Analyzing trends and uncovering value in education data. White Paper

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1 Education Data Warehousing Analyzing trends and uncovering value in education data White Paper

2 This document contains Confidential, Proprietary and Trade Secret Information ( Confidential information ) of Insystech Inc. and may not be copied, distributed, duplicated, or otherwise reproduced in any manner without the prior written consent of Insystech Inc. While every attempt has been made to ensure that the information in this document is accurate and complete, Insystech does not accept responsibility for any kind of loss resulting from the use of information contained in this document. The information contained in this document is subject to change without notice. Published April 2013 Copyright 2013 Insystech Inc. All rights reserved.

3 Overview State education agencies face many challenges to sustain the benefits now being realized as a result of significant federal investments in the US Education System. As of March 2013, The American Recovery and Reinvestment Act (ARRA) has awarded $6.5 billion i for Race to the Top, a competitive grant program designed to encourage and reward states that are creating the conditions for education innovation and reform; achieving significant improvement in student outcomes, and ensuring student preparation for success in college and careers. Additionally, the Statewide Longitudinal Data Systems (SLDS) Grant Program has invested $610 million ii (of which ARRA contributed $360 million iii ) since 2005 through five rounds of funding to 47 states, the District of Columbia, Puerto Rico, and the Virgin Islands. While it is clear that there has been a significant investment from federal government programs due to a variety of factors, at least 34 states and the District of Columbia have implemented cuts to K-12 education and over 43 states have implemented cuts to public colleges and universities and/or made large increases in college tuition to make up for insufficient state funding. iv In light of this budget cutting trend, it is important that states act now and focus on developing a sustainable model for their longitudinal data systems. The SLDS program provides grants to design, develop, and implement statewide P-20 longitudinal data systems to capture, analyze, and use student data from preschool to high school, college, and the workforce. Although many states have begun to see value from their investments in these data systems, the industry believes that there is significantly more value in such data when it is linked with other Big Data. Optimizing the value derived from these systems requires some skills that most IT departments lack today. Historically, analytics have been built without looking at data sets that were very large and complex. Stakeholders were only tasked with analyzing subsets of structured data and never considered the other (and sometimes unstructured data) within the organization. This meant that there were only a limited number of questions that could be asked. As the data grows, so do the questions that stakeholders will want to ask. When schools fail, our children and our neighborhoods suffer." U.S. Secretary of Education, Mr. Arne Duncan, March 11, 2013 $610 Race to the Top SLDS Program Figure 1 Total Investment in SLDS Programs (Millions) The Data Quality Campaign is a strong advocate for empowering stakeholders with education data. They have defined ten actions believed that once implemented, will: Increase efficiency: Ensure that our education systems produce the greatest return on investment possible Improve system performance: Inform system-wide management and evaluation decisions Figure 2 Map of Actions Implemented Increase transparency: Shine a light onto the education system to see what works and what does not Improve student achievement: Inform all education stakeholders decisions with quality data to help them make the best decisions to improve every student s achievement Page 3

4 Although there has been great progress as a result of the significant investment into SLDS programs, few states have implemented all of the ten actions required to meet their goals further demonstrating the need for additional investment into the SLDS program. Insystech recognizes that most states are actively working to define and implement these (or similar) actions under numerous budget, resource, and time constraints. Insystech has the necessary skills, partners, and solutions required to fill any gaps that states may have reaching their goals or sustaining their SLDS solutions. Education Data Warehousing Solutions Data warehouses have been around for a long time and many organizations are great at creating them The data warehouse, admittedly, is a critical component to the SLDS solution; however, a number of other components are required to work together to deliver a functional data warehousing solution that meets the stakeholders goals. As each project is unique, so can the solution for getting answers to questions using data be unique. As a result, there is strong desire to conform existing systems, merge data from new systems, and link data to other systems in order to make sense of the readily available information. As states evolve and mature their data warehousing practices more and more data is conformed using a variety of methods to meet their business objectives. There is a tipping point however, where data becomes unmanageable; for many, this point was crossed the moment they began to link their K-12 education data with other state systems such as workforce, higher education, and other data systems. Insystech has provided excellent IT consulting services to my team at Fairfax County Public Schools. The IT consultants provided to us were high quality professionals who had the experience and skills that we needed. FCPS has enjoyed a long term relationship with Insystech, Inc. The company has provided quality IT services to our school district since Ken Rice, Coordinator, Instructional Systems, Fairfax County Public Schools, VA Figure 2 Education Data Warehousing Solution

5 A modern approach to Education Data Warehousing makes managing data possible through: Collecting and matching data stored in the current systems while providing capability to support data exchange to and from other sources as the system evolves Organizing a comprehensive longitudinal data repository based on Data Quality Campaign (DQC) standards consisting of several integrated data marts that store information for all aspects of the school system, including student enrollment, student test scores, student grades, transcripts,program participation, teacher education/professional development, and school infrastructure Presenting student trends, performance, progress, and program effectiveness longitudinally through a common and easy to use web portal using ad-hoc and interactive reports, charts, and dashboards Controlling access to information and system capabilities for various groups including the general public, parents, teachers, principals, school administrators, analysts, and system administrators/developers Data Collection When developing complex data collection and matching processes, data structures, and reports that make up the data warehouse solution, Insystech follows a Kimball approach (considered industry best practice) to data warehousing. Distribution reports can help decision makers quickly identify best and worst performers (example: What K-12 courses, high school career clusters, programs and other experiences are preparing students well for STEM postsecondary degrees?) The solution must be designed to integrate data from multiple source systems and multiple agencies. Data systems that would act as source for the data warehouse are analyzed to help develop both the business and technical team s understanding of the availability and quality of data in the source systems. This information is also used to complete functional gap analysis identifying potential gaps in the availability of data for the reports and dashboards planned for the system. Data Matching A component essential to the sustainability of the solution is the controlled vocabulary for which business rules are established to interpret data in the data warehouse. It is natural for each source system to have their own set of terms used to describe the data elements they provide to the SLDS; however, a number of attributes such as demographic attributes must be conformed to establish proper links between the source data to support longitudinal analysis. Data transformation (ETL) process are developed to load the data from the source systems to meet the requirements of the data warehouse, and are conformed and linked using record matching technology which overcomes issues such as misspelling, transposition of data elements, internationalization of names, as well as numerous other data quality issues. Page 5

6 Data Organization Data is loaded into a comprehensive, multi-dimensional, statewide longitudinal education data warehouse. ETL processes keep the data updated and organized so that it may be managed consistently over time and presented to end-users as reports. For each facet of information managed by the system, additional characteristics (many of which are shared) that describe these facets are linked to facilitate data management, reporting, and analysis. These dimensions help describe what kinds of events and characteristics are measured over an individual s (and by extension to groups) learning lifetime. As educators use this information to make decisions that improve student performance and/or education policies, an improvement cycle is created; thus, users of the system can see trends in key performance indicators over time. This information helps all stakeholders develop a better understanding of their students which can help institutions better prepare students for the 21 st century workforce. Figure 3 Preparing the 21st Century Workforce

7 Data Presentation End users will usually access the system via a single web based business intelligence portal, through which unstructured information may be shared such as documents, web pages, blogs etc., along-side interactive dashboards and reports. Since the SLDS program serves as an authoritative data repository for all education programs, it creates an opportunity for a variety of different stakeholders to access a common set of data at different levels of aggregation and scope: Student data such as performance data for each student in his/her class might be made available for teachers. They can use this information to aggregate that data to analyze trends, determine what content needs to be reinforced, and decide how to alter teaching methods to ensure students acquire the content knowledge and skills in the state s college and career-ready or internationally bench-marked standards. School data to help guide staff time and resources might be available to school administrators such as teacher assignment, evaluation, and professional development, student course assignments and targeted supports, and interim and summative testing. Of course, administrators will also have access to data that helps identify which students from which classrooms are off-track to scoring proficient on end-of-grade or end-of-course exams in key subjects and why. School District Administrators may have access to data to help improve curriculum and practices both for their institution(s) and in under-performing schools to allocate teacher and staff resources, and to provide professional development opportunities. Report Annual Trends in KPIs alongside other measures to help discover/predict why and when changes occur (example: What K- 12 courses, programs and other experiences are predictive of college readiness?) Interactive dashboards to display frequently requested information on KPIs at a glance (example: How much student loan debt do students leave compared to their employment rates and earnings?) Policy makers may have access to valuable data on a robust set of key performance indicators that measure and report school and district progress towards college and career readiness goals, including measures of progress, such as Adequate Yearly Progress. They may be able to identify schools and districts in need of targeted supports and interventions and those deserving of recognition for outstanding achievements. Policy makers can also use the data to analyze trends across schools and districts helping them evaluate policies. Comparing multiple student cohorts over time can help answer specific questions to help support changes to policies (Example: What is the profile of high school students (across time) entering and non-entering some type of postsecondary education immediately following high school graduation) Page 7

8 Education Data Warehousing in Practice In 2012, Insystech completed the design, development, and implementation of a P-20 Statewide Longitudinal Education Data (SLED) System for the West Virginia Higher Education Policy Commission. The solution included a data warehouse, dashboards, and governance that now provides answers to questions from the state legislature, higher education research staff, K-12 staff including administrators, teachers, and workforce research staff. Governance Governance describes the overriding authority and legislative requirements for all architectural, design, development, and business decisions, including all policies and procedures created on behalf of the agencies responsible for the system. The West Virginia P-20 SLED implementation involved the effective interaction of multiple groups, individuals, and disciplines. To provide a unified, centrally governed approach throughout the lifecycle of the solution, a governance model was implemented in conjunction with the technical solution. Data Model At a very high level, the solution created for West Virginia structured the data warehouse to the processes for which education programs are managed and delivered to students. The data model was developed based on data warehousing best practices, input from industry experts, and lessons learned. The P-20 model is the evolution of an award winning K12 data warehouse created in partnership with Fairfax County Public Schools called EDSL which, since 2000, continues to be supported and enhanced by Insystech serving over 170,000 students and 25,000 educators. The current model stores outcomes and other information at point in time events such as graduation, taking a test, enrolling in a school, getting approval for a student loan, completing a grade, etc. Each event in the student s academic history may have one or more outcomes which are recorded as facts that are aggregated at the level in which it is collected (typically at the student level). This method of classifying events in the data model enables policy makers to develop a framework for exploring the data warehouse in terms that are easy to understand from a business perspective. Functionality Ability to easily connect to any contributing systems to extract, transform and load data into the data warehouse Data exchange capabilities to provide for the easy submission of data from districts and other partners Unique record matching technology with master person index which overcomes issues such as misspelling, transposition of data elements, internationalization of names, as well as numerous other data quality issues Comprehensive, multi-dimensional statewide longitudinal education data warehouse organizing student records from pre-school through age 20 years including enrollment, assessments, earnings, financial aid, debt, and much more. Subject specific data marts for cohort comparisons and analysis of various types high school graduates and degree seekers in areas such as high school feedback, college performance, college indebtedness and income earnings, remedial development, Insystech team worked well with our research staff to define standard taxonomy for the data, gather and process data, design and develop dashboards and reports. Insystech team of experts also assisted in the setup of governance procedures to help sustain the system. Rob Anderson Executive Vice Chancellor for Administration West Virginia Higher Education Policy Commission Technical Environment The following off the shelf products were used to implement the P-20 SLDS solution for West Virginia: Network/Operating System: Windows 2008 R2, Secure Public Access (SSL 256bit), Internet Information Server 7.0, N-Tier Server Architecture, and VMWare Virtualization Database: Oracle 11g R2 Enterprise Edition with Partitioning Option ETL: IBM Cognos Data Manager 10.1, IBM Cognos Adaptive Warehouse 10.1, and Oracle PL/SQL stored procedures Portal/Reporting: IBM Cognos 10.1, SharePoint 2010

9 workforce feedback, STEM Pipeline, dual enrollment, teacher education, and proficiency testing predictors. Public and private web portals with interactive dashboards and scorecards Conclusion Insystech provides a robust set of products and services for K-12 and P-20 longitudinal data systems that allow local and state education agencies to integrate and/or expand existing data systems within and across agencies to allow for maximum transparency, accountability, and decision quality information. Our professionals apply expert knowledge of systems architecture and educational software applications to deliver increased performance, scalability, usability, efficiency, and reliability, all while streamlining processes to decrease total cost. With Insystech, education agencies benefit from the leadership and tactical recommendations of skilled subject matter experts ensuring a solid data warehousing foundation through which they can design, implement, and maintain their SLDS applications. Our Professional Services include: Enterprise Architecture Data integration strategy, planning and implementation Data quality improvement strategy, planning and execution Stakeholder outreach and change management Requirements analysis Enterprise Data Warehouse design, development and maintenance Extract, transform and load (ETL) process design and development Custom web application development Systems Integration Portal development Web Services development Mobile Apps designs, development and deployment Business process automation Training and documentation About Insystech Insystech is an educational technology firm with more than 15 years of experience providing IT services and solutions to K-12 and higher ed institutions. Insystech staff has extensive experience and knowledge in working with the development of educational policy, evaluation of educational programs as well as extensive design, deployment and management of information technology solutions including the design and deployment of data warehouse systems. Since its inception, Insystech has achieved consistent repeat business (80%) from its education customers. i Recovery.gov, GL&CFDA_CODE=257 (March 20, 2013) ii Institute of Education Sciences National Center for Education Statistics, (March 20, 2013) iii Recovery.gov, AwardType=CG&CFDA_CODE=256 (March 20, 2013) iv An Update on State Budget Cuts, (February 9, 2011) Page 9

10 Insystech, Inc Avion Parkway, Suite 1000 Chantilly, VA Tel: (703) Fax: (703) Insystech, Inc. All rights reserved. Printed in the U.S.A. Insystech, the Insystech logo are trademarks or registered trademarks of Insystech, Inc. in the United States and in jurisdictions throughout the world. All other company and product names may be trade names or trademarks of their respective owners.

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