10. Data Management

Benefits of Standards-Compliant Applications

- Accesses existing data versus time and expense of re-entering it - Reduces incorrect or inconsistent (dirty) data - Eliminates wasteful redundancy - Trend analysis from data from various sources for optimal learning for all students

Professional development is key to successful use of a data-driven decision-making system by all stakeholders:

- Administrators need training in continuous improvement processes and the opportunity to share ideas with peers to better learn how to ask the right questions. - Faculty and staff members need training to learn how to read data and apply it to their goals and objectives. - Teachers need training in the various types of instructional strategies to apply when data shows traditional methods are not working with students.

An IAM system can enable a resource holder to answer these questions:

- Are you who you claim to be? - What is known about you? - What are you allowed to access or do?

Teachers and administrators have the data they need in meaningful formats to help them

- Assess student progress - Analyze data to help individualize instructional approaches and plan interventions -Understand progress toward school improvement efforts - Tie per-pupil expenditures to student achievement and measures of progress

CoSN's "Closing the Gap Professional Development Toolkit" aims to present one approach to achieving a more data-driven culture and to provide key steps and critical resources for getting there:

- Building a Culture for the Effective Use of Data - Establishing Professional Learning Communities (PLCs) - Supporting Evidence-Based Practices Through the Use of Educational Data - Analyzing Data - Identifying and Selecting Technologies That Enable the Use of Data

The data-driven decision-making process includes three functional areas:

- Collection, integration, and dissemination of data - Analysis and reporting of data - Process and procedures for acting on the data

The key elements of data-driven decision making focus on

- Data culture and leadership - Professional development - Use of data to personalize and individualize the learning process - Drive continuous improvement

Commonly accepted data integration components

- Either an architecture that permits "self-assembly" of network members or a broker to centrally manage security, access, and communication—the SIF Zone Integration Server (ZIS) and the Enterprise Service Bus (ESB) are examples of a service based on the broker approach - An independent data model based on a data structure standard such as XML - A connector that can speak natively with the centralized broker or directly to member nodes where no central broker is used - A system model that defines the data flow and rules of engagement for interfacing with it in a standardized way

SIF is designed specifically for technology providers and educators. It is not a product, but a technical blueprint for software that:

- Enables your current applications to interact and share data seamlessly in real time - Manages your current educational data - Now works cross-platform over modern technologies - Allows automated reporting

It is suggested that district stakeholders ask the following three guiding questions whenever they look at data:

- How are we doing compared to the standard? - How are we doing compared to ourselves? - How are we doing compared to others?

Benefits of using SIF include

- Improve management - Future proofing - Improve learner attainment - Safeguard your learners - Single sign-on - Reduce administration costs - Vertical reporting solutions

When selecting third-party solution vendors consider

- Product comprehensiveness: Product breadth, including being current with specifications and providing unmatched coverage across APIs (JDBC, ODBC, ADO.NET), databases (Oracle, Microsoft SQL Server, DB2, Sybase, Informix, and more) and operating systems (Windows, UNIX, Linux, iSeries, z/OS). - Production-proven: A record of successful use in a variety of environments as well as quality-proven through specification certification and a large customer base. - Technical support: Multi-channel support via phone, fax, email, and Web. - Technical leadership: Industry-trusted specification leader for JDBC, ODBC, ANSI SQL, and XQuery. - Corporate focus and strength: 100% focused on database connectivity.

Key elements for districts seeking to utilize data-driven decision making for continuous improvement and increased student achievement include:

- Publicly stated and shared goals - Understanding of and adaptability to change - A clear sense of what needs to be done, progress made, and what remains to be addressed - Free exchange of information - Openness and trust that allows for valuable feedback

Addressing data risks and vulnerabilities - "Whos data is it anyway?" article addressing concerns

- Safety and legality concerns require schools to be very careful about verifying that the people being granted access to highly personal data are actually the legal guardians. - Districts need to make decisions regarding migrating from print records to digital ones. Providing digital information might improve ease of access but raises issues about unintentionally sharing data via email or online in ways that could have negative repercussions. - Educating parents about the meaning of certain information in the record they'll receive is important to avoid confusion or unnecessary concerns. - Stakeholders need to understand and communicate guidelines and procedures for sharing student information that does not originate with the school (SAT test scores, for example). Who has access to them? How is this authorized? Who "owns" the data? - The increasing use of home-grown wikis and other Web 2.0 tools by teachers to communicate with parents makes it harder to monitor what information is made available to whom and put uniform security measures in place. - Schools need to have procedures in place to transfer ownership of data from parents to students when the student turns 18.

Potential barriers to the adoption of data-driven decision-making systems

- Schools often do not have enough qualified staff to properly analyze data - Data may not be uniformly collected among organizations or over time - Some school district leaders have not embraced or made a commitment to continuous improvement - There may be outdated technology, which cannot be effectively used - Data collection and analysis is too often not clearly tied to the district's vision and strategic plan, goals, and objectives - Stakeholders may not be able to trust the data collected or how it will be used

In the process of continuous improvement, data collection helps to ensure

- Students and teachers get more immediate feedback - Students have clear, standards-based goals and individualized learning plans - Attention is paid to individual learning styles and needs

Stakeholders who share responsibility in a data-driven culture

- Superintendent - determines systems and process for achieving goals set by the board; provides leadership, models accountability, and communicates achievements to all - Research and Assessment personnel - provide analysis to help principals and teachers use data and develop assessment tools aligned to standards - Curriculum and Instruction personnel - ensure that development of the data system includes assessment and evaluation reports aligned to standards and to the district's curriculum - Principals - ensure data becomes a critical part of instruction and teachers get training and support needed to help them make best use of data in teaching and learning; provide staff, parents, and community with a process for ongoing participation in the plan - Instructional and Technology Specialists - assist principals and teachers with data mining and analysis; help promote community outreach - Teachers - use data to effectively individualize instruction for each student; provide timely feedback on student work

Characteristics of a data-rich culture:

- They have an established vision and supporting goals for how data will be used to improve student achievement. - They have a standard approach and set of resources for collecting, reporting, and analyzing student data. - They consistently and regularly use student assessment data to inform and improve policies, interventions, and teaching approaches and to improve communication among teachers, students, and parents. - They have a mechanism in place to continuously monitor and improve the process of collecting and analyzing data in order to enhance teaching methods and interventions.

Data demands on schools also bring new opportunities

- To use data to transform teaching, learning, and administration - To inform decisions about everything from class schedules to textbook reading levels to professional development budgets - To provide a rationale for decisions that parents, teachers, taxpayers, and students can understand

Some of the ways decisions might be made from data reports include but are not limited to:

- Tracking student achievement for diagnosis and placement - Helping create individualized learning plans for students - Tracking and guiding professional development - Linking student interventions to results - Assessing progress on school improvement plans - Allocating district resources - Deciding what to change - Determining if goals are being met - Identifying root causes of problems - Aligning instruction to standards - Meeting accountability requirements - Keeping stakeholders informed about progress

Data Warehouse

A central storage area where data can be integrated from multiple data sources, merged, and cleaned up

Successful integration of data in your district's decision-making process requires

A culture of change and data management systems to support change

The Family Educational Rights and Privacy Act (FERPA)

A federal law that protects student privacy by prohibiting the disclosure of personally identifiable information from education records without prior written consent. It also allows parents and "eligible students" to inspect and review their education records and to request that inaccuracies in their records be corrected.

Data Quality Campaign (DQC)

A national, collaborative effort to improve the collection, availability, and use of high-quality education data and implement state longitudinal data systems to improve student achievement.

Data-driven decision making (DDDM or D3M)

A process of making choices based on appropriate analysis of relevant information.

SCORM (Sharable Content Object Reference Model)

A set of technical standards and specifications for how Web-based e-learning software should be built

Knowledge management

Integrating data and information into the daily activities of decision makers

Single Sign-On (SSO)

Allows users to login once for access to multiple applications for a specific time period without having to re-login each time.

Registration

Also known as credentialing; the process whereby users are given electronic credentials, leveraging the identification process to ensure they are coupled with the correct electronic identity information.

Information management

An emphasis on the technology infrastructure used to collect and manage data

Identity Management

An integrated system of business processes, policies, and technologies that enable organizations to facilitate and control their users' access to online applications and resources while protecting confidential personal and business information from unauthorized users.

Credential

An object that is verified when presented to a verifier in the authentication transaction, such as a paired user id and password.

Focuses on things as they are right now

Baseline data

Data integration

Begins with data connectivity but goes beyond that to include data translation, standard data output format, and other transformation services to make the data usable by each individual application.

Investing in data systems that enable better analysis and reporting of financial and productivity data at the school, district, and state level can mean

Better long-term decision-making

- Looking at baseline data - Looking at resource alignment - Looking at programs and practices - Looking at student outcomes

Data First quadrant cycle

Why it is vital to clean up data

Data is integrated from a number of sources and gathered through a variety of tools and then reported in a number of formats to meet varied requirements

Process of continuous improvement

Data-driven decision making improves the overall effectiveness of a district, and data collection becomes powerful in the process, beginning with: - Community vision, which leads to - Measurable goals, which leads to - Assigned responsibility for success, and finally - Access to relevant information for every member of the organization throughout the school year.

Educational data is used to support decisions at the district, school, and classroom levels

Data-rich culture or data-driven environment

Open Source Software

Distributed for free, although vendors can charge for their versions of the software and technical support. It is different from public domain software, because the copyright is held by the public.

Using data for school improvement is a major

Education reform priority in the US Dept. of Education

The FIRST step in creating a data rich culture

Establish the need for data rich culture and set the vision

Standardized tests fall short of providing

Formative, detailed information needed to really address individualized student learning needs.

Newer assessments aligned with instructional goals provide students, teachers, and schools with

Immediate feedback to adjust instructional practice

SIF - Schools Interoperability Framework Software

Is an open specification for K-12 institutions that enables diverse applications to interact and share data

The use of data is increasingly shifting away from

Its use for compliance reasons to being used as a flashlight to determine students' strengths, weaknesses, and to allow them to use their own data to plan their learning trajectory.

Effective use of data will

Link needs to outcomes

Data Management involves

Managing the establishment and maintenance of systems and tools for gathering, mining, integrating, and reporting data in usable and meaningful ways to produce an information culture in which data management is critical to strategic planning.

Having teachers collaborate to review data and make decisions

One of the critical success factors identified for effectively using data at the classroom level

The Obama administration has stated as one of its goals:

Our education system at all levels will leverage the power of technology to measure what matters and use assessment data for continuous improvement.

Data First Project

Project website designed to provide data about schools and teach site visitors how to use it better. Their assertion is that education data, used well, can help district stakeholders "...make good decisions—ones based not on the loudest voices or the latest theories but on the facts about what students need and how they are currently doing."

Federated Identity and Access Management (Federated IAM)

Provides a sophisticated yet simple infrastructure for managing a person's multiple logins to access local and remote resources; it streamlines the administration of online resources for authenticated, authorized users.

Every goal and objective in your strategic plan needs

Quantitative or qualitative measure to indicate progress

Children's Internet Protection Act (CIPA)

Requires an Internet safety policy addressing: - Access by minors to inappropriate matter on the Internet; - The safety and security of minors when using electronic mail, chat rooms and other forms of direct electronic communications; - Unauthorized access, including so-called "hacking," and other unlawful activities by minors online; - Unauthorized disclosure, use, and dissemination of personal information regarding minors; and - Measures restricting minors' access to materials harmful to them.

Testing results arrive months after exams have been taken, they tend to be used to

Select and sort students rather than provide a meaningful opportunity for intervention.

Obtain more comprehensive data—accessible anytime and anywhere

So teachers and parents can intervene before students fall behind. A related goal is for schools to improve communication of relevant data to all stakeholders who share the objective of improving educational outcomes for students.

Assessment data should be made available to students so

Students can play a larger role in directing their own learning

Data Connectivity Standards

Supports the transfer of data from a variety of platforms (including student information systems, data warehouses, learning management systems, etc.) using a standard set of commands in an efficient and cost-effective way.

It is not just about collecting and reporting data.

The CTO must strive to help district stakeholders ask the right questions and get the real messages to be learned from the data.

Provide leadership for a district and school data-driven culture, manage the technology infrastructure, coordinate system planning and development, provide access tools, and stay current regarding new technologies for future planning.

The CTO's primary role in the data-driven decision-making process

Interoperability

The ability to share data between different systems on different machines

All data in the warehouse should be aligned to

The goals and objectives in the district's strategic plan

The effective use of data is critical to addressing continuous improvement

The path to get there is neither static nor linear.

Identification

The process by which information about a person is gathered and used to provide some level of assurance that the person is who they claim to be.

Data migration

The process of transferring data between storage types, formats, or computer systems. It is a key consideration for any system implementation, upgrade, or consolidation.

Summative uses of assessment

Using assessments to determine what students have learned for grading and accountability purposes

Formative uses of assessment

Using assessments to diagnose and modify the conditions of learning and instruction