Inside the Black Box of School Performance

 

Inside the Black Box of School Performance: 5 Surprising Lessons from West Virginia’s Education Data Architecture

Evaluating whether a public school system is truly succeeding or failing remains one of the most contentious challenges in modern public policy. Too often, public debate relies on surface-level test scores or broad demographic assumptions, treating the internal mechanics of school operations as a black box. A low assessment score is frequently cited as proof of educational failure, while high spending is assumed to guarantee strong outcomes. However, isolated metrics rarely capture the complex interplay between financial inputs, instructional quality, and student learning growth.

To move beyond these simplistic judgments, West Virginia has established a multidimensional diagnostic framework designed to query state data repositories, including the ZoomWV Data Dashboard, the West Virginia Education Information System (WVEIS), and OpenGov transparency platforms. Grounded in a five-year longitudinal analysis spanning academic years 2021–2022 through 2025–2026—using 2021–2022 as the post-pandemic baseline—this empirical protocol synthesizes per-pupil financial tracking, individual student growth trajectories, and statutory curriculum fidelity.

By auditing school performance through this integrated data architecture, diagnosticians can isolate the true causal drivers of educational achievement. The findings reveal that standard assumptions about school quality, spending efficiency, and intervention strategies are frequently incorrect. Here are the top five counter-intuitive takeaways buried within West Virginia’s state educational accountability data and legal policies.

1. The Growth Metric Trap: Student Growth Percentiles (SGP) vs. Value-Added Models (VAM)

Public school accountability dashboards, such as the West Virginia Balanced Scorecard, heavily emphasize academic growth metrics to measure student progress. However, a major technical flaw exists in how these public dashboards evaluate progress: they rely on descriptive models rather than causal statistical models.

West Virginia’s state dashboard utilizes the Student Growth Percentile (SGP) model. SGP simply ranks a student's current assessment achievement against a peer cohort with identical historical test score trajectories. What is frequently misunderstood is that SGP is strictly a descriptive metric; it does not adjust for external student background characteristics, such as socioeconomic status, poverty, or disability status. By contrast, statistical Value-Added Models (VAM) attempt to isolate the specific causal effect of a school or educator on student learning. VAM accomplishes this by controlling for exogenous variables—including demographic background, prior test scores, and measurement errors in baseline testing—effectively adjusting expectations for historically underserved student populations to measure true instructional impact.

"The Student Growth Percentile (SGP) model... is a descriptive metric. It ranks a student's current achievement relative to a peer cohort... but it explicitly does not control for student background characteristics such as poverty or disability."

Analytical Reflection: Evaluating school quality strictly through unadjusted SGP metrics without overlaying socio-demographic context creates a statistical trap. Because SGP fails to account for background variables, high-poverty schools that achieve significant, hard-won instructional progress with vulnerable populations may still receive artificially deflated progress evaluations on state dashboards. Diagnostic evaluations must contextualize raw growth percentiles with demographic overlays to avoid unfairly penalizing high-poverty campuses.

2. The Per-Pupil Spending Anomaly: Operational Bloat vs. True Classroom Investment

A common assumption in education policy is that lower-performing schools are simply underfunded. However, federal Resource Allocation Reviews (RAR) mandated under the Every Student Succeeds Act (ESSA) and forensic accounting via the WVEIS Chart of Accounts reveal a persistent resource allocation paradox: localized campus data frequently uncovers schools that spend significantly more per pupil than their district average, yet remain stuck in the state's lowest performance designations—such as Comprehensive Support and Improvement (CSI) or Targeted Support and Improvement (TSI).

This dynamic is particularly stark when evaluated alongside West Virginia's Public School Support Program (PSSP) funding structure. The PSSP model incorporates weighted student allocations designed to direct higher funding to vulnerable populations, including special education intensity weights (0.50 for Level I, 1.00 for Level II, and 2.00 for Level III) and progressive poverty multipliers for schools with concentrations exceeding 40%, 60%, and 75%. While state funding formulas generate elevated revenue streams intended for high-need campuses, WVEIS accounting flexfield tracking reveals that these targeted dollars frequently fail to reach the classroom.

WVEIS Account Dimension	Operational Purpose & Impact
Fund Code 11	General Current Expense: Tracks baseline operational and general education funding.
Fund Code 61 / 7X	Special Revenue & Federal Stimulus: Tracks restricted state/federal grants, Title I funds, and emergency stabilization allocations.
Function Code 1000	Direct Instruction: Isolates expenditures directly impacting classroom learning, core teaching staff, and direct instruction.
Function Code 2000	Support Services & Administration: Tracks non-instructional overhead, including school leadership, administrative operations, and central support services.

Analytical Reflection: High per-pupil spending in a low-performing school often signals severe operational inefficiency or administrative bloat rather than robust classroom investment. When equity-weighted revenues generated by vulnerable student populations are absorbed by Function 2000 administrative overhead or fragmented support structures, state aid intent gets distorted. Achieving financial equity requires more than just increasing aggregate budgets; districts must actively reallocate unrestricted general funds directly into Function 1000 core classroom instruction, certified teachers, and foundational learning resources.

3. The 40% Red Flag: When More Interventions Signal a Systemic Core Breakdown

Under the West Virginia Tiered System of Supports (WVTSS) framework, schools address academic and behavioral challenges through a multi-tiered delivery model: Tier 1 Universal instruction (standards-based core instruction for 100% of students), Tier 2 Targeted interventions (small-group supplemental skill building for 10–20% of students), and Tier 3 Intensive interventions (individualized high-intensity support for 5–10% of students).

A healthy educational ecosystem relies on a functional Tier 1 baseline, where approximately 75% to 80% of students succeed without supplemental assistance. A major systemic paradox occurs when longitudinal data reveals that 40% of a school's population requires Tier 3 intensive reading interventions. In this scenario, adding more interventionists or expanding remedial pull-out programs will not fix the issue.

"If the longitudinal data indicates that 40 percent of a school's population requires Tier 3 intensive reading interventions, the diagnostician can conclude that the Tier 1 core instruction is structurally flawed."

Analytical Reflection: School systems routinely fall into the trap of over-budgeting for high-intensity remediation programs to cure low achievement scores. However, when 40% of students trigger intensive intervention thresholds, the failure is not at the student level—it is a structural breakdown of whole-staff Tier 1 classroom instruction. Diagnosticians must direct leaders away from costly, fragmented remediation programs and redirect efforts toward comprehensive curriculum reform, baseline teaching practices, and whole-staff professional development.

4. The Third Grade Success Act: Strict Timelines and the 2026–2027 Retention Wall

Early elementary education in West Virginia is governed by strict legal mechanisms under House Bill 3035, known as the Third Grade Success Act. Designed to address foundational reading and mathematics deficits in grades K–3, HB 3035 establishes mandatory procedural timelines that schools must follow upon identifying a student deficiency via benchmark screeners:

• 15-Day Notification Mandate: School staff must provide written notification to parents or guardians within 15 days of identifying an early literacy or mathematics deficiency.
• 30-Day Plan Mandate: An Individualized Improvement Plan (reading or mathematics) must be formally established for the student no later than 30 days after the deficiency is identified.

To operationalize these requirements, HB 3035 funds a three-year phased deployment of Early Childhood Classroom Assistant Teachers (ECCATs) alongside targeted interventionists in K–3 classrooms. This funded staffing model ensures lower student-to-adult ratios during critical early literacy blocks.

However, the most critical element of HB 3035 is an impending statutory deadline: beginning in the 2026–2027 academic year, third-grade students who fail to demonstrate proficiency on the West Virginia General Summative Assessment (WVGSA) in English Language Arts or Mathematics face mandatory grade retention, unless they meet specific statutory "good cause exemptions" (e.g., severe IDEA disabilities, English Learners with less than two years of instruction, or students previously retained for two years).

Analytical Reflection: The 2026–2027 retention requirement creates a strict operational wall for elementary schools. Longitudinal data tracking of K–2 diagnostic screeners, combined with monitoring the effective deployment of ECCAT personnel, serves as an essential predictive warning system. By evaluating screening cut scores and intervention compliance in real time, districts can identify at-risk early learners and correct instructional trajectories years before students reach the mandatory third-grade retention wall.

5. The Scheduling Audit: Balancing 8,100-Minute Courses and Escalating Credit Mandates

High school master scheduling is often viewed as a routine administrative task, but under West Virginia Board of Education (WVBE) Policy 2510, course scheduling directly impacts state compliance and academic performance reviews.

High schools face escalating state graduation credit mandates that require continuous scheduling adjustments:

• 2024–2025 Freshman Cohort: Graduation requirements increase from 22 to 23 total credits, introducing a mandatory credit in Personal Finance.
• 2027–2028 Freshman Cohort: Graduation requirements increase to 24 total credits, integrating a required credit in Computer Science.

Additionally, schools must maintain access to advanced coursework, mandating annual access to at least four Advanced Placement (AP) courses across core subjects and offering specific Career and Technical Education (CTE) clusters scaled to school size (e.g., three clusters for enrollments under 400; five clusters for enrollments over 800).

Crucially, Policy 2510 contains a statutory audit trigger: if a high school utilizes condensed courses scheduled for fewer than 8,100 instructional minutes and fails to meet state proficiency standards for two consecutive years, it triggers a mandatory, formal schedule review by the County Board of Education.

Analytical Reflection: Rigid instructional minute requirements combined with expanding credit mandates create operational friction inside high schools. Small or understaffed campuses often struggle to balance mandatory AP/CTE access, core credit expansions, and minute-count mandates within traditional bell schedules. Auditing schedule integrity helps administrators spot structural bottlenecks early, ensuring students receive adequate instructional time to master standards before triggering state intervention.

6. Conclusion: Beyond Numbers—Building Sustainable Educational Equity

Deconstructing West Virginia's educational data architecture demonstrates that meaningful school improvement requires more than reacting to isolated standardized test scores or throwing unexamined funding at low-performing campuses. True diagnostic analysis requires a synthesized approach that bridges financial flexfield accounting, statistical growth metrics, multi-tiered support ratios, and statutory policy compliance.

When educational leaders look past high-level dashboard summaries and analyze the underlying mechanics of public school performance, they can move from reactive measures to targeted, sustainable reform. Whether evaluating financial allocations, restructuring core classroom delivery, or planning for statutory literacy deadlines, empirical data must drive policy decisions.

As state accountability models continue to evolve, policymakers, district leaders, and parents must ask a fundamental question:

Is your local district measuring true learning growth, or just tracking metrics that hide systemic inequities?

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Diagnostic Framework for West Virginia Public Schools: Financial Allocation, Student Accountability, and Curriculum Fidelity

Executive Summary

Evaluating public school efficacy in West Virginia requires a multidimensional, algorithmic diagnostic framework operating across a five-year longitudinal window (academic years 2021–2022 through 2025–2026). Designed to interface with state data repositories—including the ZoomWV Data Dashboard, the West Virginia Education Information System (WVEIS), and the West Virginia Department of Education (WVDE) OpenGov platform—this diagnostic architecture integrates three core operational domains: Financial Level Diagnostics, Student-Level Accountability, and Curriculum-Level Fidelity.

By disaggregating data by student demographics (requiring a statutory minimum cell size of 20 Full Academic Year [FAY] students) and benchmarking performance against state averages, educational diagnosticians can isolate root causes of performance deficits. The framework connects fiscal resource distribution (via the Public School Support Program and WVEIS Chart of Accounts) directly to student growth models (Student Growth Percentiles vs. Value-Added Models), early literacy mandates (The Third Grade Success Act / HB 3035), Policy 2510 high school programmatic requirements, and multi-tiered intervention systems (WVTSS and Student Assistance Teams). Ultimately, this system provides the empirical foundation necessary for data-driven strategic planning and targeted corrective action.

1. Diagnostic Architecture and Longitudinal Data Parameters

The diagnostic evaluation relies on a longitudinal data query designed to establish post-pandemic baseline metrics and trace systemic trends.

Data Query Infrastructure and Timelines

• Baseline Establishment: Due to severe disruptions from the COVID-19 pandemic and the total absence of accountability metrics during the 2020–2021 academic year, the 2021–2022 school year serves as the baseline for measuring post-pandemic recovery.
• Longitudinal Window: The framework tracks data across five consecutive academic years (2021–2022 through 2025–2026).
• Data Repositories Querying:
  • WVEIS: Provides micro-level accounting expenditures, master scheduling, credit accumulation, and behavioral tracking.
  • ZoomWV Data Dashboard: Source for aggregated and disaggregated student performance, growth metrics, and Balanced Scorecard indicators.
  • WVDE OpenGov Transparency Platform: Tracks district- and county-level annual reporting and fiscal disbursements.

Subgroup Disaggregation & Reporting Thresholds

Accountability calculations in West Virginia require a minimum cell size of 20 FAY students for a demographic subgroup to be statistically valid for reporting. The diagnostic prompt intersects operational domains across specific student populations:

• Economically Disadvantaged Students
• English Learners (EL)
• Students with Disabilities (receiving services under the Individuals with Disabilities Education Act [IDEA])
• Homeless Students (identified under the McKinney-Vento Homeless Assistance Act)

By intersecting demographics with fiscal allocations and instructional compliance, the diagnostician isolates root causal variables. For instance, localized reading deficiencies in early grades can be systematically cross-referenced against targeted instructional spending, chronic absenteeism rates, and statutory early literacy compliance.

2. Financial Level Diagnostics: Resource Allocation and Equity

The financial diagnostic assesses how state aid, federal funds, and local revenues are distributed across schools to ensure fiscal equity and operational efficiency.

2.1 The Public School Support Program (PSSP) Analysis

West Virginia allocates baseline state resources to county boards of education through the Public School Support Program (PSSP). The framework traces funds across the seven foundational steps of the PSSP to evaluate district- and school-level efficiency.

PSSP Step	Funding Objective	Diagnostic Query Focus
Step 1	Allowance for Professional Educators	Analyzes ratio of state-aid eligible professional educators per 1,000 students in net enrollment, adjusted for county population density (sparse to high-density).
Step 2	Allowance for Service Personnel	Evaluates allocation of service personnel (aides, custodians, interventionists) based on enrollment ratios and density tiers.
Step 3	Allowance for Fixed Charges	Tracks employer contributions for social security, unemployment, and workers' compensation.
Step 4	Allowance for Transportation	Assesses operational expenses cross-referenced with attendance rates and geographical sparsity.
Step 5	Current Expenses	Calculates operational and maintenance funding using total building square footage and net enrollment.
Step 6	Local Share	Computes equalized local tax effort required to supplement state aid, identifying local revenue generation disparities.
Step 7	Improvement of Instructional Programs	Isolates funds explicitly dedicated to instructional delivery enhancement and curriculum fidelity.

Modernized Weighted Funding Frameworks

Recent modernization proposals incorporate progressive weights to address high-need demographics:

• Special Education Weights (shifting from disability category to service intensity):
  • Level I Needs: Weight of 0.50
  • Level II Needs: Weight of 1.00
  • Level III Needs: Weight of 2.00
  • Gifted Students: Weight of 0.05
• Poverty Weights: Cumulative multipliers applied to schools with poverty concentrations exceeding 40%, 60%, and 75% to verify proper delivery of Title I and state compensatory funds.

2.2 Micro-Level Expenditure Tracking (WVEIS Flexfield)

To track micro-level financial allocations, the system extracts data from the multidimensional accounting flexfield of the WVEIS Chart of Accounts:

• Fund Code (2-Digit): Distinguishes between General Current Expense funds (Fund 11), Special Revenue funds (Fund 61), and Federal Stimulus/Stabilization funds (Fund 7X).
• Project Code (5-Digit): Differentiates unrestricted general initiatives from restricted federal and state grants.
• Function Code: Categorizes operational spending. Direct instructional expenditures (Function 1000) are separated from support services and administrative overhead (Function 2000).

Diagnostic Objective: Calculate the precise percentage of per-pupil funding reaching the classroom and highlight institutions burdened by administrative bloat or systemic underfunding.

2.3 ESSA Resource Allocation Reviews (RAR)

Under the Every Student Succeeds Act (ESSA), districts containing schools designated for Comprehensive Support and Improvement (CSI), Targeted Support and Improvement (TSI), or Additional Targeted Support and Improvement (ATSI) must conduct Resource Allocation Reviews (RAR). The diagnostic prompt identifies structural spending anomalies—such as campuses spending significantly above the district per-pupil average yet remaining in the lowest academic performance tier—triggering recommendations to reallocate general funds toward core instructional staffing, leadership development, and foundational operations.

3. Student-Level Diagnostics: Accountability and Growth Analytics

Student performance is evaluated using the West Virginia Balanced Scorecard, which tracks schools across standardized performance tiers and growth metrics.

3.1 The West Virginia Balanced Scorecard Framework

The diagnostic system categorizes student achievement across four performance tiers:

Performance Level Designation	WVGSA Point Value Range	WVASA Counterpart Level	Expectation Definition
Exceeds Standard	100 to 125 Points (80%+)	Advanced	Distinctive performance exceeding state expectations.
Meets Standard	81.25 to 100 Points (65–80%)	At Target	Performance falls within the expected state range.
Partially Meets Standard	62.5 to 81.25 Points (50–65%)	Approaching Target	Approaching the expected range of performance.
Does Not Meet Standard	Below 62.5 Points	Below Target	Unacceptably below the expected level of performance.

Long-Term Proficiency Trajectory Goals

Following the post-pandemic reset (using 2020–2021 as the baseline), West Virginia established a long-term goal to reduce the gap between baseline proficiency and 100% proficiency by half by the 2035–2036 school year on the West Virginia General Summative Assessment (WVGSA) in English Language Arts (ELA) and Mathematics. The diagnostic prompt projects five-year trajectories to evaluate whether a school is meeting its required annual targets.

English Learner Progress (ELP)

Monitored via the ELPA21 assessment across four domains: listening, reading, speaking, and writing. Overall proficiency requires achieving a performance level of 4 (Early Advanced) or 5 (Advanced) in all four domains.

3.2 Methodological Evaluation: SGP vs. VAM

When analyzing academic growth metrics (defined in WV as the percentage of students advancing \ge 1 performance level increment or maintaining "Exceeds Standard"), diagnosticians must differentiate between descriptive and causal growth models:

                            GROWTH MODEL COMPARISON
┌─────────────────────────────────────────┬─────────────────────────────────────────┐
│     STUDENT GROWTH PERCENTILES (SGP)    │        VALUE-ADDED MODELS (VAM)         │
├─────────────────────────────────────────┼─────────────────────────────────────────┤
│ • Descriptive measure used on state     │ • Causal attribution model designed for │
│   dashboards.                           │   educator effectiveness evaluation.    │
│ • Ranks student achievement relative to │ • Controls statistically for exogenous  │
│   academic peers with identical past    │   variables (socioeconomic status,      │
│   test score histories.                 │   disability, prior achievement).       │
│ • Does NOT adjust for background,       │ • Applies errors-in-variables           │
│   poverty, or demographic factors.      │   corrections for measurement error.    │
└─────────────────────────────────────────┴─────────────────────────────────────────┘

Analytical Imperative: Because state accountability relies primarily on unadjusted SGP descriptive metrics, diagnosticians must manually overlay socio-demographic contexts onto progress scores. Failing to contextualize SGP scores results in artificially deflated evaluations for schools serving high concentrations of at-risk students.

3.3 Non-Academic & Behavioral Indicators

• Chronic Absenteeism: Defined as missing >10% of enrolled instructional days. Unexcused absences or total absences exceeding 10 days without physician documentation trigger statutory legal interventions.
• Behavior Indicator: Percentage of students maintaining zero out-of-school suspensions during the academic year.
• On-Track to Graduation (High School): Percentage of 10th-grade students earning \ge 12 cumulative credits across 9th and 10th grades, with \ge 2 credits in each core area (ELA, Math, Science, Social Studies).
• Cohort Graduation Rates: 4-year and 5-year adjusted cohort rates (State standard for "Meets Standard" is 90% to 95%).

3.4 Support Designations (CSI, TSI, ATSI)

• Comprehensive Support and Improvement (CSI): Flagged if a school scores in the lowest performance tier (Red) across all indicators, or if a high school fails to graduate at least 67% of its four-year cohort.
• Targeted Support / Additional Targeted Support (TSI/ATSI): Flagged if specific demographic subgroups perform at a level equivalent to the lowest 5% of Title I schools statewide.

4. Curriculum Level Diagnostics: Instructional Fidelity and Legislative Mandates

Instructional diagnostics audit master schedules, programmatic offerings, and legal compliance with statutory mandates.

4.1 WVBE Policy 2510: High School Programmatic Rigor

Policy 2510 dictates operational standards, scheduling integrity, and graduation requirements:

• Graduation Credit Progression:
  • Historical Baseline: 22 Total Credits
  • 2024–2025 Freshman Cohort: 23 Total Credits (incorporates a required credit in Personal Finance)
  • 2027–2028 Freshman Cohort: 24 Total Credits (incorporates a required credit in Computer Science)
• Course Scheduling Integrity: Courses utilizing schedules shorter than 8,100 minutes that simultaneously fail to meet state proficiency standards for two consecutive years are flagged for a mandatory schedule audit by the County Board of Education.
• Advanced Coursework Mandates:
  • Advanced Placement (AP): Schools must offer at least 4 AP courses annually, covering all 4 core content areas.
  • Career & Technical Education (CTE): Schools with enrollments <400 students must offer \ge 3 CTE clusters; schools with enrollments >800 students must offer \ge 5 CTE clusters.

4.2 Early Literacy & Numeracy Mandates: Third Grade Success Act (HB 3035)

HB 3035 establishes a comprehensive, multi-tiered framework for K–3 early reading and mathematics development.

                  HB 3035 STATUTORY TIMELINE & REQUIREMENTS
┌───────────────────────────┬───────────────────────────┬───────────────────────────┐
│    1. BENCHMARK SCREEN    │   2. PARENT NOTIFICATION  │    3. IMPROVEMENT PLAN    │
├───────────────────────────┼───────────────────────────┼───────────────────────────┤
│ Administer state-approved │ Mandated written notice   │ Individualized plan must  │
│ benchmark screeners for   │ to parents within 15 DAYS │ be generated no later     │
│ reading, math, dyslexia,  │ of identifying a reading  │ than 30 DAYS following    │
│ and dyscalculia.          │ or math deficiency.       │ initial identification.   │
└───────────────────────────┴───────────────────────────┴───────────────────────────┘

• Personnel Deployment: Directs phased funding for Early Childhood Classroom Assistant Teachers (ECCATs) and specialized interventionists in early elementary classrooms.
• Mandatory Third-Grade Retention: Beginning in the 2026–2027 school year, students who fail to demonstrate reading or math proficiency on the WVGSA by the end of 3rd grade must be retained.
• Good Cause Exemptions from Retention:
  1. Students with severe disabilities.
  2. English Learners (EL) with less than two years of English instruction.
  3. Students previously retained for a total of two years in early elementary grades.

4.3 WVBE Policy 2322: Standards for Effective Schools

Qualitative instructional alignment is evaluated across seven common standards via the annual West Virginia School Learning Environment Surveys (administered to students, staff, and parents):

1. Positive Climate and Cohesive Culture
2. School Leadership
3. Standards-Focused Curriculum and Instruction
4. Student Support Services
5. Educator Growth and Development
6. Efficient and Effective Management
7. Continuous Improvement

5. Corrective Interventions and Strategic Improvement Planning

Diagnostic outputs map directly into state-sanctioned operational intervention structures to correct resource deficiencies and academic performance gaps.

5.1 West Virginia Tiered System of Supports (WVTSS)

When widespread academic or behavioral vulnerabilities are diagnosed, schools must realign their framework according to WVTSS parameters.

WVTSS Tier Level	Academic Interventions	Behavioral & Mental Health Interventions	Target Population & Systemic Efficacy Expectations
Tier 1 (Universal)	High-quality standards-based core instruction; differentiated learning plans.	School-wide Positive Behavior Interventions and Supports (PBIS); universal mental health screening.	Delivered to 100% of students. A functional Tier 1 core should result in ~75–80% of students achieving proficiency without added support.
Tier 2 (Targeted)	Targeted small-group instruction; supplemental skill-building pull-outs.	Restorative circles; check-in/check-out tracking; targeted counseling groups.	Serves ~10–20% of students requiring supplemental scaffolding.
Tier 3 (Intensive)	High-intensity individualized instruction; formal special education evaluation referrals.	Crisis protocols; community wraparound services; individualized Behavior Intervention Plans (BIP).	Reserved for ~5–10% of students needing intensive, individualized interventions.

Diagnostic Analysis: If longitudinal data reveals that 40% of a school's population requires Tier 3 interventions, the diagnostician must conclude that Tier 1 core instruction is structurally compromised. Corrective action must focus on foundational curriculum reform and whole-staff professional development rather than hiring additional Tier 3 interventionists.

5.2 Student Assistance Team (SAT) Operational Dynamics

Managed under Policy 2510, the SAT (comprising the principal, teachers, and counselors) acts as the operational body executing interventions:

• Timeline Mandates: Enforces the statutory 30-day window for generating improvement plans following HB 3035 screening deficiencies.
• Truancy Interventions: Tracks chronic absenteeism, deploying community resources and attendance directors when unexcused absences exceed statutory limits.
• High School Credit Recovery Pathways: Diverts off-track high school students into credit recovery programs or the Option Pathway (allowing at-risk students ages 16–21 to complete a CTE pathway and high school equivalency assessment in lieu of traditional credit accumulation).

5.3 Annual Strategic Improvement Planning

The diagnostic evaluation culminates in the statutory Comprehensive Needs Assessment (CNA) and annual Strategic Plan mandated by State Code and Policy 2322.

The finalized strategic plan must integrate diagnostic data to:

1. Set Targeted Subgroup Goals: Establish quantifiable targets to narrow achievement gaps in alignment with the 2035–2036 state targets.
2. Align Resource Spending: Direct PSSP Step 7 instructional improvement funds and federal Title I allocations directly to evidence-based interventions.
3. Execute Action Steps: Modernize master scheduling to fulfill Policy 2510 mandates, deploy instructional coaches, and implement WVTSS protocols.
4. Monitor Fidelity: Establish routine administrative walkthroughs and formative assessments to continuously evaluate intervention efficacy.

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West Virginia School Performance Diagnostic Framework: Study Guide

This study guide provides a structured review of the architectural framework used to diagnose school performance in West Virginia public schools. It synthesizes financial mechanisms, student outcome metrics, legislative curriculum mandates, and multi-tiered intervention systems to evaluate systemic educational efficacy.

Part 1: Short-Answer Quiz Questions

1. What baseline academic year and minimum subgroup cell size (N-count) does the West Virginia longitudinal diagnostic prompt establish for valid statistical reporting post-COVID-19?
2. How do proposed modernizations to the Public School Support Program (PSSP) alter the funding allocation model for special education services?
3. Within the WVEIS Chart of Accounts flexfield structure, how do Function Codes assist educational diagnosticians in evaluating expenditure efficiency?
4. What specific performance and graduation thresholds trigger a school to be designated for Comprehensive Support and Improvement (CSI)?
5. What is the fundamental conceptual and statistical difference between Student Growth Percentiles (SGP) and Value-Added Models (VAM) regarding student demographic characteristics?
6. How does WVBE Policy 2510 update high school graduation credit requirements for the freshman cohorts entering in 2024–2025 and 2027–2028?
7. Under House Bill 3035 (Third Grade Success Act), what are the strict statutory timelines for parental notification and intervention plan implementation following the identification of an early literacy or numeracy deficiency?
8. What specific student populations qualify for "good cause exemptions" from the mandatory third-grade retention rule established by HB 3035 beginning in the 2026–2027 school year?
9. According to the West Virginia Tiered System of Supports (WVTSS) framework, what systemic issue is indicated if 40 percent of a school's population requires Tier 3 intensive reading interventions?
10. What role does the Student Assistance Team (SAT) play in facilitating alternative pathways for off-track high school students experiencing credit deficiencies?

Part 2: Quiz Answer Key

1. ** baseline & subgroup size:** The diagnostic prompt establishes the 2021–2022 academic year as the baseline for post-pandemic recovery analysis over a five-year longitudinal window (through 2025–2026). To maintain statistical validity and protect privacy, West Virginia accountability rules require a minimum cell size of twenty (20) Full Academic Year (FAY) students for any demographic subgroup to be reported.
2. PSSP special education modernizations: Modernized PSSP proposals shift funding from rigid disability categories to a service intensity model based on weighted student multipliers. Special education weights are assigned as 0.50 for Level I, 1.00 for Level II, 2.00 for Level III, and 0.05 for gifted students.
3. Function Codes in WVEIS expenditure tracking: Function Codes categorize expenditures by operational purpose, allowing diagnosticians to isolate direct instructional costs (Function 1000) from support services and administrative overhead (Function 2000). This isolation enables the calculation of the exact percentage of per-pupil funding reaching the classroom to identify operational inefficiencies or administrative bloat.
4. Comprehensive Support and Improvement (CSI) criteria: A school is flagged for CSI if it falls into the lowest performance tier (represented as red on the West Virginia Balanced Scorecard) across all indicators. Additionally, any high school that fails to graduate at least 67 percent of its adjusted cohort is automatically assigned a CSI designation.
5. SGP vs. VAM growth models: The Student Growth Percentile (SGP) model is a purely descriptive metric that ranks a student's progress relative to academic peers without controlling for background characteristics such as poverty or disability. Conversely, Value-Added Models (VAM) statistically control for exogenous demographic variables and pretest measurement errors to isolate the specific causal impact of a school or teacher on student learning.
6. WVBE Policy 2510 credit updates: Policy 2510 expands high school graduation requirements from 22 credits to 23 credits for the 2024–2025 freshman cohort to integrate a mandatory Personal Finance course. The requirement increases to 24 credits for the 2027–2028 freshman cohort with the addition of a required Computer Science credit.
7. HB 3035 statutory timelines: Schools are legally required to notify parents or guardians in writing within 15 days of identifying a literacy or mathematics deficiency via benchmark screeners. Furthermore, an individualized reading or mathematics improvement plan must be formulated and implemented no later than 30 days following the initial identification.
8. HB 3035 good cause exemptions: Exemptions from mandatory third-grade retention include students with severe disabilities receiving services under IDEA, English learners with less than two years of English language instruction, and students who have already been retained for a total of two years in early elementary grades (K–2).
9. WVTSS systemic diagnostics: In a balanced WVTSS model, Tier 1 core instruction should successfully support approximately 75 to 80 percent of the student population, leaving 5 to 10 percent requiring Tier 3 intensive supports. A 40 percent Tier 3 load mathematically signals that Tier 1 core instruction is structurally flawed, requiring whole-staff professional development and core curriculum reform rather than additional interventionist hires.
10. SAT alternative pathways: The SAT evaluates credit-deficient students and facilitates non-traditional pathways to keep them on track for graduation. For at-risk students aged 16 to 21, the SAT can transition the student into the Option Pathway, which allows them to earn a diploma by completing a Career and Technical Education (CTE) cluster and a high school equivalency assessment in lieu of standard credit accumulation.

Part 3: Essay-Format Questions

Note: The following essay topics are designed to test deep synthesis and critical analysis of the source material. Answers are not provided.

1. Financial Equity and Accountability: Analyze how an educational diagnostician intersects data from the Public School Support Program (PSSP) seven-step formula, WVEIS Chart of Accounts expenditure flexfields, and ESSA Resource Allocation Reviews (RAR) to detect structural funding inequities between high-performing and low-performing schools within the same county district.
2. Growth Measurement Methodologies: Compare and contrast the Student Growth Percentile (SGP) model used in public dashboards with Value-Added Models (VAM). Critically evaluate the policy risks of utilizing descriptive growth metrics without controlling for socioeconomic status when making high-stakes accountability decisions for high-poverty schools.
3. Early Elementary Legislative Mandates: Discuss the systemic requirements established by the Third Grade Success Act (HB 3035). Evaluate how benchmark screeners, statutory parental notification deadlines, Early Childhood Classroom Assistant Teacher (ECCAT) personnel deployment, and mandatory retention rules interact to form an early literacy and numeracy framework.
4. Multi-Tiered Support Systems and Behavioral Diagnostics: Explain how non-academic metrics—specifically chronic absenteeism and out-of-school suspensions—correlate with academic achievement metrics on the West Virginia Balanced Scorecard. Detail how school leaders should utilize the West Virginia Tiered System of Supports (WVTSS) and the Student Assistance Team (SAT) to address these non-academic barriers.
5. Curriculum Standards and Continuous Strategic Planning: Detail the operational expectations set forth in WVBE Policy 2510 (high school programming and course minute requirements) and Policy 2322 (Standards for Effective Schools). Describe how data extracted from School Learning Environment Surveys feeds into a Comprehensive Needs Assessment (CNA) to form a legally compliant annual strategic improvement plan.

Part 4: Comprehensive Glossary of Key Terms

• Comprehensive Needs Assessment (CNA): A formal, data-driven analytical process conducted by district and school leadership utilizing multi-year longitudinal datasets to identify operational vulnerabilities, subgroup performance gaps, and instructional deficiencies prior to writing strategic plans.
• Comprehensive Support and Improvement (CSI): A federal and state accountability designation assigned to schools performing in the lowest tier across all Balanced Scorecard indicators or high schools with an adjusted cohort graduation rate below 67 percent.
• Early Childhood Classroom Assistant Teacher (ECCAT): Specialized classroom support personnel funded under HB 3035 and deployed in K–3 classrooms to assist with early literacy, numeracy delivery, and targeted student scaffolding.
• ELPA21 Assessment: The English Language Proficiency Assessment for the 21st Century, used to measure English Learner Progress (ELP) across four discrete domains: listening, reading, speaking, and writing.
• Every Student Succeeds Act (ESSA): Federal education legislation mandating state accountability systems, subgroup reporting, and Resource Allocation Reviews (RAR) for low-performing schools.
• Full Academic Year (FAY): A student enrollment status requirement for accountability reporting. A minimum cell size of 20 FAY students is required for a subgroup to be included in public reporting in West Virginia.
• McKinney-Vento Homeless Assistance Act: Federal legislation defining rights and educational protections for students experiencing homelessness; tracked as a specific demographic subgroup under West Virginia accountability protocols.
• On-Track to Graduation Indicator: A high school accountability metric evaluating the percentage of 10th-grade students who have earned at least 12 cumulative credits, including a minimum of two credits in each core content area (ELA, math, science, social studies).
• Option Pathway: An alternative pathway managed by the SAT allowing at-risk students ages 16 to 21 to earn a high school diploma by completing a Career and Technical Education (CTE) concentration and passing a high school equivalency exam.
• Public School Support Program (PSSP): West Virginia’s statutory state aid formula allocating baseline funding to county boards of education across seven foundational steps (educators, service personnel, fixed charges, transportation, current expenses, local share, and instructional improvement).
• Resource Allocation Review (RAR): An ESSA-mandated financial audit conducted in districts with CSI, TSI, or ATSI schools to evaluate whether state, local, and federal funds are equitably distributed relative to student needs.
• Student Assistance Team (SAT): A statutory school-level committee consisting of principals, teachers, and counselors tasked with reviewing at-risk student data, managing 30-day intervention plans, addressing attendance, and facilitating credit recovery.
• Student Growth Percentile (SGP): A descriptive statistical metric that ranks a student's current achievement relative to an academic peer group with identical historical assessment score trajectories; it does not adjust for socioeconomic background.
• Third Grade Success Act (HB 3035): West Virginia legislation passed in 2023 establishing a multi-tiered framework for early literacy and numeracy, including mandatory screening, parental notification, ECCAT deployment, and 3rd-grade retention rules.
• Value-Added Model (VAM): A complex statistical growth model designed to isolate the direct causal contribution of an educator or school on student learning by controlling for prior test scores, measurement errors, and exogenous demographic characteristics.
• WVEIS (West Virginia Education Information System): The centralized state database used to collect student-level demographics, attendance, academic records, and district financial data structured via account flexfields.
• WVTSS (West Virginia Tiered System of Supports): A multi-tiered framework providing universal (Tier 1), targeted (Tier 2), and intensive (Tier 3) instructional, behavioral, and mental health interventions based on continuous student monitoring.
• WVBE Policy 2322: The West Virginia Board of Education policy defining the System of Support and Accountability, establishing seven qualitative Standards for Effective Schools evaluated through annual learning environment surveys.
• WVBE Policy 2510: The West Virginia Board of Education policy establishing programmatic structures, graduation requirements, instructional minute minimums, advanced course offerings (AP/CTE), and SAT operations.
• WVGSA (West Virginia General Summative Assessment): The primary state standardized assessment administered annually to measure student proficiency in English Language Arts (ELA) and Mathematics.
• ZoomWV Data Dashboard: The public and administrative reporting tool used by West Virginia educational diagnosticians to visualize longitudinal school metrics, balanced scorecard indicators, and financial data.

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Demystifying Educational Growth Models: A Novice Analyst's Guide to Student Growth Percentiles (SGP) vs. Value-Added Models (VAM)

1. Introduction: The Imperative of Measuring Student Growth

Evaluating school performance is one of the most vital tasks in modern education, yet it is frequently oversimplified. Traditionally, public reporting has relied on static achievement metrics—such as the percentage of students scoring at or above "proficiency" on year-end state tests like the West Virginia General Summative Assessment (WVGSA). However, relying solely on a single, static snapshot of student performance fails to tell the complete story of a school’s operational and instructional efficacy. Static achievement often reflects the demographic advantages or legacy background of a student body rather than the actual learning facilitated by educators during a given academic year.

To capture true school impact, modern state accountability systems look beyond static scores to measure Academic Progress. Within public reporting systems—such as the West Virginia Balanced Scorecard—academic progress tracks how student performance changes over time. Specifically, state accountability frameworks define progress as the percentage of students who successfully improve their performance by one or more achievement level increments between academic years, or who maintain a top-tier "Exceeds Standard" designation from the prior year.

Static Achievement vs. Academic Growth

• Static Achievement: A snapshot measurement of where students stand academically at one single point in time (e.g., standard proficiency rates on year-end assessments).
• Academic Growth: A dynamic longitudinal measurement showing how student performance changes and progresses across multiple evaluation periods.

As a novice educational analyst, your primary mission is learning to evaluate these growth metrics on public data dashboards without falling into statistical traps. To accurately interpret public data, you must understand the underlying psychometric machinery that powers growth metrics. To accurately measure this growth, statisticians rely on two fundamentally different model architectures.

2. Methodological Architecture: Descriptive (SGP) vs. Causal (VAM) Models

When quantifying longitudinal student growth, educational measurement relies primarily on two statistical paradigms: Student Growth Percentiles (SGP) and Value-Added Models (VAM). While both attempt to track progress over time, their underlying mechanics, mathematical assumptions, and intended applications differ fundamentally.

Student Growth Percentiles (SGP) serve as a descriptive statistical metric. An SGP ranks a student's current assessment score relative to a normative peer cohort (a comparison group of students across the state who demonstrated identical historical score trajectories on prior assessments). Mechanically, SGPs are calculated using quantile regression (a statistical method that estimates conditional percentiles of a response variable across different points of a distribution). SGP simply describes where a student stands in relation to academic peers with similar prior testing histories. Crucially, the SGP model explicitly does not control for exogenous background characteristics, such as socioeconomic status, poverty, or disability status. Because of this design, the creators of the SGP methodology formulated it strictly as a descriptive progress tool and explicitly caution against using unadjusted SGP metrics for high-stakes evaluations, such as determining individual teacher efficacy.

Value-Added Models (VAM), by contrast, are constructed as causal statistical models. VAM attempts to isolate the specific causal impact that a particular school or teacher has on student learning. It achieves this by statistically controlling for exogenous variables outside the educator's control, including student demographics, socioeconomic status, and prior test scores.

Furthermore, VAM incorporates errors-in-variables corrections to adjust for pretest measurement error. In psychometrics, uncorrected pretest scores inevitably harbor classical measurement error, which induces regression to the mean (the statistical phenomenon where extreme initial test scores naturally bounce back toward the population average on subsequent assessments, independent of true learning changes). Without error correction, low-scoring pretests misrepresent a student's baseline capabilities. VAM's errors-in-variables adjustment mathematically lowers the predicted achievement baseline for historically low-scoring students. Consequently, educators who work with low-performing cohorts and help them achieve moderate gains receive a fairer, higher measured contribution under VAM, preventing them from being unfairly penalized by uncorrected measurement error.

The following table summarizes the core structural differences between these two methodologies:

Model Feature	Student Growth Percentiles (SGP)	Value-Added Models (VAM)
Model Classification (Descriptive vs. Causal)	Descriptive: Ranks relative student growth using quantile regression without asserting cause.	Causal: Attempts to isolate and attribute student learning directly to a school or teacher.
Comparison Group Standard	Compares students to a normative peer cohort (students with identical prior score histories).	Compares actual student performance against a statistically predicted score adjusted for multiple variables.
Control for Demographics/Poverty	No: Explicitly omits controls for exogenous variables (e.g., poverty, disability status).	Yes: Statistically controls for socioeconomic status, demographic background, and prior scores.
Handling of Measurement Error	Does not apply errors-in-variables corrections; vulnerable to regression to the mean.	Applies errors-in-variables corrections to adjust pretest scores for measurement error.
Appropriate High-Stakes Usage	Low/Informational: Designed as a descriptive measure; improper for high-stakes educator attribution.	High/Evaluative: Formulated specifically to isolate educator contributions for high-stakes attribution.

Understanding these mechanical differences is critical when analyzing real-world dashboard data containing diverse student demographics.

3. Demographic Interaction and Analytical Bias in State Dashboards

State accountability dashboards (such as the West Virginia Balanced Scorecard, fed by data repositories like ZoomWV and WVEIS) overwhelmingly utilize Student Growth Percentiles or similar descriptive growth indices because they are easier to communicate to the public. However, because SGP does not statistically filter out exogenous factors, using raw descriptive growth metrics creates severe diagnostic risks for the analyst.

When you open a public dashboard like ZoomWV, your first diagnostic action must be verifying subgroup cell sizes. Accountability rules mandate a minimum cell size of twenty Full Academic Year (FAY) students for any demographic subgroup to be statistically valid for public reporting. As an analyst, you must disaggregate performance across key student populations meeting this cell size, including:

• Economically Disadvantaged students
• English Learners (EL)
• IDEA (Students with disabilities receiving services under the Individuals with Disabilities Education Act)
• McKinney-Vento (Students identified under the McKinney-Vento Homeless Assistance Act)

If you evaluate a school using unadjusted descriptive growth scores without overlaying these socio-demographic contexts, your analysis will be severely biased. Schools serving high concentrations of economically disadvantaged or at-risk populations will frequently display artificially deflated growth scores, misrepresenting the true educational gains occurring inside those classrooms. Crucially, evaluating vulnerable cohorts (such as McKinney-Vento or IDEA populations) against unadjusted normative standards can trigger false positive labels for Targeted Support and Improvement (TSI) or Additional Targeted Support and Improvement (ATSI) designations, penalizing schools that are actually delivering substantial value to high-need students.

3 Diagnostic Pitfalls of Uncontextualized Growth Data

1. The Demographic Confounding Pitfall: Treating raw descriptive growth scores (SGP) as pure reflections of school quality without accounting for student poverty or disability concentration, leading to biased evaluations.
2. The Attribution Fallacy: Incorrectly using descriptive growth scores to assign high-stakes cause or blame to teachers, ignoring the fact that SGP was never statistically designed to isolate educator effects.
3. The Subgroup Masking Pitfall: Evaluating a school solely on aggregate growth averages, which conceals critical performance gaps in vulnerable subgroups (e.g., EL or McKinney-Vento cohorts) that meet the 20-FAY student reporting threshold.

Primary Analyst Directive: Always overlay socio-demographic context—specifically tracking economically disadvantaged, English Learner, IDEA, and McKinney-Vento student cohorts—onto raw, descriptive growth metrics. Failing to contextualize descriptive dashboard data will result in artificially deflated evaluations for schools serving highly vulnerable student populations.

These analytical pitfalls directly impact high-stakes school support classifications and administrative designations.

4. Accountability Designations and Diagnostic Application

When growth and achievement metrics are integrated into state accountability frameworks under ESSA and West Virginia Policy 2322, they directly determine administrative school support classifications:

• Comprehensive Support and Improvement (CSI): Assigned to schools scoring in the lowest performance tier (represented by the color red on public dashboards) across all indicators, or high schools failing to graduate at least 67% of their student cohorts.
• Targeted Support and Improvement (TSI) & Additional Targeted Support and Improvement (ATSI): Assigned when specific demographic subgroups within a school consistently perform at a level commensurate with the lowest 5% of Title I schools statewide.

When you identify a school flagged for CSI, TSI, or ATSI status, contextualized growth data prevents wrongful diagnoses. Rather than reflexively assuming a school is instructionally ineffective based on low raw proficiency, you must cross-reference growth metrics with systemic instructional frameworks and financial audits.

Structural Curriculum Diagnosis via WVTSS

When low contextualized growth indicates widespread instructional lagging, inspect the implementation of the West Virginia Tiered System of Supports (WVTSS). A healthy educational framework follows a strict operational distribution:

• Tier 1 (Universal Core Instruction): Expected to successfully support 75–80% of all students.
• Tier 2 (Targeted Intervention): Designed for the 10–20% of students requiring supplemental scaffolding.
• Tier 3 (Intensive Intervention): Reserved for the 5–10% of students needing profound, individualized support.

The Operational Diagnostic Math: If your data analysis reveals that ~40% of a school's student population requires Tier 3 intensive interventions, Tier 1 core instruction is structurally broken. In this scenario, recommending more Tier 3 interventionists is a diagnostic failure; the school cannot remediate its way out of a core instructional collapse. The required administrative intervention must focus on Tier 1 structural curriculum reform, core instructional fidelity, and whole-staff professional development.

Forensic Financial Integration via WVEIS and RAR

To determine whether low growth is driven by instructional failure or resource starvation, conduct a forensic audit using ESSA Resource Allocation Reviews (RAR) integrated with the WVEIS Chart of Accounts. You must navigate the accounting flexfield to inspect spending allocations:

1. Fund Codes: Isolate Fund 11 (General Current Expense) and Fund 61 (Special Revenue).
2. Function Codes: Compare expenditures in Function 1000 (Direct Classroom Instruction) against Function 2000 (Support Services & Administrative Overhead).
3. State Aid Alignment: Trace whether dedicated state funds—specifically PSSP Step 7 (Improvement of Instructional Programs)—are directly reaching classroom instruction.

If your financial analysis reveals that Fund 11/61 expenditures are heavily skewed toward Function 2000 (administrative overhead) while Function 1000 (direct instruction) is starved, low subgroup SGP growth is a symptom of resource maldistribution. RAR findings can then mandate the structural reallocation of funds directly into classroom instruction and core learning supports.

To execute systematic evaluations of educational growth and accountability data, adhere to the following protocol:

The Analyst's Diagnostic Protocol

• Rule 1: Verify Subgroup Cell Sizes: Confirm that student demographic subgroups (economically disadvantaged, EL, IDEA, McKinney-Vento) meet the minimum threshold of 20 FAY students before drawing statistical conclusions.
• Rule 2: Adjust Descriptive Metrics with Context: Never evaluate raw Student Growth Percentiles in isolation; always overlay socio-demographic factors to prevent deflating growth ratings and triggering false-positive TSI/ATSI designations in high-poverty schools.
• Rule 3: Separate Description from Causality: Treat SGP strictly as a descriptive indicator of relative student movement, avoiding high-stakes attribution of teacher effectiveness that requires causal models like VAM with errors-in-variables corrections.
• Rule 4: Align Interventions to Structural Diagnoses: Cross-reference contextualized growth with WVTSS operational math (flagging Tier 1 breakdown if Tier 3 reaches ~40%) and WVEIS financial vectors (Function 1000 vs. 2000 in Funds 11/61 under RAR) to distinguish curriculum delivery failure from administrative underfunding.

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Strategic Improvement Plan: Data-Driven Intervention Framework for West Virginia Public Schools

1. Longitudinal Diagnostic Architecture & Data Query Protocols

To achieve long-term educational reform and eradicate systemic school deficiencies, diagnostic evaluation must move beyond subjective observations and establish empirical, multidimensional frameworks. In West Virginia public education, evaluating a school district’s operational and instructional efficacy requires a calibrated diagnostic architecture that interfaces directly with centralized state data platforms. By simultaneously analyzing financial inputs, student-level outcomes, and curriculum alignment, educational diagnosticians can construct a data-driven model capable of isolating root causes of low performance, promoting educational equity, and directing targeted corrective interventions across all public school demographics.

1.1 Data Repositories and 5-Year Longitudinal Baseline Construction

The operational protocol for constructing the master diagnostic query requires systematically interfacing with three primary state data repositories:

• ZoomWV Data Dashboard: Interfaced to extract state accountability metrics, student growth trajectories, longitudinal subgroup trends, and school-level performance designations.
• West Virginia Education Information System (WVEIS): Queried for detailed student demographic records, course schedules, attendance records, behavioral history, and multi-dimensional financial account flexfields.
• West Virginia Department of Education (WVDE) OpenGov Transparency Platforms: Queried to analyze financial transparency metrics, district-level expenditure trends, and public reporting data.

The diagnostic protocol establishes a mandatory five-year longitudinal analytical window spanning the 2021–2022 through 2025–2026 academic years. A critical distinction must be maintained regarding baseline years within West Virginia's data architecture:

1. Goal-Modeling Baseline (2020–2021): The state established the 2020–2021 academic year as the static benchmark anchor to model long-term proficiency trajectories aimed at cutting the non-proficiency gap in half by the 2035–2036 school year.
2. Operational Data Query Baseline (2021–2022): Because the COVID-19 pandemic severely disrupted assessment administration and resulted in a complete absence of statewide accountability metrics for the 2020–2021 academic year, the operational data query baseline must anchor at the 2021–2022 academic year.

Establishing 2021–2022 as the operational query anchor enables the framework to accurately evaluate post-pandemic growth patterns, multi-year recovery trajectories, and resource allocation efficacy without data gaps.

1.2 Statistical Validity Protocols & Subgroup Disaggregation

To preserve statistical validity and protect student privacy in public reporting, the diagnostic query enforces the state-mandated accountability reporting threshold. Subgroup metrics are evaluated only when the subgroup contains a minimum cell size of twenty (N \ge 20) Full Academic Year (FAY) students. Subgroups failing to meet this threshold are excluded from isolated accountability reporting to prevent statistically invalid inferences and preserve privacy.

To evaluate equity across educational environments, the diagnostic architecture applies a disaggregation protocol isolating the performance, financial resource allocation, and instructional access of the following statutory student populations:

• Economically Disadvantaged Students: Identified through free and reduced-price meal eligibility and community eligibility provisions to assess socio-economic equity.
• English Learners (EL): Isolated to measure language acquisition progress and academic performance under state assessment accommodations.
• Students with Disabilities (IDEA): Evaluated based on specialized instructional services received under Individualized Education Programs (IEP) pursuant to the Individuals with Disabilities Education Act.
• Homeless Students: Identified under the provisions of the McKinney-Vento Homeless Assistance Act to monitor educational stability and targeted resource delivery.

1.3 Cross-Domain Diagnostic Intersections

The core power of this diagnostic architecture lies in its ability to cross-reference data across three analytical domains: financial inputs, student-level outcomes, and curriculum alignment. Intersecting these domains allows diagnosticians to isolate causal variables behind localized underperformance rather than treating symptoms in isolation.

+-------------------------------------------------------------------+
|                   FINANCIAL INPUTS (WVEIS/PSSP)                   |
|  - Instructional Spending (Function 1000)                         |
|  - PSSP Step 7 & Title I Resource Allocations                     |
+---------------------------------+---------------------------------+
                                  |
                                  v
+-------------------------------------------------------------------+
|                    CROSS-DOMAIN INTERSECTION                      |
|  Isolates Causal Variables Behind Localized Underperformance      |
+---------------------------------+---------------------------------+
                                  |
        +-------------------------+-------------------------+
        |                                                   |
        v                                                   v
+-------------------------------+   +-------------------------------+
|    STUDENT-LEVEL OUTCOMES     |   |      CURRICULUM ALIGNMENT     |
|  - 3rd Grade Reading Scores   |   |  - HB 3035 Screener Alignment |
|  - Chronic Absenteeism Rates  |   |  - Tier 1 Core Instructional  |
|  - Behavior & Suspensions     |   |    Delivery Fidelity          |
+-------------------------------+   +-------------------------------+

For example, when the diagnostic query identifies a localized deficiency such as a high failure rate in third-grade reading proficiency, the system cross-references this outcome against:

1. Financial Inputs: Evaluating whether the campus receives adequate PSSP Step 7 instructional enhancement funds or if Function 1000 direct instructional expenditures per pupil fall below state averages.
2. Student Success Indicators: Assessing student engagement by examining chronic absenteeism rates (>10% of enrolled days) and statutory attendance intervention triggers.
3. Curriculum Fidelity: Auditing compliance with statutory early literacy mandates (HB 3035), including benchmark screener administration, 15-day parental notifications, and 30-day intervention plan execution.

If financial resources are sufficient but early literacy screening fidelity is low and chronic absenteeism is elevated, the framework identifies systemic implementation failure rather than resource starvation.

Having established the structural parameters of the longitudinal data architecture, the diagnostician must now apply these query protocols to execute a forensic financial audit of district resource allocation.

2. Forensic Financial Diagnostics & Resource Reallocation Strategy

Forensic financial analysis is essential for establishing operational transparency and ensuring that public funds directly enhance classroom instruction. By evaluating state aid funding formulas, local tax contributions, federal grant structures, and multi-dimensional expenditure accounts, educational diagnosticians can identify structural inequities, administrative inefficiencies, and resource misallocations, thereby realigning financial inputs with student academic needs.

2.1 Public School Support Program (PSSP) Seven-Step Audit

The Public School Support Program (PSSP) serves as West Virginia's foundational state aid funding formula. The diagnostic architecture performs a systematic audit across all seven steps of the PSSP formula to evaluate resource generation and distribution equity from the county level down to individual school sites.

PSSP Step	Funding Objective	Diagnostic Query Focus
Step 1	Allowance for Professional Educators	Analyzes the ratio of state-aid eligible professional educators per 1,000 students in net enrollment, adjusting for county population density tiers (sparse to high-density).
Step 2	Allowance for Service Personnel	Evaluates the allocation of service personnel (aides, custodians, interventionists) based on established enrollment ratios and density tiers.
Step 3	Allowance for Fixed Charges	Tracks the disbursement of employer contributions for social security, unemployment, and workers' compensation.
Step 4	Allowance for Transportation	Assesses transportation operating expenses, cross-referencing costs with school-level attendance rates and geographical sparsity.
Step 5	Current Expenses	Calculates operational and maintenance funding utilizing a statutory formula based on total square footage and net enrollment.
Step 6	Local Share	Computes the equalized local tax effort required to supplement state aid, identifying disparities in local revenue generation capacity.
Step 7	Improvement of Instructional Programs	Isolates funds explicitly dedicated to the enhancement of instructional delivery, professional development, and curriculum fidelity.

Modernized PSSP frameworks incorporate weighted funding structures designed to allocate resources based on service intensity and demographic challenges:

• Special Education Weights: Funding operates on a service-intensity model, assigning weights of 0.50 for Level I (mild/moderate), 1.00 for Level II (intermediate), 2.00 for Level III (intensive support), and 0.05 for Gifted education, shifting away from flat disability categories.
• Poverty Multipliers: Resource allocations incorporate cumulative multipliers based on campus poverty concentrations. Specific funding adjustments apply when school poverty levels exceed thresholds of 40 percent, 60 percent, and 75 percent, ensuring higher concentrations of compensatory funding reach high-poverty environments.

2.2 WVEIS Chart of Accounts Flexfield Expenditure Tracking

Micro-level financial diagnostics rely on parsing multi-dimensional accounting flexfields within the WVEIS Chart of Accounts. The diagnostic system parses explicit accounting dimensions to trace every dollar to its operational destination:

+-----------------------------------------------------------------------+
|                 WVEIS ACCOUNTING FLEXFIELD STRUCTURE                  |
|  [Fund] - [Project] - [Function] - [Object] - [Location/Organization] |
|   (2 Dig)   (5 Dig)     (4 Dig)    (3 Dig)            (3 Dig)         |
+-----------------------------------------------------------------------+
                                    |
          +-------------------------+-------------------------+
          |                         |                         |
          v                         v                         v
  [Fund Code: 11]           [Project Code: 00000]     [Function Code: 01100]
  General Expense           Unrestricted Revenue      Direct Classroom Instruction

• Concrete Accounting String Example: 11-00000-01100-111-001
  • Fund Code 11 (2 Digits): Identifies General Current Expense funds (contrasted against Fund 61 Special Revenue and Fund 7X Federal Stimulus/Stabilization).
  • Project Code 00000 (5 Digits): Denotes unrestricted operational revenues (contrasted against restricted state/federal grant codes).
  • Function Code 01100 / 1000 Series (4 Digits): Specifies direct classroom instructional activities.
  • Object Code 111 (3 Digits): Specifies professional regular teacher salaries.
  • Location Code 001 (3 Digits): Isolates the specific school site destination.

The diagnostic prompt isolates direct classroom instructional costs (Function 1000 series, e.g., Function 01100) and contrasts them against support services and administrative overhead (Function 2000 series, such as General Administration or School Administration).

To conduct an operational general ledger audit, the diagnostician extracts line-item expenditures across Functions 1000 and 2000. By calculating the ratio of Function 1000 expenditures to total operating expenditures, the diagnostician determines the precise percentage of per-pupil funding entering the classroom. Local per-pupil expenditure rates are tracked over the five-year longitudinal period and compared against the state average, highlighting campuses experiencing administrative bloat or structural underfunding.

2.3 ESSA Resource Allocation Reviews (RAR) & Structural Equity Mandates

Under the Every Student Succeeds Act (ESSA), school districts maintaining campuses designated for Comprehensive Support and Improvement (CSI), Targeted Support and Improvement (TSI), or Additional Targeted Support and Improvement (ATSI) must execute formal Resource Allocation Reviews (RAR).

The diagnostic query automates RAR protocols by analyzing cross-domain anomalies—specifically highlighting spending discrepancies where a school maintains per-pupil spending levels significantly above the district average yet consistently performs in the lowest state accountability tier. Such anomalies indicate severe operational inefficiency or a misalignment of instructional materials and staffing.

To resolve these disparities, the diagnostician applies a mandatory resource reallocation matrix:

Designated Support Status	Identified Spending Anomaly	Mandatory Resource Reallocation Directive
CSI Campus	Excessive Function 2000 Non-Instructional Overhead paired with low 3rd-grade reading proficiency.	Reallocate 15–20% of unrestricted Function 2000 funds directly into Function 1000 to hire state-certified reading interventionists and fund evidence-based core materials.
ATSI Campus	Subgroup underperformance (e.g., SWD) with low Step 7 instructional enhancement spending.	Divert PSSP Step 7 and Title I funds directly into specialized Tier 2/3 co-teaching models and evidence-based math/ELA intervention software.
TSI Campus	Disparate per-pupil allocation compared to high-performing district campuses.	Rebalance general fund baseline staffing ratios to guarantee equitable teacher-to-student ratios and dedicated paraprofessional support.

With financial resource flows rigorously audited and aligned to classroom needs, the diagnostic protocol shifts to evaluating student-level accountability metrics, growth analytics, and behavioral health indicators.

3. Student-Level Accountability, Growth Analytics, and Behavioral Diagnostics

Student outcome measurement under the West Virginia Accountability System (WVAS) provides the empirical basis for assessing school performance and targeting academic and behavioral interventions. Visualized publicly through the West Virginia Schools Balanced Scorecard, this system measures academic achievement, longitudinal growth, language proficiency, and student engagement indicators.

3.1 West Virginia Balanced Scorecard Metric Evaluation

The Balanced Scorecard evaluates school performance across four standardized performance tiers. Point values are assigned based on student achievement on the West Virginia General Summative Assessment (WVGSA) and West Virginia Alternate Summative Assessment (WVASA).

Performance Designation	WVGSA Point Range	WVASA Counterpart Level	Expectation Definition
Exceeds Standard	100 to 125 Points (80%+)	Advanced	Distinctive performance exceeding state expectations.
Meets Standard	81.25 to 100 Points (65–80%)	At Target	Performance falls within expected state range.
Partially Meets Standard	62.5 to 81.25 Points (50–65%)	Approaching Target	Approaching expected range of performance.
Does Not Meet Standard	Below 62.5 Points	Below Target	Unacceptably below expected level of performance.

Following COVID-19 pandemic disruptions, West Virginia reset its long-term accountability trajectory using the 2020–2021 academic year as the static benchmark baseline. The state established an explicit trajectory target: to reduce the gap between baseline proficiency levels and 100 percent proficiency by half by the 2035–2036 school year. The diagnostic engine evaluates five-year trajectory curves for ELA and Mathematics to determine if a school is maintaining the annual growth velocity required to hit its 2035–2036 milestone.

For the English Learner demographic, the framework monitors English Learner Progress (ELP) using the ELPA21 assessment across four language domains:

1. Listening
2. Reading
3. Speaking
4. Writing

To demonstrate overall proficiency, an English Learner must achieve a performance level of Level 4 (Early Advanced) or Level 5 (Advanced) in all four assessment domains. The diagnostic prompt tracks the percentage of the EL cohort meeting these criteria annually.

3.2 Methodological Critique: Student Growth Percentiles (SGP) vs. Value-Added Models (VAM)

Evaluating longitudinal student progress requires a clear understanding of the statistical models underlying growth metrics:

+-----------------------------------------------------------------------------------+
|                            VALUE-ADDED MODELS (VAM)                               |
| - Isolates teacher/school causal impact.                                          |
| - Controls for demographic factors (poverty, disability, prior scores).           |
| - Employs errors-in-variables corrections for measurement error in pretests.      |
+-----------------------------------------------------------------------------------+
                                        vs
+-----------------------------------------------------------------------------------+
|                        STUDENT GROWTH PERCENTILES (SGP)                           |
| - Descriptive ranking relative to academic peers with identical score histories.   |
| - Unadjusted for exogenous socioeconomic or background factors.                    |
| - Risk: Deflates ratings for high-poverty schools if uncontextualized.             |
+-----------------------------------------------------------------------------------+

• Value-Added Models (VAM): VAM methodologies seek to isolate the specific causal impact of an educator or school on student learning. VAM controls for exogenous variables, including socioeconomic status, demographic background, and prior test histories. By applying errors-in-variables corrections to address measurement error in pretests, VAM lowers predicted achievement thresholds for historically low-scoring students, thereby measuring the true added value contributed by educators.
• Student Growth Percentiles (SGP): The SGP model—which heavily informs state accountability dashboards—is a purely descriptive metric. SGP ranks a student’s current score relative to an academic peer group displaying identical historical test trajectories. SGP explicitly does not control for background characteristics such as poverty or disability status.

Analytical Risk & Explicit Contextualization Method: Using raw SGP data without overlaying socio-demographic context creates significant diagnostic error. To prevent artificially deflating performance evaluations for schools serving high concentrations of at-risk students, diagnosticians must execute a multivariable regression residual adjustment. Diagnosticians model expected SGP as a function of demographic variables:

SGP_{i} = \beta_0 + \beta_1 (\text{PovertyRate}_i) + \beta_2 (\text{SWDRate}_i) + \beta_3 (\text{ELRate}_i) + \epsilon_i

By extracting and analyzing the standardized residual (\epsilon_i), the diagnostician isolates relative academic growth performance independent of background characteristics, providing an un-biased evaluation of school-level value added.

3.3 Behavioral Diagnostics & Student Success Indicators

Academic outcome evaluation is integrated with non-academic indicators of student engagement and behavioral health across grade spans:

• Elementary and Middle School Indicators:
  • Chronic Absenteeism: Defined as the percentage of students absent for more than 10 percent of enrolled instructional days. State statutory triggers mandate immediate interventions when unexcused absences occur or total absences exceed 10 days without formal physician documentation.
  • Behavior Indicator: Tracks the percentage of enrolled students maintaining zero out-of-school suspensions across the academic year.
• High School Indicators:
  • On-Track to Graduation: Tracks the percentage of 10th-grade students who have earned at least 12 cumulative credits across 9th and 10th grade, including a minimum of 2 credits in each of the four core content areas: ELA, mathematics, science, and social studies.
  • Adjusted Cohort Graduation Rates: Evaluates both 4-year and 5-year adjusted cohort graduation rates against the state standard, which requires a graduation rate of 90 percent to 95 percent to achieve a "Meets Standard" designation.

3.4 Diagnostic Support Identification (CSI, TSI, ATSI)

By analyzing five-year longitudinal trends, the diagnostic framework automatically flags schools for state-mandated accountability designations:

• Comprehensive Support and Improvement (CSI): Assigned to schools performing in the lowest performance tier overall (represented as red on the Balanced Scorecard) across all indicators, or high schools exhibiting a 4-year cohort graduation rate below 67 percent.
• Targeted Support and Improvement (TSI) & Additional Targeted Support and Improvement (ATSI): Assigned to schools where specific demographic subgroups consistently underperform at a level equivalent to the lowest 5 percent of Title I schools statewide.

Evaluating student outcome metrics and growth trajectories establishes the empirical evidence needed to audit classroom instructional delivery, curriculum fidelity, and statutory policy compliance.

4. Curriculum Fidelity & Statutory Legislative Mandates

Ensuring high levels of academic achievement requires structural compliance with state board policies and early childhood literacy legislation. Educational diagnosticians audit school master schedules, early learning interventions, and institutional practices to verify that instructional delivery aligns with state rigor standards and legislative mandates.

4.1 WVBE Policy 2510 Compliance Audit (High School Programming & Rigor)

WVBE Policy 2510 establishes the operational parameters for high school programming, graduation standards, and instructional time.

       GRADUATION CREDIT REQUIREMENT TIMELINE (WVBE Policy 2510)
       
       Historical Baseline:     [ 22 Total Credits ]
                                        |
       2024–2025 Cohort:        [ 23 Total Credits ] (+1 Personal Finance)
                                        |
       2027–2028 Cohort:        [ 24 Total Credits ] (+1 Computer Science)

The diagnostic framework monitors compliance across three core areas:

• Credit Requirement Trajectory: Audit thresholds adjust based on student cohort year. While historical cohorts required 22 credits, the 2024–2025 freshman cohort requires 23 credits due to the mandatory addition of Personal Finance. The 2027–2028 freshman cohort will require 24 credits, incorporating a mandatory credit in Computer Science.
• Instructional Time and Schedule Audits: Course schedules must provide sufficient time to achieve content mastery. If a high school delivers courses shorter than 8,100 instructional minutes and fails to meet state proficiency standards for two consecutive years, the diagnostic system flags the school for a mandatory schedule review by the County Board of Education.
• Advanced Programmatic Access & CTE Enrollment Tiers: High schools must provide equitable access to advanced coursework, offering at least 4 Advanced Placement (AP) courses annually across all four core academic areas. Career and Technical Education (CTE) cluster offerings are audited based on student enrollment tiers:
  • Small High Schools (<400 students): Must offer at least 3 CTE clusters.
  • Mid-Sized High Schools (400–800 students): Policy expectations mandate scaled programming offering at least 4 CTE clusters.
  • Large High Schools (>800 students): Must offer a minimum of 5 CTE clusters.

4.2 Early Literacy and Numeracy Framework (HB 3035 Third Grade Success Act)

At the elementary level, the diagnostic framework monitors compliance with House Bill 3035 (the Third Grade Success Act), which establishes multi-tiered supports for early literacy and numeracy in grades K–3.

+-----------------------------------------------------------------------------------+
|               THIRD GRADE SUCCESS ACT (HB 3035) COMPLIANCE TIMELINE               |
+-----------------------------------------------------------------------------------+
|  [Day 0]   Diagnostic Screening identifies benchmark deficiency in K-3.            |
|     |                                                                             |
|  [Day 15]  Mandatory Statutory Written Parental Notification issued.               |
|     |                                                                             |
|  [Day 30]  Individualized Reading or Mathematics Improvement Plan established.    |
|     |                                                                             |
|  [2026-27] Mandatory 3rd-Grade Retention implemented for non-proficient students   |
|            (Unless Good Cause Exemption applies).                                 |
+-----------------------------------------------------------------------------------+

The audit protocol evaluates five key components of HB 3035 implementation:

1. Screening Benchmark Fidelity: Auditing the administration of approved diagnostic screeners to detect early deficiencies in reading, mathematics, dyslexia, and dyscalculia against state cut scores.
2. Statutory Parental Notification: Enforcing the legal requirement that parents or guardians receive written notification within 15 days of an identified literacy or numeracy deficiency.
3. Individualized Improvement Plans: Verifying that an individualized reading or mathematics improvement plan is formally established within 30 days of deficiency identification.
4. Personnel Deployment: Tracking the allocation of state-funded Early Childhood Classroom Assistant Teachers (ECCATs) and interventionists in K–3 classrooms to ensure staffing reaches schools with the highest concentration of reading and math deficiencies.
5. Retention Projections & Good Cause Exemptions: Beginning in the 2026–2027 school year, students failing to demonstrate 3rd-grade proficiency on the ELA or Math WVGSA face mandatory retention. The diagnostic system calculates projected retention numbers while filtering for statutory Good Cause Exemptions:
   • Students with severe cognitive disabilities.
   • English Learners with less than 2 years of language instruction.
   • Students who have previously been retained for a cumulative total of 2 years in early elementary grades.

4.3 Policy 2322 Effective School Standards Integration

Qualitative instructional efficacy is evaluated against the seven standards for effective schools set forth in WVBE Policy 2322. These standards are operationalized by extracting feedback from the annual West Virginia School Learning Environment Surveys administered to students, school personnel, and parents:

1. Positive Climate and Cohesive Culture: Assesses shared beliefs, high academic expectations, safety, and respect for diversity.
2. School Leadership: Evaluates instructional leadership, implementation of high-yield teaching practices, and student leadership opportunities.
3. Standards-Focused Curriculum and Instruction: Measures the alignment of classroom instruction with state standards and the efficient use of instructional time.
4. Student Support Services: Evaluates the integration of health, counseling, nutrition, special education, and English learner programs.
5. Educator Growth and Development: Assesses the frequency and quality of teacher collaboration within high-functioning professional learning teams.
6. Efficient and Effective Management: Measures operational integrity, resource allocation, facility maintenance, and technology integration.
7. Continuous Improvement: Evaluates institutional commitment to analyzing data and executing strategic revisions to raise student performance.

Having audited curriculum fidelity and statutory mandates, the diagnostician synthesizes these findings to construct an actionable, strategic operational reform blueprint.

5. Strategic Corrective Interventions & Operational Reform Blueprint

Translating diagnostic findings into systemic reform requires a structured framework that aligns campus-level practices with statewide support systems. By integrating diagnostic data into multi-tiered support models, Student Assistance Team structures, and comprehensive strategic planning, school leaders can address operational vulnerabilities and improve outcomes for all students.

5.1 West Virginia Tiered System of Supports (WVTSS) Optimization

When diagnostic outputs indicate widespread academic or behavioral deficiencies, districts must optimize their implementation of the West Virginia Tiered System of Supports (WVTSS). This framework organizes academic, behavioral, and mental health interventions across three tiers of increasing intensity.

WVTSS Tier Level	Academic Interventions	Behavioral & Mental Health Interventions	Target Population & Expected Efficacy
Tier 1 (Universal)	High-quality, standards-based core instruction; differentiated learning plans.	School-wide Positive Behavior Interventions and Supports (PBIS); universal mental health screening.	Administered to 100% of students. A healthy system achieves ~75–80% success through Tier 1 alone.
Tier 2 (Targeted)	Small-group instruction; targeted literacy/math skill-building pull-out sessions.	Restorative circles; check-in/check-out behavioral tracking; targeted group counseling.	Designed for the ~10–20% of students requiring supplemental scaffolding to access core curriculum.
Tier 3 (Intensive)	Individualized high-intensity instruction; formal special education evaluation referrals.	Crisis intervention protocols; community wraparound services; individualized Behavior Intervention Plans (BIP).	Reserved for the ~5–10% of students exhibiting severe, persistent learning or behavioral needs.

Step-by-Step Pyramid Diagnostic Protocol: Diagnostic data must be validated against the mathematical structure of the WVTSS pyramid. If diagnostic outputs show that more than 20 percent of a school's population requires Tier 3 intensive reading interventions, leadership must diagnose structural failure in Tier 1 core instruction. In such instances, leadership must execute the following administrative protocol rather than inflating Tier 3 intervention staff:

+-------------------------------------------------------------------+
|             WVTSS TIER 1 CORE REFORM OPERATIONAL STEP             |
+-------------------------------------------------------------------+
| [Phase 1: Day 1-15] Core Curriculum Alignment Audit               |
| Conduct formal fidelity audits of Tier 1 instructional materials  |
| against state academic standards using approved audit rubrics.    |
+---------------------------------+---------------------------------+
                                  |
                                  v
+-------------------------------------------------------------------+
| [Phase 2: Day 16-45] Whole-Staff Instructional Coaching Cycles   |
| Reallocate instructional coaches for mandatory 8-week coaching    |
| blocks focused on explicit direct instruction and differentiation.|
+---------------------------------+---------------------------------+
                                  |
                                  v
+-------------------------------------------------------------------+
| [Phase 3: Day 46-60] Formative Re-Assessment & Benchmark Review   |
| Administer mid-cycle benchmark screeners to measure Tier 1 growth |
| velocity and re-calibrate classroom instruction.                  |
+-------------------------------------------------------------------+

       THE WVTSS VALIDATION PROTOCOL MATRIX
       
       [ Standard WVTSS Pyramid ]             [ Structural Core Deficit ]
             /   5-10%   \                       /   > 20%   \  <-- Excessive Tier 3 Demand
            /-------------\                     /-------------\
           /    10-20%     \                   /    Tier 2     \
          /-----------------\                 /-----------------\
         /      75-80%       \               /      Tier 1       \ <-- Target For Whole-Staff
        /  (Core Instruction) \             /  (Flawed Tier 1)    \    Curriculum Reform
       +-----------------------+           +-----------------------+

5.2 Student Assistance Team (SAT) Operational Protocols

At the individual student level, intervention design and progress monitoring are managed through the Student Assistance Team (SAT), mandated by Policy 2510. Composed of school administrators, regular and special education teachers, and support personnel, the SAT executes key operational duties:

• HB 3035 Intervention Compliance: Enforces the mandatory 30-day timeline for establishing and implementing individualized reading and math improvement plans following screener deficiencies.
• Attendance Crisis Review: Reviews attendance records when unexcused absences occur or total absences exceed 10 days. The SAT coordinates with county attendance directors and community service agencies to resolve underlying causes of chronic absenteeism.
• Credit Recovery & Option Pathway Interventions: For credit-deficient high school students aged 16 to 21, the SAT evaluates placement into alternative completion tracks. This includes directing off-track students into credit recovery programs or the Option Pathway, which allows at-risk youth to remain enrolled, complete a CTE pathway, and pass a high school equivalency assessment in lieu of traditional credit accumulation.

5.3 Comprehensive Needs Assessment (CNA) & District Strategic Planning

The synthesis of financial, academic, and statutory diagnostics culminates in the annual strategic improvement plan mandated by Policy 2322 and West Virginia Code. Leadership teams utilize a Comprehensive Needs Assessment (CNA) to translate longitudinal data into operational directives.

+-----------------------------------------------------------------------------------+
|               COMPREHENSIVE NEEDS ASSESSMENT (CNA) STRATEGIC FLOW                 |
+-----------------------------------------------------------------------------------+
|  [Step 1: CNA Data Synthesis] Multi-year data from ZoomWV, WVEIS, & RAR integrated|
|                                                                                   |
|  [Step 2: Subgroup Gap Goals] Target goals aligned with 2035-2036 trajectory.     |
|                                                                                   |
|  [Step 3: Resource Direction] Direct PSSP Step 7 and Title I funds to evidence.   |
|                                                                                   |
|  [Step 4: Monitoring Protocol] Continuous walkthroughs and formative assessments  |
|                                ensure execution fidelity.                        |
+-----------------------------------------------------------------------------------+

The resulting strategic plan incorporates four critical components:

1. Targeted Subgroup Gap Goals: Setting measurable annual goals designed to close achievement gaps for marginalized demographics, aligning campus growth curves with the state's 2035–2036 target.
2. Evidence-Based Resource Deployment: Directing federal Title I funds and state PSSP Step 7 instructional improvement allocations strictly toward validated core instructional programs and targeted interventions.
3. Action-Step Execution: Defining operational steps, such as updating master schedules to meet Policy 2510 credit and CTE requirements, deploying instructional coaches, and training personnel on WVTSS protocols.
4. Fidelity Monitoring Infrastructure: Establishing continuous monitoring mechanisms—including structured classroom walkthroughs and periodic formative assessments—to verify that interventions are implemented with fidelity.

By uniting forensic financial auditing, rigorous outcome tracking, and strict statutory adherence into a cohesive strategy, educational leaders establish a transparent, sustainable framework capable of delivering an equitable education to all West Virginia students.

-----------------------------------------------------------------------------------------------------

Demystifying West Virginia K-12 Education: A Conceptual Guide to School Funding, Performance Evaluation, and Student Support Systems

1. Introduction: The Architecture of West Virginia Educational Diagnostics

Evaluating public school performance requires moving beyond isolated classroom observations toward a systemic, multi-dimensional diagnostic framework. In West Virginia, educational diagnosticians assess institutional efficacy by analyzing three interconnected pillars: Financial Inputs, Student Outcomes, and Curriculum Alignment. Together, these three analytical domains form a diagnostic triad that enables researchers, policymakers, and school leaders to trace how public resources directly translate into classroom instruction and long-term academic achievement.

       +-------------------------------------------------------+
       |             EDUCATIONAL DIAGNOSTIC TRIAD              |
       +-------------------------------------------------------+
       |                                                       |
       |  1. FINANCIAL INPUTS                                  |
       |     (PSSP Aid, WVEIS Flexfields, Resource Equity)     |
       |                           │                           |
       |                           ▼                           |
       |  2. STUDENT OUTCOMES ◄────────► 3. CURRICULUM FIDELITY|
       |     (Balanced Scorecard,       (Policy 2510, HB 3035 /|
       |      Growth, Absenteeism)       W.Va. Code §18-2E-10) |
       +-------------------------------------------------------+

To execute these evaluations, diagnosticians construct queries across the state's primary educational data repositories:

• WVEIS (West Virginia Education Information System): The administrative backbone tracking granular student records, enrollment codes, and multi-dimensional expenditure accounts.
• ZoomWV Data Dashboard: The public-facing transparency interface displaying school accountability metrics, growth trajectories, and subgroup outcomes.
• WVDE OpenGov: The statewide financial transparency platform designed to facilitate school- and district-level budget comparisons and fiscal audits.

To capture meaningful longitudinal trends while accounting for major systemic disruptions, evaluations utilize a five-year longitudinal window spanning the 2021–2022 through 2025–2026 academic years. The 2021–2022 school year serves as the baseline because the COVID-19 pandemic severely disrupted statewide assessment administration, resulting in a complete absence of state accountability metrics for the 2020–2021 academic year.

Rigorous statistical analysis requires strict adherence to West Virginia’s subgroup disaggregation protocol. To protect student privacy and ensure data integrity, state reporting mandates a minimum cell size of 20 Full Academic Year (FAY) students (N \ge 20). If a demographic subgroup contains fewer than 20 FAY students at a given school site, its performance data is suppressed in public reporting to prevent statistical distortion. To guarantee educational equity, evaluations systematically track four historically marginalized student populations:

1. Economically Disadvantaged Students
2. English Learners (EL)
3. Students with Disabilities receiving special education services under the Individuals with Disabilities Education Act (IDEA)
4. Homeless Students identified under the McKinney-Vento Homeless Assistance Act

The Core Diagnostic Objective: By intersecting financial allocations, standardized outcome metrics, and statutory instructional policies, educational diagnosticians isolate the root causes of learning deficiencies. For instance, a targeted query can determine whether a localized drop in third-grade reading proficiency stems from inadequate direct instructional spending, severe chronic absenteeism, or systemic non-compliance with statutory early literacy mandates.

Understanding this diagnostic triad provides the essential analytical foundation for examining the starting point of public education: how public funds are generated, structured, and allocated across West Virginia’s fifty-five county school districts.

2. Decoding School Funding: Resource Allocation and Financial Equity

Public school finance in West Virginia requires a forensic examination of how state foundation aid, local tax revenues, and federal grants flow into county school districts and individual school sites. The financial diagnostic evaluates whether funding mechanisms distribute resources equitably and whether spent dollars directly reach the classroom.

2.1 The Public School Support Program (PSSP) State Aid Formula

The Public School Support Program (PSSP) is West Virginia’s statutory funding formula used to compute and distribute state baseline aid to county boards of education. The formula is structured around seven foundational steps:

PSSP Step	Funding Objective	Diagnostic Focus
Step 1	Allowance for Professional Educators	Analyzes the ratio of state-aid eligible professional educators per 1,000 students in net enrollment, adjusting for county population density tiers (sparse to high-density).
Step 2	Allowance for Service Personnel	Evaluates the allocation of service personnel (e.g., aides, custodians, bus operators) based on net enrollment ratios and geographic density tiers.
Step 3	Allowance for Fixed Charges	Tracks state funding for mandatory employer contributions including social security, unemployment, and workers' compensation.
Step 4	Allowance for Transportation	Assesses transportation operating expenses, which diagnosticians cross-reference against school attendance rates and geographic sparsity factors.
Step 5	Current Expenses	Calculates baseline facility operational and maintenance funding using a statutory formula derived from school square footage and net student enrollment.
Step 6	Local Share	Computes the equalized local property tax revenue subtracted from total PSSP costs to determine final state aid, identifying local revenue generation capacity.
Step 7	Improvement of Instructional Programs	Isolates funds explicitly dedicated to teacher professional development, curriculum enhancement, and instructional delivery.

Modern legislative revisions have integrated weighted funding models into the PSSP to direct enhanced resources toward high-need student populations:

• Special Education Weights: Funding has shifted from rigid disability classifications to a service-intensity model:
  • Level I (Low Intensity): 0.50 multiplier
  • Level II (Moderate Intensity): 1.00 multiplier
  • Level III (High Intensity): 2.00 multiplier
  • Gifted Education: 0.05 multiplier
• Poverty Weights: Applied as cumulative funding multipliers when a school's concentration of low-income students crosses specific statutory thresholds: 40%, 60%, and 75%.

These weights allow diagnosticians to verify whether compensatory state aid effectively reaches the campuses bearing the highest instructional challenges.

2.2 Micro-Expenditure Tracking via WVEIS Chart of Accounts

To evaluate spending efficiency at the school building level, diagnosticians analyze expenditure data extracted from the multi-dimensional WVEIS Chart of Accounts. The account flexfield structure categorizes every transaction across several financial dimensions:

• Fund Codes (2 Digits): Identifies the funding stream source:
  • Fund 11: General Current Expense Funds (state and local revenues).
  • Fund 61: Special Revenue Funds (restricted state grants and targeted funding).
  • Fund 7X: Federal Stimulus, Stabilization, and Special Revenue Funds.
• Project Codes (5 Digits): Distinguishes unrestricted general operating initiatives from restricted federal Title grants or state-mandated projects.
• Function Codes (4 Digits): Defines the specific operational purpose of an expenditure:
  • Function 1000 (Direct Instruction): Direct classroom teaching, teacher salaries, instructional supplies, and educational software.
  • Function 2000 (Support Services): School and district administration, building maintenance, guidance services, and facilities operation.

By isolating Function 1000 expenditures from Function 2000 overhead, diagnosticians calculate the exact percentage of per-pupil spending that directly supports classroom learning, highlighting campuses experiencing administrative bloat or severe instructional under-resourcing.

2.3 ESSA Resource Allocation Reviews (RAR) and Expenditure Auditing

Under the Every Student Succeeds Act (ESSA), districts with schools identified for Comprehensive Support and Improvement (CSI), Targeted Support and Improvement (TSI), or Additional Targeted Support and Improvement (ATSI) must undergo mandatory Resource Allocation Reviews (RAR).

The diagnostic value of an RAR lies in identifying fiscal anomalies—such as a school spending significantly more per pupil than the district average while remaining in the lowest state academic performance tier. To audit these anomalies, diagnosticians execute a concrete flexfield audit:

  ┌─────────────────────────────────────────────────────────────┐
  │ 1. EXTRACT TOTAL EXPENDITURES BY CAMPUS                     │
  │    Aggregate Fund 11, Fund 61, and Fund 7X accounts.        │
  └──────────────────────────────┬──────────────────────────────┘
                                 │
                                 ▼
  ┌─────────────────────────────────────────────────────────────┐
  │ 2. ISOLATE FUNCTION CODES                                   │
  │    Divide Function 1000 (Instruction) by Function 2000      │
  │    (Support Services/Admin).                                │
  └──────────────────────────────┬──────────────────────────────┘
                                 │
                                 ▼
  ┌─────────────────────────────────────────────────────────────┐
  │ 3. CROSS-EXAMINE PROJECT CODES                              │
  │    Trace federal (e.g., Title I) and PSSP Step 7 allocations│
  │    to determine if restricted dollars reach the classroom.  │
  └──────────────────────────────┬──────────────────────────────┘
                                 │
                                 ▼
  ┌─────────────────────────────────────────────────────────────┐
  │ 4. CORRELATE WITH ACADEMIC OUTCOMES                         │
  │    Identify spending imbalances where low Function 1000     │
  │    ratios match chronic underperformance.                   │
  └──────────────────────────────┘

When an audit reveals high overall per-pupil spending paired with low Function 1000 proportions, diagnosticians recommend reallocating unrestricted general funds toward baseline instructional staffing, evidence-based reading interventions, and direct classroom materials.

Evaluating financial allocations provides necessary insight into systemic inputs, but determining overall school performance requires assessing academic and behavioral student outcomes.

3. Measuring Performance: Accountability, Growth Analytics, and Support Designations

West Virginia tracks and reports public school performance through the West Virginia Accountability System (WVAS), which is publicly displayed on the West Virginia Schools Balanced Scorecard.

3.1 The West Virginia Balanced Scorecard Metrics

The Balanced Scorecard evaluates student academic performance across four standardized performance tiers:

Performance Level Designation	WVGSA Point Value Range	WVASA Counterpart Level	Expectation Definition
Exceeds Standard	100 to 125 Points (80%+)	Advanced	Distinctive performance exceeding state expectations.
Meets Standard	81.25 to 100 Points (65–80%)	At Target	Performance falls within the expected state range.
Partially Meets Standard	62.5 to 81.25 Points (50–65%)	Approaching Target	Approaching the expected range of performance.
Does Not Meet Standard	Below 62.5 Points	Below Target	Unacceptably below the expected level of performance.

Long-Term Achievement Goals

Academic Achievement measures the percentage of FAY students scoring proficient or higher on the West Virginia General Summative Assessment (WVGSA) in English Language Arts (ELA) and Mathematics. Historically, baseline targets were established in the 2016–2017 academic year. However, post-pandemic disruptions necessitated a structural reset. Using the 2020–2021 academic year as the reset baseline, West Virginia established a long-term goal to cut the proficiency gap between the baseline rate and 100% proficiency in half by the 2035–2036 school year. Diagnosticians calculate five-year trajectory slopes to verify if a school is meeting its required annual benchmark increments.

English Learner Progress (ELP)

The ELP metric tracks the progress of English learners in attaining English language proficiency across four domains—listening, reading, speaking, and writing—measured by the ELPA21 assessment. Full proficiency requires achieving a Level 4 (Early Advanced) or Level 5 (Advanced) across all four tested domains.

Student Success Indicators

The Balanced Scorecard incorporates key non-academic measures to assess school culture and student engagement:

• Elementary & Middle School Level:
  • Chronic Absenteeism: The percentage of enrolled students missing more than 10% of total instructional days.
  • Behavior Indicator: The percentage of students maintaining zero out-of-school suspensions across the academic year.
• High School Level:
  • On-Track to Graduation: The percentage of 10th-grade students earning at least 12 cumulative credits across 9th and 10th grade, including a minimum of 2 credits in each core content area (ELA, mathematics, science, and social studies).
  • Graduation Rates: Tracks 4-year and 5-year adjusted cohort graduation rates (state standard target: 90% to 95% to achieve "Meets Standard").

3.2 Student Growth: SGP vs. VAM Analytical Framework

Diagnosing longitudinal academic progress requires an understanding of the statistical models used to evaluate student growth:

                      GROWTH MODEL COMPARISON
┌──────────────────────────────────────┬──────────────────────────────────────┐
│     STUDENT GROWTH PERCENTILES       │         VALUE-ADDED MODELS           │
│                (SGP)                 │                (VAM)                 │
├──────────────────────────────────────┼──────────────────────────────────────┤
│ • Descriptive Metric                 │ • Causal / Explanatory Model         │
│ • Ranks student against historical   │ • Isolates specific school/teacher   │
│   academic peers                     │   contributions                      │
│ • DOES NOT adjust for poverty,       │ • Adjusts for socioeconomic status   │
│   disability, or background          │   & pretest measurement error        │
└──────────────────────────────────────┴──────────────────────────────────────┘

• Student Growth Percentiles (SGP): A descriptive metric utilized on West Virginia’s public dashboards. SGP ranks a student’s current test score against an academic peer group displaying identical historical testing trajectories. However, SGP does not adjust for exogenous background factors such as socioeconomic status, household income, or disability status.
• Value-Added Models (VAM): A causal/explanatory statistical model. VAM attempts to isolate the specific contribution of a school or teacher to student learning by controlling for student demographic background and prior test scores. Crucially, VAM incorporates errors-in-variables corrections to account for measurement error in pretests. Because uncorrected pretest measurement error tends to understate baseline capabilities for historically low-scoring students, VAM's error correction prevents the systematic underestimation of growth achieved by educators serving high-poverty student populations.

Crucial Diagnostic Insight: Because West Virginia’s public accountability dashboard relies primarily on unadjusted SGP descriptive metrics, diagnosticians must overlay demographic context onto growth scores. Evaluating high-poverty schools strictly through unadjusted SGP risks artificially deflating performance evaluations for educators working with historically disadvantaged student populations.

3.3 Identification of Marginalized Schools: CSI, TSI, and ATSI

Disaggregating longitudinal outcomes enables the state to identify schools requiring structural intervention:

• Comprehensive Support and Improvement (CSI): Assigned to schools performing in the lowest tier (represented visually as Red on the Balanced Scorecard) across all indicators, or high schools failing to graduate at least 67% of their adjusted cohort.
• Targeted Support and Improvement (TSI): Assigned when specific demographic subgroups perform at a level equivalent to the lowest 5% of Title I schools statewide.
• Additional Targeted Support and Improvement (ATSI): Assigned when a school has low-performing subgroups experiencing chronic achievement gaps that require intensive resource allocation.

Evaluating outcome metrics allows diagnosticians to determine whether low student performance reflects isolated learning gaps or systemic non-compliance with state curriculum mandates.

4. Curriculum Fidelity, Legislative Mandates, and School Standards

The third pillar of the diagnostic framework evaluates instructional quality, policy compliance, and programmatic rigor across classrooms.

4.1 WVBE Policy 2510: High School Programmatic Rigor

West Virginia Board of Education (WVBE) Policy 2510 establishes operational rules, graduation credit requirements, and master schedule standards across middle and high schools.

Graduation Credit Baseline Progression

High school graduation credit baselines in West Virginia are expanding:

• Historical Cohorts: 22 total credits.
• 2024–2025 Freshman Cohort: 23 total credits (incorporates a mandatory credit in Personal Finance).
• 2027–2028 Freshman Cohort: 24 total credits (incorporates a mandatory credit in Computer Science).

Master Schedule Compliance and Equity Mandates

• 8,100-Minute Rule: High school courses must provide adequate instructional time. If a school schedules courses under 8,100 total instructional minutes while failing to meet state academic proficiency standards for two consecutive years, the issue triggers a mandatory schedule review by the County Board of Education.
• Advanced Coursework Access: High schools must offer a minimum of 4 Advanced Placement (AP) courses annually, covering ELA, mathematics, science, and social studies.
• Career & Technical Education (CTE): Schools must provide CTE programs based on total enrollment (minimum 3 CTE clusters for schools under 400 students; minimum 5 CTE clusters for schools exceeding 800 students).

4.2 Early Literacy and Numeracy: The Third Grade Success Act (HB 3035 / W. Va. Code §18-2E-10)

Enacted under W. Va. Code §18-2E-10, House Bill 3035 (The Third Grade Success Act) establishes an early intervention framework in grades K–3. Diagnosticians monitor implementation fidelity through a five-step statutory workflow:

  ┌─────────────────────────────────────────────────────────────┐
  │ 1. SCREENING & IDENTIFICATION                               │
  │    Administer state screeners (Reading, Math, Dyslexia,     │
  │    Dyscalculia).                                            │
  └──────────────────────────────┬──────────────────────────────┘
                                 │
                                 ▼
  ┌─────────────────────────────────────────────────────────────┐
  │ 2. STATUTORY PARENTAL NOTIFICATION                          │
  │    Issue written notification to parents within 15 DAYS of   │
  │    identifying a learning deficiency.                       │
  └──────────────────────────────┬──────────────────────────────┘
                                 │
                                 ▼
  ┌─────────────────────────────────────────────────────────────┐
  │ 3. INDIVIDUALIZED INTERVENTION PLAN                         │
  │    Draft reading/math improvement plan within 30 DAYS of     │
  │    identification.                                          │
  └──────────────────────────────┬──────────────────────────────┘
                                 │
                                 ▼
  ┌─────────────────────────────────────────────────────────────┐
  │ 4. PERSONNEL DEPLOYMENT                                     │
  │    Deploy Early Childhood Classroom Assistant Teachers      │
  │    (ECCATs) and interventionists in K–3 classrooms.         │
  └──────────────────────────────┬──────────────────────────────┘
                                 │
                                 ▼
  ┌─────────────────────────────────────────────────────────────┐
  │ 5. RETENTION MANDATE (Effective 2026–2027)                  │
  │    Retain 3rd graders scoring "Does Not Meet Standard"      │
  │    on WVGSA ELA/Math, unless qualifying for Good Cause.    │
  └─────────────────────────────────────────────────────────────┘

Statutory Good Cause Exemptions

The retention mandate effective in 2026–2027 applies to third-grade students failing to reach proficiency benchmarks on the ELA or Mathematics WVGSA. However, W. Va. Code §18-2E-10 defines explicit Good Cause Exemptions:

1. Students with Disabilities: Students whose Individualized Education Program (IDEA/IEP) specifies that participation in statewide summative assessments is not appropriate or provides alternative assessment pathways.
2. English Learners: EL students with less than two years of instruction in an English language program.
3. Prior Retentions: Students who have already been retained for a total of two years in early elementary grades (K–3).

4.3 WVBE Policy 2322: Standards for Effective Schools

WVBE Policy 2322 defines seven quantitative and qualitative standards expected of all public schools, evaluated annually via the West Virginia School Learning Environment Surveys administered to students, school staff, and parents:

• Standard 1: Positive Climate and Cohesive Culture: Establishes shared beliefs, high academic expectations, and an orderly environment that respects student diversity.
• Standard 2: School Leadership: Evaluates principal leadership in driving instructional strategies and student development.
• Standard 3: Standards-Focused Curriculum and Instruction: Measures the degree to which instructional time is aligned directly with state learning standards.
• Standard 4: Student Support Services: Assesses integrated delivery of health, nutrition, counseling, special education, and English learner services.
• Standard 5: Educator Growth and Development: Evaluates teacher collaboration within professional learning teams to analyze assessment data and improve teaching.
• Standard 6: Efficient and Effective Management: Measures operational integrity across facility maintenance, budget allocations, and educational technology systems.
• Standard 7: Continuous Improvement: Assesses ongoing data monitoring processes used to evaluate and refine instructional programs.

When diagnostic evaluations reveal policy non-compliance or instructional weaknesses, school leaders shift from evaluation to designing active support interventions.

5. Corrective Interventions and Strategic Continuous Improvement

Diagnosticians translate evaluation findings into action by applying state-sanctioned intervention frameworks and structured local strategic planning processes.

5.1 The West Virginia Tiered System of Supports (WVTSS)

The WVTSS is a multi-tiered framework designed to deliver academic, behavioral, and mental health interventions based on real-time student performance data:

WVTSS Tier Level	Academic Interventions	Behavioral & Mental Health Interventions	Target Population & Expected Efficacy
Tier 1 (Universal)	High-quality, standards-based core instruction; differentiated learning plans.	School-wide Positive Behavior Interventions and Supports (PBIS); universal mental health screening.	Delivered to 100% of students. A healthy core system meets the needs of ~75–80% of students.
Tier 2 (Targeted)	Small-group instruction; targeted skill-building (e.g., small-group literacy pull-out sessions).	Restorative circles; check-in/check-out behavioral tracking systems; targeted counseling groups.	Serves ~10–20% of students needing temporary, targeted scaffolding.
Tier 3 (Intensive)	Individualized, high-intensity academic interventions; formal special education referrals.	Crisis intervention protocols; community wraparound services; individualized Behavior Intervention Plans (BIP).	Serves ~5–10% of students requiring high-intensity, individualized support.

Systemic Diagnostic Rule: If data reveals that more than 40% of a school's population requires Tier 3 intensive intervention, the primary problem is not a shortage of intervention staff. It indicates that the Tier 1 core instructional model is broken and requires comprehensive curriculum reform and core instructional development.

5.2 Student Assistance Team (SAT) Operations

The Student Assistance Team (SAT) is a statutory body mandated by Policy 2510, consisting of school administrators, classroom teachers, and support specialists:

• Academic Timelines: Ensures reading and math intervention plans are created within the required 30-day statutory window following an HB 3035 screening deficiency.
• Attendance Interventions: Reviews unexcused absences. Absences exceeding 10 days (without formal physician documentation) trigger SAT interventions, attendance directors, and community resources to address truancy under state law.
• Alternative High School Pathways: For credit-deficient high school students, the SAT evaluates alternative interventions such as the Option Pathway. This pathway allows at-risk students (ages 16–21) to complete a CTE credential and a high school equivalency assessment to graduate on time.

5.3 Strategic Planning and the Comprehensive Needs Assessment (CNA)

Under Policy 2322 and West Virginia Code, all public schools and districts must formulate an annual Strategic Improvement Plan based on a Comprehensive Needs Assessment (CNA).

Diagnosticians ensure funding alignment during the strategic planning process by completing a explicit budget-to-needs verification:

  ┌─────────────────────────────────────────────────────────────┐
  │ 1. CONDUCT COMPREHENSIVE NEEDS ASSESSMENT (CNA)             │
  │    Analyze 5-year longitudinal data across Finance,         │
  │    Outcomes, and Curriculum to identify deficit areas.      │
  └──────────────────────────────┬──────────────────────────────┘
                                 │
                                 ▼
  ┌─────────────────────────────────────────────────────────────┐
  │ 2. CROSS-EXAMINE WVEIS FUNCTION 1000 ACCOUNTS               │
  │    Audit direct instructional spending to ensure funds      │
  │    target identified CNA academic deficits.                 │
  └──────────────────────────────┬──────────────────────────────┘
                                 │
                                 ▼
  ┌─────────────────────────────────────────────────────────────┐
  │ 3. VERIFY PSSP STEP 7 & TITLE FUND ALIGNMENT                │
  │    Confirm PSSP Step 7 (Instructional Improvement) lines    │
  │    and federal Title dollars finance CNA priority goals.    │
  └──────────────────────────────┬──────────────────────────────┘
                                 │
                                 ▼
  ┌─────────────────────────────────────────────────────────────┐
  │ 4. ESTABLISH FIDELITY MONITORING PROTOCOLS                  │
  │    Deploy quarterly formative assessments and classroom     │
  │    walkthroughs to monitor implementation.                  │
  └──────────────────────────────┘

By connecting budget flexfield transparency, student performance analytics, and legislative policy mandates, school leaders ground educational reform in empirical, long-term data rather than subjective observation.

6. Conclusion: Summary Framework for the Educational Diagnostician

Evaluating public school performance in West Virginia requires connecting school funding inputs directly to classroom instructional practices and student academic outcomes. Effective educational research depends on synthesizing data across these domains to support continuous school improvement.

Key Takeaways for Educational Researchers

1. Integrate the Diagnostic Triad: Avoid analyzing standardized test scores in isolation. Always cross-reference student outcomes with local expenditure distributions (WVEIS Function 1000 vs. Function 2000) and statutory instructional policy compliance (WVBE Policy 2510 and W. Va. Code §18-2E-10 / HB 3035).
2. Contextualize Growth Data: Recognize the statistical limitations of unadjusted descriptive metrics like Student Growth Percentiles (SGP). Always overlay socio-demographic context and consider Value-Added Model (VAM) error corrections to ensure equitable evaluations of schools serving high concentrations of at-risk students.
3. Prioritize Tier 1 Core Instruction: Apply the WVTSS framework mathematically. If student failure rates exceed standard Tier 2/3 thresholds (e.g., >40% requiring intensive intervention), focus resources on whole-school curriculum reform and core instructional delivery rather than over-referring students to interventionists.

----------------------------------------------------------------------------------------------------

West Virginia District Assessment Framework: A Longitudinal Protocol for Systemic Performance Diagnosis

1. Data Architecture & Longitudinal Query Parameters

Evaluating the systemic efficacy of a West Virginia public school district requires a calibrated, multi-dimensional diagnostic framework. Assessing educational performance extends beyond high-level observation; it necessitates establishing an algorithmic analytical protocol to query primary state data repositories, including the West Virginia Education Information System (WVEIS), the ZoomWV Data Dashboard, and the West Virginia Department of Education (WVDE) OpenGov transparency platforms. Following the severe operational and assessment disruptions caused by the COVID-19 pandemic—which resulted in a complete absence of state accountability metrics for the 2020–2021 academic year—establishing a valid post-pandemic baseline is essential to measure systemic recovery, resource equity, and longitudinal student growth across all public school campuses.

To construct a mathematically sound and relational longitudinal dataset, the technical protocol interfaces directly with WVEIS, ZoomWV, and WVDE OpenGov platforms. The query protocol defines precise relational join keys to merge financial, demographic, and assessment tables:

• COUNTY_CODE (2-digit West Virginia LEA identifier)
• SCHOOL_CODE (3-digit facility identifier)
• WVEIS_STUDENT_ID (9-digit unique state student identifier)
• FISCAL_YEAR (YYYY format covering baseline through current evaluation)
• FAY_FLAG (Binary indicator: 1 = \text{Enrolled } \ge 133 \text{ instructional days / Full Academic Year}, 0 = \text{Non-FAY})

The diagnostic timeline establishes the 2021–2022 academic year as the foundational baseline for post-pandemic recovery analysis and extends through the 2025–2026 academic year. This five-year analytical window aggregates quantitative financial inputs, student outcomes, and curricular access at both the individual school level and specific grade levels, comparing local variance directly against West Virginia statewide performance benchmarks.

                  STATE DATA REPOSITORY INTEGRATION ARCHITECTURE
  
       ┌────────────────┐     ┌────────────────┐     ┌────────────────┐
       │     WVEIS      │     │    ZoomWV      │     │  WVDE OpenGov  │
       │ (Finance/Admin)│     │(Accountability)│     │ (Transparency) │
       └───────┬────────┘     └───────┬────────┘     └───────┬────────┘
               │                      │                      │
               └──────────────────────┼──────────────────────┘
                                      ▼
     ┌──────────────────────────────────────────────────────────────────┐
     │                   RELATIONAL DATA ENGINE (JOIN KEYS)             │
     │  `COUNTY_CODE` + `SCHOOL_CODE` + `WVEIS_STUDENT_ID` + `FISCAL_YEAR`│
     └────────────────────────────────┬─────────────────────────────────┘
                                      │ Filter: `FAY_FLAG` = 1
                                      ▼
     ┌──────────────────────────────────────────────────────────────────┐
     │             FIVE-YEAR LONGITUDINAL DATASET (2021-22 to 2025-26)   │
     └───────┬────────────────────────┬────────────────────────┬────────┘
             │                        │                        │
             ▼                        ▼                        ▼
     ┌───────────────┐        ┌───────────────┐        ┌───────────────┐
     │ Financial     │        │ Outcome       │        │ Curriculum    │
     │ Domain        │        │ Domain        │        │ Access Domain │
     └───────────────┘        └───────────────┘        └───────────────┘

Statistically valid reporting under West Virginia accountability standards mandates strict adherence to state demographic disaggregation protocols. The diagnostic architecture enforces the state-mandated minimum cell size rule of n = 20 Full Academic Year (FAY) students; subgroups containing fewer than 20 FAY students are suppressed from public reporting to maintain statistical reliability and individual student privacy. The framework isolates and evaluates performance, financial allocations, and curriculum access for four mandated demographic subgroups:

1. Economically Disadvantaged students (identified via Direct Certification or Community Eligibility Provision household data);
2. English Learners (EL) (assessed via ELPA21);
3. Students with Disabilities (SWD) receiving special education services under the Individuals with Disabilities Education Act (IDEA) and WVBE Policy 2419;
4. Homeless Students identified under the McKinney-Vento Homeless Assistance Act.

To isolate the root causes of systemic underperformance, the analyst must execute a multi-domain causal synthesis. The following step-by-step analytical algorithm formalizes how the diagnostician determines whether a localized academic deficiency—such as 3rd-grade reading failure—stems from fiscal misallocation, non-compliance with statutory mandates, or chronic absenteeism:

                  CROSS-DOMAIN ROOT-CAUSE SYNTHESIZER ALGORITHM
  
  [Input: Low 3rd-Grade ELA Proficiency (<62.5 Point Average / Red Scorecard Tier)]
                                      │
                                      ▼
                  ┌───────────────────────────────────────┐
                  │ STEP 1: Audit HB 3035 Compliance      │
                  │ (W. Va. Code §18-2E-10)               │
                  └───────────────────┬───────────────────┘
                                      │
           ┌──────────────────────────┴──────────────────────────┐
           ▼                                                     ▼
 [NON-COMPLIANT: >15-day notice    [COMPLIANT: Screeners, Notices, &]
  or >30-day SAT Plan delay]        [30-day SAT Plans Executed Timely]
           │                                                     │
           ▼                                                     ▼
┌──────────────────────────┐                   ┌──────────────────────────────────┐
│ ROOT CAUSE A:            │                   │ STEP 2: Audit WVEIS Financials   │
│ Statutory Instructional  │                   │ (PSSP Step 7 & Fund 11/61 Flex)  │
│ non-compliance; SAT      │                   └─────────────────┬────────────────┘
│ operational failure.     │                                     │
└──────────────────────────┘         ┌───────────────────────────┴───────────────────────────┐
                                     ▼                                                       ▼
                       [EXPENDITURE DEFICIT: Step 7      [EXPENDITURE SUFFICIENT: Direct     ]
                        funds diverted to Admin/Func 2000] [Classroom Function 1000 Funded  ]
                                     │                                                       │
                                     ▼                                                       ▼
                       ┌──────────────────────────┐             ┌──────────────────────────┐
                       │ ROOT CAUSE B:            │             │ STEP 3: Audit WVEIS      │
                       │ Fiscal misalignment &    │             │ Student Attendance Flags │
                       │ instructional under-     │             └────────────┬─────────────┘
                       │ investment.              │                          │
                       └──────────────────────────┘              ┌───────────┴───────────┐
                                                                 ▼                       ▼
                                                      [ABSENTEEISM HIGH:      [ABSENTEEISM NORMAL:]
                                                       >10% Chronic Rate]      [<10% Chronic Rate]
                                                                 │                       │
                                                                 ▼                       ▼
                                                      ┌────────────────────┐  ┌──────────────────┐
                                                      │ ROOT CAUSE C:      │  │ ROOT CAUSE D:    │
                                                      │ Chronic Truancy &  │  │ Tier 1 Core      │
                                                      │ Statutory Attendance│ │ Instructional    │
                                                      │ Enforcement Breakdown││ Pedagogical Failure│
                                                      └────────────────────┘  └──────────────────┘

With the data architecture, relational join parameters, and root-cause diagnostic algorithms established, the diagnostic framework advances to an empirical evaluation of district financial structures and resource allocation.

2. Financial-Level Diagnostics: Resource Allocation, Equity, and Modernization

Financial diagnostics provide a forensic analysis of how state aid, local tax revenues, and federal funds are distributed and deployed across individual school campuses. Within this framework, per-pupil spending rates and resource allocations are evaluated not merely as administrative bookkeeping, but as rigorous assessments of educational equity, fiscal compliance, and operational efficiency.

State-level baseline funding is governed by the Public School Support Program (PSSP), established under West Virginia Code §18-9A. The diagnostic framework evaluates district and school-level operational efficiency by auditing financial disbursements across all seven foundational steps of the PSSP formula:

PSSP Step	Funding Objective	Diagnostic Query Focus & Operational Mechanism
Step 1: Allowance for Professional Educators	Baseline instructional staffing allocation.	Audits ratio of state-aid eligible professional educators per 1,000 students in net enrollment. Queries density tiers: Sparse (<10 students/sq mi), Medium (10–20), and High-Density (>20) to detect baseline staffing under-allocation.
Step 2: Allowance for Service Personnel	Operational and instructional support staffing.	Evaluates service personnel ratios (aides, custodians, bus drivers) per 1,000 net enrollment across county density tiers. Audits deployment of instructional aides versus non-instructional facility staff.
Step 3: Allowance for Fixed Charges	Statutory employee benefit obligations.	Tracks employer contribution disbursements for Social Security, Unemployment, Workers' Compensation, and Public Employees Insurance Agency (PEIA) premiums. Queries statutory compliance rates.
Step 4: Allowance for Transportation	Student transit operations and maintenance.	Assesses total transportation operating costs, fuel expenditures, and bus replacement schedules. Cross-references per-pupil transit costs with geographical sparsity and chronic absenteeism flags.
Step 5: Current Expenses	Facility operations and instructional supplies.	Audits operational and maintenance disbursements generated by statutory formulas matching gross school building square footage and net enrollment. Flags facility maintenance deferrals.
Step 6: Local Share	Direct local tax effort equalization.	Calculates equalized local tax revenue derived from regular county property tax levies. Audits county capacity to pass special instructional levies, identifying structural funding inequities between property-wealthy and property-poor LEAs.
Step 7: Improvement of Instructional Programs	Direct instructional enhancement & professional development.	Isolates statutory allocations earmarked specifically for direct instructional delivery, teacher professional development, and curriculum adoption. Audits whether funds are misallocated to operational deficits.

Modernization proposals for the PSSP incorporate weighted funding models that allocate resources dynamically based on documented student need and service intensity. For special education, the framework transitions from traditional categorical diagnoses to service intensity weights: Level I receives a weight of 0.50, Level II receives 1.00, Level III receives 2.00, and Gifted services receive 0.05. Concurrently, concentrated poverty is evaluated using cumulative multiplier weights applied when a school's poverty concentration exceeds specific thresholds (>40%, >60%, and >75%).

To model how these progressive weights alter base funding allocations, the diagnostician applies the following algebraic formula:

\text{Weighted Student Count (WSC)} = N_{\text{Base}} + \sum_{k=1}^{4} \left( N_{\text{SpecEd}_k} \times W_k \right) + \left( N_{\text{Poverty}} \times M_{\text{Poverty Tier}} \right)

\text{Adjusted Per-Pupil Allocation} = \frac{\text{Base State Aid Allocation} \times \text{WSC}}{N_{\text{Base}}}

(Where N_{\text{Base}} is net enrollment, N_{\text{SpecEd}_k} represents student counts in special education intensity tiers k \in \{\text{Level I, Level II, Level III, Gifted}\}, W_k represents respective weights \{0.50, 1.00, 2.00, 0.05\}, N_{\text{Poverty}} is the economically disadvantaged headcount, and M_{\text{Poverty Tier}} is the applicable cumulative multiplier \{0.05 \text{ for } >40\%, 0.10 \text{ for } >60\%, 0.15 \text{ for } >75\%\}).

At the micro-level, expenditure tracking relies on parsing the multi-dimensional WVEIS Chart of Accounts flexfield. The diagnostic protocol parses three specific accounting dimensions:

1. Fund Code (2 Digits): Differentiates General Current Expense funds (Fund 11), Special Revenue funds (Fund 61), and Federal Stimulus/Stabilization funds (Fund 7X).
2. Project Code (5 Digits): Distinguishes between unrestricted operational expenditures and restricted federal or state grant allocations.
3. Function Code (4 Digits): Categorizes expenditures by operational purpose, contrasting direct classroom instruction (Function 1000) against support services and central administrative overhead (Function 2000).

                      WVEIS ACCOUNTING FLEXFIELD PARSING ARCHITECTURE
  
       Fund Code (2 Digits)         Project Code (5 Digits)      Function Code (4 Digits)
    ┌──────────────────────┐       ┌──────────────────────┐     ┌──────────────────────┐
    │  11: General Current │       │  00000: Unrestricted │     │ 1000: Direct         │
    │  61: Special Revenue │  ──►  │  Operational         │ ──► │       Instruction    │
    │  7X: Federal Stimulus│       │  XXXXX: Restricted   │     │ 2000: Admin & Support│
    └──────────────────────┘       │         Federal/State│     └──────────────────────┘
                                   └──────────────────────┘

The diagnostician must exercise forensic intensity when evaluating Function 2000 spending. Expenditures coded under Function 2000 that exhibit sustained longitudinal growth while Function 1000 classroom expenditures stagnate represent unambiguous evidence of administrative overhead expansion and non-instructional capital leakage. When low-performing campuses exhibit high Function 2000 spending ratios, the diagnostician flags these line items for mandatory reallocation under federal Resource Allocation Reviews.

Under the Every Student Succeeds Act (ESSA), districts containing schools designated for Comprehensive Support and Improvement (CSI), Targeted Support and Improvement (TSI), or Additional Targeted Support and Improvement (ATSI) must undergo formal Resource Allocation Reviews (RAR). The diagnostic framework automates RAR protocols to detect spending anomalies—such as a school maintaining significantly higher per-pupil expenditures than the district average while remaining in the lowest academic performance tier. Isolating these operational inefficiencies provides the empirical basis required to reallocate unrestricted general funds toward core instructional operations, school leadership, and baseline staffing in marginalized schools.

Connecting these fiscal resources directly to academic returns requires transitioning from financial diagnostics to student-level outcome metrics.

3. Student-Level Diagnostics: Accountability, Growth Analytics, and Subgroup Identification

Student-level outcome diagnostics measure district effectiveness under the West Virginia Accountability System (WVAS), which synthesizes performance data into the publicly accessible West Virginia Schools Balanced Scorecard.

The Balanced Scorecard evaluates student performance across four distinct performance tiers on the West Virginia General Summative Assessment (WVGSA) and West Virginia Alternate Summative Assessment (WVASA):

Performance Level Designation	WVGSA Point Value Range	WVASA Counterpart Level	Expectation Definition	State Dashboard Visual Tier
Exceeds Standard	100 to 125 Points (80%+ Proficiency Index)	Advanced	Distinctive performance exceeding state expectations.	Blue
Meets Standard	81.25 to 100 Points (65–80% Proficiency Index)	At Target	Performance falls within expected state standards.	Green
Partially Meets Standard	62.5 to 81.25 Points (50–65% Proficiency Index)	Approaching Target	Approaching expected state performance range.	Yellow
Does Not Meet Standard	Below 62.5 Points (<50% Proficiency Index)	Below Target	Unacceptably below expected state standards.	Red

Academic Achievement measures the percentage of FAY students achieving proficiency (Meets or Exceeds Standard) in English Language Arts (ELA) and Mathematics. Following the post-pandemic baseline reset in 2020–2021, West Virginia established a long-term goal to halve the gap between baseline proficiency and 100 percent proficiency by the 2035–2036 school year.

To project a school’s annual growth trajectory against this statutory target, the diagnostician applies the following LaTeX trajectory growth formula:

Target_{Annual}(t) = Baseline_{2020-21} + t \times \left( \frac{100 - Baseline_{2020-21}}{30} \right)

(Where Baseline_{2020-21} is the school's ELA or Math proficiency percentage in the 2020–2021 baseline year, and t \in [1, 15] represents the specific academic year index following the baseline, with t=5 corresponding to the 2025–2026 evaluation year).

For English Learners, the framework tracks English Learner Progress (ELP) via the ELPA21 assessment across four domains: listening, reading, speaking, and writing. Achieving overall ELP proficiency requires an EL student to attain a Level 4 (Early Advanced) or Level 5 (Advanced) across all four tested domains.

                  LONG-TERM ACCOUNTABILITY TRAJECTORY (2020-21 TO 2035-36)
  
  100% ┌─────────────────────────────────────────────────────────────────┐
       │                                                         TARGET  │
       │                                                      (2035-36)  │
       │                                                   ▲             │
       │                                        ┌──────────┘             │
       │                             ┌──────────┘ [Trajectory Formula]   │
       │                  ┌──────────┘ Target_Annual(t)                  │
   Baseline ──────────────┘                                              │
   (2020-21)                                                             │
    0% └─────────────────────────────────────────────────────────────────┘
         Year 0    Year 1    ...    Year 5    ...    ...    ...    Year 15
        (2020-21) (2021-22)        (2025-26)                       (2035-36)

When diagnosing longitudinal growth, the analyst must critically distinguish between descriptive growth metrics and causal growth methodologies:

• Student Growth Percentiles (SGP): The descriptive metric utilized on West Virginia state dashboards. SGP ranks a student’s current score relative to an academic peer group with identical historical test score trajectories. SGP does not adjust for background characteristics such as socioeconomic status, language status, or disability.
• Value-Added Models (VAM): Advanced statistical models designed to isolate the specific causal effect of an educator or school by controlling for exogenous variables, including poverty, prior test scores, and demographic background. VAM incorporates errors-in-variables corrections to adjust for measurement error in pretests, preventing the artificial deflation of effectiveness scores for educators serving high-poverty student populations.

Because state dashboards rely exclusively on unadjusted, descriptive SGP metrics, diagnosticians must overlay socio-demographic context onto raw SGP outputs. Evaluating high-poverty schools strictly through unadjusted SGP scores risks misinterpreting school performance and inappropriately penalizing effective educators.

Non-academic Student Success Indicators provide essential context for academic outcome metrics:

• Chronic Absenteeism: Evaluates the percentage of students missing >10\% of enrolled instructional days. Under W. Va. Code §18-8-4, unexcused absences or total absences exceeding 10 days without formal physician documentation trigger mandatory statutory legal notices and Student Assistance Team (SAT) interventions.
• Behavior Indicator: Measures the percentage of students maintaining zero out-of-school suspensions during the academic year.
• On-Track to Graduation (High School): Measures the percentage of 10th-grade students who have earned at least 12 cumulative credits across 9th and 10th grades, with a minimum of 2 credits in each of the four core content areas (ELA, mathematics, science, and social studies).
• Cohort Graduation Rates: Audits both 4-year and 5-year adjusted cohort graduation rates against the state benchmark of 90% to 95% required to achieve "Meets Standard."

Disaggregating these outcome metrics across the five-year baseline isolates campuses requiring formal state support designations:

• Comprehensive Support and Improvement (CSI): Triggered if a school falls into the lowest performance tier (Red) across all scorecard indicators, or if a high school fails to achieve a 67% four-year adjusted cohort graduation rate.
• Targeted Support and Improvement (TSI) / Additional Targeted Support and Improvement (ATSI): Triggered if specific demographic subgroups within a campus perform at a level commensurate with the lowest 5 percent of Title I schools statewide.

Diagnosing student outcome anomalies leads directly to auditing the structural driver of academic performance: curriculum alignment and instructional fidelity.

4. Curriculum-Level Diagnostics: Instructional Fidelity and Legislative Mandates

Auditing instructional fidelity, course rigor, and compliance with West Virginia Board of Education (WVBE) policies and state statutes is essential to identify the root systemic causes of low student achievement.

WVBE Policy 2510 governs programmatic requirements and credit escalations for high school graduation across progressive freshman cohorts:

• Historic Baseline: 22 Total Credits.
• 2024–2025 Freshman Cohort: Escalates to 23 Total Credits, incorporating 1 mandatory credit in Personal Finance.
• 2027–2028 Freshman Cohort: Escalates to 24 Total Credits, incorporating 1 mandatory credit in Computer Science.

Scheduling integrity is audited under the Policy 2510 instructional time rule. Courses scheduled for fewer than 8,100 minutes per academic year that simultaneously fail to meet state proficiency standards for two consecutive years trigger a mandatory master schedule review by the County Board of Education. Furthermore, the diagnostic query audits advanced programmatic access thresholds:

• High schools must offer a minimum of 4 Advanced Placement (AP) courses annually, spanning all four core content areas (ELA, math, science, social studies).
• High schools must maintain dedicated Career and Technical Education (CTE) clusters based on total enrollment: a minimum of 3 CTE clusters for schools with enrollment <400, and 5 CTE clusters for schools exceeding 800 students.

Subgroup enrollment across AP and CTE courses is cross-referenced against total subgroup demographics to eliminate invisible tracking and ensure equitable access.

At the elementary level, early literacy and numeracy compliance is audited under House Bill 3035 (The Third Grade Success Act, codified in W. Va. Code §18-2E-10) alongside WVBE Policy 2510, Policy 2322, and Policy 2419. Diagnosticians evaluate implementation fidelity using a structured five-point operational protocol:

1. Screening & Identification Fidelity: Verifies continuous administration of approved benchmark screeners for reading, mathematics, dyslexia, and dyscalculia in grades K–3, monitoring strict adherence to state-established cut scores.
2. Statutory Parental Notification Verification: Audits compliance with the statutory legal mandate requiring written parental notification within 15 days of identifying a literacy or numeracy deficiency in any K–3 student (W. Va. Code §18-2E-10).
3. Individualized Intervention Planning: Confirms that an individualized reading or mathematics improvement plan is formally instituted for identified students no later than 30 days post-identification.
4. Personnel Deployment & Ratio Audits: Merges WVEIS expenditure tracking (Fund 11/61, Project Codes) with classroom roster data to perform operational audits of state-funded Early Childhood Classroom Assistant Teachers (ECCATs) and reading interventionists. The audit verifies that ECCAT staffing achieves state-mandated classroom adult-to-student ratios (1:15 in Kindergarten, 1:12 in 1st–3rd grade target classrooms) and that personnel are deployed directly into K–3 classrooms exhibiting the highest concentration of academic deficiencies.
5. Retention Forecasting & Good Cause Exemption Parsing: Evaluates student growth trajectories to project retention rates tied to the mandatory third-grade WVGSA ELA and Math retention mandate taking effect in the 2026–2027 school year. The query filters WVEIS student record flags to audit and project statutory "Good Cause Exemptions" under W. Va. Code §18-2E-10, isolating:
   • Students with Disabilities (SWD) under IDEA (Policy 2419) whose Individualized Education Program (IEP) indicates that state assessment participation is inappropriate or specifies alternative retention guidelines;
   • English Learners (EL) receiving ELA instruction for less than 2 academic years;
   • Students demonstrating proficiency on an approved alternative literacy screener;
   • Students who have received intensive academic intervention for two or more years and were previously retained in grades K, 1, 2, or 3 for a cumulative total of 2 years.

Qualitative instructional diagnostic data is gathered via WVBE Policy 2322 (West Virginia System of Support and Accountability), which evaluates campuses across the 7 Standards for Effective Schools:

1. Positive Climate and Cohesive Culture
2. School Leadership
3. Standards-Focused Curriculum and Instruction
4. Student Support Services
5. Educator Growth and Development
6. Efficient and Effective Management
7. Continuous Improvement

Data extracted from the annual West Virginia School Learning Environment Surveys (administered to students, school staff, and parents) operationalizes these qualitative standards to measure climate, leadership impact, standards alignment, and collaborative professional development.

Once curriculum non-compliance and academic gaps are identified, diagnostic data must be operationalized into targeted corrective interventions.

5. Corrective Interventions, Support Systems, and Strategic Planning Formulation

The ultimate objective of performance diagnosis is translating five-year longitudinal data into actionable, evidence-based intervention strategies. District performance recovery relies on aligning diagnostic findings with established state support structures.

For schools demonstrating widespread academic or behavioral deficiencies, the framework mandates deploying or refining the West Virginia Tiered System of Supports (WVTSS). WVTSS establishes a continuum of prevention and intervention across academic, behavioral, and mental health domains:

WVTSS Tier Level	Academic Interventions	Behavioral & Mental Health Interventions	Target Population & Expected Efficacy
Tier 1 (Universal)	Delivery of high-quality, standards-based core instruction; differentiated personalized learning plans.	School-wide Positive Behavior Interventions and Supports (PBIS); universal mental health screening; relationship building.	100% of Students. A healthy core instructional system yields 75–80% student success through Tier 1 alone.
Tier 2 (Targeted)	Small-group instruction; supplemental evidence-based skill building (e.g., targeted pull-out literacy sessions).	Restorative circles; check-in/check-out behavioral tracking systems; targeted counseling groups.	Designed for 10–20% of students requiring supplemental scaffolding to access core content.
Tier 3 (Intensive)	Individualized, high-intensity skill interventions; formal referrals for special education evaluation.	Crisis intervention protocols; wraparound community services; individualized Behavior Intervention Plans (BIP).	Reserved for 5–10% of students requiring intensive, individualized support.

Diagnosticians evaluate whether a school's population distribution matches the structural expectations of the WVTSS pyramid. If diagnostic data reveals that >40\% of students require Tier 3 intensive reading interventions, the diagnostic conclusion is that Tier 1 core instruction is structurally deficient. In such scenarios, corrective action must prioritize systemic curriculum reform and whole-staff pedagogical professional development, rather than attempting to overload the system with Tier 3 interventionists.

                      WVTSS OPERATIONAL ALIGNMENT DIAGNOSTIC
  
        HEALTHY SYSTEM                             STRUCTURAL TIER 1 FAILURE
      (Standard Efficacy)                          (Requires Core Reform)
  
          /  5-10%  \  Tier 3                       /    >40%    \  Tier 3
         /-----------\                             /--------------\
        /   10-20%    \  Tier 2                   /    20-30%      \  Tier 2
       /───────────────\                         /──────────────────\
      /     75-80%      \  Tier 1               /       <40%         \  Tier 1
     /───────────────────\                     /──────────────────────\

At the individual student level, interventions are managed by the Student Assistance Team (SAT), mandated by Policy 2510. The diagnostic query audits SAT operational efficacy by assessing turnaround times and program placement metrics:

• HB 3035 Turnaround: Verifies strict compliance with the 30-day statutory window for instituting individualized improvement plans following identified screener deficiencies.
• Attendance Interventions: Confirms that unexcused absences exceeding 10 days trigger SAT reviews, attendance director actions, and community resource referrals under W. Va. Code §18-8-4.
• Alternative Pathways: Evaluates SAT utilization of credit recovery and the Option Pathway—which allows off-track students aged 16 to 21 to earn CTE credentials and pass a high school equivalency assessment in lieu of standard credit accumulation—to mitigate dropout rates.

The diagnostic process culminates in formulating the annual Strategic Improvement Plan, mandated by West Virginia State Code §18-2E-5 and Policy 2322. District and school leadership utilize diagnostic outputs to complete a Comprehensive Needs Assessment (CNA), driving a continuous improvement monitoring loop:

                  STRATEGIC IMPROVEMENT CONTINUOUS MONITORING LOOP
  
   ┌────────────────────────────────────────────────────────────────────────┐
   │ 1. DATA INPUT NODE: Comprehensive Needs Assessment (CNA)               │
   │    Query 5-Yr Baseline, Disaggregate Subgroups, Audit Financial/Policy │
   └───────────────────────────────────┬────────────────────────────────────┘
                                       │
                                       ▼
   ┌────────────────────────────────────────────────────────────────────────┐
   │ 2. PRIORITY GOAL FORMULATION                                           │
   │    Target Subgroup Gap Reduction aligned to 2035-36 Target Formula     │
   └───────────────────────────────────┬────────────────────────────────────┘
                                       │
                                       ▼
   ┌────────────────────────────────────────────────────────────────────────┐
   │ 3. RESOURCE DIRECTIVE                                                  │
   │    Allocate Title I, Title II, and PSSP Step 7 Funds to Core Deficits  │
   └───────────────────────────────────┬────────────────────────────────────┘
                                       │
                                       ▼
   ┌────────────────────────────────────────────────────────────────────────┐
   │ 4. ACTION STEP EXECUTION                                               │
   │    Schedule Redesigns (8,100 Min), ECCAT Ratios, WVTSS Protocols       │
   └───────────────────────────────────┬────────────────────────────────────┘
                                       │
                                       ▼
   ┌────────────────────────────────────────────────────────────────────────┐
   │ 5. FEEDBACK DECISION POINT: Quarterly Formative Benchmark Cycles       │
   │    (Admin Walkthroughs, interim Screeners, WVEIS Absenteeism Checks)   │
   └───────────────────────────────────┬────────────────────────────────────┘
                                       │
            ┌──────────────────────────┴──────────────────────────┐
            │                                                     │
            ▼                                                     ▼
  [METRIC ON TRACK]                                    [METRIC OFF TRACK]
  Maintain Strategy & Progress                       Trigger SAT / CNA Re-evaluation &
  to Next Formative Benchmark                        Reallocate Step 7 / Title Funds

1. Data Input Node (CNA): Integrates five-year longitudinal query parameters, disaggregated subgroup performance, WVEIS flexfield expenditure ratios, and Policy 2510/HB 3035 compliance audits.
2. Priority Goal Formulation: Establishes quantifiable performance targets aimed at closing achievement gaps for identified subgroups, directly aligned with state 2035–2036 trajectory milestones.
3. Resource Directive: Directs restricted federal Title funds and state PSSP Step 7 instructional enhancement funds directly toward evidence-based core classroom interventions.
4. Action Step Execution: Executes structural reforms, such as master schedule redesigns under Policy 2510, deployment of ECCAT staff into K–3 classrooms, and staff implementation of WVTSS protocols.
5. Continuous Monitoring Loop: Institutes quarterly formative benchmark cycles incorporating administrative walkthroughs, interim literacy/math screeners, and WVEIS attendance parsing to evaluate intervention efficacy and trigger mid-course corrections.

By integrating multi-dimensional data across finance, student outcomes, and curriculum mandates into a unified analytical protocol, this framework replaces subjective observation with empirical, longitudinal analysis—securing an equitable, high-quality public education system for all West Virginia students.

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