基于知识森林的多轮对话导学模型  

Multi-turn Dialogue Tutoring Model Based on Knowledge Forest

作　　者：肖鑫园 唐九阳[1,2] XIAO Xinyuan;TANG Jiuyang(School of Systems Engineering,National University of Defense Technology,Changsha 410000,China;Big Data and Decision Lab,National University of Defense Technology,Changsha 410000,China)

机构地区：[1]国防科技大学系统工程学院,长沙410000 [2]国防科技大学大数据与决策实验室,长沙410000

出　　处：《计算机科学》2025年第4期249-254,共6页Computer Science

基　　金：国家重点研发计划(2020AAA0108800)。

摘　　要：在智能导学场景中,传统知识图谱的智能导学算法无法表征知识主题间的认知关系,且传统推荐方法缺少对学生和知识体系的动态交互设计,这两种问题会导致学生在学习过程中面临知识迷航。基于知识森林的多轮对话导学模型从知识森林模型的角度出发,提出一种涵盖知识前后序结构、知识中心度与难度,动态可交互的导学模型,并围绕中心度与先验知识定量评估了学生在学习过程中面临的知识迷航代价。为验证算法的有效性,对随机学习策略的知识迷航问题进行量化分析,在学科数据集GeoQSP,HisQSP,PhyQSP和DSAQSP上进行了多轮对话导学模型与随机学习策略的对比实验。实验结果表明,基于知识森林的多轮对话导学模型可以较大程度缓解因缺乏知识主题间的认知关系和动态交互能力导致的知识迷航问题。In the intelligent tutoring scenario,the intelligent tutoring algorithm of traditional knowledge graph cannot represent the cognitive relationship between knowledge topics,and the traditional recommendation method lacks the dynamic interaction design between students and the knowledge system.These two problems will lead to students being lost in the learning process.Multi-turn dialogue tutoring model based on knowledge forest is from the perspective of the knowledge forest model.This paper proposes a tutoring model that covers the sequence structure of knowledge,knowledge centrality and difficulty,and dynamic interactive.It quantitatively evaluates the cost of knowledge lost faced by students in the learning process around the centrality and prior knowledge.In order to verify the effectiveness of the algorithm,this paper quantitatively analyzes the knowledge disorientation problem of random learning strategy,and carries out comparative experiments between multi-turn dialogue tutoring model and random learning strategy on subject datasets GeoQSP,HisQSP,PhyQSP and DSAQSP.The experimental results show that the multi-turn dialogue tutoring model based on knowledge forest can greatly alleviate the problem of knowledge lost caused by the lack of cognitive relationship between knowledge topics and the lack of dynamic interaction ability.

关 键 词：知识森林 智能导学 知识迷航 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]