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 Pub Number  Title  Date
NFES 2017168 Forum Guide to Reporting Civil Rights Data
The Forum Guide to Reporting Civil Rights Data presents a variety of effective methods through which local education agencies (LEAs) report civil rights data to the U.S. Department of Education’s Office for Civil Rights. In addition, the guide provides examples of how state education agencies can voluntarily help their LEAs with Civil Rights Data Collection (CRDC) reporting. The guide includes an overview of the CRDC, a discussion of the challenges and opportunities in reporting civil rights data, an explanation of the CRDC reporting process, and case studies that examine how specific education agencies report civil rights data.
2/5/2018
REL 2017175 Benchmarking the state of Pohnpei's education management information system
The purpose of this study was to provide information on the current quality of the education management information system (EMIS) in Pohnpei, Federated States of Micronesia, so that data specialists, administrators, and policy makers might identify areas for improvement. As part of a focus group interview, knowledgeable data specialists in Pohnpei responded to 46 questions covering significant areas of their EMIS. The interview protocol, adapted by Regional Educational Laboratory Pacific from the World Bank's System Assessment and Benchmarking for Education Results assessment tool, provides a means for rating aspects of an EMIS system using four benchmarking levels: latent (the process or action required to improve the aspect of quality is not in place), emerging (the process or action is in process of implementation), established (the process or action is in place and it meets standards), and mature (the process or action is an example of best practice). Overall, data specialists scored their EMIS as established. They reported that the prerequisites of quality, that is, both the institutional frameworks that govern the information system and data reporting, and the supporting resources, are established. They also rated integrity of education statistics, referring to the professionalism, objectivity, transparency, and ethical standards by which staff operate and statistics are reported, as established. Data specialists reported the accuracy and reliability of education statistics within their system to be established. They reported that the serviceability (the relevance, timeliness, and consistency of data) and accessibility of education data within their system are established. Results show that data specialists know and can apply sound techniques and validate data and generate statistical reports; however the system does not ensure that their roles and responsibilities are defined, nor does it provide any assurance, in the form of a legal mandate, that they receive the data they require. Data specialists provide timely services, but the system cannot assure the public that such services are provided independently, or that public has information regarding internal governmental access to statistics prior to their release. The results of this study provide the Pohnpei State Department of Education and the National Department of Education with information regarding the strengths and areas of the EMIS that may benefit from improvement efforts through the development of action plans focused on priority areas.
10/6/2016
REL 2017176 Benchmarking the state of Chuuk's education management information system
The purpose of this study was to provide information on the current quality of the education management information system (EMIS) in Chuuk, Federated States of Micronesia, so that data specialists, administrators, and policy makers might identify areas for improvement. As part of a focus group interview, knowledgeable data specialists in Chuuk responded to 46 questions covering significant areas of their EMIS. The interview protocol, adapted by Regional Educational Laboratory Pacific from the World Bank’s System Assessment and Benchmarking for Education Results assessment tool, provides a means for rating aspects of an EMIS system using four benchmarking levels: latent (the process or action required to improve the aspect of quality is not in place), emerging (the process or action is in progress of implementation), established (the process or action is in place and it meets standards), and mature (the process or action is an example of best practice). Overall, data specialists scored their EMIS as emerging. They reported that the prerequisites of quality, that is, both the institutional frameworks that govern the information system and data reporting, and the supporting resources, are established. They rated integrity of education statistics, referring to the professionalism, objectivity, transparency, and ethical standards by which staff operate and statistics are reported, as emerging. Data specialists reported the accuracy and reliability of education statistics within their system as established. They reported that the serviceability (the relevance, timeliness, and consistency of data) and accessibility of education data within their system are emerging. Results show that data specialists know and can apply sound techniques and validate data and generate statistical reports, and that the institutional frameworks and resources meet standards. Data specialists indicate that the relevance, timeliness, and consistency of the data and statistics provided to stakeholders could be improved. In addition, the reports that present these data and statistics could be better adapted for the intended audience. The results of this study provide the Chuuk State Department of Education and the National Department of Education with information regarding the strengths and areas of the EMIS that may benefit from improvement efforts through the development of action plans focused on priority areas.
10/6/2016
NCEE 20154013 A Guide to Using State Longitudinal Data for Applied Research
State longitudinal data systems (SLDSs) promise a rich source of data for education research. SLDSs contain statewide student data that can be linked over time and to additional data sources for education management, reporting, improvement, and research, and ultimately for informing education policy and practice.

Authored by Karen Levesque, Robert Fitzgerald, and Joy Pfeiffer of RTI International, this guide is intended for researchers who are familiar with research methods but who are new to using SLDS data, are considering conducting SLDS research in a new state environment, or are expanding into new topic areas that can be explored using SLDS data. The guide also may be useful for state staff as background for interacting with researchers and may help state staff and researchers communicate across their two cultures. It highlights the opportunities and constraints that researchers may encounter in using state longitudinal data systems and offers approaches to addressing some common problems.
6/30/2015
NFES 2015158 Forum Guide to Alternative Measures of Socioeconomic Status in Education Data Systems
The Forum Guide to Alternative Measures of Socioeconomic Status in Education Data Systems provides “encyclopedia-type” entries for eight plausible alternative measures of socioeconomic status (SES) to help readers better understand the implications of collecting and interpreting a range of SES-related data in education agencies. Chapter 1 reviews recent changes in how SES data are collected in many education agencies and presents a call to action to the education community. Chapter 2 reviews practical steps an agency can take to adopt new measures. Chapter 3 describes each of the eight alternative measures, including potential benefits, challenges, and limitations of each option.
6/22/2015
REL 2015046 A Primer for Analyzing Nested Data: Multilevel Modeling in SPSS Using an Example from a REL Study
Analyzing data that possess some form of nesting is often challenging for applied researchers or district staff who are involved in or in charge of conducting data analyses. This report provides a description of the challenges for analyzing nested data and provides a primer of how multilevel regression modeling may be used to resolve these challenges. An illustration from the companion report, The correlates of academic performance for English language learner students in a New England district (REL 2014–020), is provided to show how multilevel modeling procedures are used and how the results are interpreted.
12/23/2014
REL 2015049 Using Administrative Data for Research: A Companion Guide to A Descriptive Analysis of the Principal Workforce in Florida Schools
This report outlines the processes and procedures used to analyze data from the Florida education staffing database. The report also provides directions and examples for conducting similar work using administrative databases.
12/23/2014
NFES 2012809 Forum Guide to Supporting Data Access for Researchers: A State Education Agency Perspective
The Forum Guide to Supporting Data Access for Researchers: A State Education Agency Perspective recommends policies, practices, and templates that can be adopted and adapted by SEAs as they consider how to most effectively respond to requests for data about the education enterprise, including data maintained in longitudinal data systems. These recommendations reflect sound principles for managing the flow of data requests, establishing response priorities, monitoring appropriate use, protecting privacy, and ensuring that research efforts are beneficial to the education agency as well as the research community.
7/10/2012
REL 2012118 What Four States are Doing to Support Local Data-Driven Decision-Making: Policies, Practices, and Programs
This report documents how four state education agencies are supporting local data-driven decisionmaking through their policies, practices, and programs for creating data systems, improving data access and use, and building district and school capacity to use data.
11/15/2011
NCES 2011802 Traveling Through Time: The Forum Guide to Longitudinal Data Systems Book IV: Advanced LDS Usage
This document, Book Four of Four: Advanced LDS Usage, is the fourth and final installment of this Forum series of guides on longitudinal data systems (LDS). One goal of the Forum is to improve the quality of education data gathered for use by policymakers and program decisionmakers. An approach to furthering this goal has been to pool the collective experiences of Forum members to produce “best practice” guides in areas of high interest to those who collect, maintain, and use data about elementary and secondary education. Developing LDSs is one of those high-interest areas. These systems hold promise for enhancing both the way education agencies use data to serve students and the way they do business, from the policy level to the school office and into the classroom.
7/25/2011
NFES 2011805 Traveling Through Time: The Forum Guide to Longitudinal Data Systems Book III: Effectively Managing LDS Data
This document, Book Three of Four: Effectively Managing LDS Data, is the third installment of this Forum series of guides on longitudinal data systems (LDS). One goal of the Forum is to improve the quality of education data gathered for use by policymakers and program decisionmakers. An approach to furthering this goal has been to pool the collective experiences of Forum members to produce “best practice” guides in areas of high interest to those who collect, maintain, and use data about elementary and secondary education. Developing LDSs is one of those high-interest areas. These systems hold promise for enhancing both the way education agencies use data to serve students and the way they do business, from the policy level to the school office and into the classroom.
2/7/2011
NFES 2011804 Traveling Through Time: The Forum Guide to Longitudinal Data Systems Book II: Planning and Developing an LDS
This book, Planning and Developing an LDS, is the second in a four-part series about longitudinal data systems (LDS). The first book, What is an LDS?, focused on the fundamental questions of what an LDS is (and what it is not), what steps should be taken to achieve a sound system, what components make up an ideal system, and why such a system is of value in education. The present installment discusses the early stages of LDS development, and will help state and local education agencies through the process of determining what they want to accomplish with their LDS and what they will need in order to achieve these goals. The organization’s vision for an LDS should be heavily informed by the needs of a broad range of stakeholders. Throughout the systems development life cycle, policymakers and system developers need to engage in self-assessment, identifying the system they have before figuring out what type of system they want. Policymakers’ requirements should be driven by the needs of the education community, the costs involved given the legacy system and staff, and the institutional support for the project. Planners should ensure project sustainability by creating interest and sustained buy-in, and by securing long-term funding. Procurement planning must be done, that is, lining up a vendor or building the staffing capacity to construct the system. In addition, having the right developers may not be enough: an informed commitment to building, using, and maintaining the LDS must permeate the organization to ensure long-term success. And, throughout the life of the system, thorough evaluation must be done on a regular basis to ensure continued data quality and user satisfaction.
1/19/2011
NCES 2011603 Statistical Methods for Protecting Personally Identifiable Information in Aggregate Reporting
This Statewide Longitudinal Data Systems (SLDS) Technical Brief examines what protecting student privacy means in a reporting context. To protect a student’s privacy, the student’s personally identifiable information must be protected from public release. When schools, districts, or states publish reports on students’ educational progress, they typically release aggregated data—data for groups of students—to prevent disclosure of information about an individual. However, even with aggregation, unintended disclosures of personally identifiable information may occur. Current reporting practices are described and each is accompanied by an example table that is used to consider whether the intended protections are successful.

The Brief also illustrates that some practices work better than others in protecting against disclosures of personally identifiable information about individual students. Each data protection practice requires some loss of information. The challenge rests in identifying practices that protect information about individual students, while at the same time minimizing the negative impact on the utility of the publicly reported data. Drawing upon the review and analysis of current practices, the Brief concludes with a set of recommended reporting rules that can be applied in reports of percentages and rates that are used to describe student outcomes to the public. These reporting rules are intended to maximize the amount of detail that can be safely reported without allowing disclosures from student outcome measures that are based on small numbers of students.

NCES welcomes comments on the recommended reporting rules.
12/21/2010
NCES 2011601 Basic Concepts and Definitions for Privacy and Confidentiality in Student Education Records
This Technical Brief discusses basic concepts and definitions that establish a common set of terms related to the protection of personally identifiable information, especially in education records in the Statewide Longitudinal Data Systems (SLDS). This Brief also outlines a privacy framework that is tied to Fair Information Practice Principles that have been promulgated in both the United States and international privacy work.
11/23/2010
NCSER 20113001 A Study of States' Monitoring and Improvement Practices Under the Individuals with Disabilities Education Act
This report provides a description of the nature and scope of states' Part B and Part C monitoring systems. Data on 20 states' monitoring systems in 2004–05 and 2006–07 were collected during two site visits. The report describes states' approaches to monitoring and how states' monitoring systems and processes mapped onto a framework developed for the study.
10/28/2010
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