智慧教育视域下高校教学资源与社区教育融合模式的探索
Exploration of the Integration Model of University Teaching Resources and Community Education under the Perspective of Smart Education
徐喆 1李振江1
作者信息
摘要
社区教育作为终身教育的重要组成部分具有"无边界"的特性,能够覆盖更广泛的受众,打破传统教育的界限,是促进教育公平和包容性的强大推动力.然而,社区教育在发展中面临着资金、师资、设施等方面的限制,这直接影响其课程质量和教育效果.本文旨在于智慧教育的框架内,探索如何将高校的教学资源有效地融入社区教育,以此充分发挥高校教学资源的优势,填补社区教育在教学资源上的缺口.为此,本文深入研究了语音识别、大规模语言模型、知识图谱和个性化推荐等人工智能技术在促进高校教学资源与社区教育融合上的潜力和应用场景.此外,本文也对未来的发展趋势、所面临的挑战以及可能的解决方案进行了深入探讨,旨在推动人工智能和社区教育的深度结合,从而促进终身教育的创新与发展.
Abstract
Community education,as an essential component of lifelong education,possesses the characteristic of being"borderless",which enables it to reach a broader range of audience and break the boundaries of traditional education.It serves as a powerful force to promote educational fairness and inclusiveness.However,community education faces restrictions in funding,teaching staff,and facilities during its development,which directly affects its course quality and educational outcomes.This paper aims at exploring how to effectively integrate university teaching resources into community education within the framework of smart education in order to fully leverage the strengths of university teaching resources and fill the gaps in community education in terms of teaching resources.Therefore,this paper thoroughly investigates the potential and application scenarios of artificial intelligence technologies such as speech recognition,large-scale language models,knowledge graphs and personalized recommendations in promoting the integration of university teaching resources and community education.Additionally,this paper also deeply discusses future trends,challenges and potential solutions,with the aim to advance the deep integration of artificial intelligence and community education,thus promoting the innovation and development of lifelong education.
关键词
智慧教育/社区教育/高校教学/人工智能技术Key words
smart education/community education/university education/artificial intelligence technology引用本文复制引用
基金项目
天津市终身教育研究计划(2022)(202212)
出版年
2024
NETL
NSTL
万方数据