人工智能赋能应用型高校大学生学习力精准提升的路径研究
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南京工程学院交通工程学院,江苏 南京, 211167

作者简介:

王潘潘,硕士,讲师,研究方向为大学生思想政治教育。E-mail:1185967612@qq.com

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G642

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An Exploration of Pathways to Augment the Learning Capacities of Students in Application-Oriented Higher Education through the Empowerment of Artificial Intelligence
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School of Traffic Engineering, Nanjing Institute of Technology, Nanjing 211167 , China

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    摘要:

    本研究以教育数字化转型为背景,针对应用型高校大学生学习力培养中同质化、粗放的问题,构建了“数据治理—智能诊断—靶向干预”三阶实施框架,通过将人工智能技术与教育创新理念融合,创新地提出了精准育人实施路径:在数据治理层整合多源数据构建动态学生画像;在智能诊断层建立分层预警与潜力识别模型;在靶向干预层设计产教协同与混合学习机制。具体而言,靶向干预层通过产教协同与混合学习机制,设计了分层响应的干预策略,包括建立学业危机、潜力激发、特殊群体三级干预策略;开发岗位能力与课程内容的对接体系;利用智能分组系统提升团队协作效率。实践表明,该路径显著提升了学业危机识别效率,缩短了学生向职业角色转化的过渡周期,增强了学生的实践能力与岗位适应能力,创新了应用型高校人才培养模式的思路和方法。本研究不仅为应用型高校的教育数字化转型提供具体实践指导,也为教育强国建设提供新思路与方法。

    Abstract:

    This study unfolds against the dynamic backdrop of digital transformation in education, tackling the pressing challenges of homogenization and broad-spectrum methodologies in nurturing learning capabilities within application-oriented higher education institutions. A three-tiered implementation framework that encompasses “data governance—intelligent diagnosis—targeted intervention” have been meticulously crafted. By integrating artificial intelligence technology with pioneering educational paradigms, a meticulously crafted pathway for talent cultivation has been presented: at the data governance level, the diverse data sources have been amalgamated to construct dynamic and comprehensive student profiles; at the intelligent diagnostic level, a stratified early warning systems and models for potential identification has been developed; at the targeted intervention level, the innovative mechanisms that foster collaborative integration between industry and education alongside blended learning approaches has been devised. Specifically, within the realm of targeted intervention strategies, the tiered response frameworks have been crafted through synergistic collaborations between industry and academia, alongside innovative blended learning modalities. The approach encompasses the establishment of three distinct levels of interventions: academic crisis management, potential enhancement initiatives and specialized support for unique groups. Furthermore, a comprehensive system that aligns job competencies with curricular content while employing an intelligent grouping mechanism designed to optimize team collaboration efficiency are committed to be developed. Practical applications reveal that this pathway significantly improves the efficiency of identifying academic crises, while concurrently expediting students transition into professional roles. Furthermore, it cultivates students practical skills and adaptability to job requirements, while innovating ideas and methodologies for talent cultivation in application-oriented higher education institutions. This research not only furnishes concrete practical guidance for application-oriented higher education institutions navigating digital transformation but also offers novel concepts and strategies for building a strong educational nation.

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引用本文

王潘潘,柯靖琪.人工智能赋能应用型高校大学生学习力精准提升的路径研究[J].南京工程学院学报(社会科学版),2025,25(1):23-29.

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  • 收稿日期:2025-02-18
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  • 在线发布日期: 2025-05-09
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