Spatial analytics receive increased attention in educational data mining. A critical issue in stop detection (i.e., the automatic extraction of timestamped and located stops in the movement of individuals) is a lack of validation of stop accuracy to represent phenomena of interest. Next to a radius that an actor does not exceed for a certain…

This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…

Multiple-choice tests are generally scored using a conventional number right scoring method. While this method is easy to use, it has several weaknesses. These weaknesses include decreased validity due to guessing and failure to credit partial knowledge. In an attempt to address these weaknesses, psychometricians have developed various scoring…

In conventional practice, most educators and educational researchers score cognitive tests using a dichotomous right-wrong scoring system. Although simple and straightforward, this method does not take into consideration other factors, such as partial knowledge or guessing tendencies and abilities. This paper discusses alternative scoring models:…

The use of stepwise regression has been criticized for both interpretive misunderstandings and statistical aberrations. A major statistical problem with stepwise regression and other procedures that involve multiple significance tests is the inflation of the Type I error rate. General approaches to control the family-wise error rate such as the…