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基于形式背景构建多分知识结构与个性化指导学习的方法

The method of constructing polytomous knowledge structure and personalized instruction learning based on formal context
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摘要 多分知识结构的提出有助于评价个体对于问题的掌握程度,而操作程序映射是构建多分知识结构的重要工具之一,操作程序映射是问题层次集到操作程序集的映射.着重考虑将操作程序映射转化为形式背景,并通过合取模型构建多分知识结构、寻找学习路径,指导个性化学习.首先,提出通过构建面向操作程序概念格求解合取操作程序映射诱导的多分知识结构的方法.其次,研究面向操作程序概念格中内涵之间的关系,给出逐步学习操作程序的路径图和个性化指导学习的方法,并给出了相应的算法.最后,选取“一元一次方程”这一章节作为知识域进行分析,验证了算法的可行性. The establishment of polytomous knowledge structure is helpful to evaluate the degree of individual mastery of the problem,and the operation procedure map is one of the important tools to construct polytomous knowledge structure.The operation procedure map refers to the map from the problem level set to the operation procedure set.In this paper,the operation procedure map is transformed into formal context,based on which constructing polytomous knowledge structure,finding learning paths and guiding personalized learning are proposed in conjunction model.Firstly,a method is proposed to solve the polytomous knowledge structure induced by conjunctive operation procedure map by constructing operation⁃procedure⁃oriented concept lattices.Secondly,the relationship between intensions in the operation⁃procedure⁃oriented concept lattice is studied.The path graph of learning operation procedure is introduced step by step,the method of personalized instruction learning is provided,and the corresponding algorithms are given.Finally,the chapter of"the root equation of a degree"is selected as the knowledge domain to analyze and verify the feasibility of the algorithm.
作者 林宇静 李进金 陈惠琴 Lin Yujing;Li Jinjin;Chen Huiqin(School of Mathematics and Statistics,Minnan Normal University,Zhangzhou,363000,China)
出处 《南京大学学报(自然科学版)》 CAS CSCD 北大核心 2024年第3期477-490,共14页 Journal of Nanjing University(Natural Science)
基金 国家自然科学基金(11871259,12271191) 福建省自然科学基金(2020J02043,2022J01306,2022J05169)。
关键词 多分知识结构 形式背景 合取操作程序映射 学习路径 个性化指导学习 polytomous knowledge structure formal context conjunctive operation procedure map learning path personalized instruction learning
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