This paper explores the potential of abductive reasoning to enhance the analysis of international large-scale assessments which have traditionally relied on deductive and inductive reasoning. While these conventional methods have provided valuable insights into global student achievement, they often fail to capture the complexity of educational…

Purpose: The purposes of this tutorial are (a) to describe a method of language sample analysis (LSA) referred to as SUGAR (Sampling Utterances and Grammatical Analysis Revised) and (b) to offer step-by-step instructions detailing how to collect, transcribe, analyze, and interpret the results of a SUGAR language sample. Method: The tutorial begins…

Assessing students' performance in online learning could be executed not only by the traditional forms of summative assessments such as using essays, assignments, and a final exam, etc. but also by more formative assessment approaches such as interaction activities, forum posts, etc. However, it is difficult for teachers to monitor and assess…

The statistical problem-solving process is key to the statistics curriculum at the school level, post-secondary, and in statistical practice. The process has four main components: formulate questions, collect data, analyze data, and interpret results. The Pre-K-12 Guidelines for Assessment and Instruction in Statistics Education (GAISE) emphasizes…

"The Forum Guide to Strategies for Education Data Collection and Reporting (SEDCAR)" was created to provide timely and useful best practices for education agencies that are interested in designing and implementing a strategy for data collection and reporting, focusing on these as key elements of the larger data process. It builds upon…

Contributions: This article explores the impact of environmental education interventions about e-waste recycling and management practices as well as about the energy usage of data centers (DCs) into the Information and Communication Technologies (ICTs) university curricula. Intended Outcomes: An education program was implemented aiming to raise…

This teaching tip describes using Microsoft Power BI Desktop in a class to analyze unstructured data from an exit survey of prior students from a Master of Science in Management Information Systems program. Results from a short survey administered to these students showed that the students, using the no-code Power BI, were able to accomplish their…

Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…

Variability is underemphasized in domains such as engineering. Statistics and data science education research offers a variety of frameworks for understanding variability, but new frameworks for domain applications are necessary. This study investigated the professional practices of working engineers to develop such a framework. The Neglected,…

In the context of higher education's growing significance and the persistence of inequalities in it, the article aims to further develop the understanding of higher education as a public good and to explore its association with social cohesion in a European comparative perspective. It shifts the focus from the content of higher education as a…

Purpose: This article advocates that privacy literacy research and praxis mobilize people toward changing the technological and social conditions that discipline subjects toward advancing institutional, rather than community, goals. Design/methodology/approach: This article analyzes theory and prior work on datafication, privacy, data literacy,…

Learning analytics (LA) involves the measurement, collection, analysis, and reporting of data about learners and their contexts, aiming to understand and optimize both the learning process and the environments in which it occurs. Among many themes that the LA community considers, natural language processing (NLP) algorithms have been widely…

This guide provides cross-sector teams at the state, territory, tribal, and local levels with strategies for collecting and using data across the mixed delivery system of early care and education programs. (This guide uses the term "state and local" to refer to all of these levels.) Collecting and analyzing qualitative and quantitative…

Enhancing special educators' data literacy is critical to informing instructional decision-making, especially for students with learning disabilities. One tool special educators commonly use is curriculum-based measurement (CBM). These data are displayed on time-series graphs, and student responsiveness is evaluated. Graph construction varies and…

This Toolkit presents lessons learned from the process of implementing a new system for collecting student-level work-based learning (WBL) data in high school career and technical education (CTE) programs. As part of a study on career academies and WBL, a research team worked closely with a district CTE office and school staff to design and…