ABSTRACT

The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework compared to the traditional frequentist approach are discussed. The application of the model is illustrated with real data from a logical ability test. The results show how the incorporation of previous practice into the linear logistic model improves the fit of the model as well as the prediction of the Rasch item difficulty estimates. The model provides evidence of learning associated with two of the logic operations involved in the items, which supports the hypothesis of practice effects in deductive reasoning tasks.

摘要

本研究提出了一种用于估计和测试特定于操作的学习模型的贝叶斯方法，这是线性逻辑测试模型的一种变体，它允许测量在测试期间由于重复使用所涉及的操作而发生的学习项中。讨论了使用贝叶斯框架与传统频率论方法相比的优势。通过逻辑能力测试的真实数据说明了该模型的应用。结果表明，将先前的实践纳入线性逻辑模型如何改进模型的拟合以及 Rasch 项目难度估计的预测。该模型提供了与项目中涉及的两个逻辑运算相关的学习证据，