|Using Technology to Make the Link Between Assessment Data and Instructional Resources|
Once we have assessments in place that assess the full range of expertise and competencies reflected in standards, we could collect student learning data and use the data to continually improve learning outcomes and productivity. For example, such data could be used to create a system of interconnected feedback for students, educators, parents, school leaders, and district administrators.
The goal of creating an interconnected feedback system would be to ensure that key decisions about learning are informed by data and that data are aggregated and made accessible at all levels of the education system for continuous improvement. The challenge associated with this idea is to make relevant data available to the right people, at the right time, and in the right form. Included in this system should be assessment data to support educators' efforts to improve their professional practice. Data from student assessments can enable teachers to become more effective by giving them evidence regarding the effectiveness of the things they do.
In addition, teams of educators reflecting on student data together can identify colleagues who have the most success teaching particular competencies or types of students, and then all team members can learn from the practices used by their most effective colleagues (Darling-Hammond, 2010; U.S. Department of Education, 2010). Using student data in this way could also improve educators' collaboration skills and skills in using data to improve instruction. At times, it might be useful to have educators use common assessments to facilitate this kind of professional learning.
The same student learning data that guide students and educators in their decision-making can inform the work of principals and district administrators. Administrators and policymakers should be able to mine assessment data over time to examine the effectiveness of their programs and interventions.
The need for student data plays out at the district level as well. Districts adopt learning interventions they believe will address specific learning needs, but these interventions often rely on untested assumptions and intuition. In a data-driven continuous improvement process, the district could review data on the intervention's implementation and student learning outcomes after each cycle of use, and then use the data as the basis for refining the learning activities or supports for their implementation to provide a better experience for the next group of students.
As good as technology-based assessment and data systems might be, educators need support in learning how to use them. An important direction for development and implementation of technology-based assessment systems is the design of technology-based tools that can help educators manage the assessment process, analyze data, and take appropriate action.
Removing Technical and Regulatory Barriers
Two types of challenges to realizing the vision of sharing data across systems are technical and regulatory. On the technical front, multiple student data systems, the lack of common standards for data formats, and system interoperability pose formidable barriers to the development of multi-level assessment systems.
For example, student and program data today are collected at various levels and in various grain sizes to address different needs in the educational system. State data systems generally provide macro solutions, institution-level performance management systems are micro solutions, and student data generated by embedded assessment are nano solutions. Providing meaningful, actionable information that is collected across multiple systems will require building agreement on the technical format for sharing data.
On the regulatory front, regulations such as the Family Educational Rights and Privacy Act (FERPA) serve the very important purpose of protecting the rights of individuals but also can present barriers to data sharing and the improvement of education through research. Many of the barriers to research and data sharing posed by FERPA in its original form were reduced or eliminated through a 2008 revision of the act. Still, varying interpretations of FERPA requirements and differences in district and state policies have made data sharing a complex, time-consuming, and expensive process.
Reducing the technical and regulatory barriers to data aggregation and sharing would facilitate efficient use of data that are already being collected to make judgments about students' learning progress and the effectiveness of education programs.
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