<?xml version="1.0"?>
<rss version="2.0"><channel><title>NCEE What's New</title><link>http://ies.ed.gov/ncee/whatsnew/</link><description>For the latest in events, developments, and updates to the NCEE website, check back here often.</description><language>en-us</language><category>education</category><category>statistics</category><category>data access tools</category><category>libraries</category><category>schools</category><category>colleges</category><item><title>RFP: Evaluation of the Comprehensive Technical Assistance Centers </title><description><![CDATA[On March 1, 2013, the U.S. Department of Education re-released the Request for Proposals (RFP) for the Evaluation of the Comprehensive Technical Assistance Centers with modifications.  Recognizing that a potential conflict of interest (COI) exists for prospective offerors, the Department is implementing a two-phase process for this procurement in which prospective offerors are requested to submit a COI strategy by March 15 for Department review. Other modifications include a reduction in scope and reduced period of performance.  Proposals are due May 3.]]></description><pubDate>3/7/2013 7:07:06 AM</pubDate><link>http://ies.ed.gov/funding/ccp.asp</link></item><item><title>School Improvement Grants: Analyses of State Applications and Eligible and Awarded Schools</title><description><![CDATA[School Improvement Grants (SIG) are authorized under Title I section 1003(g) of the <em>Elementary and Secondary Education Act</em> (ESEA) and provide funds to assist with turning around the nation's persistently lowest-achieving schools. Using publicly-available data, "School Improvement Grants: Analyses of State Applications and Eligible and Awarded Schools" examines (1) the SIG policies and practices states intend to implement based on their Cohort 2 applications for federal SIG funds, (2) the characteristics of schools eligible for and awarded SIG in Cohort 2, and (3) how these intended policies, practices, and school characteristics compare between Cohort 1 and Cohort 2. The first cohort of grantees began implementing reforms in the 2010-11 school year, with a second cohort of grantees beginning reforms in the 2011-12 school year.]]></description><pubDate>10/24/2012 8:38:49 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20124060/</link></item><item><title>Impact Evaluation of Math Professional Development</title><description><![CDATA[This contract was awarded to the American Institutes for Research (AIR).  The contractor will conduct a random assignment evaluation of Intel Math and Mathematics Learning Communities, which is an intensive, sustained, and interactive math PD intervention focused on comprehensively enhancing teacher content knowledge and integrating this knowledge into the classroom. The evaluation will examine how the PD intervention is implemented, as well as how the PD intervention impacts teacher knowledge, teacher practice, and student achievement. ]]></description><pubDate>9/27/2012 1:07:20 PM</pubDate><link>http://ies.ed.gov/ncee/projects/evaluation/math_pd.asp</link></item><item><title>NCEE Releases a Report Examining State and District Receipt of Recovery Act K-12 Education Funds</title><description><![CDATA[This report uses Department of Education and publicly-available data sources to examine the distribution of Recovery Act K-12 education funds.  In particular, data from Recovery.gov (a new cross-agency website developed to gather and make public reporting on the receipt and use of Recovery Act funds) made it possible to examine both grant and sub-grant award amounts and to track funds at the state and district levels.  Specifically, the report examines (1) how much states and districts received from the Recovery Act and its different programs and (2) whether and how the distribution of funds varied by key characteristics (e.g., child poverty rates) of the recipient states and districts.  Findings lay the groundwork for ED's multi-year evaluation "Charting the Progress of Education Reform: An Evaluation of the Recovery Act's Role", which examines the implementation of Recovery Act promoted K-12 education reforms.]]></description><pubDate>9/18/2012 7:39:06 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20124057/</link></item><item><title>Ruth Curran Neild Named Commissioner of the NCEE</title><description><![CDATA[John Q. Easton, Director of IES, announced that Ruth Curran Neild has been named Commissioner of the National Center for Education Evaluation and Regional Assistance starting September 1st. "Ruth has been a superb Associate Commissioner and will bring her steady guidance and creative leadership to the Center," said Easton.<br/><br/>	
From January 2011 until her appointment as Commissioner, Dr. Neild served as the Associate Commissioner for NCEE's Knowledge Utilization division. In that capacity, she emphasized the importance of both technically excellent education research and its clear, engaging presentation for educators in user-friendly formats. Prior to joining NCEE, she was a Research Scientist at the Johns Hopkins University Center for Social Organization of Schools, where she worked on research projects that ranged from descriptive and correlational to studies of impact. She also served on the standing faculty of the University of Pennsylvania's Graduate School of Education.<br/><br/>
Neild is succeeding Rebecca Maynard, who is returning to the University of Pennsylvania. "Ruth is a fantastic choice for this position," said Maynard. "She brings to the job not only years of experience as a producer of highly policy relevant research, but also familiarity with and expertise in the full range of work that goes on in NCEE&#8212;from large-scale randomized controlled trials to the dissemination activities of the National Library of Education and ERIC.  In the relatively short time Ruth has been at NCEE, she has demonstrated both vision for bringing more rigor and relevance to education research and an amazing talent for recruiting and mentoring staff to carry out the diversity of work that goes on in the center."<br/><br/>			
As Commissioner, she will oversee NCEE, one of four centers in the Institute of Education Sciences. NCEE helps educators and policy makers make informed decisions about education programs through the work of its two divisions: <a href="http://nces.ed.gov/ncee/projects/evaluation/index.asp">Evaluation</a>, which conducts large-scale evaluations of federally funded education programs and practices, and Knowledge Utilization, which supports locally developed research and evaluation projects and technical assistance on data use through the ten <a href="http://nces.ed.gov/ncee/edlabs/">Regional Educational Laboratories</a>, and the synthesis and widespread dissemination of research through the <a href="http://nces.ed.gov/ncee/wwc/">What Works Clearinghouse</a>, the <a href="http://nces.ed.gov/ncee/projects/nat_ed_library.asp">National Library of Education</a>, and the Education Resources Information Center (<a href="http://eric.ed.gov/">ERIC</a>) online database.<br/><br/>
Neild said, "Conducting rigorous research on topics of greatest concern to educators and policymakers remains a top priority of NCEE.  At the same time, we seek to lead the field in how we communicate about research, including development of products that are user-friendly, engaging, and attuned to the needs of the target audienc]]></description><pubDate>9/5/2012 7:47:20 AM</pubDate><link>http://ies.ed.gov/ncee/aboutus/</link></item><item><title>NCEE Releases Report on the Inclusion of Students with Disabilities in School Accountability Systems</title><description><![CDATA[This interim report presents descriptive information on school-level accountability, adequate yearly progress (AYP), and school improvement status of schools accountable and schools not accountable for the performance of the students with disabilities (SWD) subgroup under the Elementary and Secondary Education Act.  Based on U. S. Department of Education EDFacts data from the 2005-06 to 2008-09 school years for up to 40 states, key findings from the study include:
<ul>
<li>Across the 40 states with relevant data, 35 percent of public schools were accountable for the performance of the SWD subgroup in the 2008-09 school year, representing 58 percent of tested SWDs in those states.  In those same 40 states, 62 percent of middle schools were accountable for SWD performance, while 31 percent of elementary schools and 23 percent of high schools were accountable.</li>
<li>In 20 states that had relevant data for all fours years, there was a steady increase in the percentage of SWD-accountable schools, from 25 percent in the 2005-06 school year to 34 percent in the 2008-09 school year.</li>
<li>In 32 states with relevant data, 55 percent of public schools were not accountable for the SWD subgroup in any of the 4 years examined, while 18 percent of schools that were consistently accountable in each of the 4 years.</li> 
<li>In 37 states with relevant data, nine percent of all public schools missed AYP in the 2008&#8211;09 school year because of SWD subgroup performance and other reason(s), and 5 percent missed it solely because of SWD subgroup performance. Together these schools served 28 percent of tested SWDs in all public schools in these states.</li>
<li>Among schools that were consistently accountable for the performance of the SWD subgroup during the 4 years across 27 states, 56 percent were never identified for school improvement over this time period.  By comparison, among schools that were not accountable for SWD subgroup performance in any of the 4 years, 76 percent were never identified for improvement.</li>
</ul>]]></description><pubDate>5/29/2012 7:47:48 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20124056/</link></item><item><title>Impacts of Title I Supplemental Educational Services on Student Achievement</title><description><![CDATA[A new report examines the potential achievement benefits of Title I Supplemental Education Services on the reading and mathematics achievement of students in six school districts where services are oversubscribed.  "Impacts of Title I Supplemental Educational Services on Student Achievement," uses a regression discontinuity design to obtain estimates of the impacts of SES in the six study districts in three states (Connecticut, Ohio, and Florida) where more eligible students applied for SES than could be served with available funds, requiring prioritization of SES to the lowest-achieving students among the eligible applicants.  Analyses compare the outcomes of students just below and above the cutoff value for receiving services.<br/><br/>
The report presents analyses based on district data collected on all SES applicants and survey data collected from SES providers serving the six study districts.]]></description><pubDate>5/3/2012 8:00:13 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20124053/</link></item><item><title>NCEE releases Technical Methods paper on comparing experimental and non-experimental designs</title><description><![CDATA[This NCEE Technical Methods Paper compares the estimated impacts of the offer of charter school enrollment using an experimental design and a non-experimental comparison group design. The study examined four different approaches to creating non-experimental comparison groups ordinary least squares regression modeling, exact matching, propensity score matching, and fixed effects modeling.  The data for the study are from students in the districts and grades that were represented in an experimental design evaluation of charter schools conducted by the U.S. Department of Education in 2010 (For more information, see: <a href="http://ies.ed.gov/ncee/pubs/20104029/index.asp">http://ies.ed.gov/ncee/pubs/20104029/index.asp</a>)<br/><br/>
The study found that none of the comparison group designs reliably replicated the impact estimates from the experimental design study.  However, the use of pre-intervention baseline data that are strongly predictive of the key outcome measures considerably reduced, but did not eliminate the estimated bias in the non-experimental impact estimates. Estimated impacts based on matched comparison groups were more similar to the experimental estimators than were the estimates based on the regression adjustments alone, the differences are moderate in size, although not statistically significant.]]></description><pubDate>4/26/2012 8:10:02 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20124019/</link></item><item><title>Replicating Experimental Impact Estimates Using a Regression Discontinuity Approach</title><description><![CDATA[This NCEE Technical Methods Paper compares the estimated impacts of an educational intervention using experimental and regression discontinuity (RD) study designs. The analysis used data from two large-scale randomized controlled trials&mdash;the <a href="http://ies.ed.gov/pubsearch/pubsinfo.asp?pubid=NCEE20074006">Education Technology Evaluation</a> and the <a href="http://nces.ed.gov/transfer.asp?location=www.mathematica-mpr.com/publications/howtoorder.asp">Teach for America Study</a>&mdash;to provide evidence on the performance of RD estimators in two specific contexts. More generally, the report presents and implements a method for examining the performance of RD estimators that could be used in other contexts. The study found that the RD and experimental designs produced impact estimates that were meaningful in size, though not significantly different from one another. The study also found that manipulation of the assignment variable in RD designs can substantially influence RD impact estimates, particularly if manipulation is related to the outcome and occurs close to the assignment variable's cutoff value.]]></description><pubDate>4/25/2012 8:05:59 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20124025/</link></item><item><title>Moving Teachers: Implementation of Transfer Incentives in Seven Districts</title><description><![CDATA[A new report describes implementation and intermediate impacts of an intervention designed to provide incentives to induce a school district's highest-performing teachers to work in its lowest-achieving schools.  The report, "Moving Teachers: Implementation of Transfer Incentives in Seven Districts," uses random assignment within each district to form two equivalent groups of classrooms at the same grade level ("teacher teams"), a treatment group that had the chance to participate in the intervention and a control group that did not. Analyses include 90 vacancy pairs and 86 schools in the 7 study districts. 
Data for this report were collected on program implementation and teacher-  and principal-reported behaviors and perceptions.]]></description><pubDate>4/3/2012 9:08:28 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20124051/</link></item><item><title>What Are Districts&amp;#8217; Written Policies Regarding Student Substance-Related Incidents?</title><description><![CDATA[Recent events have increased interest in district policies relating to student substance use and whether they best serve the needs of their communities and students. To better understand the nature of the policies that may be in use around the country, the Institute of Education Sciences commissioned a study to examine the features of the written substance-related policies for the 100 largest school districts in the country.]]></description><pubDate>2/1/2012 10:26:57 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20124022/</link></item><item><title>NCEE Reference Report Examines the Use of State Test Scores in Multi-State and Multi-Grade Randomized Experiments</title><description><![CDATA[An important question for educational evaluators is how best to measure academic achievement, the outcome of primary interest in many studies. In large-scale evaluations, student achievement has typically been measured by administering a common standardized test to all students in the study (a "study-administered test"). In the era of No Child Left Behind (NCLB), however, state assessments have become an increasingly viable source of information on student achievement. Using state tests scores can yield substantial cost savings for the study and can eliminate the burden of additional testing on students and teaching staff. On the other hand, state tests can also pose certain difficulties: their content may not be well aligned with the outcomes targeted by the intervention and variation in the content and scale of the tests can complicate pooling scores across states and grades.]]></description><pubDate>10/12/2011 9:20:10 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20124015/</link></item><item><title>NCEE Reference Report Analyzes the Consequences of Using State Assessments to Measure Student Achievement in Evaluations of Educational Interventions </title><description><![CDATA[State assessments provide a relatively inexpensive and increasingly accessible source of data on student achievement.  In the past, rigorous evaluations of educational interventions typically administered standardized tests selected by the researchers ("study-administered tests") to measure student achievement outcomes.  Increasingly, researchers are turning to the lower cost option of using state assessments for measures of student achievement.]]></description><pubDate>10/11/2011 1:58:17 PM</pubDate><link>http://ies.ed.gov/ncee/pubs/20124016/</link></item><item><title>NCEE releases report on &amp;quot;Variability in Pretest-Posttest Correlation Coefficients by Student Achievement Level&amp;#8221;</title><description><![CDATA[State assessments are increasingly used as outcome measures for education evaluations. The scaling of state assessments produces variability in measurement error, with the conditional standard error of measurement increasing as average student ability moves toward the tails of the achievement distribution. This report examines the variability in pretest-posttest correlation coefficients of state assessment data for samples of low-performing, average-performing, and proficient students to illustrate how sample characteristics (including the measurement error of observed scores) affect pretest-posttest correlation coefficients. As an application, this report highlights how statistical power can be attenuated when correlation coefficients vary according to sample characteristics. Achievement data from four states and two large districts in both English/Language Arts and Mathematics for three recent years are examined. The results confirm that pretest-posttest correlation coefficients are smaller for samples of low performers, reducing statistical power for impact studies. Substantial variation across state assessments was also found. These findings suggest that it may be useful to assess the pretest-posttest correlation coefficients of state assessments for an intervention&#8217;s target population during the planning phase of a study.]]></description><pubDate>9/7/2011 11:15:01 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20114033/</link></item><item><title>Final Report on the Evaluation of the Comprehensive Technical Assistance Centers Program</title><description><![CDATA[This congressionally mandated report examines the work of the Comprehensive Technical Assistance Centers in three of the five program years (2006-07, 2007-08, 2008-09), starting with the second year of program funding. The Comprehensive Technical Assistance Centers program is authorized under the Educational Technical Assistance Act of 2002 to provide technical assistance to states to implement provisions of NCLB through 16 Regional Comprehensive Centers (RCCs) and 5 Content Centers (CCs). The evaluation focuses on the Centers' work drawing upon information gathered from Center management plans, an inventory of each Center&#8217;s projects, interviews with staff from each Center, surveys of state managers and project participants, and an assessment of the projects by an expert panel. The main findings include:
<ul>
<li>Consistent with the program design, RCCs worked directly with states on an ongoing basis in over 80 percent of sampled projects in each year, and CCs focused on synthesizing, translating, and delivering knowledge to RCCs and states in more than 70 percent of sampled projects in each year.</li>
<li>Centers addressed the most frequently cited state priority of "statewide systems of support," and an increasing number of state managers reported each year that Center assistance served their purposes. In 2008-09, 82 percent of state managers reported that Center assistance expanded state capacity in "statewide systems of support" to a "great" or "moderate" extent. </li>
<li>On average across each of the three years, expert panels rated sampled project materials as "moderate" to "high" quality, and project participants rated the sampled projects "high" on relevance and usefulness. Ratings were on a 5-point scale, with 3 representing "moderate" and 4 representing "high."</li></ul>
]]></description><pubDate>8/31/2011 9:42:03 AM</pubDate><link>http://ies.ed.gov/ncee/pubs/20114031/</link></item></channel></rss>
