Low-skilled adults in literacy in English are those with skills insufficient to complete tasks requiring comparing and contrasting information, paraphrasing, or making low-level inferences. Low-skilled adults in numeracy in English are those who would have difficulty making calculations with whole numbers and percentages, estimating numbers or…

Fidelity is defined as doing what is intended. The purpose of measuring fidelity is to assist with supporting implementation. Collecting fidelity data provides an opportunity to problem-solve throughout the process versus waiting for outcome data. More often than not, purchased programs and curriculum materials are missing a research-validated…

Item Response Theory (IRT) models are a popular analytic method for self report data. We show how traditional IRT models can be vulnerable to specific kinds of asymmetric measurement error (AME) in self-report data, because the models spread the error to all estimates -- even those of items that do not contribute error. We quantify the impact of…

Hierarchical data is often observed in education data. Analyzing such data with Multilevel Modeling becomes crucial to understanding the relationship at the individual and group levels. However, one of the most significant problems with this kind of data is small sample sizes and very low Intraclass Correlations. The multivariate Latent Covariate…

Higher education institutions in the United States are under intense scrutiny to engage in data-driven decision-making to address systemic deficiencies. An innovative strategy to increase the use of data in higher education is through interactive data visualization whereby users are more involved in the creation of knowledge. The problem that was…

This case study reflects upon a mixed-methods exploratory study utilized by the Leadership in Times of Crisis Framework within the paradigm of pragmatism to survey 976 Minnesota teachers in April of 2020 to determine the demographic profile of teachers in Minnesota who were facing the COVID-19 pandemic and the greatest challenges in their…

Although the use of real-world data sets is encouraged when teaching statistics, it can be difficult for instructors to find meaningful data for introducing students to univariate descriptive statistics such as the mean, median, and percentiles. The recent lead contamination of the water supply in Flint, Michigan, provides a real-life data set…

In this chapter, we review the strengths of NCES survey data, provide an example of analyzing NCES survey data to explore the pathways between coursework in career and technical education in high school and postsecondary success, and offer suggestions for future data collection.

Artificial intelligence and data analysis (AIDA) are increasingly entering the field of education. Within this context, the subfield of learning analytics (LA) has, since its inception, had a strong emphasis upon ethics, with numerous checklists and frameworks proposed to ensure that student privacy is respected and potential harms avoided. Here,…

Multiple perspective interviews (MPIs) involve interviewing members of a social group separately and triangulating their accounts during analysis to gain insights into the functioning of such groups (e.g. families). So far, there has been little engagement with the specific challenges of MPI research during the analysis, particularly with…

In this project, students asked and attempted to answer questions about themselves by collecting and analyzing data. With the prevalence of big data and business analytics, managers have data and quantitative information available more immediately than ever. However, managers need to understand how to use this information. In this project,…

Data sprints have emerged as a popular way to involve stakeholders in datawork. In this chapter we discuss what it takes to turn a sprint into a productive situation of inquiry (in the sense of Dewey, 1938). We argue that sprint organizers must work actively to counteract an otherwise docile setting where the preference for agreement between…

A gap in practice at CES Elementary School (pseudonym) was the lack of data driven instructional decision making that contributed to the problem of low school scores on the State of Texas Assessments of Academic Readiness (STAAR). Low STAAR scores have negatively impacted student, teacher, and administrator retention. Unsuccessfully, data chats…

Purpose: The purpose of this study was to better understand K-12 district leaders' reasoning and processes for selecting and deploying EdTech instructional products, including which, if any, types of data are used to support decision-making. Design/methodology/approach: This multisite case study of educational technology (EdTech) decision-making…

In order to study the manifestation of data sense and identify ways of thinking about variability in authentically realistic problems in a group of Chilean fifth-grade students, a lesson plan was designed and implemented, within the framework of statistical literacy and using the "lesson study" modality, in which students were urged to…