In an age of boundless technological advances and increased accountability, school districts nationwide increasingly rely upon innovative tools that allow administrators and educators to use high-quality student data to inform decisions. Organizations, such as the following, have developed resources to help school districts adopt the best data governance practices and technological solutions to adequately protect student privacy and improve student achievement:
- The U.S. Department of Education Privacy Technical Assistance Center (PTAC), established as “a ‘one-stop’ resource for education stakeholders to learn about data privacy, confidentiality, and security practices related to student-level longitudinal data systems;”
- The Data Quality Campaign (DQC), a partnership of approximately 100 organizations “committed to realizing the vision of an education system in which all stakeholders—from parents to policymakers—are empowered with high-quality data from the early childhood, K–12, postsecondary, and workforce systems;” and
- Closing the Gap: Turning SIS/LMS Data into Action, which exists as a collaboration of the American Association of School Administrators (AASA), the Consortium for School Networking (CoSN), and Gartner Inc., a technology research and advisory firm.
Research shows that most data management systems for education function as either student information systems (which focus on the collection, organization, and management of student data) or learning management systems (which are used for planning, delivering and managing, tracking, and reporting learner events, programs, records, and training content). While in the past, districts have found basic student information systems sufficient to serve reporting and administrative purposes, in the current era of increased accountability, districts increasingly use student data to improve instruction and guide decision making. As such, leaders must adequately plan for data use, selectively choose data sets, and adequately train all data users.
Planning for data use
Research recommends districts develop a “data collection and use plan” for each type of data the district intends to evaluate. The data collection and use plan should include a description of the data, the source where the data is stored prior to the implementation of the new data collection system, the data extraction method and frequency of extraction, the “data owner” or “point of contact” responsible for that type of data, the groups that will use the data, and intended uses for the data once it has been collected.
During the planning process, district leaders may also take careful steps to ensure stakeholders throughout all levels of the district have the tools and support to effectively use data.
Because districts increasingly collect student data to serve a variety of purposes, leaders may find the data collected for reporting purposes to be insufficient for guiding decisions on the district, school, and classroom levels. As research shows that there is often “a fundamental misalignment between the types of data that districts deem to be imperative for student achievement and the types of data that are being requested by the state for federal accountability purposes,” Closing the Gap recommends that districts choosing to collect additional categories of data consider restraints on data collection and the district’s ability to store and analyze data. In assessing data collection feasibility, this recommends that district leaders consider the following questions:
- Is the data you wish to collect protected by laws and government mandates (e.g. Health Insurance Portability and Accountability Act – HIPAA, Children’s Online Privacy Protection Act – COPPA, Family Educational Rights and Privacy Act – FERPA, etc.)?
- Do you have the resources or technical bandwidth and capacity to store the data? Once collected from every student within the district, will the data be too large to store in your current database/data warehouse (e.g. photos of every student and their parents/guardians)?
- Do you have the staff to update and maintain the data for accuracy (e.g. you may want daily trend analysis of how assessments [go] in every classroom in every school but teachers may not have the time to conduct such an analysis on a daily basis)?
- Do you have the ability to display the data on different types of displays (e.g., computer screens, smart phones, tablets, etc.)?
- Is the data currently collected somewhere? How accurate is that data?
Although districts may find they have access to a large amount of data, Closing the Gap warns against the collection of more data than the district will have the “capacity or capability to store, mine, and analyze.” Accordingly, it is recommended that district leaders consider the following questions to prioritize which pieces of data they choose to collect:
- Does the data element answer a question that directly supports current and future school, district, state, and national education goals?
- Does the district currently have a means for accurately collecting and displaying the data element across the district?
- Does the district have a means of securely and accurately storing/maintaining the data?
Finally, it is recommended that district leaders select data after consideration of the eventual use of the data, using questions such as these:
- What are the instructional questions the data should answer?
- Which professional learning resources are needed to support the effective use of the data to strengthen classroom practices?
- Which evidence-based instructional practices will the data further enable (e.g., the role of feedback and assessment for learning)?
Training and Professional Development
In most cases, district leaders, school leaders, and teachers will require training and professional development to effectively collect and use student data. Research finds multiple training practices commonly in place in best-practice districts:
- Best-practice districts provide twice as much data-related training and professional development for new teachers and 50 percent more data-related training and professional development for returning teachers than other districts.
- Best-practice districts devote a greater proportion of training and professional development to data analysis than to technology. The result of this practice has been “tangible differences, such as the use of advanced data analysis techniques including correlations, regression, analysis of variance and multivariate analysis.”
- Educators with data analysis training more frequently use available analytical tools. In best-practice districts that provided training in data analysis training, 63 percent of teachers and principals used analytical tools, in comparison with six percent of teachers and 14 percent of principals employed by other districts.
Data collection efforts, such as the U.S. Department of Education Civil Rights Data Collection (CRDC), use innovative technologies and web-based tools to facilitate the collection of data. As we increasingly use data to support student achievement in our schools, guiding principles of data collection and use will help shape the way that data is ultimately used to support achievement in our schools.