In the current study, we compare propensity score (PS) matching methods for data with a cross-classified structure, where each individual is clustered within more than one group, but the groups are not hierarchically organized. Through a Monte Carlo simulation study, we compared sequential cluster matching (SCM), preferential within cluster…

The purpose of this study is to demonstrate clustering methods within a functional data analysis (FDA) framework for identifying subgroups of individuals that may be exhibiting categories of misfit. Person response functions (PRFs) estimated within a FDA framework (FDA-PRFs) provide graphical displays that can aid in the identification of persons…

The importance of data literacies and the shortage of research surrounding data science in elementary schools motivated this research-practice partnership (RPP) between researchers and teachers from a STEM elementary school. We used a narrative case study methodology to describe the instructional practices of one music teacher who co-designed a…