There is a growing need for chemistry students to be able to handle and manipulate large datasets and analyze them in an efficient and accessible way. This creates the need to develop course materials that introduce these topics early in the undergraduate curriculum. To address this growing need, this activity introduced RStudio to students…

Trend scoring constructed response items (i.e. rescoring Time A responses at Time B) gives rise to two-way data that follow a product multinomial distribution rather than the multinomial distribution that is usually assumed. Recent work has shown that the difference in sampling model can have profound negative effects on statistics usually used to…

Conducting and publishing rigorous empirical research based on original data is essential for advancing and sustaining high-quality counseling practice. The purpose of this article is to provide a one-stop-shop for writing a rigorous quantitative Methods section in counseling and related fields. The importance of judiciously planning,…

In today's data-driven and data-informed educational landscape, leaders face increasing pressure to make decisions and present results based on what appear to be comprehensive statistical analyses. However, the ethical implications of these responsibilities can be complex, particularly when statistical results carry the potential to be…

Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for balancing weights estimators, an increasingly popular approach that solves an optimization problem to…

Quantitative reasoning (QR) is a key skill for undergraduate biology education. Despite this, many students struggle with QR. Here, we use the theoretical framework of student noticing to investigate why some students struggle with QR in introductory biology labs. Under this framework, what students notice when given new information and data…

This article introduces the concept of the carrying capacity of data (CCD), defined as an integrated, evaluative judgment of the credibility of specific data-based inferences, informed by quantitative and qualitative analyses, leavened by experience. The sequential process of evaluating the CCD is represented schematically by a framework that can…

Research studies in Educational Data Mining (EDM) often involve several variables related to student learning activities. As such, it may be necessary to run multiple statistical tests simultaneously, thereby leading to the problem of multiple comparisons. The Benjamini-Hochberg (BH) procedure is commonly used in EDM research to address this…

In this study, we propose a MOOC Analytic Statistical Visual model (MOOC-ASV) to explore students' engagement in MOOC courses and predict their performance on the basis of their behaviors logged as big data in MOOC platforms. The model has multifunctions, which performs on visually analyzing learners' data by state-of-the-art techniques. The model…

This article introduces an open-source software package--R for Qualitative Data Analysis (RQDA). RQDA is an R package for analysis of text-formatted data, which is compatible across operating platforms. It is user-friendly and seamlessly integrates with R, which makes it possible to conduct statistical analyses on qualitative coding. Alternative…

Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…

The growth of school choice programs, including publicly funded private school vouchers and charter schools, raises questions about the relative effectiveness and cost of these options. A recent Wisconsin Institute for Law & Liberty (WILL) report analyzes publicly available test score data in Wisconsin to investigate these questions. The…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

School inspections are a common feature of many education systems. These may be informed by quantitative background data about schools. It is recognised that there are pros and cons of using such quantitative information as part of the inspection process, though these have rarely been succinctly set out. This paper seeks to fill this gap by…

Large-scale analyses are a powerful and increasingly common tool for investigating a range of public health and social concerns (Pienta, O'Rourke, & Franks, 2011). This series will provide a primer on large-scale secondary analysis in school psychology, with this article focusing on considerations for researchers interested in applying and…