The use of data in schools may contribute to reducing educational and social inequalities. This article seeks to examine the use of data in school intervention programs implemented within vulnerable schools in Chile and the transfer and use of this data by schools. Utilizing an exploratory descriptive multiple case study design. Results indicate…

Data-driven decision-making (DDDM) has been playing an increasing role in contemporary teaching, since it includes systematic collection, analysis, and application of data to improve students' educational performance. However, little is known about the affective factors that influence this data-based practice. Thus, the purpose of this study was…

A gap exists between the ability to gauge the success of institutions by deploying a relatively simple set of measures typically based upon the federal cohort, versus the ability to monitor the successful (or unsuccessful) progression of the varied students who move through them. Daniel Regan questions which matters more. To gauge the health of an…

This article introduces the concept of the carrying capacity of data (CCD), defined as an integrated, evaluative judgment of the credibility of specific data-based inferences, informed by quantitative and qualitative analyses, leavened by experience. The sequential process of evaluating the CCD is represented schematically by a framework that can…

Academic department chairs are key in helping universities achieve student success. To succeed in their decisions and furthering their university's educational mission, department chairs can use institutional data to inform their decision-making. In many cases, however, there are gaps, misalignments, and inefficiencies between department chairs…

Among the 50 states, 44 use free and reduced-price lunch enrollment to identify low-income students. These data are also commonly used to allocate federal, state, and local funding to schools serving low-income children. School and district poverty rates, as determined by free and reduced-price lunch enrollment, additionally feature prominently in…

In the United States, the Next Generation Science Standards advocate for the integration of computational thinking (CT) as a science and engineering practice. Additionally, there is agreement among some educational researchers that increasing opportunities for engaging in computational thinking can lend authenticity to classroom activities. This…

Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…

Although various academic disciplines use data papers to support effective research practices, data papers are still uncommon in the educational sciences. Main goals of data papers are enhancing transparency regarding research processes and supporting data sharing among researchers and thus, open science. As many educational research projects…

This brief describes how several commonly used per-pupil funding measures derived from federal data include passthrough funding in the numerator but exclude students attached to this funding from the denominator, artificially inflating per-pupil ratios. Three forms of passthrough funding for students not educated by the school district where they…

The evidence deployed in the policy process is often done so from sources hoping to shape policy along preconceived ideological lines. This chapter presents the data and research cited as evidence in tuition-free community legislation proposed and enacted by 10 states, along with the sources that produced this evidence when applicable. Results…

Decision-making is a critical topic in any management and organizational behavior course. Navigating and understanding the various processes and influences on decision-making, however, can be complicated. This article revises and expands on a common "employee ranking" format activity. It uses in-class student data to systematically…

In this study, we propose a MOOC Analytic Statistical Visual model (MOOC-ASV) to explore students' engagement in MOOC courses and predict their performance on the basis of their behaviors logged as big data in MOOC platforms. The model has multifunctions, which performs on visually analyzing learners' data by state-of-the-art techniques. The model…

This qualitative case study was designed to explore elementary teacher perceptions of what it means to provide an equitable education for their students. These perceptions allow educational leaders insight into how teachers navigate systems that create inequities and what professional development may be needed to further support equitable learning…

Data literacy is the ability to collect, manage, evaluate, and apply data, in a critical manner. It is a relatively new field of study, dating only from the 2010s. It includes the skills necessary to discover and access data, manipulate data, evaluate data quality, conduct analysis using data, interpret results of analyses, and understand the…