Given the increased focus of educational research on what works for whom and under what circumstances over the last decade, educational researchers are increasingly turning toward mixture models to identify heterogeneous subgroups among students. Such data are inherently nested, as students are nested within classrooms and schools. Yet there has…

Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…

Postsecondary Institutions are under pressure to explain their costs. Noninstructional administrative staff represent a significant cost and number of people working in higher education. Postsecondary institutions hire noninstructional staff in response to their specific needs related to educational activity at the institution. Past research on…

This work considers group discussion data, as recorded in video conferencing settings, and demonstrates the ability to use readily available computational tools to glean important information characterizing the dynamics of the group discussion. In particular, our toolbox reveals a number of important characteristics of a discussion, including who…

As data-informed decision-making continues to evolve across multiple disciplines in higher education institutions, and as the role of research administration continues to expand from proposal submissions, compliance, and managing research and development expenditures to a profession with an active partnership with investigators to support…

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.,…

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…

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…

Predictive models play a pivotal role in education by aiding learning, teaching, and assessment processes. However, they have the potential to perpetuate educational inequalities through algorithmic biases. This paper investigates how behavioral differences across demographic groups of different sizes propagate through the student success modeling…

Open science has become an important part of contemporary science, and some open science practices (such as data sharing) have been prominent aspects of Educational Data Mining (EDM) since the start of the field. There have been recent pushes for EDM to more fully embrace the range of open science practices that are seen in other fields. In this…

Purpose: The main objective of the paper is to develop an investment model using data envelopment analysis (DEA) that provides a decision-making framework to allocate resources efficiently, such that the relative efficiency is improved within an available investment budget. Design/methodology/approach: Firstly, DEA models are used to evaluate the…

We investigated the effect of careless or insufficient effort (C/IE) responses in a study using Amazon's Mechanical Turk. A factor mixture model was used to identify latent classes based on the pattern of responses with biases and examine the effect of C/IE responses on the fit of the theoretical model.

Video data offer important insights into social processes because they enable direct observation of real-life social interaction. Though such data have become abundant and increasingly accessible, they pose challenges to scalability and measurement. Computer vision (CV), i.e., software-based automated analysis of visual material, can help address…

This study aims to determine the graphical literacy levels of middle school mathematics teachers. The participants of the study consisted of 33 middle school mathematics teachers working in different provinces. The data of the study were collected with the help of the graphical literacy test created by the researchers. The data were analyzed by…