陕西开放大学学报

随着我国老龄化进程加快,老年教育需求呈多元化、个性化,实现课程资源与老年学习者需求精准匹配成为成人教育核心问题。本文基于知识图谱技术,融合内容推荐、协同过滤与图推理理论,构建老年教育多维度课程推荐模型,引入Knowles成人学习理论与终身学习体系,提出多维度指标体系,结合实证数据验证模型有效性。结果显示,模型推荐准确率、用户满意度、类别覆盖率均显著优于传统方法。研究为突破地域样本局限、提升普适性,提出跨区域数据融合与联邦学习优化方案,设计老年教育实施策略,为老年教育资源精准供给提供技术路径,为成人教育数字化转型与信息化建设提供理论与实践参考。

With the acceleration of the aging process in our country, the demand for elderly education has become diversified and personalized. Achieving precise matching between course resources and the needs of elderly learners has become a core issue in adult education. Based on knowledge graph technology, this paper integrates content recommendation, collaborative filtering and graph reasoning theories to construct a multi-dimensional course recommendation model for elderly education. It introduces Knowles' adult learning theory and the lifelong learning system, and proposes a multi-dimensional index system. Combined with empirical data, the validity of the model is verified. The results show that the model's recommendation accuracy, user satisfaction and category coverage are significantly better than traditional methods. The research proposes cross-regional data fusion and federated learning optimization schemes, designs elderly education implementation strategies, providing a technical path for the precise supply of elderly education resources, and offering theoretical and practical references for the digital transformation and informatization construction of adult education.