基于人工智能的“五研共同体”模式探索与研究

Exploration and Research on the “Five Research Communities” Model Based on AI Theme

数字化转型是数字技术发展的必然结果,也是教育领域数字化改革逐渐加速的必然选择。人工智能技术可作为教育数字化转型的实施路径之一,但在它赋能现代教育、进一步促进跨学科融合与创新教育发展的同时,也暴露出应用环境参差不齐、课程定位不够清晰、专业素质尚未匹配、学习能力难以适应等诸多问题。经深度剖析、项目设计、实验验证,作者尝试在数字化转型背景下,合理利用“双减”课后托管时间,以信息技术学科为出发点,以探究身边的AI实例为导向,利用在线平台实现区域协同研究,吸纳与学习活动相关的各类主体,构建“五研共同体”,通过群体性知识建构和跨学科探究实验,引导学生亲历混合式学习全过程,对AI产生立体多维理解,为AI教学研究初步建立起流程运作模型。这是现实机遇下AI领域教学适应数字化转型时代需求的战略路径,也是AI项目引导内部资源配置的重要策略。

Digital transformation is the necessary result of the development of digital technology,and it also is the choice of the gradually accelerating digital reform in the field of education.Artificial intelligence technology can be used as one of the implementation paths for the digital transformation of education,however,there are still many problems in enabling modern education and further promoting the development of interdisciplinary integration and innovation education,for instance,the uneven application environment,the unclear curriculum positioning,the lack of matching of professional quality,and the difficulty of learning ability.After in-depth analysis,project design and experimental verification,the authors try to use the after-school care under the background of“double reduction”.Take the information technology discipline as the starting point and being orientated by exploring the surrounding AI examples,the online platform is used to realize the regional collaborative research.Then,the“Five research community”is built by absorbing all subjects related to learning activities.Through the construction of group knowledge and the interdisciplinary inquiry experiments,students are encouraged to engage into the whole process of blended learning,which aim is to produce a stereographically multidimensional understanding of AI and initially establish a process operation model for AI teaching and research.It is a strategic path for AI field teaching to adapt to the needs of the digital transformation era under the realistic opportunity,while it is an important strategy for AI projects to guide the internal resource allocation.