Latent class analysis (LCA) is a useful statistical approach for understanding heterogeneity in a population. This article provides a pedagogical introduction to LCA modeling and provides an example of its use to understand youths' daily coping strategies. The analytic procedures are outlined for choosing the number of classes and integration of…

Multivariate count data is ubiquitous in many areas of research including the physical, biological, and social sciences. These data are traditionally modeled with the Dirichlet Multinomial distribution (DM). A new, more flexible Dirichlet-Tree Multinomial (DTM) model is gaining in popularity. Here, we consider Bayesian DTM regression models. Our…

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…

Teacher professional vision as a concept is gaining importance in research on teaching, and recently models for studying teacher professional vision and student self-regulated learning (SRL) have been proposed. There are interview and video intervention studies investigating teacher professional vision for SRL, but no real-life classroom research…

Measures of positive well-being are needed to support the shift away from a deficit-based approach to mental health. This study examined one measure, the Mental Health Continuum-Short Form (MHC-SF), as a measure of positive well-being used in school-based mental health monitoring efforts. This study used latent profile analysis (LPA) to explore…

The authoritative school climate construct, or the degree to which schools demonstrate student support and disciplinary structure, predicts several important student outcomes (e.g., racial suspension gap, student disengagement). To better understand this construct, we used multilevel latent class analysis to identify latent classes of student…

Few studies holistically examine how students experience the multiple dimensions of school climate and resilience promoting characteristics, or how these two constructs may be interrelated. This study utilised a sample of 78,550 7th, 9th, and 11th grade students in California. Roughly half of the participants were female (52%), and roughly half…

Research on data use and school Early Warning Systems (EWS) notes a central practice of researchers and practitioners is to search for patterns in student data to predict outcomes so schools can support success when students experience challenges. Yet, the domain lacks a means to visualize the rich longitudinal data that schools collect. Here, we…

The National Assessment of Educational Progress (NAEP) program only reports state-level subgroup results if it samples at least 62 students identifying with the subgroup. Since some subgroups constitute small proportions of many states' general student populations, these minority subgroups are seldom sufficiently sampled to meet this sample size…

The unskilled and unaware effect occurs when low-performing individuals overestimate their performance, while high performers underestimate it. The aim of the present study was to examine an occurrence of the unskilled and unaware effect in a self-assessment of creative performance, linking this phenomenon to creative metacognition (CMC) research.…

Purpose: Self-efficacy plays a crucial role in achievement; and thus, it is important to determine the factors affecting self-efficacy. It has been known that one's reflections and evaluations of their thoughts, emotions, and behaviors are of paramount importance in the development of self-efficacy. Therefore, the aim of this study was to…

The test of understanding graphs in kinematics (TUG-K) has widely been used to assess students' understanding of this subject. The TUG-K poses different objectives to the test takers such as (1) the selection of a graph from a textual description, (2) the selection of corresponding graphs, and (3) the selection of a textual description from a…

Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…

Recent work in predictive modeling has called for increased scrutiny of how models generalize between different populations within the training data. Using interaction data from 69,174 students who used an online mathematics platform over an entire school year, we trained a sensor-free affect detection model and studied its generalizability to…

Problematic gaming behavior is an important problem that may lead to a recently introduced psychiatric condition named internet gaming disorder (IGD). Gaming addiction has been reported to have major influence on the lives of adolescents and young adults affected by it. Our aim was to determine relationships between gaming-related parameters,…