Cognitive and Response Model for Evaluation of MOOC Learners

WANG Lian-hong; LUO Zhi-hui; LIU Chang

doi:10.12263/DZXB.20211580

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Cognitive and Response Model for Evaluation of MOOC Learners

PAPERS | 更新时间：2025-07-02

- Cognitive and Response Model for Evaluation of MOOC Learners
- ACTA ELECTRONICA SINICA Vol. 51, Issue 1, Pages: 18-25(2023)
- 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：
- 基金信息：
  
  Special Research Project on Digital Curriculum Resources of China Association of Higher Education(21SZYB15)
- DOI：10.12263/DZXB.20211580
  CLC： TP391
- Received：24 November 2021，
  
  Revised：2022-06-27，
  
  Published：25 January 2023
- 稿件说明：
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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

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