Common Data ViewsData Driven Instruction and Inquiry (DDI) is a critical component of the Regents’ Reform Agenda. As educators strive to effectively implement the NYS Common Core Curriculum, having access to high-quality data related to student learning has become increasingly important.

As a result, the 12 Regional Information Centers are collaborating in effort to provide all school districts with a common report package that can be leveraged to support the following needs:

• Provide educators, across the state, with a common framework to discuss effectiveteaching strategies.

• Improve the quality of reports available by leveraging programming and dataanalysis expertise across the state.

Please review the following pages to learn more about the 12 Regional Information Centers and the Common Data Views that will be available in 2014, as a result of this initiative. As you explore your local Cognos environments, please note these Common Data Views may look slightly different based on regional input.

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Overview of

Contents:

Page 1Common Data Reports

Initiative

Page 2Regional Information Centers’ Expertise

Page 3-7Exploring 5 NYS

Common Data Views

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April 2014

Regional Information Centers’ ExpertiseThe Regional Information Centers (RICs) are organized under the Board of Cooperative Educational Services (BOCES).  Regional Information Centers (RICs) offer 21st century classroom tools to optimize student achievement. Similar to BOCES, RICs are a trusted provider of collaborative services. By regionalizing services, the RICs, in particular, make a wider range of technology skill sets available to school districts. This relationship increases the buying power of a district and promotes consistent technical standards. This cost effective system continues to lighten the burden placed on local taxpayers and has leveled the playing field so that no matter the size of a district, the best resources remain within reach for New York students. 

RICs provide an array of services that support New York State’s Testing Program and Data Driven Instruction and Inquiry (DDI), including:

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Central New York RIC http://www.cnyric.org

Genesee Valley / Wayne Finger Lakes Educational Technology Service

(EduTech)  http://www.edutech.org

Greater Southern Tier RIC http://www.gstboces.org

Lower Hudson RIC http://www.lhric.org

Mid-Hudson RIC http://www.mhric.org

Mohawk RIC http://www.mohric.org

Monroe RIChttp://www.monroe.edu

Nassau RIChttp://www.nassauboces.org

Northeastern RIChttp://neric.org

South Central RIC http://www.scric.org

Suffolk RIChttp://www.esboces.org

Western New York RIC http://www.e1b.org/wnyric

12NYSIT Centers

NYS Data Warehouse Support

3-8 Testing Support

Regents Scanning

Benchmark and Local Assessments Support

Erasure Analysis 

Data Integration Support

Data Report Development

Data Analysis Support

Network and Inquiry Teams Support

Individual Student PerformanceFor all students taught in a particular section or building, this view provides information related to students’ individual performance. Each student’s results are grouped by domain, cluster, and standard.

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Data Analysis Best Practice:When interpreting results for single students, the greater number of questions examined, the greater the confidence in the interpretations about the student’s performance on questions grouped in meaningful ways.

“It’s important for students to have access to their own data and to get that feedback from teachers so they can start to direct their own learning.”

-Deb Duffy, Mohawk Regional Information Center Network Team Member and Data Leader

Regional Gap AnalysisThis common view shows the percentage of total possible points earned for the district, as compared to the regional percent correct for each item.

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Data Analysis Best Practice:Examining regional trends supports educators’ efforts to leverage regional expertise. Using this data, teachers and administrators are able to have informed collaborative conversations with colleagues and identify and share instructional best practices.

“By studying regional perspectives, longitudinal data and discrete skill item analysis our Network Team is able to help teachers triangulate the data and then help them refine their practice.”

-Laurie Hedges, Herkimer BOCES Assistant Superintendent

Released Questions PerformanceThis common view provides performance information on each question released by NYSED. The view highlights the distribution of responses for multiple choice and constructed response items.

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Data Analysis Best Practice:Educators should use this report in conjunction with New York State Education Department’s 2013 released sample of questions. Questions are available in every grade (3-8) for both ELA and Mathematics. To access these questions visit: http://www.engageny.org/resource/new-york-state-common-core-sample-questions.

“I absolutely love the report that gives an item analysis for the released questions. I have been sharing it with teachers and administrators and they are thrilled to be able to do this level of analysis with the released questions.”

-Lorena Stabins, Monroe 2-Orleans BOCES Staff Developer

Constructed Response DistributionThis common view shows students’ performance on constructed response items. Tables and/or graphs show aggregated performance within a domain and/or distribution of performance by standard.

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Data Analysis Best Practice:Analysis of constructed response distribution reports supports educators in improving writing across the content areas and ensures that students gain adequate mastery of a range of skills and applications.

“This report allows teachers and administrators to drill-down to the standards level... it allows us to align instruction with ongoing formative assessment – aligned to the Core – to monitor student progress throughout the year.”

-Larry Dake, Union-Endicott Central School District Principal

P-ValueThis common view shows the p-value for each question. For multiple choice items, p-value is the proportion of students responding correctly. For constructed response items, p-value is the mean raw score divided by the maximum number of score points for an item.

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Data Analysis Best Practice:District performance on individual questions can be compared to regional levels to determine how similar students performed on a particular question. The larger the sample size the more accurate the results.

“If we’re giving assessments and don’t use data, how can we drive instruction? We would just keep teaching what we’re teaching and never close gaps.”

-Anne Marie Palladino, Utica City School District Principal