There has been a growing interest in approaches based on machine learning (ML) for detecting test collusion as an alternative to the traditional methods. Clustering analysis under an unsupervised learning technique appears especially promising to detect group collusion. In this study, the effectiveness of hierarchical agglomerative clustering…

In computerized adaptive testing, overexposure of items in the bank is a serious problem and might result in item compromise. We develop an item selection algorithm that utilizes the entire bank well and reduces the overexposure of items. The algorithm is based on collaborative filtering and selects an item in two stages. In the first stage, a set…

There is much discussion about and many policies to address achievement gaps in education among groups of students. The focus here is on a different gap and it is argued that it also should be of concern. Speed gaps are differences in how quickly different groups of students answer the questions on academic assessments. To investigate some speed…