Educational Testing Service, Princeton, NJ, USA.
Psychometrika. 2018 Mar;83(1):67-88. doi: 10.1007/s11336-017-9570-0. Epub 2017 Apr 26.
Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and simulation studies report on parameter recovery within the context of a simple strategy game. The model is then applied to empirical data from an educational game. Estimates from the model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.
任务内动作可以提供关于学生能力的额外信息,但建模具有挑战性。本文探讨了使用决策的认知模型——马尔可夫决策过程,在任务内动作和感兴趣的潜在特征之间提供映射的可能性。研究了模型的心理测量学性质,并在简单策略游戏的背景下进行了参数恢复的模拟研究。然后将该模型应用于教育游戏的实证数据。模型的估计与后测结果的相关性强于仅基于结果数据的部分信用IRT 模型。