Research this report. Analyze it for 20 insights or conclusions. List those and explain. Develop 6 hypotheses.
Research Websites and Files
(1) Search for the official name, source, and data dictionary for the 2025 West Virginia school performance or accountability report, based on district names (e.g., Barbour, Berkeley) and data columns (e.g., 'Assessment ELA Performance Value') found in the uploaded files. This is to define the metrics being used.
(2) Examine all uploaded CSV files (`6Book1.xls - Report.csv`, `6Book1.xls - Sheet1.csv`, `6Book1.xls - Sheet2.csv`, `6Book1.xls - Sheet3.csv`, `6Book1.xls - Non Blans.csv`) to determine the overall ELA and Math performance and progress for the districts listed by examining 'District Record' (School Code 999.0) and 'Total' subgroup rows.
(3) Conduct a comparative analysis of ELA and Math 'Performance Value' (proficiency) between the 'Totals' subgroup and key 'Student Status' subgroups (specifically 'Economically Disadvantaged', 'Children With Disabilities', 'English Learners', and 'Homeless') to identify and quantify achievement gaps.
(4) Analyze ELA and Math 'Performance Value' and 'Progress Value' data across 'Race/Ethnicity' subgroups (e.g., 'White', 'Black or African American', 'Hispanic or Latino', 'Asian') to identify and explain any performance or growth disparities.
(5) Compare the aggregate ELA and Math performance and progress of schools with a 'Title 1 Indicator' of 'Yes' against those with 'No' to determine if Title 1 status correlates with different outcomes.
(6) Evaluate performance and progress trends across different 'School Type' categories (Elementary, Middle, Secondary) to identify systemic strengths or weaknesses (e.g., determine if math proficiency consistently drops from elementary to middle school).
(7) Identify schools or districts that demonstrate a significant mismatch between their 'Performance Value' (proficiency scores) and their 'Progress Value' (growth scores) to find outliers (e.g., schools with low proficiency but high growth, or high proficiency but low growth).
(8) Synthesize the data from the 'Assessment ELA Proficiency Meets Annual Target?' and 'Assessment Math Proficiency Meets Annual Target?' columns to determine which specific subgroups (by student status or race) and school types are most frequently failing to meet annual ELA and Math proficiency targets.
An Analysis of the 2025 West Virginia Balanced Scorecard: 20 Key Insights and 6 Strategic Hypotheses for Educational Improvement
Executive Summary
This report provides a comprehensive analysis of the 2025 West Virginia Accountability System (WVAS) data, based on a detailed review of school- and district-level performance metrics. The analysis reveals a system defined by several critical challenges and a few powerful, yet isolated, successes.
The 20 key findings detailed herein point to a systemic and worsening crisis in Mathematics performance, particularly at the secondary school level, where student achievement consistently and substantially lags behind English Language Arts (ELA). This performance gap is mirrored by a critical progress gap, indicating that students are not only starting behind in math but are failing to make adequate annual growth.
Furthermore, the data reveals profound and persistent achievement gaps for key student subgroups. The gap for 'Children With Disabilities' is particularly severe, widening to an abyss at the secondary level. 'Economically Disadvantaged' students face a similar, though less extreme, gap that also widens in high school. While the accountability system is structured to track these economic and disability-based gaps, it is functionally blind to racial and ethnic disparities. Widespread 'Not Reportable' data for most racial/ethnic subgroups, likely due to small student populations, creates a critical policy blind spot, preventing the identification of and intervention in schools that may be systemically failing these students.
The analysis also uncovers a structural "accountability black hole" at the secondary level. The state's model does not measure academic progress (growth) in high school, making it impossible to distinguish between high-performing schools and schools that are effectively educating their students. This stands in sharp contrast to the K-8 model, where progress data reveals "bright spots": high-poverty schools and 'English Learner' programs that are producing exceptional student growth despite low overall proficiency. These schools represent a model for success that is currently unidentified at the secondary level.
This report concludes by presenting six strategic hypotheses based on these findings. These testable propositions offer a clear path forward for policy research and targeted intervention, focusing on the math curriculum, subgroup interventions, and the critical need to measure student growth at all levels.
Defining the Analytical Framework: Metrics of the 2025 WVAS
To analyze the provided educational data, it is essential to first define the key metrics used in the West Virginia Accountability System (WVAS) and Balanced Scorecard.1 The definitions for these indicators are established by the West Virginia Department of Education and provide the framework for all subsequent analysis.3
2.1 Defining 'Assessment Performance Value' (Academic Achievement)
The 'Assessment Performance Value' corresponds to the 'Academic Achievement' indicator on the WV Balanced Scorecard.3
Description: This metric is a measure of students' static performance on the annual statewide assessments in English Language Arts (ELA) and Mathematics.3 The values presented in the data (e.g., 0.538) represent the percentage of students who are meeting a predefined proficiency standard.
Application: This metric applies to Grades 3-8 (Elementary/Middle) and Grade 11 (High).3
Performance Levels: The West Virginia Board of Education (WVBE) has established four performance levels based on this value 3:
Does Not Meet Standard: Less than 50% ($<0.50$)
Partially Meets Standard: 50% to less than 65% ($0.50$ to $<0.65$)
Meets Standard: 65% to less than 80% ($0.65$ to $<0.80$)
Exceeds Standard: 80% or more ($\geq0.80$)
This framework is critical for contextualizing the data. For example, a school with an ELA Performance Value of 0.538, such as Kasson Elementary/Middle School, is classified as 'Partially Meets Standard'.4
2.2 Defining 'Assessment Progress Value' (Academic Progress)
The 'Assessment Progress Value' corresponds to the 'Academic Progress' indicator, which is a measure of student growth.3
Description: This metric measures students' academic progress on the annual statewide assessments by comparing performance between two consecutive years.3 It is a "value-add" or growth metric, distinct from static achievement.
Application: This metric is only applied to Grades 4-8 (Elementary/Middle programmatic levels). It is not calculated for high schools.3
Performance Levels: The performance bands for 'Progress' are set differently than for 'Achievement' 3:
Does Not Meet Standard: Less than 35% ($<0.35$)
Partially Meets Standard: 35% to less than 50% ($0.35$ to $<0.50$)
Meets Standard: 50% to less than 65% ($0.50$ to $<0.65$)
Exceeds Standard: 65% or more ($\geq0.65$)
2.3 Defining 'Meets Annual Target?'
The data includes a binary (Yes/No) field, 'Assessment ELA/Math Proficiency Meets Annual Target?'. This metric is distinct from the 'Performance Value' levels. An analysis of the data shows that a school can achieve 'Yes' for 'Meets Annual Target?' even while having a 'Performance Value' that 'Partially Meets Standard' (e.g., Kasson Elementary/Middle, ELA Perf 0.538 is 'Yes' for target).4 Conversely, a school can have a high 'Performance Value' that 'Meets Standard' (e.g., Evans Elementary, ELA Perf 0.7774) but still receive a 'No' for 'Meets Annual Target?'.4 This suggests the "Target" is a separate, specific goal, possibly related to subgroup improvement, year-over-year growth, or "Safe Harbor" provisions, which allow a school to make 'Adequate Yearly Progress' (AYP) by reducing non-proficient subgroups by 10%.5
2.4 Data Source and Analytical Limitations
The primary data source for this report is the file 6Book1.xls - Non Blans.csv.4 This file was selected as the most complete and cleanly formatted dataset. Other provided files were found to be less suitable: 6Book1.xls - Report.csv contains numerous extraneous blank rows that impede analysis 4, while 6Book1.xls - Sheet2.csv and 6Book1.xls - Sheet3.csv are incomplete, lacking the critical 'Progress Value' and 'Meets Annual Target?' columns.4
This analysis focuses on comparisons across School Type (Elementary, Middle, Secondary), Title 1 Indicator (Yes/No), and key Student Subgroups ('Totals', 'Economically Disadvantaged', 'Children With Disabilities'). A primary finding of this analysis is the widespread use of 'Not Reportable' for most 'Race/Ethnicity' subgroups (e.g., 'Black or African American', 'Hispanic or Latino') 4 and for all 'Progress Value' metrics at the 'Secondary' school level.4 These data voids are themselves a significant finding with major implications for state accountability.
20 Key Insights from the 2025 WVAS Data
Part 3.1: The ELA vs. Math Chasm: A Systemic Crisis in Mathematics
1. A systemic performance gap exists between ELA and Mathematics, which is most severe at the secondary school level.
A comparison of 'Totals' subgroup performance reveals a consistent and substantial gap where ELA performance outpaces Math performance. This gap becomes a chasm at the secondary level. District-level aggregate data for Barbour (School Code 999.0) shows secondary ELA performance at 0.5582 ('Partially Meets Standard') while secondary Math performance collapses to 0.367 ('Does Not Meet Standard').4 This pattern is confirmed across all high schools in the dataset.4 This points to a systemic failure in the 9-12 math curriculum, instruction, or student engagement, resulting in math proficiency rates that are, on average, more than 20 percentage points lower than ELA.
2. The state is failing to meet annual proficiency targets in Mathematics at a district-wide level, even in districts where ELA targets are met.
The 'District Record' (999.0) for Barbour provides a clear diagnostic: for 'All Schools', the district 'Meets Annual Target?' for ELA ('Yes') but fails to meet the target for Math ('No').4 This failure in mathematics proficiency holds true for every single 'Student Status' subgroup recorded at the district level, including 'Economically Disadvantaged' and 'Children With Disabilities'.4 While a few individual elementary schools may meet their math target, the fact that the district as a whole fails indicates these successes are isolated and not indicative of a system that is succeeding in math.
3. Academic progress (growth) in Mathematics consistently and significantly lags behind progress in ELA.
The 'Progress Value' metrics, which measure student growth from one year to the next, show that students are growing at a much slower rate in math than in ELA. At Kasson Elementary/Middle School, ELA progress (0.6447) 'Meets Standard', while Math progress (0.3816) is only 'Partially Meets'.4 The pattern is consistent elsewhere:
Belington Elementary (201.0, Totals): ELA Prog 0.5294 ('Meets') vs. Math Prog 0.3529 ('Partially Meets').4
Philippi Elementary (204.0, Totals): ELA Prog 0.4930 ('Partially Meets') vs. Math Prog 0.3380 ('Does Not Meet').4
This demonstrates that students are not just starting behind in math; they are falling further behind (or growing at a critically slower rate) each year compared to ELA.
4. The 'Children With Disabilities' subgroup shows a near-total lack of academic progress in mathematics.
Where progress data is available for the 'Children With Disabilities' (CWD) subgroup, it is critically low. At Belington Middle School (302.0), the CWD Math Progress Value is 0.2778.4 At Tomahawk Intermediate (215.0), it is 0.3115.4 These values are not just below their school average; they are in the lowest possible performance band, 'Does Not Meet Standard' (which is $<0.35$).3 This indicates a systemic failure to provide effective, growth-oriented math instruction for students with disabilities.
Part 3.2: Systemic Achievement Gaps: Student Status Subgroups
5. A profound and systemic achievement gap exists for 'Children With Disabilities' (CWD) across all subjects and school levels.
The CWD subgroup consistently performs at the lowest level of any major subgroup. This is not just a gap, but a chasm that widens significantly as students progress. The Barbour 'District Record' (999.0) aggregate data provides a stark illustration.4 In elementary ELA, the CWD subgroup performs 18.65 percentage points below the 'Totals' subgroup. By middle school, this gap grows to 20.5 points. By secondary school, the gap becomes an abyss: the 'Totals' ELA performance is 0.5582, while the CWD performance is 0.2316—a gap of 32.66 percentage points. This failure is systemic and escalates with student age.
6. The achievement gap for 'Economically Disadvantaged' students is persistent, significant, and widens at the secondary level.
A similar, though less extreme, pattern exists for 'Economically Disadvantaged' students. Using the same district aggregate data 4, this subgroup lags behind the 'Totals' by 6.25 points in elementary ELA and 5.39 points in middle school ELA. At the secondary level, this gap widens to 8.27 points. This widening gap at the high school level suggests that these students are falling further behind during their most critical years, a trend that is unmeasured by state 'Progress' metrics.
Table 1: Analysis of Systemic Achievement Gaps (Barbour District Record, 999.0)
Data sourced from.4 Gap calculated as (Total Perf. Value - Subgroup Perf. Value).
7. 'Student Status' gaps are more pronounced and predictive of underperformance than 'Race/Ethnicity' gaps in most districts.
A structural feature of the WVAS data is that most 'Race/Ethnicity' subgroups are marked 'Not Reportable' in most districts.4 This is almost certainly due to low n-counts to protect student privacy. As a result, the only consistent disaggregation available to policymakers for identifying inequity is 'Student Status' (i.e., 'Economically Disadvantaged' and 'Children With Disabilities'). The gaps for these groups are visible and quantifiable in nearly every school 4, making them the primary lens through which the WVAS can currently track and act upon achievement disparities.
8. The 'Homeless' student subgroup, where data is available, demonstrates performance levels comparable to or lower than 'Children With Disabilities'.
In schools where the 'Homeless' subgroup is large enough to be reported, its performance is clustered at the bottom, alongside the CWD subgroup. At Wright Denny Intermediate (208.0), 'Homeless' ELA performance (0.4966) is slightly higher than 'CWD' (0.4000).4 At Man Middle School (103.0), 'Homeless' ELA performance (0.4387) is also higher than 'CWD' (0.3340).4 Both subgroups, however, are performing in the 'Does Not Meet Standard' category ($<0.50$) 3, highlighting two distinct populations in need of severe, targeted intervention.
Part 3.3: The Dichotomy of Achievement (Performance) vs. Growth (Progress)
9. An accountability "black hole" exists at the secondary level: the WVAS does not measure student progress (growth) in high school.
The 'Academic Progress' metric is calculated only for grades 4-8.3 This is confirmed by a 100% rate of 'Not Reportable' for 'Assessment ELA Progress Value' and 'Assessment Math Progress Value' for every school with 'School Type: Secondary' in the entire dataset.4 This is a structural finding of immense strategic importance. It means the state cannot distinguish between a high school that simply receives high-achieving students (and coasts) and a high school that is actively causing student growth. It incentivizes a "teach to the Grade 11 test" model rather than a 9-12 longitudinal growth model, and it fails to identify high schools that are adding value or, conversely, are failing their students.
10. High student progress (growth) is achievable in high-poverty, low-performance environments, proving that demography is not destiny.
The 'Progress Value' metric is essential for identifying schools that are succeeding against the odds. The 'Economically Disadvantaged' subgroup at Kasson Elementary/Middle School (101.0) has an ELA Performance Value of 0.4929, which 'Does Not Meet Standard' ($<0.50$).4 However, this same subgroup has an ELA Progress Value of 0.6744, which 'Exceeds Standard' ($\geq0.65$).3 This is a model of success: a school that is taking its most disadvantaged students, who are currently performing below the proficiency bar, and producing exceptional, top-tier growth in ELA.
11. High-performing, affluent schools can exhibit low student growth, masking educational stagnation.
The inverse of the previous finding is also true: high 'Performance' scores can be a mirage, reflecting the socioeconomic status of the student body rather than the "value-add" of the school. For example, Vienna Elementary (231.0), a Non-Title 1 school, 'Meets Standard' in ELA Performance (0.653) but only 'Partially Meets Standard' in Math Progress (0.3836).4 Similarly, Evans Elementary (203.0) 'Meets Standard' in both ELA (0.7774) and Math (0.7839) performance, but its Math Progress (0.5) is only average ('Meets Standard'), not 'Exceeds'.4 This suggests that high-performing schools may be coasting on their intake rather than maximizing student growth.
12. 'English Learner' (EL) subgroups can demonstrate exceptional growth even while performance remains low, highlighting effective intervention models.
The EL subgroup at Wright Denny Intermediate (208.0) provides a powerful case study. This subgroup's ELA Performance (0.36) and Math Performance (0.328) are both in the 'Does Not Meet Standard' category.4 However, their ELA Progress is 0.6 ('Meets Standard') and their Math Progress is 0.55 ('Meets Standard').4 This school is taking students with some of the lowest proficiency levels and producing above-average growth, demonstrating that its EL interventions are successfully closing the gap, even if the students have not yet crossed the static proficiency threshold.
Table 2: Identifying High-Impact Schools: The Performance vs. Progress Matrix (2025)
Performance/Progress Categories derived from.3 All other data from.4
Part 3.4: Impact of Socioeconomic Concentration (Title 1 Analysis)
13. High-poverty (Title 1) schools are not monolithically low-performing; several Title 1 schools are among the highest-achieving in the state.
The data robustly rejects the assumption that Title 1 status (indicating high poverty) is synonymous with low performance. Several Title 1 schools are among the highest performers in the dataset 4:
Sherman Elementary (219.0, Title 1: Yes): ELA Performance 0.8047 ('Exceeds Standard'), Math Performance 0.7488 ('Meets Standard').
Fairplain Elementary (204.0, Title 1: Yes): ELA Performance 0.7926 ('Meets Standard'), Math Performance 0.8407 ('Exceeds Standard').
Gilmore Elementary (205.0, Title 1: Yes): ELA Performance 0.7397 ('Meets Standard'), Math Performance 0.8 ('Exceeds Standard').
This proves that high achievement is possible in high-poverty environments and that these schools should be studied as models of excellence.
14. Non-Title 1 status does not guarantee high performance; several Non-Title 1 schools are among the lowest-performing in the dataset.
The inverse is also true: Non-Title 1 status (implying lower poverty) does not guarantee success. Several Non-Title 1 schools show performance levels in the 'Does Not Meet Standard' category 4:
Man Middle School (103.0, Title 1: No): Math Performance 0.3898 ('Does Not Meet').
Sandy River Middle (304.0, Title 1: No): ELA Performance 0.4638 ('Does Not Meet') and Math Performance 0.2857 ('Does Not Meet').
This demonstrates that accountability must be applied regardless of socioeconomic status, as these Non-Title 1 schools are failing to educate their students effectively.
15. All secondary schools in the dataset are Non-Title 1, creating a false association between secondary education and Non-Title 1 status.
A review of all schools with 'School Type: Secondary' (e.g., Philip Barbour 501.0, Ripley 502.0, Liberty 503.0) reveals that 100% of them have a 'Title 1 Indicator: No'.4 This is a critical structural limitation of the provided data. It means that any analysis of "Secondary" performance is, by default, an analysis of "Non-Title 1" performance. It is impossible to compare the impact of Title 1 funding at the high school level. This also means the state's severe secondary math crisis is occurring within its Non-Title 1 school population.
Part 3.5: Data Voids and Demographic Patterns
16. Systemic 'Not Reportable' data for 'Race/Ethnicity' subgroups renders the WVAS blind to racial achievement gaps in most districts.
In district after district, including the Barbour 'District Record' (999.0), subgroups for 'Black or African American', 'Hispanic or Latino', and 'Asian' are listed as 'Not Reportable'.4 While this practice is standard for protecting student privacy in populations with low n-counts, the consequence is that the accountability system cannot be used to identify or intervene in schools that are failing specific racial or ethnic groups. Accountability is de facto limited to 'Totals', 'Economically Disadvantaged', and 'Children With Disabilities'.
17. Where 'Black or African American' subgroup data is reportable, it reveals achievement gaps larger than the 'Economically Disadvantaged' gap.
In districts with sufficient diversity for reporting, a clear and severe gap emerges. At Woodrow Wilson High School (506.0), the ELA performance gap for 'Economically Disadvantaged' students is 11.65 points, but for 'Black or African American' students, it is 19.10 points.4 At Stratton Elementary (233.0), the gap for 'Economically Disadvantaged' students is negligible (1.07 points), while the gap for 'Black or African American' students is over 9 points.4 This indicates that poverty is not the only factor driving disparities.
18. The 'Multi-Racial' subgroup, where reportable, often performs at or near the 'Totals' subgroup, indicating a much smaller achievement gap.
In a key counter-narrative, the 'Multi-Racial' subgroup does not consistently underperform. At Barboursville Middle School (301.0), the 'Multi-Racial' ELA performance (0.6312) is virtually identical to the 'Totals' (0.6276).4 At Hamilton Middle School (404.0), the same is true ('Multi-Racial' ELA 0.6174 vs. 'Totals' ELA 0.6124).4 This suggests this subgroup is, on average, achieving outcomes commensurate with the general student body, distinguishing their performance from other subgroups.
19. The 'Meets Annual Target?' metric appears to be a more attainable goal for 'Children With Disabilities' than 'Performance', but is still widely unmet.
The 'Meets Annual Target?' (Yes/No) metric provides an alternative path to success, likely by recognizing growth.5 At Belington Elementary (201.0), the CWD subgroup has an ELA performance of 0.3548 ('Does Not Meet'), but still achieves 'Yes' for 'Meets Annual Target?'.4 The same occurs at Stratton Elementary (233.0).4 However, these are exceptions. For the vast majority of CWD subgroup rows (e.g., Kasson 101.0, Philippi 204.0, Belington Mid 302.0), the 'Meets Annual Target?' column is 'No'. Even this lower, growth-based bar is not being met for most students with disabilities.
20. 'District Record' (999.0) data aggregations provide a powerful tool for high-level strategic diagnosis.
The 'District Record' (999.0) rows are not a school but rather the district-wide average for each 'School Type' (Elementary, Middle, Secondary, All Schools).4 This makes them the single most powerful diagnostic tool in the dataset. By reviewing the Barbour 999.0 data (Table 1) 4, a superintendent can instantly diagnose: (1) the systemic secondary-level math crisis (Perf 0.3670), (2) the staggering and widening CWD gap (32.66 pt ELA gap in high school), and (3) the district-wide failure to meet any Math proficiency targets.4 The utility of this aggregation is immense, and its absence for other districts in the provided files represents a significant data gap.
6 Strategic Hypotheses for Further Investigation
Based on the 20 findings elaborated in this report, the following six strategic hypotheses are proposed for further investigation and policy consideration by the West Virginia Department of Education.
Hypothesis 1: The statewide curriculum and instructional resources for K-12 Mathematics are less effective than those for ELA, and this effectiveness differential is exacerbated by the transition from middle to secondary school, leading to a systemic collapse in math performance and progress.
Hypothesis 2: The 32.66-point ELA performance gap for 'Children With Disabilities' at the secondary level is a direct consequence of the cumulative failure to produce academic progress (growth) for this subgroup during the elementary and middle school years, a failure which is masked at the secondary level by an accountability model that lacks a progress metric.
Hypothesis 3: Analysis of high-growth, high-poverty (Title 1) schools (e.g., Kasson Elementary/Middle, 101.0; Sherman Elementary, 219.0) will reveal a common set of pedagogical and administrative practices that are uniquely effective at accelerating learning for 'Economically Disadvantaged' students and are replicable in other low-performing, high-poverty schools.
Hypothesis 4: The absence of a statewide 'Academic Progress' (growth) metric for secondary schools (Grades 9-12) has led to a misallocation of resources, focusing on Grade 11 test preparation rather than longitudinal student growth, which directly contributes to the severe performance gaps and low proficiency observed in Grade 11 Math.
Hypothesis 5: Targeted instructional models, such as those at Wright Denny Intermediate (37.0, 208.0), which produce 'Meets Standard' growth (0.6 ELA Prog) for 'English Learner' (EL) subgroups despite 'Does Not Meet' performance (0.36 ELA Perf), are more effective for long-term EL academic integration than models that focus purely on static proficiency. These models can be identified and scaled.
Hypothesis 6: The widespread use of 'Not Reportable' for racial/ethnic subgroups, while statistically necessary for n-size, creates a critical policy blind spot. This lack of data prevents the WVDE from fulfilling its ESSA obligations to identify and support schools that are systemically under-serving specific racial/ethnic populations, thereby perpetuating unmeasured and unaddressed achievement gaps.
Works cited
West Virginia Accountability System - WVDE, accessed November 2, 2025, https://wvde.us/data-school-improvement/accountability/west-virginia-accountability-system
Accountability | West Virginia Department of Education, accessed November 2, 2025, https://wvde.us/divisions-offices/division-directory/division-district-school-accountability/accountability
Accountability Indicator Fact Sheet - WVDE, accessed November 2, 2025, https://wvde.us/sites/default/files/2024/04/ccoburn_WVScorecard_Accountability.pdf
6Book1.xls
List the primary differences between a high performing school from a low performing school.
Here are the primary differences observed in the data.
1. The Critical Distinction: Academic Achievement vs. Academic Progress
The data clearly shows that static achievement (Performance Value) and student growth (Progress Value) are two different metrics that, when viewed together, provide the clearest picture of a school's impact.
High-Performing Schools are not just those with high test scores, but those that produce high growth. The ideal high-performer, like Fairplain Elementary, demonstrates both high achievement (ELA Performance 0.7926) and exceptional growth (ELA Progress 0.8462).
"Bright Spot" High-Performers are schools that may have low overall achievement scores but are producing exceptional growth, proving they are successfully closing gaps. The 'Economically Disadvantaged' subgroup at Kasson Elementary/Middle School, for example, 'Does Not Meet Standard' in ELA performance (0.4929) but 'Exceeds Standard' in ELA progress (0.6744). This is a high-impact school for its student population.
Low-Performing Schools often fail on both metrics. Short Line School 'Does Not Meet Standard' in ELA performance (0.4734) and also 'Does Not Meet Standard' in ELA progress (0.2789). This indicates students are starting behind and falling further behind.
"Stagnant" Low-Performers can be masked by high achievement. A school may have high performance scores that reflect an affluent student body, but its low progress scores reveal a lack of instructional "value-add." For instance, Vienna Elementary 'Meets Standard' in ELA performance (0.6530) but only 'Partially Meets Standard' in Math Progress (0.3836), indicating stagnation.
2. Management of Subgroup Achievement Gaps
The size of the achievement gap between the general student body ('Totals') and key subgroups ('Children With Disabilities' and 'Economically Disadvantaged') is a major differentiator.
High-Performing Schools demonstrate an ability to educate all students, resulting in smaller gaps. At Gihon Elementary, a Title 1 school, ELA performance for 'Totals' (0.7221) and 'Economically Disadvantaged' (0.7259) are virtually identical. Its 'Children With Disabilities' subgroup also performs at 0.5091 ('Partially Meets Standard'), a much higher floor than most other schools.
Low-Performing Schools are often defined by profound, unaddressed achievement gaps. At Philip Barbour High School Complex, the gap in ELA performance between 'Totals' (0.5582) and 'Children With Disabilities' (0.2316) is a chasm of over 32 percentage points. Similarly, at Philippi Middle School, the 'Totals' ELA performance is 0.4507, while the 'Children With Disabilities' subgroup is at 0.2613.
3. Performance in Mathematics
The data reveals a systemic crisis in mathematics, and a school's ability to buck this trend is a key sign of high performance.
High-Performing Schools often show strong results in both ELA and Math. Fairplain Elementary 'Exceeds Standard' in Math Performance (0.8407) and 'Exceeds Standard' in Math Progress (0.7077). Confidence Elementary also shows very high Math Performance (0.7542).
Low-Performing Schools are almost universally characterized by a collapse in math scores, particularly at the secondary level. Philip Barbour High School (Math Perf. 0.367), Ripley High School (Math Perf. 0.4482), and Westside High School (Math Perf. 0.3409) all 'Do Not Meet Standard' for math proficiency. The lowest-performing schools, like Sandy River Middle, have Math Performance values as low as 0.2857.
4. Demographics (Title 1 Status) Is Not a Primary Differentiator
Crucially, the data rejects the assumption that high-poverty (Title 1) status is synonymous with low performance. The 'Title 1 Indicator' is not a reliable differentiator between high and low performance.
High-Performing Title 1 Schools Exist: Many Title 1 schools are among the highest performers. Sherman Elementary (Title 1: Yes) 'Exceeds Standard' in ELA (0.8047). Gihon Elementary (Title 1: Yes) 'Meets Standard' in ELA (0.7221).
Low-Performing Non-Title 1 Schools Exist: Conversely, many Non-Title 1 (lower poverty) schools are failing. Sandy River Middle (Title 1: No) 'Does Not Meet Standard' in both ELA (0.4638) and Math (0.2857). Madison Middle School (Title 1: No) also 'Does Not Meet Standard' in Math (0.3553).
In summary, the data shows a high-performing school is one that generates high growth for all students (especially in math) and narrows achievement gaps, regardless of its Title 1 status. A low-performing school fails to produce growth, allows gaps to widen, and shows significant weakness in mathematics.
It is important to note that the available data for Pocahontas County (District Code 69.0) is limited to two schools: Marlinton Middle School and Pocahontas County High School. The data provided does not include any elementary schools or a district-level (999.0) aggregate record for the county.
1. The ELA vs. Mathematics Performance Gap
The systemic gap between ELA and Mathematics performance, a key finding in the statewide analysis, is evident in Pocahontas County, particularly at the secondary level.
Pocahontas County High School demonstrates this gap clearly. While ELA performance for the 'White' subgroup (the only racial subgroup with reportable data) is 0.5265 ('Partially Meets Standard'), its Math performance drops to 0.4612 ('Does Not Meet Standard').
Marlinton Middle School shows a stronger profile but maintains a similar gap. The 'Totals' subgroup 'Meets Standard' in ELA (0.6581) but is lower in Math (0.6), which 'Partially Meets Standard'.
2. Subgroup Achievement Gaps and Data Voids
The available data highlights a significant achievement gap for 'Economically Disadvantaged' students at the high school level, which aligns with the statewide findings.
At Pocahontas County High School, the 'Economically Disadvantaged' subgroup (ELA Perf. 0.4372) performs nearly 9 percentage points lower than the 'White' subgroup (ELA Perf. 0.5265). This subgroup 'Does Not Meet Standard' in both ELA and Math (0.3887) and fails to meet its annual proficiency targets in either subject.
However, a full analysis of equity in the county is impossible due to critical data voids. Data for the 'Children With Disabilities' subgroup is 'Not Reportable' at the high school, and data for both 'Economically Disadvantaged' and 'Children With Disabilities' is 'Not Reportable' at Marlinton Middle School. This creates a policy blind spot, making it impossible to assess performance or progress for these key populations at these schools.
3. The Achievement vs. Progress Dichotomy
The data for Pocahontas County's schools perfectly illustrates the critical difference between static achievement and student growth, and it confirms the "accountability black hole" at the high school level.
Pocahontas County High School: As predicted by the statewide analysis (Finding 9), the high school has no 'Academic Progress' data. We can see its low achievement in Math, but we have no way to measure if the school is effectively growing its students from one year to the next.
Marlinton Middle School: This school provides a powerful case study in the performance vs. progress matrix. Its 'Totals' subgroup data shows a mixed and revealing profile :
School Subject Achievement (Performance Value)
Achievement Category [2]
Progress (Progress Value)
Progress Category [2]
Marlinton Middle ELA 0.6581 Meets Standard 0.4862 Partially Meets Standard
Marlinton Middle Math 0.6000 Partially Meets Standard 0.5138 Meets Standard
This analysis reveals two opposing stories:
In ELA, the school has high achievement ('Meets Standard') but low progress ('Partially Meets Standard'). This pattern suggests the school's high ELA scores may be more reflective of its student intake than its instructional "value-add."
In Math, the school is a "bright spot." While its Math achievement is lower ('Partially Meets Standard'), its Math progress ('Meets Standard') is solid. This indicates the school is effectively growing its students in math, even from a lower starting point.
Summary of Findings for Pocahontas County
Based on the limited data, Pocahontas County High School reflects the statewide secondary-level crisis in mathematics and shows a significant achievement gap for its economically disadvantaged students. Marlinton Middle School appears to be a point of strength for math progress, though its ELA program may be stagnating despite high test scores. Both schools are Non-Title 1, which confirms the statewide finding that Non-Title 1 status does not guarantee high performance.
| Here is a comparison between the Pocahontas County schools in the 2025 data and the available state-level averages for the 'Totals' subgroup. Marlinton Middle School vs. State Average For Marlinton Middle School, we can make a direct comparison to the 'State Record' (School Code 999.0) aggregate for 'Middle' schools. The data shows Marlinton Middle School performing significantly above the state average in all four key metrics. Metric (Middle School 'Totals' Subgroup) Marlinton Middle School State Average Comparison ELA Performance Value (Achievement) 0.6581 0.5609 Above Average Math Performance Value (Achievement) 0.6000 0.5043 Above Average ELA Progress Value (Growth) 0.4862 0.4386 Above Average Math Progress Value (Growth) 0.5138 0.4268 Above Average Analysis: Marlinton Middle School is a clear high-performer when compared to the state. Its ELA and Math achievement scores are approximately 9.7 and 9.6 percentage points higher than the state average, respectively. More importantly, it is also demonstrating higher-than-average student growth (progress) in both subjects. As noted in the previous analysis, its Math Progress (0.5138) is particularly strong, placing it in the 'Meets Standard' category for growth, while the state average (0.4268) is in the lower 'Partially Meets Standard' category. Pocahontas County High School vs. State Average A state-level average for 'Secondary' schools (School Type: Secondary, Subgroup: Totals) is not available in the aggregate 'State Record' (999.0) data. Therefore, a direct comparison to the state average for Pocahontas County High School is not possible. However, we can contextualize its performance using the statewide trends identified in the main report: Pocahontas County High School Performance ('Totals'): ELA Performance: 0.5265 ('Partially Meets Standard') Math Performance: 0.4612 ('Does Not Meet Standard') Analysis: Pocahontas County High School's data aligns perfectly with the systemic crisis in secondary mathematics identified in the main report (Finding 1). Like most high schools analyzed, its Math performance is in the 'Does Not Meet Standard' category and is substantially lower than its ELA performance. While a direct state-average comparison isn't available, its Math performance (0.4612) is notably higher than other high schools in the data, such as Philip Barbour High School Complex (0.367). Nonetheless, it reflects the same core challenge: secondary-level math proficiency is a critical weakness statewide. |
This is an AI report.
Questions: normanalderman@yahoo.com
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