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Exploring Multiple Strategic Problem Solving Behaviors in Educational Psychology Research by Using Mixture Cognitive Diagnosis Model

机译:用混合认知诊断模型探索教育心理学研究中的多种战略问题解决行为

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A mixture cognitive diagnosis model (CDM), which is called mixture multiple strategy-Deterministic, Inputs, Noisy “and” Gate (MMS-DINA) model, is proposed to investigate individual differences in the selection of response categories in multiple-strategy items. The MMS-DINA model system is an effective psychometric and statistical approach consisting of multiple strategies for practical skills diagnostic testing, which not only allows for multiple strategies of problem solving, but also allows for different strategies to be associated with different levels of difficulty. A Markov chain Monte Carlo (MCMC) algorithm for parameter estimation is given to estimate model, and four simulation studies are presented to evaluate the performance of the MCMC algorithm. Based on the available MCMC outputs, two Bayesian model selection criteria are computed for guiding the choice of the single strategy DINA model and multiple strategy DINA models. An analysis of fraction subtraction data is provided as an illustration example.
机译:提出了一种混合认知诊断模型(CDM),其称为混合多种策略确定性,输入,噪声“和”门(MMS-DINA)模型,以研究多策略项目中的响应类别的各个差异。 MMS-DINA模型系统是一种有效的心理和统计方法,包括多种实用技能诊断测试的策略,这不仅允许解决多种问题的策略,而且还允许不同的策略与不同的难度相关联。 Markov链蒙特卡罗(MCMC)用于参数估计的算法估计模型,并提出了四种模拟研究来评估MCMC算法的性能。基于可用的MCMC输出,计算两个贝叶斯模型选择标准,以指导单一策略DINA模型和多策略DINA型号的选择。提供了对分数减法数据的分析作为图示例。

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