Predicting Working Memory Failure: A Subjective Bayesian Approach to Model Selection
预测工作记忆失误：主观贝叶斯模型选择方法
We use Bayes factors to compare two alternative characterizations of human working memory load in their ability to predict errors in database query-writing tasks. The first measures working memory load by the number of different features each task contains, while the second attempts instead to measure the complexity of the task by giving more weight to features that require more mental time for their correct execution. We reanalyze data from a previously conducted experiment…