How do young children learn, and what do educators need to know and do to teach them? Covering the full birth-8 early childhood age range, this introductory text delivers up-to-date answers through a unique lens: a deep focus on the neurological foundations of developmentally appropriate practices. Preservice and inservice educators will explore…

This guide provides information and best practices that will help state education agencies (SEAs) and local education agencies (LEAs) manage data related to students who frequently change schools, with a focus on actions to minimize student learning disruptions and allow agencies to provide support for those particular students. This document…

The following case studies explore how emerging and established Statewide Longitudinal Data Systems have used the Education-to-Workforce Indicator Framework (E-W Framework) to support their data system efforts. Developed by Mathematica in partnership with the Gates Foundation, the framework offers guidance on how states can use data to…

The tutor-web is an open-source learning environment designed to be used for teaching mathematics and statistics. The system offers thousands of exercises at high school and university level, and has been used for a decade to teach introductory statistics courses with good results. A new component has recently been added to the tutor-web so that…

A "Cone of Uncertainty" has become ubiquitous in hurricane forecasting, encompassing the likeliest possible path that a storm might take as it approaches landfall. These forecasts are crucial because they help government agencies at all levels prepare even in these far-from-certain future conditions. Although individual institutions have…

Exploratory data analysis (EDA) is an iterative, open-ended data analysis procedure that allows practitioners to examine data without pre-conceived notions to advise improvement processes and make informed decisions. Education is a data-rich field that is primed for a transition into a deeper, more purposeful use of data. This article introduces…

Personalized education--the systematic adaptation of instruction to individual learners--has been a long-striven goal. We review research on personalized education that has been conducted in the laboratory, in the classroom, and in digital learning environments. Across all learning environments, we find that personalization is most successful when…

In this article, I describe how principals accessed teacher and student data on a centralized data warehouse (DWH) during an academic school year. I found that principals did not use the DWH very often during the year. When logged on, principals most often looked at reports on student achievement, teachers' performance, or student demographics.…

Statewide technical assistance providers support many school teams through training, consultation, and coaching to improve systems and outcomes for mathematics for every student. They have the opportunity to work with many school psychologists, who often indicate they are more comfortable engaging in systems-level work for literacy, behavior, and…

Purpose: The objective of this paper is to present a comprehensive review of the literature on learning analytics (LA) stakeholders' expectations to reveal the status of ongoing research in this area and to highlight gaps in research. Design/methodology/approach: Conducting a literature review is a well-known method to establish knowledge and…

The shortage of qualified administrators who can utilize data analytics means that institutions are not able to harness data analytics to its fullest potential in order to remain competitive in a higher education market that continued to reward institutions that embrace entrepreneurship. Examining how new student affairs professionals in US higher…

Leveraging big data for student data analytics is increasingly integrated throughout university operations from admissions to advising to teaching and learning. Though the possibilities are exciting to consider, they are not without risks to student autonomy, privacy, equity, and educational value. There has been little research showing how…

Using data to inform decision-making in the educational environment has increased over the last decade due to accountability requirements at the federal, state, and local level (Bernhardt, 2013; Datnow & Hubbard, 2016; Garland, 2014; Mandinach & Gummer, 2016; McKay, 2018; Wayman, 2005). While research supported the inclusion of data in…

This dissertation provides empirical evidence on estimating the treatment effects of school choice programs using quasi-experimental data. Chapter 1 implements the new econometric method proposed by Abdulkadiroglu et al. (2017a) in the context of the magnet school program in Wake County, North Carolina. Chapter 2 gives an in-depth analysis of the…

The purpose of this study was to examine the factors that influence the use of institutional assessment in support of student outcomes at four-year public institutions of higher education. This study focused on small institutions, defined as having enrollment below that of the median value, across the nation. An electronic survey was sent to chief…