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…

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…

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…

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…

"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…

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…

Schools, state and local education and workforce agencies, colleges, career education and training programs, and employers collect and use education and workforce data. But without a connected, cohesive system through which students, job seekers, and college and career counselors can get that information, it often remains just out of reach for…

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…

School leadership in education is thinking, communicating, and modeling to maximize student growth and achievement. This quantitative research study explored how school leadership can strengthen the academic progress of students within Multi-Tiered Systems of Support (MTSS). When implementation of MTSS is guided by adaptive school leadership,…

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…

This essential science methods resource integrates principles of learning and motivation with practical teaching ideas for the elementary and middle school science classroom. It employs project-based learning (PBL) to enable educators to engage their students in meaningful, real-world questioning about the world. It provides concrete strategies…

Students who have graduated from high schools across the EU member states can choose from a wide variety of study programs and universities at which to pursue their degree studies. Each combination of a university and study program is unique, which further complicates student choice. Lack of information transparency regarding the unique…

Tracking and using data to inform decisions pays off for college success programs on multiple levels. Having data allows program staff to monitor the progress of individual students and tailor support to their particular needs. It enables staff to understand the effectiveness of program activities and make improvements as necessary. Most…

This paper describes a partnership-based approach for analyzing data from a learning management system (LMS) used by students in grades 6-12. The goal of the partnership was to create indicators for the ways in which students navigated digital learning activities, referred to as playlists, that were comprised of resources, pre-assessments, and…

To be literate in a society where the information shared online is often exploited, learners should be exposed to multiple aspects of contemporary predictive modeling. This article explores an activity in which grade 10 students learned how a famous AI algorithm (the Apriori algorithm) uses conditional probability to automate the process of…