Realist evaluations, a form of theory-driven evaluation, aim to explain how, why, for whom, and to what extent a complex health intervention works (or does not work). Realist evaluations are often "methods-flexible" and encourage the appropriate use of a range of evidence types that provide explanatory value. However, there is a lack of…

Analyzing the teaching and learning environment (TLE) through student feedback is essential for identifying curricular gaps and improving teaching practices. However, traditional feedback analysis methods, particularly for qualitative data, are often time-consuming and prone to human bias. Large Language Models (LLMs) offer a promising solution by…

With the development of mobile Internet and digital technologies, online education platforms transcend time and space constraints to provide ubiquitous learning environments. However, high dropout rates and low pass rates pose a great challenge. Predicting student performance enables early identification of academic failure tendencies,…

Predicting learner actions and intentions is crucial for providing personalized real-time support and early intervention in programming education. This approach enables proactive, context-aware assistance that is difficult for human instructors to deliver by foreseeing signs of potential struggles and misconceptions, or by inferring a learner's…

According to the cliché, it is not what one says so much as how one says it. In the business world, those words ring particularly true. How one presents information can influence all forms of business decisions, from level of investment to expansion to downsizing and everything in between. This brings up significant questions relating to the…

Data visualization technologies are powerful tools for telling evidence-based narratives about oneself and the world. This paper contributes to the literature on data science education by examining the sociotechnical practices of data wrangling--strategies for selecting and managing large, aggregated datasets to produce a model and story. We…

In the contemporary society a massive amount of data is generated continuously by various means, and they are called Big-Data sets. Big Data has potential and limits which need to be understood by statisticians and statistics consumers, therefore it is a challenge to develop Big-Data Literacy to support the needs of constructive, concerned, and…

"Using Data for Continuous Improvement in Educator Preparation" provides case studies that illuminate and contextualize the ways in which educator preparation programs determine the data they need to improve, collect data, analyze data, share data with stakeholders, and close the loop by making focused improvements based on the data.…

In undergraduate research settings, students are likely to encounter anomalous data, that is, data that do not meet their expectations. Most of the research that directly or indirectly captures the role of anomalous data in research settings uses post-hoc reflective interviews or surveys. These data collection approaches focus on recall of past…

Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…

This multiple descriptive case-study explored the perceptions and experiences of eight occupational therapy program academic fieldwork coordinators (AFWCs), regarding their usage of Formstack, as an online fieldwork data collection system. Previous survey research revealed that AFWCs had positive feelings about the new AOTA Fieldwork Performance…

In this article, industry-based certification attainment rates were compared by student ethnicity/race as reported by the Texas Education Agency for the 2019-2020, 2020-2021, and 2021-2022 school years. Through analyses of Texas statewide data, statistically significant differences were revealed in industry-based certification attainment rates…

The "Morbidity and Mortality Weekly Report" ("MMWR") series of publications is published by the Office of Science, Centers for Disease Control and Prevention (CDC), U.S. Department of Health and Human Services. Articles included in this supplement are: (1) Overview and Methods for the Youth Risk Behavior Surveillance System --…

In this review, I examined the last two decades of research on data use in education to outline the ways in which principals used data to inform their own leadership practices. I found three themes: first, student achievement data were the most widespread form of data that principals used; second, principals' work has been reshaped by teacher…

Background: A paucity of qualitative research on sensitive topics that focuses on participants with intellectual disabilities leaves their views unexplored. This scoping review mainly aimed to provide an overview of qualitative data collection methods used in research involving participants with intellectual disabilities to explore death and…