Data Quality: Improving Education Data

This first lesson will introduce the key concepts associated with producing quality data to all the members of a district with some responsibility for creating or applying data and to begin the conversations among staff that will build a culture of quality data.

This lesson focuses on identifying the elements that go into a culture of quality data and to assess your school or district with regard to data quality issues.

The third lesson focuses on exploring categories of school data (as defined by educator and author, Victoria Bernhardt) and their application, and identifying the uses of data within a school. You will also examine the cycle of data production and application.

In this lesson you will learn about the security component of quality data, specifically the Family Educational Records and Privacy Act (FERPA) and Health Insurance Portability and Access Act (HIPAA) regulations that govern school confidentiality issues.

This lesson will define the roles and responsibilities of a Data Steward/Coordinator as they are actually assigned in each participant's district.

This lesson focuses on discussing data flow and data cycles. Understanding these two aspects of data collection is essential to producing high-quality data.

In this lesson, we will focus on several different issues surrounding data entry.

In this lesson we will describe a data dictionary in more detail, including one way to structure the basic data-dictionary entries that define data elements. We will also take a detailed look at the sources of information that go into developing a data dictionary and discuss various model data dictionaries that can help an LEA identify a structure for one of their own.

In this lesson, you will learn to understand the role and importance of a data dictionary in producing high-quality data on a consistent basis and you will take some of the initial steps required to produce a useful and effective data calendar for your LEA.

In this lesson we will define and describe some of the different types of data errors and identify what some of the consequences of having inaccurate data in your data systems might be.

In this lesson, we will look at some of the basic steps involved in validating data: that is, in ensuring that a specific piece of data is accurate. We will also discuss the purpose and elements of an effective data audit, which is a process for ensuring the accuracy of all the data in an LEA. This discussion will provide the basis for your beginning to plan a data audit in your own LEA.

In this lesson, we will review those LEA staff who need to be involved in planning for the production of quality data, as well as those who should be informed regularly about data-quality issues. We will then explore the various methods by which information related to maintaining quality data can be disseminated to these staff members. We will also lay the groundwork for one of those communication strategies by beginning the development of a professional development plan or structure to ensure that all relevant LEA staff are familiar with their roles regarding data quality and the policies, procedures, and standards that make quality data possible.