The practice of statistics has the power to motivate and support learning across the STEM (Science, Technology, Engineering, and Mathematics) disciplines. When connected with meaningful science contexts, statistical problem solving through the collection of data and subsequent data analysis, supported by contemporary graphing technology, presents…

Previous work has demonstrated similarities and differences between aerial and terrestrial image viewing. Aerial scene categorization, a pivotal visual processing task for gathering geoinformation, heavily depends on rotation-invariant information. Aerial image-centered research has revealed effects of low-level features on performance of various…

Predictive modeling in online education is a popular topic in learning analytics research and practice. This study proposes a novel predictive modeling method to improve model transferability over time within the same course and across different courses. The research gaps addressed are limited evidence showing whether a predictive model built on…

Predicting student performance has been a critical focus of educational research. With an effective predictive model, schools can identify potentially at-risk students and implement timely interventions to support student success. Recent developments in educational data mining (EDM) have introduced several machine learning techniques that can…

There are over one million school-age children in Missouri, and we estimate 61,000 (6% of all school-age children) are homeschooled. Missouri is one of 29 states that does not require homeschooling to be reported. Using methods that can be replicated elsewhere with publicly available data, we test three approaches to estimating homeschool…

In Single-Case Designs (SCD), the outcome variable most commonly involves some form of count data. However, statistical analyses and associated effect size (ES) calculations for count outcomes have only recently been proposed. Three recently proposed ES methods for count data are: Nonlinear Bayesian effect size (Rindskopf, 2014), Log Response…

Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on DSEM, especially on widely applied DSEM such as the two-level vector autoregressive (VAR) cross-lagged models, however, is understudied. To fill the…

The product Bayes factor (PBF) synthesizes evidence for an informative hypothesis across heterogeneous replication studies. It can be used when fixed- or random effects meta-analysis fall short. For example, when effect sizes are incomparable and cannot be pooled, or when studies diverge significantly in the populations, study designs, and…

In statistics classes, the central limit theorem has been demonstrated using simulation-based illustrations. Known population distributions such as a uniform or exponential distribution are often used to consider the behavior of the sample mean in simulated samples. Unlike such simulations, a number of real-data-based simulations are here…

Adaptive survey design refers to using targeted procedures to recruit different sampled cases. This technique strives to reduce bias and variance of survey estimates by trying to recruit a larger and more balanced set of respondents. However, it is not well understood how adaptive design can improve data and survey estimates beyond the…

The Civil Rights Data Collection (CRDC) is a mandatory survey of all public schools and school districts in the 50 states, Washington, D.C., and the Commonwealth of Puerto Rico. Since the 2009-10 CRDC, schools and school districts have reported the number of students who were referred to law enforcement and arrested at the nation's public schools.…

The authors discuss the use of surveys for collecting data from a population sample and emphasise the importance of being careful with the language of data collection. [For "The Data Files 5: Graphs for Exploring Relationships," see EJ1355504.]

The authors of this article present arguments for why and how qualitative research should be used in economic education. These arguments recognize the nature of economics as a discipline and economics educators' current expertise and preferences. The authors have five goals: (i) clarifying how and why the use of qualitative research in economic…

Jokes, cartoons, songs, videos, and quotes can be useful ways to engage students in discussion and learning key concepts about polling.

Despite the elevated importance of Data Science in Statistics, there exists limited research investigating how students learn the computing concepts and skills necessary for carrying out data science tasks. Computer Science educators have investigated how students debug their own code and how students reason through foreign code. While these…