal of Neijiang Normal University, 2026, 41(1): 84-92. DOI: 10.13603/j.cnki.51-1621/z.2026.01.014
    Citation: ZHAO Wenzheng. Multi-agent Empowerment for the Digital Transformation of Moral and Core Values Education in Higher Education: The Rationale, Problems, and Practical PathsJ. Journal of Neijiang Normal University, 2026, 41(1): 84-92. DOI: 10.13603/j.cnki.51-1621/z.2026.01.014

    多智能体赋能高校思想政治教育数字化转型:逻辑、问题和路径

    Multi-agent Empowerment for the Digital Transformation of Moral and Core Values Education in Higher Education: The Rationale, Problems, and Practical Paths

    • 摘要: 数字时代高校思想政治教育受制于智能交互主体异质性与价值引领同质化的结构性耦合困境。多智能体赋能高校思想政治教育数字化转型的逻辑表现为以多智能体协同,实现个体与群体互动的双重增益效应;以群体个性化融合,实现数字化转型中的学习方式创新;以智能化资源配置,实现基于数据驱动的教育公平保障;以数据动态反馈,实现智能系统支持的自适应教育模式,实现教育质量的动态持续优化。然而,多智能体平台的智能系统集成难题、数字化目标与内容适配的深度矛盾、智能化教学中数据隐私的伦理风险以及教师与学生数字化适应性的角色重塑交织成其赋能的现实问题。基于高校思想政治教育的实际情境,我国应开发技术框架,构建多智能体协同平台的设计与运行模式;加强学习创新,全面升级思想政治课程内容;持续强化原则,优化公正透明的数据管理与教育公平机制;深度转变角色,转型从知识传授者到学习引导者的教师素养。

       

      Abstract: Education of moral and core values (EMCV) in colleges and universities faces a structural coupling dilemma in the digital era. This dilemma arises from the heterogeneity among intelligent interaction subjects, paired with the homogenization in value guidance. The logic of multi-agent empowerment in the digital transformation of EMCV in higher education institutions is reflected in four key aspects. Firstly, multi-agent collaboration helps achieve dual gain effects in individual and group interactions. Secondly, the fusion of group personalization drives innovative learning approaches during digital transformation. Thirdly, intelligent resource distribution ensures educational equity through data-driven resource allocation. Fourthly, adaptive educational models are supported by intelligent systems and dynamic feedback-driven optimization. However, practical challenges arise from the integration of intelligent systems on multi-agent platforms, as well as the profound contradiction between digital objectives and content adaptation. Moreover, ethical risks concerning data privacy in intelligent teaching also pose significant issues. Additionally, there is the issue of the role reshaping of both teachers and students in terms of digital adaptability. Therefore, China should develop a comprehensive technological framework to advance its EMCV in fours aspects. (1) This framework should focus on platform construction, content innovation, equity assurance, and the transformation of teachers’ role. (2) This involves designing and implementing a multi-agent collaborative platform that defines the operational model for integrating resources and efforts across different stakeholders. (3) This initiative aims to comprehensively upgrade the content of ideological and political courses to foster learning innovation. It has the parallel goal of reinforcing principles of fair and transparent data management to optimize educational equity mechanisms. (4) A key aspect is the deep transformation of teachers’ roles, shifting their competencies from being primary knowledge transmitters to becoming facilitators of students’learning.

       

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