This article describes and justifies a reporting standard to improve data use documentation in Agent-Based Modelling. Following the development of reporting standards for models themselves, empirical modelling has now developed to the point where these standards need to take equally effective account of data use (which previously has tended to be…

Social research is rich in methods for analysing societal differences. Yet, although qualitative characteristics are a key component to understanding such differences, the analysis of qualitative data remains a major methodological challenge in most social research, particularly when aiming to compare more than a few cases. The article proposes an…

There is a growing consensus that the ability to understand and process visual information should be part of the second language (L2) listening construct; however, the findings of studies exploring the use of visuals in L2 listening assessment contexts remain inconclusive. To better understand the underlying reasons for these inconclusive results,…

This technical report provides an overview of the datasets and methodology used in the main report, "Investigating the Potential Use of Long-Term School and College Destination Measures. Final Report" (see ED619071). The purpose of the main report is to investigate the potential for using Department for Education's (DfE's) Longitudinal…

Higher education institutions across the country have examined equity in education outcomes through disaggregating student demographic data. However, it is not as common for academic institutions to also examine student learning outcomes for inequities in student learning. The current study explores what the greatest contributors are for the lack…

Categorical data become increasingly ubiquitous in the modern big data era. In this dissertation, we propose novel statistical learning and inference methods for large-scale categorical data, focusing on latent variable models and their applications to psychometrics. In psychometric assessments, the subjects' underlying aptitude often cannot be…

In recent years professional accountancy bodies (e.g., CPA), accreditation institutions (e.g., AACSB) and employers have steadily raised, and continue to raise expectations regarding the need for accounting graduates to demonstrate skills in data analytics. One of the obstacles accounting instructors face in seeking to implement data analytics,…

Abstract Targeted metagenomics is a rapidly expanding technology to analyze complex biological samples and genetic monitoring of environmental samples. In this research field, data analytical aspects play a crucial role. In order to teach targeted metagenomics data analysis, we developed a 4-week inquiry-driven modular course-based undergraduate…

The "Information Systems Education Journal" has published uninterrupted since 2003. Over its publication history, it has covered myriad topics related to information systems education including model curriculum, outcomes assessment, online learning, capstone courses, service learning, data analytics, and cybersecurity, just to name a…

In higher education, concept mapping has been extensively adopted as an assessment and evaluation tool for conceptual knowledge. In recent years, an increasing number of researchers have applied concept mapping to teaching in technology-based environments. However, no research was found to holistically explore the role of concept maps in…

The University of Palermo is proud to host the 18th International Conference on Educational Data Mining (EDM) in Palermo, Italy, from July 20 to July 23, 2025. EDM is the annual flagship conference of the International Educational Data Mining Society. This year's theme is "New Goals, New Measurements, New Incentives to Learn." The theme…

This study examines the implementation of a course module that integrated computing and data analysis. The module aimed to engage prospective mathematics teachers in the practice of working with datasets and analyzing data to investigate questions related to local Brooklyn schools, as well as to gain deeper insight into the students and…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

Objective: Several studies have shown that Adult ADHD presents differently in younger and older adults. We sought to assess the difference in care between these two groups using previously identified quality measures (QMs). Methods: Using electronic health record data, we matched a younger group of ADHD patients to an older group. We then assessed…

Due to the increasing demand for efficient, effective, and profitable applications of Artificial Intelligence (AI) in various industries, there is an immense need for professionals with the right skills to meet this demand. As a result, several institutions have started to offer AI programs. Yet, there is a notable gap in academia: the absence of…