The Dataset

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The Best Match Finder is built on Ohio's Education Management Information System (EMIS) data, the statewide administrative data system that Ohio school districts use to report student enrollment, demographics, services, and assessment outcomes to the Ohio Department of Education and Workforce.

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The data used in this tool cover four academic years: 2016–2017, 2017–2018, 2018–2019, and 2019–2020 (reported as 2016–2019). This is not survey data or a sample; it reflects the actual service records and assessment scores of real Ohio students as reported by their districts to the state.

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The dataset includes student-level records of gifted-identified students across all four district contexts: Urban, Suburban, Small Town, and Rural. Records are linked to Ohio State Test (OST) scale scores in English Language Arts, Mathematics, Science, and Social Studies.

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The Student Population

 

This tool is specific to gifted-identified students, students who have been formally identified as gifted under Ohio's identification criteria and are therefore eligible for gifted services. It does not include the broader student population.

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Ohio's gifted identification process is governed by state law and administered by districts. Identification can occur across multiple areas, including superior cognitive ability, specific academic ability, creative thinking, and visual or performing arts. The students reflected in this dataset were identified and enrolled in Ohio public schools during the study period.

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The tool covers six demographic and contextual dimensions that shape how gifted services are delivered and experienced: grade level, district context, race/ethnicity, English Learner status, disability status, and economic status. Results are specific to the intersection of these dimensions; a finding for one profile does not generalize to students with a different profile, even within the same district.

 

The Methodology

 

For each unique student profile, defined by the combination of grade level, district context, race/ethnicity, EL status, disability status, and economic status, the analysis compared mean Ohio State Test scale scores across every service model with sufficient student representation in that profile.

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The comparison uses a profile-stratified multilevel model (MLM) with a student-level random intercept, which accounts for the nesting of students within districts and for the possibility that district-level factors can affect outcomes independently of the service model. Where the MLM produced a singular fit due to small within-profile sample sizes, an ordinary least squares (OLS) regression was used as a fallback. The fit method for each result is recorded in the underlying data.

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A service model is classified as a Best Match when its mean scale score is statistically significantly higher than the no-service baseline for that profile at the 95% confidence level. Instructional Interference is assigned when the score is statistically significantly lower than the baseline. Results that do not reach statistical significance in either direction are classified as Neutral. Profiles where no model produces a confirmed lift, whether due to small sample sizes or genuine absence of effect, are returned as No Confirmed Match.

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The no-service baseline is the mean scale score for gifted-identified students in the same profile who were coded in EMIS as receiving no gifted services during the study period. This group serves as the reference point for all comparisons.

 

What the Data Cannot Tell You

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Implementation quality is not captured. EMIS records what service model a student was coded into, not how well it was delivered, whether the teacher had gifted training, how many minutes per week the service was provided, or whether it was implemented with fidelity. A Best Match reflects a statistical pattern across all implementations of that model in Ohio during the study period. Local quality matters enormously, and is not explicitly reflected in the tool's output.

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The data reflect the 2016–2019 school years in Ohio. The findings describe what was happening in Ohio districts during those years. District practices, staffing, and service models may have changed since then. The tool is best understood as a historical evidence base that informs, but does not determine current decisions.

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Causation cannot be confirmed. The analysis is observational. Students were not randomly assigned to service models, and districts make placement decisions based on many factors. While the multilevel modeling approach controls for important confounds, the findings reflect associations between service models and achievement outcomes, not experimentally established causal effects.

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The tool does not account for co-occurring services. Some students in the dataset received multiple services simultaneously. The analysis examines each service model as reported in EMIS and does not fully disentangle the effects of service combinations.

 

Sample Size and Suppression

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Results are reported only when a profile-model combination includes 10 or more students. Combinations with fewer than ten students are suppressed for two reasons: to protect student privacy, and to prevent misleading conclusions from samples too small to support reliable statistical inference.

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When a profile shows No Confirmed Match, it may mean that no model was tested with enough students to reach the reporting threshold, or that models were tested and none produced a statistically significant lift. The tool does not distinguish between these two cases in the displayed result, but both are honest and intentional outcomes; the tool is designed to be silent rather than misleading when the evidence is insufficient.

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A result of No data available (N < 10) in a subject area means the profile-model combination exists in the underlying records but does not meet the minimum threshold for reporting.

 

Using These Findings Responsibly

 

The Best Match Finder is a decision-support tool. Its purpose is to ensure that population-level evidence about what has worked for students who share a given demographic and contextual profile is available to the educators, counselors, and district leaders making placement decisions.

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It is not a placement mandate. No tool can replace professional judgment, family input, knowledge of individual student needs, or understanding of local context. The goal is to make sure that data about students who share this child's profile is part of the conversation, not to remove that conversation from human hands.

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Built on Ohio EMIS data 2016–2019