The purpose of this essay is to discuss the impact of the EdD experience on one teacher's understanding of data and research. From a first-person narrative, the author shares how learning to collect and analyze qualitative data has the potential to change the way teachers can engage with "data-driven decision making" in a high school…

"Pathways to Implementation" highlights innovative strategies and effective models in career pathways policy, implementation, and programming, as well as challenges states encounter in this work. This seven-part series addresses the key elements of Bellwether's framework for career pathways policy implementation. Each brief defines the…

In the boxplot, the box always represents -- regardless of its area -- the middle half of the data and thus a measure of variability (interquartile range). However, when students first learn about boxplots, they are usual already familiar with other forms of statistical representations (e.g., bar or circle graphs) in which a larger area represents…

Monitoring applications (MAs) use digital and online tools to collect and track data on student behavior, and they have become increasingly popular among schools. Empirical research on these complex surveillance platforms is scant, and little is known about the efficacy or impact that they have on students. This study used a multi-method…

The increasing availability of digital tools in science classrooms can provide students with more frequent and easier access to large amounts of data. Large data sets have considerable epistemological potential, as they enable, for instance, the observation of otherwise unobservable phenomena, but it must be assumed that handling them places…

In our data-driven society, it is essential for students to become statistically literate. A core domain within Statistical Literacy is Statistical Inference, the ability to draw inferences from sample data. Acquiring and applying inferences is difficult for students and, therefore, usually not included in the pre-10th-grade curriculum. However,…

With increased focus on data literacy and data science education in K-12, little is known about what makes a data set preferable for use by classroom teachers. Given that educational designers often privilege authenticity, the purpose of this study is to examine how teachers use features of data sets to determine their suitability for authentic…

This qualitative case study sought to discover how school-level data teams can intentionally use effective data practices to identify and implement high-leverage interventions that support all students, including Black and Latinx boys, in attaining the necessary academic requirements for high school graduation. The researcher analyzed data from…

Early Warning Systems (EWS) are research-based analytics that use statistical models to assess dropout risk. School leaders use this analytic to consolidate data about a student and provide actionable data to craft an intervention. Little is currently known about the processes involved in school implementation or data use. By analyzing Montana EWS…

This article details an exploratory data analysis project using the Common Online Data Analysis Platform (CODAP) based on the "Guidelines for Assessment and Instruction in Statistics Education" (GAISE) four-part statistical problem-solving model. The project goal was to answer what similarities and differences exist within the school…

This study examines College and Career Readiness (CCR) policy implementation through the lens of "decoupling." We investigate how high schools have jointly implemented Career and Technical Education (CTE) and Industry-Based Certifications (IBCs), and whether there is evidence of "curricular-credential decoupling" via…

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…

Since data collection technologies has become a part of daily life, measurement and data requirements now permeate many state mathematics standards, beginning as early as kindergarten and extending through high school. For example, the Standards for Mathematical Content, recommend that kindergarteners "describe and compare measurable…

In science classrooms, students usually see and work with data that's intended to tell them right away about the natural world. Students then often treat the data we provide to them as factual, rather than as a source of evidence (Duschl 2008; Sandoval and Millwood 2005; Berland and Reiser 2009; McNeill and Berland 2017; Hancock, Kaput, and…

We report the results of a convergent validity study examining the externalizing subscale (SRSS-E5, five items) of the adapted Student Risk Screening Scale for Internalizing and Externalizing (SRSS-IE 9) with the externalizing subscale of the Teacher Report Form (TRF) with two samples of K-12 students. Results of logistic regression and receiver…