There have been substantial advances in the development of states' education data systems over the past 20 years, supported by large investments from the federal government. However, the availability of modern data systems has not translated into meaningful improvements in how consequential state policies, such as funding and accountability…

This study explores the extent to which college context (two- vs. four-year), gender, and race/ethnicity correlated with worsening course outcomes during emergency remote teaching during the COVID-19 pandemic, by comparing outcomes within students between the fall 2019 pre-pandemic and spring 2020 pandemic terms. In particular, it explores the…

The paper delves into social media mining in the context of medical education programs in the information age. It explores the adaptability of Social Media Analytics (SMA) apps within the structure of online courses in medicine and proposes a conceptual framework for a learning process. This process includes practical exercises based on search and…

The intersection of Data Science (DS) and Library and Information Science (LIS) is rapidly developing, with a notable need for ongoing transdisciplinary training between practitioners in these two fields. The LIS Education and Data Science Integrated Network Group (LEADING) fellowship program and its ancillary community of practice (CoP) showcase…

Assessment professionals are often at the helm of leading discussions around data-use and data-driven decisions for higher education stakeholders. However, the problem is that assessment practitioners must be cognizant of how to engage stakeholders with equity-minded and socially just informed assessment practices. The purpose of this article is…

The study examines the effects of different questioning strategies on elementary school students regarding scientific knowledge, views of scientific inquiry, and scientific inquiry skills during scientific inquiry video learning. A quasi-experimental design was adopted involving 78 sixth-grade Taiwanese students from three classes. The three…

Relying on the background of big data, this paper introduces the blended teaching model into the secondary vocational Japanese oral classroom and explores whether the teaching model is conducive to the improvement of the secondary vocational Japanese oral learning effect and teaching effect. In order to make this research more scientific and…

This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…

Machine learning (ML) methods are among the most promising technologies with wide-ranging research opportunities, particularly in the field of education, where they can be used to enhance student learning outcomes. This study explores the potential of machine learning algorithms to build and train models using log data from the "3D…

A small subset of education studies analyzes school data collected seasonally (separating the summer from the school year). At first, this work was primarily known for documenting learning loss in the summers, but scholars have since recognized that observing how inequality changes between summer and school periods provides leverage for…

In response to the heavy demand for business analysts in various industries, many universities have developed business analyticsrelated courses and programs, which aim to develop a competent labor force that can help companies make sense of business data and generate sustainable competitive advantages. Ensuring high levels of student success in…

We consider Bayesian estimation of a hierarchical linear model (HLM) from small sample sizes. The continuous response Y and covariates C are partially observed and assumed missing at random. With C having linear effects, the HLM may be efficiently estimated by available methods. When C includes cluster-level covariates having interactive or other…

The use of videos in teaching has gained impetus in recent years, especially after the increased attention towards remote learning. Understanding students' video-related behaviour through learning (and video) analytics can offer instructors significant potential to intervene and enhance course designs. Previous studies explored students' video…

The use of information and communication technology-based data systems to support teachers in data-driven decision-making (DDDM) remains limited. Despite the growing number of data systems available, their uptake remains limited, and there is a limited understanding of what data system characteristics increase and factors that influence teacher…

Retention, persistence, and academic achievement for first-generation students have become increasingly prevalent with increasing access to higher education. Beyond access, the most discernible challenge relates to their identity as a first-generation college student and the lack of mentorship from their parents in navigating the college…