Data-Based Decision-Making Teams in Middle School - Observations and Implications From the Middle School Intervention Project

Oct 15, 2026

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The study investigates how data-based decision making (DBDM) is actually practiced in middle schools, addressing the limited documentation of real classroom and team processes despite strong policy promotion. Observations from 80 standardized data-team meetings and survey responses cover structure, process, content, quality, and alignment. Findings show brief student-level discussion, actionable decisions for behavior/reading issues in 34% to 40% of cases, and weak alignment between self-reports and observations, motivating further research on outcomes.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages15

Reading Time38 min

AccessFree to download

Abstract

Data-Based Decision-Making and Its Rationale

Current Recommendations for Best Practices in DBDM

Iterative data-use cycles

Data-use frameworks and transformation of raw data

Data-Based Decision-Making Teams in Middle School: Observations and Implications From the Middle School Intervention Project Assessment for Effective Intervention 2016, Vol. 41(2) 79–93 © Hammill Institute on Disabilities 2015 Reprints and permissions: [sagepub.com/journalsPermissions.nav](sagepub.com/journalsPermissions.nav)[ ](sagepub.com/journalsPermissions.nav)[DOI: 10.1177/1534508415610322](DOI: 10.1177/1534508415610322)[ ](DOI: 10.1177/1534508415610322)[aei.sagepub.com](aei.sagepub.com) Deanne A. Crone, PhD 1, Sarah E. Carlson, PhD 1, Marcia K. Haack, PhD 1, Patrick C. Kennedy, PhD 1, Scott K. Baker, PhD2, and Hank Fien, PhD 1 Abstract The use of data-based decision making (DBDM) in schools to drive educational improvement and success has been strongly promoted by educational experts and policymakers, yet very little is documented about the actual DBDM practices used in schools. This study examines DBDM practices in 25 middle schools through 80 standardized observations of data team meetings and through survey responses. DBDM practices in terms of structure, process, content, quality, and alignment between self-report and observation are described. Key findings include the following: (a) The average amount of time spent discussing an individual student was brief, less than 2 min; (b) on average, actionable decisions following discussions of behavior or reading issues were made 34% to 40% of the time; and (c) there was weak alignment on key topics between self-reported and observed DBDM practices. These findings underscore the need for additional studies of DBDM practices in school and of the impact of DBDM practices on important student outcomes. Keywords interventions, middle school, observation In the past decade, the expectation that educators use data to inform instructional decisions has increased dramatically, as has awareness of the potential that this process, known as data-based decision making (DBDM), holds for improving student outcomes (Mandinach, 2012) . This combination has led to more widespread adoption of DBDM practices in schools, across all levels of educational delivery. The types of data collected and the ways in which data are used vary, depending on the role and purpose of the individual or team using the data. The literature on formative assessment, including curriculum-based measurement (CBM), has contributed to the trend toward increased data use in schools. This literature demonstrates that regular, reliable, and valid evaluation of essential skills paired with instructional modifications, as necessary, can have a positive and significant impact on student achievement (see, for example, Fuchs & Fuchs, 1986; Marcotte & Hintze, 2009) . Stan Deno and colleagues (e.g., Deno, 1985) pioneered much of the early work on collecting and integrating frequent, current assessment data to identify and address skill deficits in critical academic areas. Their groundbreaking work in CBM is considered by many to be the original model ofDBDM in education. A critical impetus for the increased use of data in schools was the No Child Left Behind Act (NCLB; 2001), which mandated that schools and states systematically collect, report, and respond to data measuring student achievement in key content areas. Because NCLB also legislated sanctions for schools whose achievement data demonstrated inadequate progress toward grade-level standards, schools and districts were strongly incentivized to collect data and use them to improve student achievement, at least on statewide assessment measures. What NCLB did not do, however, was to specify the mechanisms for schools and teachers to effectively implement and evaluate DBDM practices (Wayman & Stringfield, 2006) . Thus, although teachers and administrators typically have access to multiple sources of student performance data, relatively little is known about the specific DBDM practices that school personnel utilize to improve student achievement. This st

FAQs

What is the main purpose of the study?

To examine how data-based decision making (DBDM) is practiced in 25 middle schools, using observations and survey responses to describe team meeting practices.

How did the researchers measure DBDM practices?

Through 80 standardized observations of data-team meetings and by collecting survey responses about school DBDM practices.

What were the key findings about decision making and alignment?

Discussion time per student was under 2 minutes on average, actionable decisions followed behavior/reading discussions 34% to 40% of the time, and alignment between self-reported and observed practices was weak.

Oct 15, 2026

Uploaded by McGucket