The leadership team at the district and school levels is responsible for fostering a culture of data-driven decision making to advance teaching and learning to personalize instruction for all students. Data should be used not only to assess and report student achievement but to identify areas for school improvement, determine short- and long-term school improvement goals, guide professional learning workshops, narrow achievement gaps among student subgroups, and transform student learning.
Research to Practice
Schools have been collecting, storing, and reporting data for decades on student achievement, the number of students receiving special education services, the number of students participating in the free and reduced-price lunch program, budget and finance information, and human resources. Further, school, district, and state administrators have been dealing with increased reporting requirements which have resulted in the development of extensive databases for storing and reporting these data. Despite the wide array of information collected at the district and school levels, more often than not, school leaders are overwhelmed in this data-rich environment. The popular answer often is to improve the analytical skills and tools of your team. But the real challenge is for leaders to manage their teams in an increasingly analytical environment and to improve their ability to quickly extract, compile, and synthesize pieces of imperfect information to make smarter decisions to:
- Narrow achievement gaps
- Improve teacher quality
- Share best practices
Gather all extant student, teacher and school data
- Conduct a thorough needs assessment.
- Examine the data that is currently being collected at the school and district level. What questions can you answer with these extant data?
- Establish an effective data-driven decision-making system so that districts and schools can assess performance data by student subgroups and personalize instruction at the school and classroom levels, e.g., use student-level achievement and demographic data to create balanced classrooms.
Analyze data and determine whether additional data need to be collected
- Establish ongoing data collection and analysis processes to inform each step of the technology implementation process.
- Review the data collection plan on a regular basis to refine the key questions needed to guide the data collection activities and instruments, identify the source of the data, determine how the data will be analyzed and how the results will be used to inform and enhance student learning and teacher practices.
Tip: Be mindful of the barriers to using data which include: incompatibility of data systems and tools that make data analysis difficult; delays in being able to access data in time to modify instruction; getting large amounts of data from a variety of incompatible source; and inconsistency in the detail and quality of data.
Collect additional data to inform PD planning and implementation activities
- Use data to define and target the specific professional development needs of their staff, e.g., an analysis of staff knowledge of and experience teaching with certain technologies should inform the need for targeted professional learning opportunities.
- Use data to provide useful information about how teachers are integrating technology with the use of evidence-based practices in the classroom. These examples of excellence can be shared with other teachers in the building to foster peer learning opportunities.
- Share assessment data with students and family so they can have an active role in determining their own learning pathways.
Tip: For personalized learning systems to reach their full potential, data systems and learning platforms should include seamless interoperability with a focus on data security and privacy.
Research, Technology & Students with Disabilities
Assessing Progress of Your Technology Initiatives
Are Your Technology Initiatives Working?