Virtual Posters
Full YouTube Playlist: https://youtube.com/playlist?list=PLOOWin7a1usKWZU57xwlMaAktTafGlYR3
Data Collection
P-1: DC's New Approach to Collecting and Using Faculty and Staff Data
https://youtu.be/ef8MHlYAScA
Melissa Amos, Office of the State Superintendent of Education
Laura Montas-Brown, Office of the State Superintendent of Education
The District of Columbia's (DC) Office of the State Superintendent of Education (OSSE) has streamlined the collection of faculty and staff data and is creating the Educator Talent and Equity dashboard to support LEAs in developing strategic staffing policies and practices by providing cross-school insights on educator supply and demand, retention, and equitable access to excellent teachers. The dashboard will also provide OSSE staff with aggregate citywide, LEA, and school workforce data.
Topic: Data Collection
Complexity: Entry Level
P-2: Demonstration of the Institute of Education Sciences (IES) Public Trust Application Manager (IPAM)
https://youtu.be/oCbMDPr_kHs
Zac Mangold, Sanametrix
Jennifer Nielsen, U.S. Department of Education
Melissa Roessler, Sanametrix
Marilyn Seastrom, U.S. Department of Education
The National Center for Education Statistics (NCES) manages its public trust security application process using Public Trust Application Manager (IPAM). If you help NCES fulfil its mission, you are connected to IPAM. IPAM is a web-based record management system for processing public trust security applications throughout the stages of agency level review and resubmissions. IPAM was designed to manage and track: contract and Contracting Officer Representative assignment, initiation of applicants, approval and/or rejection of the Public Trust application, fingerprints submission, release to Defense Counterintelligence and Security Agency (DCSA), DCSA approval or rejection, DCSA Schedule-Accepted status, and adjudication outcome. IPAM has significantly reduced the backlog of applications, increased processing time by automating data validations, streamlined the process for requesting an approval, and reduced the overall risk of sharing PII across organizations. In addition, the IPAM system includes data analysis reporting to identify most common rejections reasons, processing times, contract counts, status reports, and adjudication outcome reports. These reports contribute to the departments' continuous improvement process to ensure applications are processed in a timely manner with as few errors as possible.
Topic: Data Collection
Complexity: Entry Level
P-3: Student Dispositions: Insights from NAEP as Schools Reopen
https://youtu.be/zMy2y_dkXdQ
Jan Marie Alegre, Educational Testing Service
Ebony Walton, U.S. Department of Education, National Center for Education Statistics
The National Assessment of Educational Progress (NAEP) is known for the critically important information it provides about student achievement in our country. Many do not realize that the program also provides valuable insights into students' educational experiences and dispositions—all of which can provide meaningful pre-pandemic information for school administrators and educators as they evaluate the impact of the pandemic on students' happiness at school, confidence in their skills, and more. Learn how to dive into NAEP data to examine how students' dispositions varied across states and districts and by student demographics in 2019.
Topic: Data Collection
Complexity: Entry Level
P-4: Trouble Since 2013: Declining Overall Performance and Growing Score Gaps on NAEP
https://youtu.be/iaFq3zc68lc
Brian Cramer, U.S. Department of Education, National Center for Education Statistics
Ebony Walton, U.S. Department of Education, National Center for Education Statistics
The peak year for overall performance for the nation on NAEP reading and mathematics assessments was around 2013. From this time to the latest NAEP assessments (2019), performance has decreased, and this has been driven primarily by decreases for lower-performing students (those at the 10th and 25th percentiles), leading to a divergence in score trends between these lower-performing students and those at the higher-end of the distribution - students at the 75th and 90th percentiles. This presentation will discuss these trends along with performance for various student groups (e.g., race/ethnicity, etc.), states, and large urban districts to see which ones also experienced these patterns - and those that bucked these trends.
Topic: Data Collection
Complexity: Entry Level
Data Linking Beyond K-12
P-5: Using the CIP to SOC Crosswalk to Estimate Local Degree or Credential Worth
https://youtu.be/ix7nu1rYt88
John Evans, Public Education Foundation/Hamilton County Department of Education
Michaela Leaf, Public Education Foundation/Hamilton County Department of Education
Azilee Lyons, Public Education Foundation/Hamilton County Department of Education
Hemant Jain, University of Tennessee at Chattanooga
Providing public school students with accurate information about degree or credential worth has the potential to act as an equity lever. This presentation details the process of employing the CIP to SOC crosswalk and linking those results to local National Student Clearinghouse (NSC) major and degree data to provide potential salary projections. Additionally, a retrospective analysis of degree worth and credential attainment by high school and postsecondary site typologies was combined with the CIP to SOC crosswalk. The resulting dataset will be used in an application to increase college match and fit, leading to more equitable postsecondary opportunities and outcomes.
Topic: Data Linking Beyond K-12
Complexity: Advanced Level
Data Management
P-6: Introduction to the Department of Education's Data Strategy
https://youtu.be/kMjZUFa4460
Soumya Sathya, U.S. Department of Education, Office of the Chief Data Officer
Joanne Bogart, U.S. Department of Education, Office of the Chief Data Officer
This presentation will focus on the key elements of the Department's inaugural data strategy and how it propels the Department's data mission to optimize its ability to provide trusted data and insights to internal and external stakeholders. We will discuss the relevance of Data Strategy initiatives to the education community.
The Foundations for Evidence-Based Policymaking Act (Evidence Act) and the Federal Data Strategy put federal agencies on notice that data and evidence need to play a more prominent role in how the federal government functions. The Department's inaugural Data Strategy describes an ambitious vision for accelerating progress toward being a data-driven organization and will further push the Department in responding to current and future data needs in support of the agency's mission.
Topic: Data Management
Complexity: Entry Level
P-7: School Courses for the Exchange of Data (SCED): An Introduction
https://youtu.be/7T498jdkbYU
Ghedam Bairu, National Forum on Education Statistics
This is the first in a series of videos that provide information about the School Courses for the Exchange of Data (SCED) and the free resources available on the SCED website (
https://nces.ed.gov/forum/sced.asp) to assist education agencies with SCED implementation and use. This video focuses on the purpose of SCED and its uses in state and local education agencies. The National Forum on Education Statistics developed SCED to meet the need among schools, districts, and states for common, comparable course codes. SCED also facilitates research including National Center for Education Statistics transcript studies.
Topic: Data Management
Complexity: Entry Level
P-8: School Courses for the Exchange of Data (SCED): Course Coding
https://youtu.be/2onkhUTdITY
Ghedam Bairu, National Forum on Education Statistics
This is the second in a series of videos that provide information about the School Courses for the Exchange of Data (SCED) and the free resources available on the SCED website (
https://nces.ed.gov/forum/sced.asp) to assist education agencies with SCED implementation and use. This video explains the coding elements that make up SCED and illustrates the types of information that can be communicated through the use of SCED. The National Forum on Education Statistics developed SCED to meet the need among schools, districts, and states for common, comparable course codes. SCED also facilitates research including National Center for Education Statistics transcript studies.
Topic: Data Management
Complexity: Entry Level
P-9: Setting the Stage for Success with Generate
https://youtu.be/CNPgUv4Lr7g
Audrey Rudick, Center for the Integration of IDEA Data (CIID)
Lindsay Wise, Center for the Integration of IDEA Data (CIID)
Are you looking ahead at ED
Facts plans, and considering Generate for your state? CIID's Data Integration Toolkit provides fantastic first steps into the process. Completing "Step 1: Define the Goals for Integration" and "Step 2: Establish project plan and structures for data integration work" help to set the stage for a successful and timely Generate implementation, ensuring that the fundamental documentation and communication that support project plans are in place. Completing these early steps can mitigate risks such as staff and leadership turnover and ensure a more efficient implementation. This presentation will examine concrete steps and tools CIID provides for getting started with Generate.
Topic: Data Management
Complexity: Entry Level
P-29: Forum Guides to Data Strategy and Metadata
https://youtu.be/K0w1ZTirs6k
Georgia Hughes-Webb, West Virginia Department of Education
Laura Hansen, Metro Nashville Public Schools
Ghedam Bairu, U.S. Department of Education, National Center for Education Statistics
This session will highlight two National Forum on Education Statistics resources that are designed to help education agencies enhance their data practices. The Forum Guide to Strategies for Education Data Collection and Reporting (SEDCAR) provides information on designing and implementing a data collection and reporting strategy. The forthcoming Forum Guide to Metadata will discuss metadata and focus on its use, including how metadata can help manage data complications, improve data quality, and resolve data anomalies.
Topic: Data Management
Complexity: Entry Level
Data Privacy
P-10: Data Security and How to Develop a Plan to Protect Your Organization
https://youtu.be/touNgnvwFiQ
Ross Lemke, Privacy Technical Assistance Center
Mike Tassey, Privacy Technical Assistance Center
In the wake of the pandemic, cybersecurity at K-12 schools has become even more critical. Learn how to develop a robust security policy and how to evaluate practices based upon your organizational risk tolerance
Topic: Data Privacy
Complexity: Intermediate Level
P-11: Evaluation of Privacy and Confidentiality in an Integrated Data System
https://youtu.be/JeNs8_sBXZA
Sean Simone, Rutgers University
Shashi Yellambhatla, New Jersey Department of Education
SLDS systems combined with data from other agencies (e.g., motor vehicles, workforce, training, taxation, welfare, etc.) have extra challenges due to privacy and confidentiality laws governing each data source. This presentation describes a comprehensive privacy review conducted in New Jersey to ensure compliance across all laws when we open data up to researchers in 2022.
Topic: Data Privacy
Complexity: Entry Level
P-13: Sharing ED Data Across Activities Using Secure Multiparty Computation
https://youtu.be/BR_lJcbsfoc
Stephanie Straus, NCES Fellow/Georgetown University
David Archer, Galois, Inc.
Rawane Issa, Galois, Inc.
Amy O'Hara, Georgetown University
Sponsored by the National Center for Education Statistics (NCES), we conducted a demonstration of cryptographic privacy-preserving technology--secure multiparty computation (MPC)-- to show that two independent parties can safely share and compute on their joined confidential data. We accurately reproduced statistics on average federal Title IV aid from the annual 2015-16 National Postsecondary Student Aid Study (NPSAS). We simulated the record linkage of the two different data sources, NPSAS and the National Student Loan Data System (NSLDS), used to create these statistics, and the subsequent joint analysis. This presentation will discuss our successful results, resource utilization, and advantages of privacy assurance offered by this method.
Topic: Data Privacy
Complexity: Intermediate Level
Data Quality
P-14: Ensuring Quality: Data Quality in the 2020–21 CRDC
https://youtu.be/5-ZzG0cH3gE
Marshal Fettro, AEM Corporation
Stephanie Miller, U.S. Department of Education, Office of Civil Rights
Lauren Jetty, AEM Corporation
Data quality efforts are critical for the utility of federal surveys like the Civil Rights Data Collection (CRDC). The CRDC is a universe collection of districts and schools on key education and civil rights issues in our nation's public schools. This presentation will discuss the importance of ensuring high quality data across the breadth of CRDC modules and subject areas, including restraint and seclusion, offenses, discipline, and harassment or bullying. We will cover tips and tricks and new techniques and tools, including technical assistance documents and a new CRDC Business Rule Single Inventory, to help ensure quality data considering COVID-19.
Topic: Data Quality
Complexity: Intermediate Level
P-15: Innovations in Automated Scoring for NAEP Reading and Math Assessment
https://youtu.be/GSoa_XpRs-Y
John Whitmer, U.S. Department of Education, National Center for Education Statistics
Eunice Greer, U.S. Department of Education, National Center for Education Statistics
Conventional hand-scoring of NAEP constructed response (open-ended) items is a time- and resource-intensive process that costs millions of dollars for large-scale assessments. We will discuss the results of a 2021 RFI and prior research to demonstrate potential innovations from advances in cloud computing, natural language processing, and machine learning for NAEP reading and math items. We will discuss how models are trained to ensure accuracy and fidelity to scoring rubrics, what measures provide model interpretability, and procedures used to ensure that models do not bias based on race/ethnicity or other characteristics. No prior knowledge of NLP is expected.
Topic: Data Quality
Complexity: Intermediate Level
P-22: Using Data to Detect and Diagnose Errors in Matching Processes
https://youtu.be/VRoNDgS4Ls8
Jeff Watson, SLDS State Support Team
John Sabel, Education Research Data Center
Jeremias Solari, Utah Data Research Center
Kelsey Martinez, Utah Department of Workforce Services
The value of a P20W data system depends greatly on the ability of the system to match records between sectors despite imperfect information. This presentation will explore how data can be used to identify and diagnose errors in identity matching processes. John Sabel of Washington State's Education Research Data Center will describe how the "cardinality" of relationships between matched datasets (i.e. One-to-One, One-to-Many, Many-to-One and Many-to-Many) can be used to uncover problems. In addition, the direction of the cardinalities can be used to diagnose the nature and location of those problems. Utah's Data Research Center (URDC) will describe how it has created and used synthetic data to improve data matching. More specifically, by comparing the performance of matching algorithms on data for which the true state of affairs is known, URDC has been able to benchmark algorithm performance at various scales.
Topic: Data Quality
Complexity: Intermediate Level
Data Standards
P-16: Using the Power of CEDS to Report MOE/CEIS Data to OSEP
https://youtu.be/HOVPuudQBtA
Fred Edora, Center for IDEA Fiscal Reporting (CIFR)
Dan Mello, Center for IDEA Fiscal Reporting (CIFR)
Carol Seay, Center for the Integration of IDEA Data (CIID)
Nancy Copa, Common Education Data Standards (CEDS)
Under IDEA Part B Section 618, states are required to submit fiscal data annually to OSEP for every LEA regarding 611 and 619 allocations, Maintenance of Effort (MOE) reductions taken, and Coordinated Early Intervening Services (CEIS) data. This presentation will provide an overview of CEDS, how using CEDS can assist with this report, explain how three TA centers are collaborating to create a connection within CEDS and how this connection can help states align their data systems to more easily report MOE/CEIS data to OSEP as well as how it can help improve program decision making using fiscal data.
Topic: Data Standards
Complexity: Intermediate Level
Data Use
P-17: Common Core of Data 101
https://youtu.be/-CNoOoCukds
Beth Sinclair, AEM Education Services
Chen-Su Chen, U.S. Department of Education, National Center for Education Statistics
The Common Core of Data (CCD) is the U.S. Department of Education's primary database on public elementary and secondary education. It is an annual, comprehensive collection that gathers data on the universe of public K-12 schools and school districts. This presentation is for both new and seasoned users of public K-12 data. It will include an overview of the CCD data collection, recent data file releases, and CCD-related blog posts to support users.
Topic: Data Use
Complexity: Entry Level
P-18: Identifying High-Performing, High-Growth, and High-Needs Schools: Lessons Learned From a Data-Use Capacity-Building Collaboration in Kentucky
https://youtu.be/U4Y4mXlXtGQ
Aaron Butler, Kentucky Department of Education
Daniel Princiotta, SRI International
In 2019–20, the Kentucky Department of Education (KDE) worked with the Regional Education Laboratory Appalachia to identify high-performing and high-growth schools in grade 3 reading and mathematics. KDE used longitudinal data to fit multilevel models to predict school-level reading and math scores and their growth over time, and they identified schools that over- and under-performed relative to statistical predictions. This statistical approach and the capacity-building effort behind it hold lessons learned for SEA staff interested in strengthening their analytic capabilities. Presenters will also discuss implications for identifying schools that were effective during the pandemic and pinpointing schools in need of additional supports post-pandemic.
Topic: Data Use
Complexity: Intermediate Level
P-19: Partnering to Identify and Use Data to Inform Policy: Lessons from Palau
https://youtu.be/sPirfNpHDOE
Ben Cronkright, McREL International
Magaria Tellei, Palau Ministry of Education
Building on the Palau Ministry of Education Master Plan, researchers and practitioners are co-developing theories of action and metrics on implementation and outcomes to (re)define professional learning. This session describes approaches used to take school improvement to scale by implementing evidence-based professional learning intervention, instructional coaching cycles, which has demonstrated positive effects on teacher morale. Presenters will illustrate the ways in which they have designed and adapted strategies for improvement across a diverse range of schools. They will also share how ongoing measurement and monitoring for improvement and adaptation for specific school needs are critical for effectively scaling an intervention.
Topic: Data Use
Complexity: Intermediate Level
P-20: Preparing for Virtual Learning: What Data from International Assessments Reveal
https://youtu.be/2bMjqmUP0lU
Samantha Burg, U.S. Department of Education, National Center for Education Statistics
Sheila Thompson, U.S. Department of Education, National Center for Education Statistics
The pandemic found many schools and students across the world quickly moving to virtual learning. To better understand the global impact of COVID on education, we must first understand what technology students and teachers had access to and familiarity with technology before the pandemic. It is also important to understand characteristics such as motivation, grit and determination of students which could help them adjust and possibly thrive in a virtual world. This presentation will explore pre-pandemic results from several international education assessment (PIRLS, PISA and TIMSS) and how these variables and characteristics compare across countries including the U.S.
Topic: Data Use
Complexity: Entry Level
P-21: Stakeholder Engagement in Guam
https://youtu.be/q_QQx4TmDCQ
Christina Tydeman, REL Pacific at McREL International
Zenaida Natividad, Guam Department of Education
Moryne-Nicole Monforte, Guam Department of Education
Natasha Saelua, REL Pacific at McREL International
Mark Yu, REL Pacific at McREL International
Guam's approach to their Guam One Stop Data Village (GOSDV)'s stakeholder engagement process includes three main strategies. The first is leveraging early involvement of political leadership through their Legislative Exposure to GOSDV System (LEGS) plan to develop broad interest in, commitment to, and long-term sustainability of their SLDS system. The second is engaging a broad stakeholder base through Guam's Education Agenda for Research (GEAR) as a key component of GOSDV's ongoing stakeholder engagement process. The third is to ascertain the data use culture of GOSDV stakeholders. In the early stages of SLDS development, the GOSDV Stakeholders Committee is embarking on an environmental scan to gather information about stakeholder readiness and expectations to inform their ongoing and future stakeholder engagement and communication strategies toward developing a healthy data use culture. Members of their GOSDV team and REL Pacific will share Guam's LEGS approach and their progress implementing the plan, their strategies for stakeholder engagement through the development and dissemination of GEAR as a guiding tool and driver in their theory of change and SLDS development, and their progress in conducting an environmental scan of GOSDV stakeholders' data use.
Topic: Data Use
Complexity: Entry Level
P-23: Using PowerBI to Visualize Career and Technical Information Data
https://youtu.be/shte_B9CJ8c
Monica Mean, U.S. Department of Education, Office of Career, Technical, and Adult Education
Adam Flynn-Tabloff, U.S. Department of Education, Office of Career, Technical, and Adult Education
Jean Yan, U.S. Department of Education, Office of Career, Technical, and Adult Education
The U.S. Department of Education's Office of Career, Technical, and Adult Education (OCTAE) utilized PowerBI to create dashboards using our annual national and state-level Perkins career and technical education (CTE) data. This allowed us to identify and highlight enrollment trends, equity gaps in CTE, career clusters with the most enrollment, and other visual analyses that provide useful information to inform policymaking.
Topic: Data Use
Complexity: Entry Level
P-24: Welcome to the New DataLab: A Tour of NCES's Improved Online Data Tool
https://youtu.be/D5eZ4lCuILg
David Richards, U.S. Department of Education, National Center for Education Statistics
The all-new DataLab provides access to data from 98 primary, secondary, and postsecondary education NCES datasets. The new user-friendly interface makes it easy to create tables and charts and perform logistic and linear regressions. DataLab staff will demonstrate the functionality of this newly-modernized tool, including how to create data tables, data visualizations, and regressions; how to generate estimates that adjust dollar values to control for inflation; and how to save and share analyses and output. This presentation is appropriate for both novice users interested in learning about DataLab and advanced users interested in finding out more about the modernized tool.
Topic: Data Use
Complexity: Intermediate Level
P-25: What Would You Do With 50 Years of CRDC Data?
https://youtu.be/rEkFwGZ_HoA
Jenn Hudson, American Institutes for Research
Nabil Hageali, Vertivis
Stephanie Miller, U.S. Department of Education
Over the past year, the authors have been working on a project to digitally preserve archival CRDC data that dates back to 1968. The types of data discovered within and, in some cases, across data collection cycles includes data summaries, time-series files, flat files, reports, and user guides. This presentation will cover the process by which CRDC data and related content were extracted from CDs and digitally preserved for online access and the authors will present a preliminary database design that could be used to organize CRDC archival data, data documentation, and other related content to optimize user accessibility and data usability.
Topic: Data Use
Complexity: Intermediate Level
Fiscal Data
P-26: Highlights of School-Level Finance Data: School Year 2015–16 and 2016–17
https://youtu.be/XeA_ZsMIylc
Stephen Cornman, U.S. Department of Education, National Center for Education Statistics
Osei Ampadu, U.S. Census Bureau
Lei Zhou, Activate Research
Steve Wheeler, U.S. Census Bureau
Policymakers, researchers, and the public have long voiced concerns about the equitable distribution of school funding within and across school districts. Education expenditure data are now available at the school level through the School-Level Finance Survey (SLFS), which NCES has conducted annually since 2014.
A new NCES report, Highlights of School-Level Finance Data: Selected Findings From the School-Level Finance Survey (SLFS) School Years 2015–16 (FY 16) and 2016–17 (FY 17), presents key findings and other data highlights from the SLFS for school years 2015–16 and 2016–17:
- The majority of states participating in the SLFS are able to report school-level expenditure data requested by the survey for a high percentage of their schools.
- The SLFS can be used to evaluate and compare the variability of school-level expenditure data within states and across school districts.
- The SLFS can be used to evaluate school-level expenditure data by various descriptive school characteristics such as charter status and urbanicity.
- The SLFS can be used to evaluate and compare school-level expenditure data by various poverty indicators, such as Title I eligibility and school neighborhood income-to-poverty ratio (IPR).
Topic: Fiscal Data
Complexity: Intermediate Level
P-27: PISA Results: Are Students Smart about Money?
https://youtu.be/zeS2Yo3FQc4
Samantha Burg, U.S. Department of Education, National Center for Education Statistics
COVID had huge financial impacts that revibrated across the globe from country economies to losses of paychecks and jobs for many families. This forced many young people to become more aware of finances and budgets as their families struggled with finances. Have you ever wondered what students know and can do in financial literacy? PISA is the only program that assesses financial literacy around the world including the U.S. This presentation will look at what at pre-pandemic data from 2015 and 2018 (and 2022 results down the road).
Topic: Fiscal Data
Complexity: Entry Level
P-28: The Feasibility of Collecting School Pension and Social Security Data for Teachers: School Year 2016–17
https://youtu.be/m0zkvqEx8yg
Philip Vidal, U.S. Census Bureau
Stephen Cornman, U.S. Department of Education, National Center for Education Statistics
Melinda Caskey, U.S. Census Bureau
Osei Ampadu, U.S. Census Bureau
In 2019, the National Center for Education Statistics (NCES) commenced an exploratory data collection entitled the School Pension Survey (SPS). Prior to 2019, NCES did not collect data items that may facilitate a more comprehensive understanding of pension funds for teachers and other school personnel. The pilot SPS collected pension and social security status data at the district level from 9 state education agencies (SEAs) for FY 17 in its first year. The initial research question is whether the SPS is a viable, efficient method of collecting school pension data? The R&D report provides a discussion of respondents' ability to report survey data items including unit and item response rates; whether states have the administrative records available to report pension-related data; data quality issues; data anomalies; and edit procedures. The SEA and LEA respondent burden, as well as advantages and challenges of collecting pension data are also discussed. Finally, the report discusses whether the benefits of the SPS outweigh the challenges.
Topic: Fiscal Data
Complexity: Intermediate Level
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