|
VII–A |
Benefiting from Data
Robin Taylor, Delaware Department of Education
Delaware discussed how it utilizes longitudinal data for research; improving student
achievement and instruction; and for data driven decision making. During this session,
Delaware also shared detailed examples of the reporting systems the state uses at the
school level to support data driven decisions.
Download Zipped PowerPoint Presentation:
Sessions in LDS track:
I-A, II-A, III-A, IV-A, V-A, VI-A, VII-A, VIII-A, IX-A, X-A, XI-A, and XI-D
|
|
VII–B |
"Where Oh Where Did My Students Go…Oh Where Oh Where Could They Be?" Considerations for Calculating Graduation and Dropout Rates
Meredith Babcock, Michelle Magyar, and Karl Scheff
California Department of Education
Following the first year of data collection on student-level enrollment and exit data, the
California Department of Education (CDE) is now faced with many challenges that directly
impact the calculation of graduation and dropout rates. This session included an overview
on these issues (e.g., lost-transfers, re-enrolled dropouts, summer dropouts/no shows,
on-time graduation, adult/alternative education) and reviewed the findings from the CDE's
exploratory research efforts that investigated graduation and dropout policy and procedures
from other SEAs. Presenters also initiated a discussion that furthered our understanding
of the difficulty of calculating these rates at the state and local levels, and they proposed
possible solutions that may inform policy decision making.
Download Zipped PowerPoint Presentation:
Sessions in Statewide LDS track:
I-B, II-B, III-B, IV-B, V-B, VI-B, VII-B, VIII-B, IX-B, X-B, and XI-B
|
|
VII–C |
EDFacts, K-12 Models, and SIF
Ross Santy, U. S. Department of Education, EDFacts
Laurie Collins, School Interoperability Framework Association
Over the past two years, the data model for federal collection of K-12 performance and
enrollment data has stabilized with the EDFacts
data collection. Over the same time period,
NCES has led the development of a comprehensive K-12 data model which organizes and catalogs
all the information maintained by schools and districts in the course of conducting their
daily business. This session provided a brief overview of these data models, and it
shared updates on work being done to utilize the schema of the Schools Interoperability
Framework Association to connect the two models to ensure more efficient aggregation and
collection in the years to come.
Sessions in EDEN/EDFacts track:
I-C, II-C, III-C, IV-C, V-C, VI-C, VII-C, VIII-C, IX-C, X-C, XI-C, and XII-C
|
|
VII–D |
Reporting the On-Time Graduation Rate to ED
Zollie Stevenson, Patrick Rooney, and Chris Chapman, U.S. Department of Education
The U.S. Department of Education has defined a standard on-time high school graduation rate
for its reports from states. This session discussed the components of the rate, with a focus
on the collection and reporting requirements that state and district data managers will address.
The session also gave an overview of the averaged freshman graduation rate (AFGR) that states
may use as an interim estimate while they develop the data needed for the on-time rate.
Sessions in Federal track:
I-F, II-F, III-F, IV-D, IV-F, V-D, V-E, V-F, VI-D, VI-F, VII-D, VIII-E, X-E, and XI-E
|
|
VII–E |
Which Data for What Purpose and When? A Cycle That Works for Improving Instruction
Diana Nunnaley, TERC
Ellen Mandinach, CNA
"One consequence of the standards and accountability movement is that
district and school administrators are being asked to think very differently
about educational decision making and the use data to inform everything from
resource allocation to instructional practice" (Mandinach & Honey, 2008). Better
data systems and data tools are an intended consequence of the shift in emphasis.
And at many levels of educational purpose, the systems and the tools are informing
the planning process as they capture impact of activities. At the classroom level,
however, data can still be viewed as punitive and irrelevant to the day-to-day process
of deciding what and how to teach. This session explored the kinds of relevant data
and processes that enable teachers to change practice and content focus in the classroom.
|
|
VII–F |
Approaches to Implementing the Two Percent Cap for Adequate Yearly Progress (AYP)
Nancy Stevens and Li-Chin Wu, Texas Education Agency
In 2008, two new state alternate assessments for students with disabilities were
administered in Texas. The Texas Education Agency evaluated different approaches to
implementing U.S. Department of Education rules regarding use of proficient results
from alternate assessments in Adequate Yearly Progress. This session looked at
advantages and disadvantages of the different approaches in relation to statutory
compliance, promoting instructional improvement, equity, potential unintended
consequences, and data processing resources. The calculations to be used for
Texas AYP were described.
|
|
VII–G |
WISE and WISER, How Wyoming Is Moving Forward With Interoperability
Shadd Schutte, Wyoming Department of Education
You may have heard about the various projects that Wyoming is working on as we strive
to achieve total interoperability with our State Report Collection, Student State ID
number assignment and Wyoming Transcript Center. In this session we showed
how all of these projects are combining to create an interoperable system that strives
to ease reporting burdens for the LEAs, enhance data quality and serve us not only
today but also into the future.
Sessions in SIF track:
II-G, III-G, IV-G, V-G, VI-G, VII-G, VIII-G, IX-G, X-G, XI-G, and XII-G
|
|
VII–H |
Becoming a Data-Based Decision Making District
Jim Johnson, Iron County School District (Utah)
To achieve its promise, data-based decision making requires that 1) data be of high
quality and readily accessible in real time to those who need it to make effective
instructional decisions, and 2) that teachers and principals be trained on how to
use data to improve learning and teaching. Iron County School District (Utah) is
in the second full year of implementing a data-based decision making approach. Key
components include a student achievement management system which provides the
ability to gather information about individual students from multiple data sources
and present that information to teachers and principals and the development of data
teams within each school. In addition, the management system creates digital student
packets or digital cumulative folders for each student. Superintendent Johnson
demonstrated the depth of information within the system, the quickness with which
the data are retrieved and compiled, and the clarity in how it is presented on the
screen. All this was done using live data and interacting over the internet
with the Iron County School System in Cedar City, Utah.
|
|
VII–I |
Building an Online Unified Data Dictionary
Neal Gibson and Carmen Jordan, Arkansas Department of Education
Dennis Cribben, Metis Associates
The Arkansas Department of Education is building a data dictionary that will unify the
descriptions, business rules, and data stewardship for all data elements from its source
and reporting systems and includes the same information cross-reference to
EDFacts, NCES
Handbooks Online, and SIF. This project uses the participatory nature of Web 2.0 to
distribute the workload online. The dictionary illuminates hidden details about data
collection and illustrates how unit-level source data becomes aggregated data for
reports. This presentation showed why the dictionary is central to ADE's data
quality initiatives, demonstrated the system and work done to date, and explained how
it was created.
Download Zipped PowerPoint Presentation:
|