Teacher classroom teaching behavior indicators serve as a crucial foundation for guiding instructional evaluation. Existing indicator system suffers from limitations such as strong subjectivity and weak contextual generalization capabilities. Generalized category discovery (GCD) enables automatic data clustering to identify known categories and…

Statewide longitudinal data systems (SLDSs) often rely on personal identifiers to securely link individual-level data across early childhood, K-12, higher education, and the workforce. However, different sectors use different types of personal identifiers which can make accurately connecting records difficult. Driver's license data offers a single…

Response styles pose great threats to psychological measurements. This research compares IRTree models and anchoring vignettes in addressing response styles and estimating the target traits. It also explores the potential of combining them at the item level and total-score level (ratios of extreme and middle responses to vignettes). Four models…

Adapting interventions based on learner progress is paramount to the effectiveness of interventions in special education and applied behavior analysis. Although there is some research on effective methods for training practitioners to make general instructional decisions (e.g., modify an intervention) based on graphed performance data, research on…

Institutional researchers are acutely aware of the systemic inequities pervasive throughout higher education in the United States because the data that we collect, analyze, visualize, and disseminate quantifies and reveals them. As calls for addressing issues of equity have intensified across campuses, the question of how institutional research…

Background: Randomized controlled trials (RCTs) give unbiased estimates of average effects. However, positive effects for the majority of students may mask harmful effects for smaller subgroups, and RCTs often have too small a sample to estimate these subgroup effects. In many RCTs, covariate and outcome data are drawn from a larger database. For…

Learning analytics (LA) provides insight into student performance and progress, allowing for targeted interventions and support to improve the student learning experience. Uses of LA are diverse, including measuring student engagement, retention, progression, student well-being and curriculum development. This article provides perspectives on the…

Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…

Data-based decision-making, which involves evaluating students' progress and making instructional decisions, is an integral competency for preservice teachers. Several studies have found that visual aids, such as decision-making models, may be an effective way to train preservice teachers to make instructional decisions. The purpose of this study…

In recent years, there has been growing interest in the use of data-driven learning (DDL) in L2 writing instruction. This paper examined whether and to what extent DDL activities could enhance the writing complexity, accuracy, and fluency (CAF) of 30 Thai EFL learners. The presentation of DDL in this study was hands-on concordancing with the…

Through time-series graphs, teachers often evaluate progress monitoring data to make both low- and high-stakes decisions for students. The construction of these graphs--specifically, the presence of an aimline and the data points per x- to y-axis ratio (DPPXYR)--may impact decisions teachers make. The purpose of this study was to evaluate the…

Although research into the relationship between quantitative literacy (QL) and news reporting is sparse, the consensus among researchers is that journalists tend not to place QL very highly among their professional values and that journalism suffers as a consequence. This paper is an attempt to provide concrete examples of the ways in which news…

Randomized A/B tests within online learning platforms represent an exciting direction in learning sciences. With minimal assumptions, they allow causal effect estimation without confounding bias and exact statistical inference even in small samples. However, often experimental samples and/or treatment effects are small, A/B tests are underpowered,…

The question: "What is an appropriate role for AI?" is the subject of much discussion and interest. Arguments about whether AI should be a "human replacing" technology or a "human assisting" technology frequently take centre stage. Education is no exception when it comes to questions about the role that AI should…

This study uses the log data from Moodle learning management system for predicting student learning performance in the first third of a semester. Since the quality of the data has great influence on the accuracy of machine learning, five major data transmission methods are used to enhance data quality of log file in the data preprocessing stage.…