A prominent concern is that college students are harming their long-term economic prospects by making student loan decisions without full information about the implications of their choices. We designed an experiment to examine students' responses to a debt letter, an increasingly popular strategy to provide easily accessible information about…

In this study, we examined how in-service middle-level mathematics teachers used statistics in their own classroom research. Using an embedded single-case design, we analyzed a purposefully selected sample of nine teachers' classroom research papers, identifying several themes within each phase of the statistical problem solving process to…

The recommendations in this brief create a framework for using data effectively to make instructional decisions. The availability of student-level data for educators has pushed forward the movement to strengthen the role of data to guide instruction and improve student learning. While improvements in technology and assessments, as well as recent…

Using data to inform classroom decision-making is a salient facet of teachers' professional practice. However, some evidence suggests that teacher data use practices are unevenly distributed within and across school contexts. In response, the present study examined school-level (elementary, middle, and high) differences in four categories of data…

All around us are examples of people and organizations with good information making bad decisions. Consider the case of Blockbuster. Less than a decade ago, Blockbuster had 8,000 stores in 17 countries and millions of customers. It was awash in data, including customer surveys that said people disliked going to video stores and hated late fees.…

Formative assessment, assessment for learning, involves checking in with students during the learning process to see if they understand concept or standard, before holding them accountable for mastery and moving on to the next concept or standard. This process can be used in the classroom during the lesson or across a subject area as teachers of…

Personalized learning has become the most notable application of big data in primary and secondary schools in the United States. The combination of big data and adaptive technological platforms is heralded as a revolution that could transform education, overcoming the outdated classroom model, and realizing the progressive vision of…

This study examined the influence of a professional development project about an internet-based mathematics formative assessment tool and related pedagogies on primary teachers' instruction and student achievement. Teachers participated in 72 h of professional development during the year. Descriptive statistics and multivariate analyses of…

This study examined the effect of various district and site level conditions that influence the frequency of teacher data-driven decision-making behaviors. This study is motivated by four research questions: 1) Among various kinds of data available to teachers and principals in making data-driven decisions: a. What is the relative level of…

This 2016 document is designed to provide state Part C staff with guidance on using fiscal data to analyze and revise their allocation methodology. Allocation methodology is the process -- including practices, strategies, procedures, and policies -- used by Part C state staff to equitably distribute funds to meet the needs of the system, including…

Data use should be a continuous, integrated part of practice, a tool that is used all the time. Good teachers have been doing data-driven decision making all along, it just has not been recognized by that term. But there is more work to be done to ensure that educators know how to continuously, effectively, and ethically use data; that is, to help…

Although much has been written about the potential benefits of effective data use in schools, considerably less attention has been paid to how schools make sense of the data generated from performance-based accountability measures. This article explores schools' usage of state test data, the intensity of data use, and the perceived utility of…

This dissertation investigates the effect of observational learning in crowdsourcing markets as a lens to identify appropriate mechanism(s) for sustaining this increasingly popular business model. Observational learning occurs when crowdsourcing participating agents obtain knowledge from signals they observe in the marketplace and incorporate such…

Most data-informed decision-making in education is undermined by flawed interpretations. Educator-driven interventions to improve data use are beneficial but not omnipotent, as data misunderstandings persist at schools and school districts commended for ideal data use support. Meanwhile, most data systems and reports display figures without…

In this study, we used a paper-pencil questionnaire to investigate whether teachers, administrators, and parents differed in their preferences and accuracy when interpreting visual data displays for decision making. For the data analysis, we used nonparametric tests due to violations of distributional assumptions for using parametric tests. We…