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…

Measuring opportunities to learn (OTL) is crucial for evaluating education quality and equity, but obtaining accurate and comprehensive OTL data at a large scale remains challenging. We attempt to address this issue by investigating measurement concerns in data collection and sampling. With the primary goal of estimating group-level OTLs for large…

Purpose: The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size,…

Family income questions in general purpose surveys are usually collected with either a single-question summary design or a multiple-question disaggregation design. It is unclear how estimates from the two approaches agree with each other. The current paper takes advantage of a large-scale survey that has collected family income with both methods.…

CODAP is a widely-used programming environment for secondary school data science. Its direct-manipulation-based design offers many advantages to learners, especially younger students. Unfortunately, these same advantages can become a liability when it comes to repeating operations consistently, replaying operations (for reproducibility), and also…

There is widespread concern about declining literacy skills in recent young Japanese. The present study investigated how higher-level reading and writing proficiencies are underpinned by basic literacy skills in Japanese adolescents. From a large database of the most popular literacy exams in Japan, we retrospectively analyzed word- and text-level…

While extensive research has explored Second Language Vocabulary Acquisition (SLVA) acquisition, there has been a lack of comprehensive bibliometric analysis on this topic. This study addresses this gap by investigating research trends and collaboration networks in SLVA over the past 24 years. Publications on SLVA were retrieved and analysed using…

Currently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, but their analyses are challenging. The present paper mathematically derived, empirically compared, and step-by-step demonstrated three types (i.e.,…

In this article, we consider how to make data more meaningful to students through the choice of data and the activities we use them in drawing upon students lived experiences more in the teaching of statistics and data science courses. In translating scholarship around culturally relevant pedagogy from the fields of education and mathematics…

Data reported from memory can be unreliable. A simple activity lets students experience this firsthand.

The visual analysis of data presented in time-series graphs are common in single-case design (SCD) research and applied practice in school psychology. A growing body of research suggests that visual analysts' ratings are often influenced by construct-irrelevant features including Y-axis truncation and compression of the number of data points per…

The COVID-19 pandemic has forced the rapid adoption of remote teaching modalities including "hyflex" where students attend some class sessions in person and some online. Managing the hyflex course requires faculty to quickly generate several reports and to update these reports rapidly when the authorities adjust the rules, students…

Today's college students increasingly rely on technology in their daily activities, and a basic awareness of data privacy is becoming essential from both a personal and professional standpoint. This article describes the design of an interdisciplinary undergraduate course focused on data privacy law. It outlines the key content areas that…

What does it mean for a model to be a better model? One conceptualization, indeed a common one in Educational Data Mining, is that a better model is the one that fits the data better, that is, higher prediction accuracy. However, oftentimes, models that maximize prediction accuracy do not provide meaningful parameter estimates, making them less…

Although the fields of educational data mining and learning analytics have grown significantly in terms of analytical sophistication and the breadth of applications, the impact on theory-building has been limited. To move these fields forward, studies should not only be driven by learning theories, but should also use analytics to in form and…