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作 者:杨良盼 鲍文霞[1] 宋玉茹 YANG Liang-pan(School of Electronics and Information Engineering,Anhui University,Hefei 23060,China)
出 处:《长春工程学院学报(社会科学版)》2024年第4期28-31,共4页Journal of Changchun Institute of Technology(Social Sciences Edition)
基 金:2023年中共安徽省委教育工委“第二批全省高校党建工作标杆院系”(安徽大学电子信息工程学院党委)培育创建项目研究成果(项目编号:2023bgyx004);2022年安徽大学党建研究重点课题“大数据视域下高校学生党员教育方法创新研究”(项目编号:ahdxdjkt2022-003)。
摘 要:线上线下混合式学习模式在大学生党员继续教育方面的普及推广,为高校党组织应用多模态学习分析技术创新开展大学生党员继续教育效果跟踪评价创造了有利条件。系统阐述了应用多模态学习分析技术创新大学生党员继续教育评价方式的价值和意义,深入探究了多模态数据驱动的大学生党员继续教育的技术路径,最后结合A大学电子学院100名学生党员继续教育产生的多模态数据开展了实证研究。实证结果(准确率83.33%)证明了多模态学习分析在大学生党员继续教育跟踪评价方面具有较大的应用价值,对提升高校党建工作水平和思想政治教育效果具有重要意义。The widespread adoption of a hybrid learning model,integrating both online and offline components,in the continuing education of college CPC(The Communist Party of China)Party members has established a robust framework for CPC Party organizations within higher education institutions to leverage innovative multimodal learning analytic technologies for tracking and evaluating the effectiveness of such educational initiatives.This paper systematically articulates the value and significance of employing multimodal learning analysis technology to enhance evaluation methodologies pertaining to the ongoing education of university CPC Party members.It delves into the technical pathways facilitated by multimodal data in this context and culminates in an empirical study examining the multimodal data generated from the continuing education efforts involving 100 students who are CPC Party members at A University’s School of Electronics.The empirical findings(with an accuracy rate of 83.33%)substantiate that multimodal learning analysis holds substantial application potential for monitoring and assessing the continuing education outcomes among college CPC Party members,thereby significantly contributing to advancing CPC Party-building efforts as well as enhancing ideological and political education within colleges and universities.
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