Educator Workforce POC Project

Essential Question 1

Hiring Summary/Vacancies

Table of Contents

Essential Question (EQ)        3

Reason and Category        3

Needs Statement        3

Use Case Audience        4

Narrative        4

Current State        5

Future State        6

Decision Process        7

Data Element Table - Dissection and Analysis        8

Metrics and parameters        9

Essential Question (EQ)

FOCUS AREA: Hiring Pipeline - How do educator 1 vacancies 2 vary across our district/Education Service Agency (ESA)? 3

1 Any educator with a unique identifier (including paraprofessionals)

2 Needs to be derived from source HR system

3 Disaggregated by assignment type, assignment category, and campus (for districts)/districts (for ESA)

Reason and Category

This section will describe how to leverage the data as it relates to the identified essential question.

Inform Strategic Planning: To guide decision-making and strategic planning for hiring, resource allocation, and targeted recruitment efforts to address specific needs within the district/ESA.

Identify Patterns and Trends: To understand the distribution of educator vacancies across different schools or regions within the district/ESA, helping to identify patterns or trends that may indicate systemic issues or areas in need of intervention.

Equity and Resource Allocation: To assess if there are disparities in staffing that could affect educational equity, ensuring that all students have access to quality educators regardless of location.

Support Advocacy and Policy Development: To provide data that can support advocacy for policy changes, funding allocations, or initiatives aimed at reducing vacancies and improving working conditions for educators.

These points collectively drive the investigation into how educator vacancies vary and inform actionable steps to improve staffing levels across the district or education service agency (ESA).

Needs Statement

Visualizing and reporting on the Essential Question provides a clear and actionable snapshot of where staffing gaps exist. For example, if data shows that high-poverty schools have a significantly higher rate of vacancies compared to other schools, this insight highlights inequities that could directly impact student learning and achievement.

By answering this EQ, LEAs and ESAs can target their efforts more effectively, such as by allocating additional resources, implementing targeted recruitment strategies, or offering incentives to attract educators to the most affected areas. This data-driven approach helps ensure that all schools are adequately staffed, thereby improving the overall quality of education and supporting equitable student outcomes across the district or ESA. Moreover, regular visualization of this data can track the effectiveness of implemented strategies, enabling continuous improvement and more responsive program adjustments.

Use Case Audience

This section lists the roles that would ask this EQ and/or access this report and visual.

• District/ESA Superintendents: To oversee and address staffing needs across the entire district or ESA, ensuring that all schools have the necessary personnel to operate effectively.
• Human Resources Directors: To inform recruitment and retention strategies, identify critical shortage areas, and plan for targeted hiring efforts.
• School Principals and Administrators: To understand staffing challenges at their specific schools and advocate for additional support or resources.
• Program Evaluators and Data Analysts: To analyze trends and provide insights that guide strategic planning and resource allocation.
• Instructional Leaders and Curriculum Coordinators: To assess how staffing shortages might impact the delivery of curriculum and instruction, and to plan for compensatory measures if needed.

Narrative

The need to answer the EQ typically arises in contexts where educational leaders and stakeholders are grappling with challenges related to staffing shortages, resource allocation, and educational equity. Some specific situations include:

• Strategic Planning and Budgeting Cycles: During annual or bi-annual strategic planning sessions, LEAs and ESAs assess staffing needs to make informed decisions about budget allocations for hiring, professional development, or incentive programs aimed at addressing educator shortages.
• Policy Development and Advocacy: In discussions around new policy initiatives or advocacy efforts, such as those aimed at increasing teacher retention or addressing teacher burnout, understanding where vacancies are most pronounced provides crucial evidence to support proposed changes.
• Grant Applications and Funding Opportunities: When applying for grants or other funding opportunities, districts often need to demonstrate need and outline how they will use resources to address gaps, making a clear understanding of educator vacancies essential for compelling applications.

Current State

This section describes how the data or information for this EQ is addressed currently by LEAs.

Currently, local education agencies (LEAs) often address the Essential Question through a combination of methods, though practices can vary significantly depending on the size, resources, and data management capabilities of the LEA. Here's how the data or information for this EQ is typically handled:

• Manual Data Collection: In many LEAs, especially smaller or resource-constrained ones, data on educator vacancies is often collected manually. This can involve school administrators or HR personnel submitting vacancy reports through email, paper forms, or basic data entry into shared drives. This method is time-consuming, prone to errors, and can result in outdated information.
• Spreadsheets and Local Databases: Some LEAs utilize spreadsheets, such as Microsoft Excel or Google Sheets, to track and compile vacancy data. These spreadsheets may be updated periodically by HR departments, school sites, or district offices. While this method offers more organization than manual tracking, it still presents challenges in data consistency, real-time accuracy, and the ability to analyze trends comprehensively.
• Decentralized Systems: In larger LEAs, vacancy data may be collected in a decentralized manner, with each school or department maintaining its own records. This can lead to inconsistencies in data formats, reporting frequencies, and challenges in aggregating data across the district or ESA for a comprehensive view.
• Use of HR Management Systems: More advanced LEAs may leverage HR management systems or software platforms (e.g., Frontline ERP, PowerSchool, or other district-specific HRIS systems) that can track vacancies more systematically. These systems can capture vacancy data more accurately and provide dashboards or reports that visualize the information. However, the extent to which this data is utilized for strategic decision-making can vary.
• Data Not Compiled Systematically: In some cases, especially in districts that do not prioritize data-driven approaches or lack the infrastructure, vacancy data may not be compiled systematically at all. This can result in significant gaps in understanding the true extent of educator vacancies, leading to reactive rather than proactive approaches to addressing staffing needs.

Overall, while some LEAs have developed more sophisticated methods for tracking and analyzing educator vacancies, many still rely on fragmented or manual processes. This limits their ability to use vacancy data effectively for strategic planning, equity initiatives, and improving educational outcomes.

Future State

This section describes how operationalizing and visualizing this EQ will improve reporting, help the LEA to improve, and advance quality decision making.

Enhanced Reporting and Transparency

• Consistent Data Collection: By operationalizing this EQ, LEAs can establish standardized methods for collecting and reporting vacancy data across all campuses. This consistency reduces data discrepancies and ensures that all stakeholders are working with the same accurate and up-to-date information.
• Clear Visualizations: Visualizing data through dashboards makes it easier to identify trends, patterns, and outliers.
• Regular Updates: Automated data collection and visualization allow for regular updates, giving a snapshot of vacancies as they evolve. This enables more responsive action, such as deploying substitute teachers or adjusting recruitment strategies.

Improvement of LEA Programs and Interventions

• Targeted Resource Allocation: Visualizing vacancy data allows LEAs to pinpoint where staffing shortages are most acute and allocate resources, such as additional funding or targeted recruitment efforts, more effectively. This ensures that interventions are focused on the areas with the greatest need, maximizing impact.
• Program Evaluation and Adjustment: LEAs can use vacancy data to evaluate the effectiveness of current programs, such as incentive schemes for hard-to-staff schools. If visual data shows persistent vacancies in certain areas despite interventions, LEAs can adjust their strategies based on evidence rather than assumptions.

Advancing Quality Decision-Making

• Informed Strategic Planning: Operationalizing this EQ provides decision-makers with a clear, data-driven foundation for strategic planning. Whether setting hiring goals, crafting retention strategies, or advocating for policy changes, having a comprehensive view of vacancies supports decisions that are aligned with the district's broader educational goals.
• Proactive Risk Management: Instead of reacting to staffing shortages as they arise, LEAs can use visualized vacancy data to anticipate and address potential issues before they escalate. This proactive approach can help prevent disruptions in the classroom and maintain a stable learning environment for students.

Strengthening Partnerships with Education Service Agencies (ESA)

• Better Alignment with Certification Programs: ESAs can use vacancy data to align their certification programs with the specific needs of LEAs, ensuring that educators in training are prepared to fill critical shortage areas like STEM, special education, or bilingual education. This alignment reduces mismatches between available candidates and open positions.
• Enhanced Candidate Recruitment: By partnering with ESAs, LEAs can leverage centralized recruitment efforts that are informed by vacancy data. ESAs can focus outreach and training efforts on candidates suited to address the most pressing needs in local districts.
• Improved Collaboration: Operationalizing this EQ fosters stronger collaboration between LEAs and ESAs. For example, vacancy trends can guide joint initiatives, such as targeted retention programs or specialized teacher preparation tracks, to build a robust and sustainable educator pipeline.
• Strategic Partnerships: Visualized data helps ESAs and LEAs work together more effectively by identifying trends and opportunities to address systemic challenges, such as long-term shortages in rural areas or high-need schools.

Decision Process

List the steps, decision points, business rules, and process for answering this EQ included identifying:

• What data will be used? How will it be filtered or disaggregated?

• LEA staff data (required by state reporting).
• Data will be filtered and/or disaggregated by:

• Assignment Type
• Assignment Category
• Campus (for districts) / District (for ESA)

• Are there benchmarks, cut points or other markers that will need to be determined?

• No, there are no benchmarks or cut points for this use case.

• Is the information required to be collected over time? Are there implications due to time? How often will this data be refreshed?

• State Education Agency employment data are typically submitted annually in mid- to late fall
• Dashboard data will be refreshed at a minimum quarterly (fall, winter, spring, summer snapshots) using API integrations separate from the annual submission.

• What is the time span for this EQ?

• The most recent three years.

• Will data be compared to other data?  Is the data comparable or must the data be normalized?

• No, the data will not be compared to other data and do not need to be normalized.
• All LEAs submit data to the SEA following the same business rules, so data are comparable if a need arises to compare data across LEAs.

• Are there key differences between the current state and the future reporting?

• N/A

• What are the source systems for the data required to answer this EQ?

• LEA
• HR System

• Are there any data limitations to be considered?

• Data Timeliness:  Data may have a lag, and updates are not always real-time.
• Data Completeness: Data (especially state reporting required) may not capture all nuances of local hiring challenges, such as temporary fills or part-time gaps; for example, snapshot data will miss vacancies that appear and are filled between snapshots.
• Data Consistency: Variability in how districts report data can lead to inconsistencies.

Data Element Table - Dissection and Analysis 

Notes:

• Mapping and notes on gaps are based on State Education Agency reporting business rules. If LEAs choose to apply different rules for their needs, then some of the Ed-Fi resource mappings may need to be reevaluated.
• Ed-Fi Entity Mapping column uses Ed-Fi ODS / API Suite 3 v7.2 as reference
• Some data elements are included even though they don’t appear in the dashboard mockup because they are required properties of an Ed-Fi Resource.
• Assumes all Education Organizations have been loaded appropriately in the ODS/API e.g. schools, localEducationAgencies, educationServiceCenters, and stateEducationAgencies

Metrics and parameters

Notes:

• The definition/business rules are implemented within the dashboard tool so that it is consistent across all education agencies.