Measure Progress for Continuous Improvement
Measuring the impact of a balanced and inclusive technology plan is critical to ensuring equitable learning opportunities for all students, including those with disabilities. District leaders collect, analyze, and use data gathered across a system as part of a continuous improvement cycle. Ongoing data-collection activities enable leaders to shift and realign implementation strategies and resources to better support teaching and learning.
Actions that lead to measuring progress for continuous improvement include:
- Create a data collection plan that is robust and aligned to the district’s goals and timelines.
- Analyze the data to determine equitable technology access and use for all students.
- Take actions based on the data to ensure that all student populations have the opportunity to participate and benefit from technology for learning.
- Communicate the results of data collection and analysis through effective mechanisms for sharing results and progress.
Print the Measuring Progress Self-Assessment Tool (PDF)
Alternative version: Measuring Progress Self-Assessment Tool (MS Word)
Creating a Cycle of Continuous Improvement Through Instructional Rounds (National Council of Professors of Educational Administration (NCPEA)
Tomball ISD's Story
Tomball Independent School District serves approximately 18,000 students in Tomball, Texas. The district has grown rapidly in recent years, with shifts in district demographics and student needs. To address changing student needs, the district’s vision focuses on technology tools with built-in accessibility feature that can benefit students throughout the district, in both general and special education.
The district’s technology implementation plan began as a pilot study when a review of data found that students who were not currently identified with an IEP or a 504 plan were struggling and had limited access to resources that could support them. The AT department put together a proposal for a joint project that brings together general education, special education, instructional technology, related services and ESL teachers to conduct a needs assessment and identify primary barriers from multiple perspectives. Data collected during the pilot demonstrated improved outcomes and increased student access, so the team moved forward with district-wide implementation the following year. Goals and related data points were identified within the district strategic plan and plans for each school building to ensure that training was embedded in the professional development schedule, as well as in parent meetings, open house and personalized trainings. Data collection included requests for support, tool usage by campus, number of trainings, relationship between integration and hours of PD received, and student outcomes by tool usage. Throughout the process, the district used data to drive improvement to the implementation. Initial barriers identified during the pilot study were addressed during full implementation; data collected during full implementation were then used to identify additional needs to provide scaffolding for students.
Lange, C., Range, B., & Welsh, K. (2012). Conditions for effective data use to improve schools: Recommendations for school leaders. International Journal of Educational Leadership Preparation, 7(3), n3.
The purpose of this paper is to apply Reeves (2004) framework concerning Antecedents of Excellence in creating a school culture that routinely uses data to inform instruction. The authors highlight shared leadership as being instrumental when creating a data-driven culture.
Berglund, T., & Tosh, K. (2020). Educator Access to and Use of Data Systems.
To effectively use a variety of student data, including — but not limited to — assessment data, teachers must possess both assessment literacy (the ability to design, select, interpret and use assessment results appropriate for educational decisions) and data literacy (the ability to understand and use data to inform decisions). Results from the RAND Corporation's web-based American Educator Panels survey provide insight into teachers' access to data and the supports they receive to use it.
Wayman, J. C., Shaw, S., & Cho, V. (2017). Longitudinal effects of teacher use of a computer data system on student achievement. AERA Open, 3(1), https://doi.org/10.1177/2332858416685534.
This study sought to address the methodological gap of direct teacher interactions with data, via data systems. A significant relationship was found between system use and elementary reading improvement. The implications of this study on how to conceptualize and measure use, as well as how to support practitioners, are discussed.