面向慕课学习者评估的认知反应模型

王炼红; 罗志辉; 刘畅

doi:10.12263/DZXB.20211580

您当前的位置：

首页 >

文章列表页 >

面向慕课学习者评估的认知反应模型

学术论文 | 更新时间：2025-07-02

- 面向慕课学习者评估的认知反应模型
- Cognitive and Response Model for Evaluation of MOOC Learners
- 电子学报 2023年51卷第1期页码：18-25
- 作者机构：
  
  1.湖南大学电气与信息工程学院，湖南长沙 410082
  2.中国农业银行研发中心，天津 300392
- 作者简介：
  
  [ "王炼红　女，1971年5月生，湖南宁乡人.博士，副教授、硕士生导师.2011年3月至2012年3月，于美国布兰迪斯大学做访问学者.主要研究方向为信号处理、数据挖掘技术、人工智能.E-mail: wanglh@hnu.edu.cn" ]
  [ "罗志辉　男，1998年9月出生于湖南省永州市.2020年于南京农业大学获得工学学士学位.现为湖南大学电气与信息工程学院硕士研究生.主要研究方向为教育数据挖掘和机器学习.E-mail: luo1998@hnu.edu.cn" ]
- 基金信息：
  
  国家重点研发计划(2019YFE0105300);中国高等教育学会数字化课程资源专项研究课题(21SZYB15)
- DOI：10.12263/DZXB.20211580
  中图分类号： TP391
- 收稿：2021-11-24，
  
  修回：2022-06-27，
  
  纸质出版：2023-01-25
- 稿件说明：
移动端阅览
王炼红,罗志辉,刘畅.面向慕课学习者评估的认知反应模型[J].电子学报,2023,51(01):18-25.

WANG Lian-hong,LUO Zhi-hui,LIU Chang.Cognitive and Response Model for Evaluation of MOOC Learners[J].ACTA ELECTRONICA SINICA,2023,51(01):18-25.
王炼红,罗志辉,刘畅.面向慕课学习者评估的认知反应模型[J].电子学报,2023,51(01):18-25. DOI： 10.12263/DZXB.20211580.

WANG Lian-hong,LUO Zhi-hui,LIU Chang.Cognitive and Response Model for Evaluation of MOOC Learners[J].ACTA ELECTRONICA SINICA,2023,51(01):18-25. DOI： 10.12263/DZXB.20211580.

摘要

认知诊断模型从学习者的认知结构出发，建模学习者与试题之间的潜在关系，结合智能算法并根据试题作答结果可评估学习者的知识水平.大多数认知诊断模型是将学习者的高阶能力特征视为单维，忽视了后天努力的影响.为此，本文提出了一种考虑能力特征与努力特征相互补偿的具有二维高阶特征的新认知诊断模型——认知反应模型（Cognitive and Response Model，C&RM）.该模型通过设置能力特征与努力特征相互补偿机制来融合两高阶特征参数以精准建模学习者的知识水平.同时，还构建了知识点弱项特征参数，以综合考虑学习者的知识水平与不同知识点对作答试题的影响，进一步提高模型的解释性和预测精度.采用自建的HNU_SYS数据集和Math1，Math2，FrcSub公共数据集，通过实验对比分析了C&RM模型、最新的认知诊断模型和经典诊断模型.当数据训练集为70%最佳比例时，C&RM在4个数据集上分别比次优方法提升了6.3%，4.3%，3.3%，5.2%，其预测性能最佳，验证了本文模型的可行性和有效性.

Abstract

The cognitive diagnosis model starts from the learner's cognitive structure

models the potential relationship between the learner and the test questions

and combines intelligent algorithms to evaluate the learner's knowledge level according to the results of the test questions. Most cognitive diagnostic models treat learners' higher-order ability characteristics as a single dimension

ignoring the effect of acquired effort. To this end

this paper proposes a cognitive diagnostic model with two-dimensional high-order features that considers the mutual compensation of ability and effort features—cognitive and response model (C&RM). The model integrates two high-order feature parameters by setting the mutual compensation mechanism of ability feature and effort feature to accurately model the knowledge level of the learner. At the same time

the characteristic parameters of knowledge point weaknesses are also constructed to comprehensively consider the knowledge point level of learners and the influence of different knowledge points on answering questions

and further improve the interpretability and prediction accuracy of the model. Using the self-built HNU_SYS data set and the Math1

Math2

FrcSub public data sets

the C&RM model

the latest cognitive diagnostic model and the classic diagnostic model are compared and analyzed through experiments. When the data training set is at the best ratio of 70%

C&RM is improved by 6.3%

4.3%

3.3%

and 5.2% on the four data sets

respectively

and its prediction performance is the best

which verifies the feasibility of the model in this paper.

关键词

Keywords

references

祝智庭 , 魏非 . 教育信息化2.0: 智能教育启程,智慧教育领航 [J]. 电化教育研究 , 2018 , 39 ( 9 ): 5 - 16 .

ZHU Zhi-ting , WEI Fei . Educational informatization 2.0:Starting on a journey of intelligence education guided by smart education [J]. e-Education Research , 2018 , 39 ( 9 ): 5 - 16 . (in Chinese)

朱天宇 , 黄振亚 , 陈恩红 , 等 . 基于认知诊断的个性化试题推荐方法 [J]. 计算机学报 , 2017 , 40 ( 1 ): 176 - 191 .

ZHU Tian-yu , HUANG Zhen-ya , CHEN En-hong , et al . Cognitive diagnosis based personalized question recommendation [J]. Chinese Journal of Computers , 2017 , 40 ( 1 ): 176 - 191 . (in Chinese)

王超 , 刘淇 , 陈恩红 , 等 . 面向大规模认知诊断的DINA模型快速计算方法研究 [J]. 电子学报 , 2018 , 46 ( 5 ): 1047 - 1055 .

WANG Chao , LIU Qi , CHEN En-hong , et al . The rapid calculation method of dina model for large scale cognitive diagnosis [J]. Acta Electronica Sinica , 2018 , 46 ( 5 ): 1047 - 1055 . (in Chinese)

LIU H , ZHAO W , LIANG M . Pedagogical strategy model in adaptive learning system focusing on learning styles [C]// International Conference on Technologies for E-Learning and Digital Entertainment . Berlin : Springer , 2010 : 156 - 164 .

FAN X . Item response theory and classical test theory: An empirical comparison of their item/person statistics [J]. Educational & Psychological Measurement , 1998 , 58 ( 3 ): 357 - 381 .

DE LA TORRE J . DINA model and parameter estimation: A didactic [J]. Journal of Educational and Behavioral Statistics , 2009 , 34 ( 1 ): 115 - 130 .

Hartz M C . A Bayesian framework for the unified model for assessing cognitive abilities: Blending theory with practicality [J]. American Journal of Gastroenterology , 2002 , 95 ( 4 ): 906 - 909 .

LEIGHTON J P , GIERL M J , HUNKA S M . The attribute hierarchy method for cognitive assessment: A variation on Tatsuoka's rule-space approach [J]. Journal of Educational Measurement , 2004 , 41 ( 3 ): 205 - 237 .

李忧喜 , 文益民 , 易新河 , 等 . 一种改进的模糊认知诊断模型 [J]. 数据采集与处理 , 2017 , 32 ( 5 ): 958 - 969 .

LI You-xi , WEN Yi-min , YI Xin-he , et al . Revised model of fuzzy cognitive diagnosis framework [J]. Journal of Data Acquisition and Processing , 2017 , 32 ( 5 ): 958 - 969 . (in Chinese)

ZHAN P , WANG W C , JIAO H , et al . Probabilistic-input, noisy conjunctive models for cognitive diagnosis [J]. Frontiers in Psychology , 2018 , 9 : 997 - 1002 .

ZHAN P , MA W , JIAO H , et al . A sequential higher order latent structural model for hierarchical attributes in cognitive diagnostic assessments [J]. Applied Psychological Measurement , 2020 , 44 ( 1 ): 65 - 83 .

TORRE J , DOUGLAS J A . Higher-order latent trait models for cognitive diagnosis [J]. Psychometrika , 2004 , 69 ( 3 ): 333 - 353 .

LIU Q , WU R Z , CHEN E H , et al . Fuzzy cognitive diagnosis for modelling examinee performance [J]. ACM Transactions on Intelligent Systems and Technology , 2018 , 9 ( 4 ): 1 - 26 .

DE L , SONG H . Simultaneous estimation of overall and domain abilities: A higher-order IRT model approach [J]. Applied Psychological Measurement , 2009 , 33 ( 8 ): 620 - 639 .

WANG F , LIU Q , CHEN E , et al . Neural cognitive diagnosis for intelligent education systems [C]// Proceedings of the AAAI Conference on Artificial Intelligence . Menlo Park : AAAI , 2020 : 6153 - 6161 .

CHEN J , LIN J , LI X G . Research on cognitive diagnostic model based on BP neural network [C]// 2019 4th International Conference on Measurement, Information and Control (ICMIC) . Piscataway : IEEE , 2019 : 61 - 65 .

PARDOS Z A , HEFFERNAN N T , RUIZ C , et al . The composition effect: Conjuntive or compensatory? An analysis of multi-skill math questions in ITS [C]// International Conference Educational Data Mining . Las Vegas : IEDMS , 2008 : 147 - 156 .

GELFAND A E , HILLS S E , SMITH R P F M . Illustration of Bayesian inference in normal data models using Gibbs sampling [J]. Journal of the American Statistical Association , 1990 , 85 ( 412 ): 972 - 985 .

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

应试心理状态增强的学生表现预测模型

采用多头注意力机制的C&RM-MAKT预测算法

信息系统安全度量与评估模型

面向大规模认知诊断的DINA模型快速计算方法研究