Resource 9: Sample State Plan to Ensure Equitable Access to Excellent Educators


Section 3. Equity Gap Exploration and Analysis



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Section 3. Equity Gap Exploration and Analysis

To ensure that our equitable access work is data-driven we have relied on multiple data sources that we intend to improve upon over time. As we have worked with our stakeholder groups, their perspectives have shed greater light on the data and helped us gain a better understanding of the root causes for our equity gaps and our strategies, including unintended consequences or likely implementation challenges for certain strategies.

State A has been concerned with providing equitable access to excellent educators for several years, and our efforts to date appear to be showing results. At this time, more than 98 percent of the teachers of core academic subjects in State A fully meet the federal definition of “highly qualified teacher” (HQT) and local conditions and limitations account for the remaining 2 percent.1

Nevertheless, State A recognizes that HQT is not a strong indicator of effectiveness and that we still have a long way to go to achieving our equitable access goals. Data from the State A Public Educator Data System (our state system for collecting, analyzing, and reporting data on public school teachers, administrators, and other staff) indicate that schools with high concentrations of minority students and students from low-income families have significantly higher teacher and leader turnover (and, relatedly, inexperienced teachers) than schools with low concentrations of those students. When our State A Educator Effectiveness Evaluation System is fully operational in 2015–16, we will be able to analyze and may identify similar gaps in teacher and leader effectiveness. Our State Plan to Ensure Equitable Access to Excellent Educators provides a comprehensive strategy for state and local action to eliminate these gaps.

Definitions and Metrics

Our 2006 educator equity plan focused primarily on HQT status. In contrast, the current plan focuses instead on ensuring that all classrooms are taught by “excellent” teachers, who in turn are supported by “excellent” leaders. Recognizing that there are multiple important dimensions of educator effectiveness (e.g., qualifications, expertise, performance, and effectiveness in improving student academic achievement and social-emotional wellbeing), State A has defined excellent educators as follows:

An excellent teacher is fully prepared to teach in his or her assigned content area, is able to demonstrate strong instructional practices and significant contributions to growth in student learning (on tests and in terms of social-emotional indicators), and consistently demonstrates professionalism and a dedication to the profession both within and outside of the classroom.

An excellent school leader is fully prepared to lead both instructionally and administratively, is able to demonstrate strong leadership practices and significant contributions to growth in student learning (on student tests and in terms of social-emotional indicators), and consistently demonstrates professionalism and a dedication to the profession both within and outside of the classroom.

Because of the challenges associated with accurately and consistently capturing these qualities statewide, in selecting metrics to capture educator effectiveness ADOE has elected to err on comprehensiveness over simplicity. Rather than select a single metric, we will consider equitable access in terms of the following characteristics of teachers and leaders as well as their teaching and learning conditions:


Teacher and Principal Evaluation Ratings. These ratings capture most of the qualities noted above for effective educators. We will report both on educators rated ineffective as well as educators rated highly effective in order to tell a complete story about access to excellent teachers and leaders in our state. Our approach is to go through a validation process with an external organization to conduct an empirical study of fidelity of implementation, fairness and accuracy, and cost efficiency. As a complement, we will meet with stakeholders to assess their level of trust and satisfaction with the system and then use that feedback to continue to modify and tweak the system. When we judge that the evidence suggests the evaluation system is accurate, we will transition to using that data for State A equitable access planning.

Unqualified Teachers. Until our Educator Effectiveness Evaluation System has been revised and implemented for a full year, we will report on unqualified teachers as defined by lacking at least a bachelor’s degree, lacking full licensure, HQT status, or working under an emergency license.

Teacher and Principal Turnover. A three-year average of teacher and principal turnover rates reported at the school and district levels will serve as another indicator of equitable access. Recognizing that some turnover is acceptable, one of our goals for future data collection is to disaggregate our turnover data to depict only those leaving the profession or moving to another district. When our educator evaluation system is considered accurate, we also will disaggregate our turnover data so that we can differentiate between turnover of effective and ineffective educators.

Teacher and Principal Experience. The prevalence of teachers and principals with one or less years of experience or less than four years of experience will serve as other indicators of equitable access. We think both indicators (one or less years as an indicator and less than four years as another indicator) are important. Because or state’s data system captures only experience within State A as a regular classroom teacher, one of our plans for future data collection is to refine how experience data are documented.


Out-of-Field Teaching. Out-of-field assignment for preparation and licensure will be defined as being currently assigned to teach a subject and/or grade that one is not prepared or licensed to teach, and will indicate teachers’ preparedness to teach in their subject area.

Teacher Licensure Exam Scores. A three-year average of schools’ teacher license exam test scores will serve as another indication of relative preparedness to teach in their subject area.

Teacher and Principal Absenteeism. Schools and districts that consistently have high teacher and principal absenteeism on average over a three-year period will serve as another indicator of students’ access to effective teachers and leaders. In particular, we will look at schools and districts with average absenteeism of more than 10 days per school year.

Participation in Professional Learning Opportunities. We define this as a count of both the number of learning events that educators have participated in throughout the year that are aligned with explicitly written or discussed professional learning goals, as well as the amount of funding provided to support the educator’s participation in the activities. .This metric serves as an indication of the level of support provided to teachers and how that support is distributed within a district.

Per-Pupil Funding and the Results of the Statewide School Climate Survey. These indicators can help describe teaching and learning conditions across schools and districts.

Teacher Salaries. Data on salaries offered by State A’s LEAs have important implications for their ability to recruit and retain enough excellent teachers for all students.

To identify State A’s equity gaps, we further defined “low-income” students as those whose families meet the federal poverty level as defined by the U.S. Census,2 and “students of color” as students identified as a member of a minority race or ethnicity (e.g., African American, Hispanic, Asian, Native American, Pacific Islander/Alaskan Native). We recognize that teacher and leader effectiveness for students who are English language learners, homeless or in foster care, in isolated rural schools, tribal areas, or in the migrant agricultural stream (to name a few) is critically important. We believe that the action steps laid out in this plan will benefit all students―not just the ones specifically focused on as part of the plan.


Exploration of the Data

Data Sources. For this analysis, we used a variety of data sources, which have been pulled into a single longitudinal data system that can keep data over time without overwriting old data. Our state longitudinal data system includes data from our annual school climate surveys, our human resources system, and district-level attendance system. In order to create our integrated data system, our lead data and human resources staff worked in close collaboration to resolve any complications arising from combining disparate data systems. In addition, we relied on the expertise of our legal staff to ensure all relevant laws were taken into account.

We conducted several preliminary analyses. To start, we looked at equity gaps for numerous metrics where schools are the unit of analysis for low-income students, minority students, and students with disabilities. Next, we focused on the three statutory teacher metrics (i.e., experience, qualifications, and out-of-field assignments) across schools in the state, across districts in the state, and finally schools within districts in the state.

We chose to use quartiles to divide “low-income” and “high-income” schools. As a result of the fact that the majority of our low-income students are concentrated in large urban schools, the low-income group was slightly larger in number of teachers and principals. As we examined these metrics at different levels, we continued to take into account the size of the underlying subpopulation under consideration.

Table 1 depicts the equity gaps in State A. We chose to focus on equity gaps by schools in our state in our first round of analysis because district-level analyses may mask large disparities across schools. We chose to explore equity gaps for the three groups specified in ESEA: low-income students, students of color, and students with disabilities.


Table 1. State A Equity Gaps in School Year 2014–15

School Type1

Teacher Data2

Principal Data3

%
Unqualified Teachers


%
Teacher Turnover4


%
Teachers
<1 Year of
Experience


%
Teachers
<4 Years of Experience


%
Teachers Out of Field4


%
Teachers Absent
>10 days4


% Teachers Satisfied With School Climate

%
Principal Turnover


%
Principals
<1 Year of Experience


%
Principals
Absent
>10 days


All Schools

(Nt=120,000

Np=3,000)


0.8

(N=1,000)



8.2

(N=9,800)



6.2

(N=7,400)



14.1

(N=16,900)



4.2

(N=5,000)



10.4

(N=12,500)



67.3

(N=80,800)



8.7

(N=260)



4.7

(N=140)



4.21

(N=130)



Schools in the Top Quartile of Low-Income Students

(Nt=36,000

Np=750)

1.2

(N=400)



16.3

(N=5,900)



9.1

(N=3,300)


25.3

(N=9,100)


5.6

(N=2,000)



16.1

(N=5,800)



41.3

(N=14,900)



15.2

(N=110)



8.9

(N=70)



5.3

(N=40)



Schools in the Bottom Quartile of Low-Income Students

(Nt=24,000

Np=750)

0.6

(N=100)



4.8

(N=1,200)



3.2

(N=800)



8.7

(N=2,100)



3.1

(N=700)



6.3

(N=1,500)



88.1

(N=21,100)


3.8

(N=30)


2.4

(N=20)



2.2

(N=20)



Income equity gap

0.6

11.5

5.9

16.6

2.5

9.8

46.8

11.4

6.5

3.1

Schools in the Top Quartile of Students of Color

(Nt=31,000

Np=750)

1.1

(N=300)



14.7

(N=4,600)



10.0

(N=3,100)

24.2

(N=7,500)



4.9

(N=1,500)



14.5

(N=4,500)



58.4

(N=18,100)



12.5

(N=90)



6.8

(N=50)



5.3

(N=40)



Schools in the Bottom Quartile of Students of Color

(Nt=30,000

Np=750)

0.7

(N=200)



5.4

(N=1,600)



4.1

(N=1,200)



10.9

(N=3,300)



2.8

(N=800)

6.5

(N=2,000)



76.9

(N=23,100)



7.0

(N=50)



3.1

(N=20)



3.8

(N=30)



Minority equity gap

0.4

9.3

5.9

13.3

2.1

8.0

18.5

5.5

3.7

1.5

Schools in the Top Quintile of Students With Disabilities

(Nt=27,000

Np=600)

1.3

(N=400)



12.9

(N=3,500)



8.6

(N=2,300)



19.3

(N=5,200)



5.1

(N=1,400)



16.4

(N=4,400)



63.6

(N=17,200)



11.5

(N=70)



7.1

(N=40)



4.4

(N=30)



Schools in the Bottom 5th Percentile of Students With Disabilities

(Nt=6,000)

Np=150)

0.6

(N<100)



6.1

(N=400)

3.7

(N=200)



9.2

(N=600)



2.6

(N=200)



4.2

(N=300)



80.5

(N=4,800)



6.8

(N=10)



2.9

(N<10)



3.1

(N<10)



Students with disabilities equity gap

0.7

6.8

4.9

10.1

2.5

12.2

-16.9

4.7

4.2


1.3

Source: State A Public Educator Data System. Longitudinal data system brings in data from school climate survey, human resources data system on teacher experience, turnover, and district-level attendance system.

Note: Data on teacher licensure exam scores, access to professional learning opportunities, salaries, and per-pupil funding are pending further review and will be added in an addendum no later than August 2015.

1 Nt denotes the total number of teachers for each group, Np denotes the total number of principals for each group.

2 N values denote the number of teachers, rounded to the nearest ten.

3 N values denote the number of principals, rounded to the nearest hundred.

4 Turnover, “out-of-field,” and absenteeism data are based on a three-year average.

Equity Gap Analysis

Our data reveal that an equity gap exists for every metric we included in our analyses for all three subgroups we investigated (low-income students, minority students, and students with special needs). The size (in absolute value) of the gaps vary, from 0.4 percent for unqualified teachers in high- versus low-minority schools, to 46.8 percent for teachers satisfied with their school climate in low- versus high-income schools.

The most challenging conversation for our team was about what constitutes a significant or important gap that we should be addressing. This decision is very dependent upon our state’s unique characteristics and the local context in our districts. That said, we have conferred with neighboring states to help us think about how we might define significant gaps for our state. Based on our discussions with stakeholders, our understanding of available data, we made determinations as best we could about what gaps were of concern and highest priority for our state.

To better understand the significance of the gaps, in addition to the percentage differences for each metric for each subgroup, we also looked at the ratio of the percentages. For example, we found that the percentage of unqualified teachers is twice as large in low-income schools compared to high-income schools. We found that the smallest ratio was the difference in the percentage of teachers satisfied with their school climate (1.3 times higher in schools with low numbers of students with disabilities [SWDs]), and the largest ratio was the difference in the percentage of principals leaving their schools (the proportion of principals leaving their schools is 4.0 times higher in low-income schools in comparison to high-income schools).

Table 2 summarizes the percentage differences and percent ratios for the three equity gaps in the ESEA statute for all three subgroups:


Table 2. Percentage Difference and Ratio of Percentages for Three Statutory Teacher Metrics Across Schools in the State




Unqualified Teachers

Inexperienced Teachers
(<4 years of experience)


Out-of-Field Teachers

School Type

Percent Difference

Percent Ratio

Percent Difference

Percent Ratio

Percent Difference

Percent Ratio

Low- vs. High- Income Schools

0.6%

2.0 times as large

2.5%

1.8 times as large

16.6%

2.9 times as large

High- vs. Low- Minority Schools

0.4%


1.6 times as large

2.1%

1.8 times as large

13.3%

2.2 times as large

High- vs. Low-SWD Schools

0.7%

2.2 times as large

2.5%

2.0 times as large

10.1%

2.1 times as large

From Table 2, we can see that the percentage difference and percentage ratio are largest for out-of-field teachers for low- vs. high-income schools. In general, the percentage differences are smallest for the unqualified teacher metric.

We then conducted similar analyses across districts instead of schools (see Table 3). We think it’s important to know which districts should be the focus of our attention in this work:


Table 3. Percentage Difference and Ratio of Percentages for Three Statutory Teacher Metrics Across Districts in the State


Unqualified Teachers


Inexperienced Teachers

(<4 years of experience)

Out-of-Field Teachers

District Type

Percent Difference

Percent Ratio

Percent Difference

Percent Ratio

Percent Difference

Percent Ratio

Low- vs. High- Income Districts

0.7%

2.8 times as large

6.2%

3 times as large

19.1%

3.4 times as large

High- vs. Low- Minority Districts

0.8%

2.6 times as large

7.6%

3.4 times as large

16.3%

2.7 times as large

High- vs. Low-SWD Districts

0.9%


2.8 times as large

5.3%

2.5 times as large

13.5%

2.8 times as large

We also looked at the data by school level, focusing on low- versus high-income schools (see Table 4):

Table 4. Percentage Difference and Ratio of Percentages for Three Statutory Teacher Metrics Across Schools in the State by School Level for Low- Versus High-Income Schools




Unqualified Teachers

Inexperienced Teachers

(<4 years of experience)

Out-of-Field Teachers

School Level

Percent Difference

Percent Ratio

Percent Difference

Percent Ratio

Percent Difference

Percent Ratio


Low- vs. High- Income Elementary Schools

0.6%

2.2 times as large

5.7%

2.7 times as large

5.3%

1.7 times as large

Low- vs. High- Income Middle Schools

0.9%

3.25 times as large

6.4%

3.1 times as large

18.1%

3.4 times as large

Low- vs. High-Income High Schools

0.7%

2.2 times as large

5.5%

2.6 times as large

16.3%

2.9 times as large

Finally, we looked at the data for low- versus high-income schools within each of the three school districts we identified as having the largest equity gaps (see Table 5):

Table 5. Percent Difference and Ratio of Percentages for Three Statutory Teacher Metrics Across Schools by District for Low- Versus High-Income Schools





Unqualified Teachers

Inexperienced Teachers

Out-of-Field Teachers

Top Three Districts

Percent Difference

Percent Ratio

Percent Difference

Percent Ratio

Percent Difference

Percent Ratio

Low- vs. High- Income Schools in District A

1.2%

3 times as large

8.1%

2.6 times as large

17.9%

3.2 times as large

Low- vs. High- Income Schools in District B

0.9%

2.8 times as large

10.1%

2.9 times as large


20.1%

3.4 times as large

Low- vs. High- Income Schools in District C

0.8%

2.6 times as large

16.1%

6.0 times as large

25.3%

4.2 times as large

In addition to these high-priority metrics, we also highlighted some additional equity gaps that we think are important to consider for our state.

Equity Gap 1: Educator Turnover. State A has an 11.5 percentage point equity gap in teacher turnover, using a three-year average, with regard to low-income students, a 9.3 percentage point equity gap in teacher turnover with regard to students of color, and a 6.8 percentage point equity gap in teacher turnover with regard to students with disabilities. The gaps in principal turnover are similar with regard to low-income students, an 11.4 percentage point equity gap. They also are evident with regard to students of color and students with disabilities, though slightly smaller, 5.5 percentage point equity gap and 4.7 percentage point gap equity respectively. We see educator turnover as our primary equity gap.

Equity Gap 2: First-Year Teachers. State A has a 5.9 percentage point equity gap in first-year teachers (16.6 percentage points for teachers within their first three years) with regard to low-income students, a 5.9 percentage point equity gap in first-year teachers (13.3 percentage points for teachers within their first three years) with regard to students of color, and a 4.9 percentage point equity gap in first-year teachers (10.1 percentage points for teachers within their first three years) with regard to students with disabilities.


Equity Gap 3: Educator Absenteeism. State A has a 9.8 percentage point equity gap in teacher absenteeism with regard to low-income students, an 8.0 percentage point equity gap in teacher absenteeism with regard to students of color, and a 12.2 percentage point equity gap in teacher absenteeism with regard to students with disabilities. When we look at principal absenteeism, we find much smaller gaps: 3.1 percentage point equity gap, 1.5 percentage point equity gap, and 1.3 percentage point equity gap respectively.

Equity Gap 4: Teacher Satisfaction in School Climate. State A has a 46.8 percentage point equity gap in teacher satisfaction with school climate between low-income and high-income schools, an 18.5 percentage point equity gap in in satisfaction with school climate between schools with high and low proportions of students of color, and a 16.9 percentage point equity gap in teacher satisfaction with school climate between schools with high and low proportions of students with disabilities. In particular, teachers in these schools identified the lack of effective leadership and high leadership turnover as the biggest challenge that needs to be addressed, according to our school climate survey.




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