Monitoring applications (MAs) use digital and online tools to collect and track data on student behavior, and they have become increasingly popular among schools. Empirical research on these complex surveillance platforms is scant, and little is known about the efficacy or impact that they have on students. This study used a multi-method…

This article details an exploratory data analysis project using the Common Online Data Analysis Platform (CODAP) based on the "Guidelines for Assessment and Instruction in Statistics Education" (GAISE) four-part statistical problem-solving model. The project goal was to answer what similarities and differences exist within the school…

Since data collection technologies has become a part of daily life, measurement and data requirements now permeate many state mathematics standards, beginning as early as kindergarten and extending through high school. For example, the Standards for Mathematical Content, recommend that kindergarteners "describe and compare measurable…

Data analysis and interpretation has always played a fundamental role in the scientific curricula of high school students. The spread of digitalization has further increased the number of learning environments whereby this topic can be effectively taught: as a matter of fact, the ever-growing diffusion of data science across diverse sectors of…

Students' emotions in the classroom are highly dynamic and thus typically strongly vary from one moment to the next. Methodologies like experience sampling and daily diaries have been increasingly used to capture these momentary emotional states and its fluctuations. A recurring question is to what extent aggregated state ratings of emotions over…

Equating is a statistical procedure used to adjust for the difference in form difficulty such that scores on those forms can be used and interpreted comparably. In practice, however, equating methods are often implemented without considering the extent to which two forms differ in difficulty. The study aims to examine the effect of the magnitude…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…

Technological advances, artificial intelligence innovations, and widespread computing have all combined to necessitate a new generation of knowledge workers where data becomes a ubiquitous part of decision making (Sutton, 2006). Teaching today's students through the application of this "new" knowledge to long-established fields…

Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…

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…

In this research article, Sarah Dryden-Peterson explores the concept of researcher positionality, focusing on its malleability over time. The methodological analysis is situated in an empirical study of history teaching and learning in Cape Town, South Africa, schools in 1998 and 2019. Dryden-Peterson argues that researcher positionality is often…

In light of the replication crisis in psychology, null-hypothesis significance testing (NHST) and "p"-values have been heavily criticized and various alternatives have been proposed, ranging from slight modifications of the current paradigm to banning "p"-values from journals. Since the physics education research community…

State and local education agencies continue to make an effort to systematically assess school climate through student surveys. These assessments typically collect data from individual students about their perceptions of different components of the school and their relationship to individuals in the school and aggregate those responses to the…