1-A: What Did Machine Learning See in This Student That I Missed?
DeDe
Conner, Kentucky Department of Education
Eric
Gordee, Infinite Campus
Schools collect a treasure of student data which can be analyzed by machine learned algorithms to predict K-12 success. What started as a dropout prevention system has expanded to provide customizable dashboards to help answer the question: Why did this student get identified as at risk? The Kentucky Department of Education partnered with Infinite Campus to create an advanced and efficient statewide solution to examine student data that schools collect to support positive outcomes for students. Find out more about how these tools can make a difference in students' lives.
Topic: Data Use
Complexity: Intermediate Level
1–B: English Learners: Exit Ramp Closed
Fawn
Dunbar, State of Michigan/CEPI
Hussein
Gharib, State Of Michigan/CEPI
Michigan implemented a process to automatically exit EL students who test proficient from the EL program leveraging input from a cross-office workgroup.
Districts had difficulty reporting exited students due to complex exit criteria, data in multiple repositories, collection system rules, and leveraging test results. Those issues meant students weren't exited from EL programs and were therefore expected to test in the current school year even though they had tested proficient the year prior. The solution involved simplified exit criteria and transfer of data across systems. The result improved data quality, reduced reporting burden by districts, and eliminated frustration for everyone.Topic: Data Management
Complexity: Entry Level
1–C: Building a Modern SEA Data Estate
Nicholas
Handville, Georgia Department of Education
Jayesh
Dave, Georgia Department of Education
Adam
Churney, Georgia Department of Education
Kathy
Aspy, Georgia Department of Education
State education agencies are faced with growing data challenges and increased demands and expectations from stakeholders. In response, many SEAs are implementing multi-year projects to modernize data systems, often supported by state ESSER funds. Ensuring these efforts are fiscally sustainable and successful at meeting the ever-changing needs of stakeholders is not without challenges, and state teams have a lot to learn from the experiences of their peers.
In this session, Georgia will provide its lessons learned while building a modern data estate that will be both sustainable and successful. The lessons will cover the technical and operational aspects of the work, fiscal challenges, and the importance of people and relationships.
The session will provide guiding principles and questions to support SEAs in meeting the needs of stakeholders and ensuring the work is sustainable post-ESSER. The session will include a whole group conversation with attendees on their implementation and sustainability concerns, with an emphasis on how SEAs can engage in an ongoing conversation to encourage and facilitate collaboration.
Topic: Other
Complexity: Intermediate Level
1–D: Putting Use Cases in the ECIDS Driver's Seat
Ben
Baumfalk, Nebraska Department of Education
Jared
Stevens, Nebraska Department of Education
Kristen
Reynolds, Student1
Nebraska's Early Childhood Integrated Data System (ECIDS) is designed with users in mind. Drawing from the extensive stakeholder engagement conducted under the PDG planning grant, the Nebraska Department of Education's ECIDS team identified three priority use cases to drive the first phase of development. This session will provide an overview of the solution's cloud-first technical architecture, a new CEDS-aligned data model, and the MVP visualizations.
Topic: Data Linking Beyond K-12
Complexity: Entry Level
1–E: Getting Free Help with Your Statewide Longitudinal Data System (SLDS)
Corey
Chatis, Statewide Longitudinal Data Systems State Support Team
Dana
Brandt, DataSpark/Rhode Island Longitudinal Data System
Scott Lee, Colorado Department of Education
Do you wish you could get free, experienced help with the complicated work of planning, enhancing, using, and sustaining a statewide longitudinal data system (SLDS)? Well, you can! Join this session to learn about SLDS resources and how the SLDS State Support Team (SST), a group of technical assistance experts, can support your work and connect you with other states that have accomplished what you aim to achieve. SLDS leadership from Rhode Island and Colorado will share how SST has helped them build capacity, save time, and learn from their peers across the country.
Topic: SLDS
Complexity: Entry Level
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1–F: Strategy Workshop: Software to Empower Teachers in the Testing and Improvement of Their Instructional Strategy
Ben
Dederich, Education Analytics
Dan
Ralyea, South Carolina Department of Education
Dr. Christopher Wolfe, Marzano Research
The South Carolina Department of Education and Education Analytics have partnered to produce and introduce a platform that empowers teachers to explore new instructional strategies and promote collaboration amongst peers to improve student outcomes. Strategy Workshop houses a selective library of evidence-based strategies that teachers can try in their classroom. Furthermore, Strategy Workshop utilizes the Teacher as Researcher framework to walk an educator through planning, collecting data, and a final analysis and reflection stage so that they can determine what strategies really make a difference in their students' achievement.
Topic: Data Use
Complexity: Entry Level
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1–G: Forum Guide to Discipline Data
Ellis
Ott, Fairbanks North Star Borough School District (AK)
Bradley
McMillen, Wake County Public School System (NC)
The Forum Guide to Discipline Data is designed to help education agencies collect, manage, report, and use data about discipline. The guide discusses the importance of discipline data and how these data have changed over time, provides key considerations for data management and staff training, and identifies data reporting and use best practices. The guide is intended for education agency staff involved in collecting and using discipline data to improve student outcomes, promote positive and productive learning environments, and ensure equity in education. This includes staff responsible for reporting accurate and timely data to the federal government.
Topic: Data Management
Complexity: Entry Level
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1–H: The Use Case of Montana: SLDS Early Warning System & SLPM Data
Robin
Clausen, Montana Office of Public Instruction
Christiana
Stoddard, Montana State University
Montana's research agenda includes investigations of the processes and outcomes of the Montana Early Warning System (NCER 2021 using SLDS grant) and analysis of School Level Poverty Measures (2021 Supplemental NCES Grant). Montana began using the Early Warning System (drop out prevention) in 2012. This mixed method study assesses its efficiencies, processes, and outcomes. We examine the relationship between predicted graduation, dropout, and actuals. We find few errors. The results indicate a pattern of improved graduation rates among adopting schools. To complement the statistical results, investigators survey and interview school leaders about program implementation and processes. Framing poverty in rural areas is complex due to missing data, non-participation in NSLP, or underestimation in rural areas. Estimates based on income data from the American Community Survey use addresses to triangulate income data. There are differences between poverty measures based on community size and distance from a city. There are also income differences based on proximity to school. Students residing far from rural schools are at a relative disadvantage. In other locales and in comparison, students residing far from school are at a relative advantage. Income and the degree it can explain student outcomes vary by geography, even within a school community.
Topic: SLDS
Complexity: Intermediate Level
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1–J: Assessing the Impact of COVID-19 on Revenues and Expenditures for Public Elementary and Secondary Education: Fiscal Years 2020 (school year 2019–20) and 2021 (school year 2020–21)
Stephen Q. Cornman, U.S. Department of Education
Kaitlin Hanak, U.S. Census Bureau
Malia
Nelson, U.S. Census Bureau
Clara
Moore, U.S. Census Bureau
Congress authorized $282.35 billion in federal assistance for public elementary and secondary school districts to reduce the impact of COVID-19. This session presents data from the National Public Education Financial Survey (NPEFS) and School District Finance (F-33) Survey for fiscal years 2020 and 2021. NPEFS and F-33 added 18 items to track revenues and expenditures for public PK-12 school districts authorized through CARES, CRRSA, and ARP Acts. We will discuss states' ability to report COVID-19 federal revenues and expenditures, changes in revenues by source, changes in spending by function, and the impact on state and school district expenditures per pupil.
Topic: Fiscal Data
Complexity: Advanced Level
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1–K: Going from 0–100 - Planning for Data Modernization
Erik
Friend, Oklahoma State Department of Education/OMES
Jill Abbott, Abbott Advisor Group
Embarking on a data modernization initiative is a complex task. Addressing business challenges, determining business drivers, developing non-functional requirements, generating collaborations, and many more decisions must be made. This hands-on session provides an overview of processes the Oklahoma State Department of Education utilized in its modernization efforts. After two years of strategic planning and development, come walk us through some activities to get you started and learn where Oklahoma is in its work.
Topic: Other
Complexity: Entry Level
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