检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:陈锦 林江豪 阳爱民 李心广 CHEN Jin;LIN Jianghao;YANG Aimin;LI Xinguang(School of Foreign Languages,South China University of Technology,Guangzhou 510641,China;Laboratory for Language Engineering and Computing,Guangdong University of Foreign Studies,Guangzhou 510006,China;School of Automation,Guangdong University of Technology,Guangzhou 510006,China)
机构地区:[1]华南理工大学外国语学院,广东广州510641 [2]广东外语外贸大学语言工程与计算实验室,广东广州510006 [3]广东工业大学自动化学院,广东广州510006
出 处:《郑州大学学报(理学版)》2024年第4期88-94,共7页Journal of Zhengzhou University:Natural Science Edition
基 金:全国教育科学规划教育部青年课题(EIA180491)。
摘 要:针对现有的认知诊断模型信息利用不充分以及依赖局部作答信息而导致诊断精度低的问题,提出了基于改进级联宽度学习的自适应认知诊断方法。首先,提取题目的语义、参数等特征,采用无偏差加权进行融合。其次,提出了改进的级联宽度学习系统(improved cascade of broad learning system,ICBLS),旨在学习全序列作答信息,利用残差结构解决长序列学习遗忘的问题,采用网格搜索法确定最优参数组合,进而构建认知诊断模型。最后,经过非线性分类器实现知识状态的分类。以BP神经网络、Bi-LSTM、Bi-GRU为基线模型,在实际的接受性任务中进行了实验验证。结果表明,基于ICBLS的模型获得的最高模式准确率为95.74%,平均属性准确率为98.31%。并且,通过消融实验证明了题目的语义信息有利于模型更准确地发现被试的语言理解能力。The existing cognitive diagnosis models could not use enough information and relied on local response information.Aiming at the problem of low diagnostic accuracy,an adaptive cognitive diagnostic method based on improved cascade of broad learning was proposed.Firstly,the semantic features and parameters of the items were extracted and integrated into vectors via an unbiased weighted method.Then,an improved cascade of broad learning system(ICBLS)was put forward to acquire the full sequence of the response information,and solve the problem of long sequence learning and forgetting with the residual structure.The grid search method was used to determine the optimal combination of parameters,and then a cognitive diagnosis model was built.Finally,the classification of the knowledge state was realized through the nonlinear classifier.With BP neural network,Bi-LSTM,Bi-GRU as the baseline models,experimental verification was carried out on the actual receptive task.The results showed that ICBLS model achieved the highest model accuracy of 95.74%and the average attribute accuracy rate of 98.31%.Moreover,the ablation experiment indicated that the semantic information of items could help the model to detect the language comprehension ability of the learners more accurately.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:3.143.255.34