School closures in the wake of the COVID-19 pandemic led to kids asking pertinent questions about why they were not in school, especially some students suffering financial hardship. Virtual classrooms became the mundane venues for students to piece together the pandemic puzzle and unpack unseen inequities. This article examines disparities that…

Acting to dismantle structural racial inequities begins with identifying and clearly naming the challenges being faced. Data play a powerful role in this process. Several recent publications synthesize data sources, research findings, and expert recommendations to inform and guide equity improvement efforts. A five-part "Statement of the…

This paper describes a preliminary study of how computational methods allow us to know more about citizen science and its connection with education. Citizen science is a practice involving a general public in scientific tasks and generating knowledge and scientific results. Previous studies have shown that the education sector can take benefit of…

We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…

One in every 10 children has a disability. These 240 million children, like all others, have hopes and dreams. Yet they also face unique challenges and barriers shaped by ableism and stigma. This report documents UNICEF and its partners' disability evidence generation from 2018 to 2022. It underscores the organization's deep-rooted commitment to…

Single-subjects design has the advantage of providing detailed, individualized analyses of intervention. However, creating a tutorial for single-subject design (SSD) is challenging, and an effective version for online delivery is currently unavailable. Here, we developed an experiential SSD tutorial designed for online delivery and evaluated its…

This study examines the impact of changes in exam modalities on the performance and experiences of architectural engineering students in a domain-specific data science class. Specifically, the number and duration of exams (and thereby the amount of content on each) and setting in which the students took the exams in changed among the three years…

This study examines the limitations and ableist assumptions embedded in quantitative survey instruments used to gather data on postsecondary students with disabilities. Specifically, three National Center for Educational Statistics postsecondary surveys were examined as data sources. Employing a critical disability studies lens and discourse…

Purpose: This study examines existing automatic screening methods for developmental language disorder (DLD), a neurodevelopmental language deficit without known biomedical etiologies, focusing on languages, data sets, extracted features, performance metrics, and classification methods. Additionally, it summarizes the strengths and weaknesses of…

School climate surveys are frequently used to collect information about student experiences in school. Less is known about how educators use survey data after survey administration. This paper explores one school district's critical use of evidence to promote equitable change. We conducted eight semi-structured interviews with district and school…

Critical thinking (CT) consists of a deliberate and reflective process that can lead to informed decisions. It involves scrutinizing the trustworthiness and consistency of underlying assumptions, the sources of data, and the validity of other information. CT embodies deliberate, self-regulated judgment incorporating cognitive abilities such as…

Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and…

Despite the growing use of large language models (LLMs) in educational contexts, there is no evidence on how these can be operationalized by students to generate custom datasets suitable for teaching and learning. Moreover, in the context of network science, little is known about whether LLMs can replicate real-life network properties. This study…

This study investigates the cognitive and emotional processes involved in augmented reality (AR)-based learning. The study looks at learning outcomes, emotional responses, meditation, and attention using a comprehensive approach that includes self-assessment, electroencephalogram data gathering, and postexperiment questionnaires. In total, 12…

This study examines accounting faculty perceptions of the alignment of the newly revised CPA exam with the evolving demands of the accountancy profession. Triggered by significant technological advancements and the CPA Evolution initiative, the exam now encompasses broader coverage of data analytics, information technology, and emerging…