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In K–12 education, the beginning of the 21st century has been a time in which two major forces have converged for the purpose of improving student learning outcomes. First, technological resources and infrastructure are being used increasingly in school districts for the express purpose of supporting student assessments and improving the usefulness of assessment data for building administrators and teaching staff. Second, large-scale monitoring and accountability systems for school districts have matured into the No Child Left Behind (NCLB) Act, which elevated the importance of student assessment to an unprecedented level.

Much of the past decade has been focused on ensuring the reliability and validity of these data systems, but collecting student assessment data for state and federal reporting is only one piece of the data utility pie. While large-scale, state-mandated tests serve a number of important functions, the typical rollout of the results do not have a timely impact on instructional planning. 

A 2007 panel presentation at the National Forum on Education Statistics (“Using Data to Transform Education,” by Irene Spero, Jane Lockett and Diana Nunnaley) identified a number of pervasive problems with data use in school districts across the country:

• Most have a wealth of data, but little actual knowledge of what the data mean.
• Many have scattered and antiquated technology infrastructure made up of separate legacy systems that are difficult or impossible to link.
• Data is often only accessible through the district's assessment department.
• The timing of data releases is often late, or the data is cumbersome.

Using Technology to Improve Student Outcomes

Eagle County School District in Colorado has been actively tackling these issues for a number of years by establishing a close working relationship between the technology department and the learning services team. In the fall of 2002, ECS implemented a districtwide teaching model, known as the Teacher Advancement Program (TAP), that uses a number of structural components to integrate data throughout the teaching process. Specifically, in the area of data literacy, this model supports high-quality professional development, strong support for data-driven dialogue and skilled data teams. 

Another unique feature at ECS is that it is one of the few school districts in the nation that has a pay-for-performance compensation system that rewards teachers and building administrators for year-to-year gains in student learning outcomes. This system requires additional layers of performance analysis as well as a system for assigning students to teachers in the areas of reading, writing and math.

However, the quality of the collaborative dialogue that these systems support is driven by the timing, accessibility and interpretation of the results from the wide variety of student assessments that the district employs. In addition to the state-mandated test – the Colorado Student Assessment Program (CSAP) – ECS utilizes a number of additional student assessments to influence instruction as the school year unfolds. 

For example, in 2008–2009 the district began implementing a monthly benchmarking system in reading and math that yields results down to the skill and strand level. These results are available to individual teachers almost immediately and are the focus of monthly planning meetings at each school within the district. The success of this benchmarking system hinged largely on the technology resources and infrastructure that ECS had in place because the system is server-based and requires timely and reliable communication with the district's student information data system. 

The creation of systems to support the district's pay-for-performance compensation system also required strong and purposeful technological support. Specifically, there were a number of challenges in using the district's student information data system to align students with the teachers who had had an impact on their learning in key subject areas. In response, ECS developed a web-based system that principals used to assign up to three teachers for each subject at the end of each trimester. The technology department was a key player in designing the export structure needed to facilitate subsequent analyses. Of critical importance in the success of these solutions is that ECS technology personnel are not only experts in their field, but they also understand the unique challenges inherent in K–12 education.

Building an Integrated System

During the past two years, ECS has focused considerable attention on creating a “dashboard” or “one-stop shop” for accessing the myriad student-assessment results collected by the district. While this is still a work in progress, the following elements will be available for the next school year:

• CSAP student-level year-end and longitudinal results;
• CSAP district and building-level results;
• Northwest Evaluation Association (NWEA) student-level year-end and longitudinal results;
• NWEA district and building-level results;
• Other student diagnostic results (for example, English language proficiency);
• Individual student learning plans and goals;
• Results from monthly benchmark testing;
• End-of-unit theme tests imbedded within the district's reading curriculum; and
• Progress-monitoring results for students who are more than one grade level behind and who receive additional educational support. 

Good data-based decision making requires frequent and in-depth data use, and also requires a high level of data literacy among district and building administrators and teaching staff. To this end, the data displays being developed for the district's dashboard will be visually compelling and user friendly. Additionally, results from different assessments will be cross-referenced to the greatest extent possible. Training to enhance data literacy and facilitate use of embedded data-mining tools will accompany the dashboard rollout.

The overall purpose of this effort is to bridge the gap between collecting assessment data and using it for collaborative inquiry. Technology plays an instrumental role in yielding “high-capacity responses” to the data, defined by Lockett as “those that actually translate into improved instruction, expanded opportunities to learn for diverse learners, and improved outcomes for students.”