Educational Policy and its Impact on Teacher Preparation and Evaluation

in the United States and Puerto Rico

Summer Seminar College of Education

UPR –Rio Pierdas

June 15, 2016

Peter M. Vigil, PhD Associate Professor, Teacher Education Metropolitan State University of Denver pvigil7@msudenver.edu

Objetivos de la Sesión �  Los participantes desarrollarán una

comprensión de la “Every Student Succeeds Act“ (ESSA)

�  Los participantes serán capaces de identificar diferencias importantes en las políticas prescritas de ESSA en comparación con el anterior “No Child Left Behind"

�  Los participantes desarrollarán un entendimiento sobre el impacto potencial de ESSA en la preparación y la evaluación de los maestros en los EE.UU. y Puerto Rico

Presentation Objectives:

•  Par$cipants  will  develop  a  comprehensive  understanding  of  the  “Every  Student  Succeeds  Act”  (ESSA)  

•  Par$cipants  will  be  able  to  iden$fy  important  differences  in  the  prescribed  policies  of  ESSA  in  comparison  to  the  previous  “No-­‐Child  Le8  Behind  Act”  

•  Par$cipants  will  develop  an  understanding  on  the  poten$al  impact  of  ESSA  on  teacher  prepara$on  and  teacher  evalua$on  in  both  the  U.  S.  and  Puerto  Rico  

“Every Student Succeeds Act” (ESSA)

�  Firmado como ley Federal el 10 de Diciembre, 2015 �  Reautorización of the “Elementary and Secondary

Education Act de 1965, replaces the No Child Left Behind Act

�  Policy: Standards, Assessments, and Accountability �  La plena aplicación de ESSA en el año escolar

2017-2018 �  La elaboración de normas y el proceso de orientación

requiere la participación de las partes interesadas, con el desarrollo de un plan estatal para la implementación de políticas y programas

The “Elementary and Secondary Education Act” (ESEA) de 1965: un péndulo oscilante

�  ESSA es la versión más reciente de la ESEA firmado originalmente por Presidente L. B. Johnson en 1965

�  “War on Poverty” – Movimeinto de derechos civiles �  Title I, Title III, Title IV �  1970’s - strict federal rules and regulations guaranteed that funds would

be allocated solely to students in need – specifically students eligible for services based on socioeconomic status and academic achievement

�  1980’s - During  the  Reagan  Administra$on,  Congress  passed  the  Educa$on  Consolida$on  and  Improvement  Act  (ECIA)  in  1981  to  reduce  federal  regula$ons  of  Title  I.  

�  1990’s  -­‐    1994  Improving  America’s  Schools  Act  (IASA)  –added  math  and  language  arts  standards    for  accountability  

�  2000’s  -­‐    NCLB  required  increased  accountability  from  schools  both  from  the  teachers  and  from  the  students

Every Student Succeeds Act (ESSA): “Power to the States”

�  Mucho menos restrictivo que la ley NCLB �  Proporciona un mayor control sustancial en el nivel estatal

y local �  ESEA da a los estados y las escuelas más autoridad y

libertad para innovar �  Limita la autoridad de la Secretaría de Educación y el

Gobierno Federal �  Mantiene un enfoque en la rendición de cuentas de los

distritos y las escuelas

Every Student Succeeds Act (ESSA): Standards

�  Requiere rigurosos estándares estatales en matemáticas, lectura / lenguaje y la ciencia

�  Normas alternativas para los estudiantes con

discapacidades cognitivas significativas

�  Standards for English-language proficiency

�  Estados no están obligados a utilizar los “Common Core” standards

Every Student Succeeds Act (ESSA): Evaluacion (Assessment)

�  Las evaluaciones necesitan alinear con las normas (standards) del Estado

�  Matemáticas y lengua y artes Inglés en los grados 3-8 y una vez en la escuela secundaria (Elementary, Middle, High-school)

�  La ciencia cada vez en la escuela primaria, secundaria y preparatoria

�  Los estados pueden administrar evaluaciones como prueba única o como un conjunto de pruebas provisionales que se pueden enrollar en un único resultado anual para cada estudiante

Every Student Succeeds Act (ESSA): State Accountability

�  Achievement on State Tests (overall & disaggregated) �  Growth on State Tests (overall & disaggregated) �  Graduation Rates (overall & disaggregated) �  English Language Proficiency of ELLs �  Other School Quality or Student Success Indicator: ◦  Student Engagement; school climate; community engagement;

student access to advanced (AP classes)

�  95% Participation Rate: ◦  States will determine opt-out policies for state tests

Every Student Succeeds Act (ESSA): School Accountability

�  State is required to identify “Comprehensive Support Schools” once every three (3) years ◦  Lowest performing 5% of Title I Schools ◦  High schools with graduation rate below 67%

�  States notify districts of any comprehensive support schools

�  In partnership with stakeholders, districts must develop and implement a comprehensive support and improvement plan for each school

�  If a school does not meet the State’s exit criteria, it must implement more rigorous interventions, determined by the State

Every Student Succeeds Act (ESSA): English Language Learners

�  Los Estados deben elaborar normas (standards) para los estudiantes ELL que reflejan las habilidades de lenguaje y prácticas los ELLs deben participar con éxito en los estándares académicos

�  Los Estados deben administrar e informar sobre el rendimiento escolar anuales basados en estándares evaluaciones de dominio del idioma Inglés para los ELLs

�  Los Estados deben elaborar “exit-criteria” para los estudiantes ELL

�  Los estudiantes clasificados anteriormente como ELL deben ser incluidos en la presentación de informes y la rendición de cuentas, por un período de 4 años después de que hayan sido reclasificados.

Every Student Succeeds Act (ESSA): English Language Learners

�  Se ofrecen dos opciones para evaluar, informar, e incluir en la rendición de cuentas los ELLs recién llegados:

1.  Los Estados pueden excluir los ELLs recientemente llegaron de una administración de la evaluación de lectura / artes del lenguaje y evaluar e incorporar estos resultados de las pruebas de ELLs después de que hayan sido inscritos en una escuela de EE.UU. durante un año, como fue el caso en virtud de la ley NCLB

2.  La segunda opción requiere que los estados ponen a prueba los ELLs recién llegados y informe de resultados para los dos primeros años, pero permite a los Estados excluir los resultados de estos estudiantes desde el sistema de responsabilidad del estado en el primer año, incluir una medida de estudiante el crecimiento en el segundo año, e incluir el dominio en las evaluaciones académicas a partir de tercer año del estudiante en una escuela de EE.UU.

Every Student Succeeds Act (ESSA): Quality Instruction and Teacher Evaluation

�  ESSA eliminates “highly qualified teacher” requirement from No Child Left Behind: States  must  report  data  on  whether  low-­‐income  and  minority  students  are  being  served  at  dispropor$onate  rates  by  “ineffec<ve,  out-­‐of-­‐field,  or  inexperienced  teacher”    

�  ESSA da a los estados la capacidad para definir la definición de los siguientes:: ◦  “Teacher Effectiveness”: Student scores are NOT required to be

factored into teacher evaluation ◦  Teacher Preparacion Performance standards. Content exams, etc.

Colorado: The state of the State �  Common Core Standards: Embedded into new Colorado

Academic Standards �  New Assessments for new Standards ◦  Transitional Colorado Assessment Program (TCAP) ◦  Partnership for Assessment of Readiness for College and

Careers (PARCC) ◦  ACCESS for ELLs (WIDA)

�  SB 10-191 “Educator Effectiveness” ◦  50% multiple measure of student learning ◦  50% Professional Practice: Observation & PD

�  “Student Progress” and “Teacher Effectiveness” determined by ‘”Growth-model” system

Teacher Evaluation: Puerto Rico �  Departamento de Educaion de Puerto Rico �  http://www.de.gobierno.pr/

Value-added Models (VAM) �  Many states and school districts have adopted Value-

Added Models (VAMs) as part of educational accountability systems

�  The goal of these models is to estimate effects of

individual teachers or schools on student achievement while accounting for differences in student background.

�  VAMs are increasingly promoted or mandated as a

component in high-stakes decisions such as determining compensation, evaluating and ranking teachers, hiring or dismissing teachers, awarding tenure, and closing schools.

Value-added Models (VAM) �  El objetivo de estos modelos es estimar los

efectos de los maestros o escuelas individuales en el rendimiento estudiantil mientras cuenta las diferencias en la formación del estudiante

�  VAM (“Growth Model”) son promovidos como un componente obligatorio en las decisiones de altas apuestas, tales como la determinación de la compensación, la evaluación y la clasificación de los profesores, contratación o despido de los maestros, la concesión de la tenencia, y el cierre de las escuelas cada vez

VAM Statistical Methods �  Value-added models typically use a form of regression model

predicting student scores or growth on standardized tests from background variables (including prior test scores), with terms in the model for the teachers who have taught the student.

�  The model coefficients for the teachers are used to calculate their VAM scores.

�  In related models known as “growth models” a regression model is fit to predict students’ current test scores from previous test scores.

�  A percentile is calculated for each student from the model, relating his or her growth to the growth of other students with similar previous test scores.

�  The median or average of the percentiles of a teacher’s students is then used to calculate the teacher’s VAM score.

(ASA, 2014)

VAM Promises

� VAM results are often regarded as more objective or authoritative than other types of information because they:

� Are based on student outcomes, � Use complex quantitative statistical

models � Rely on standardized test scores and

common procedures for all teachers or schools.

VAM Problems Methodological �  Statistical Error Rate: there is a statistical error rate of 35 percent

when using one year’s worth of test data to measure a teacher’s effectiveness, and an error rate of 25 percent when using data from three years, researchers  (Schochet, P. Z. & Chiang, H. S. 2010)

�  Year-to-year Instability: value-added rankings of teachers fluctuate wildly from year to year (ASA 2014)

�  Non-Random Student Assignments �  “The assumptions required to obtain commonly estimated models and derive

econometric tests of those assumptions are easily rejected.” (Sass, et.al.2013, 2014 )

VAM Problems Logical �  VAMs typically measure correlation, not causation: Effects – positive or

negative – attributed to a teacher may actually be caused by other factors that are not captured in the model (ASA 2014)

�  The use of VAMs assumes “that student learning is measured by a given test, is influenced by the teacher alone, and is independent from the growth of classmates and other aspects of the classroom context.

(Darling, Hammond, L. 2012)

�  Most VAM studies find that teachers account for about 1% to 14% of the variability in test scores, and that the majority of opportunities for quality improvement are found in the system-level conditions.

(ASA 2014)

�  Fifty to 80 percent of any improvement or decline in a student’s standardized test scores can be attributed to one-time, randomly occurring factors (Kane & Staiger, 2002)

�  Model assumes/ attributes growth to individual teacher (homeroom/content)

Schoolview Data & Accountability Colorado Department of Education

� http://www.cde.state.co.us/schoolview/coloradogrowthmodel

� https://edx.cde.state.co.us/SchoolView/DataCenter/reports.jspx?_afrWindowMode=0&_afrLoop=235627037710306&_adf.ctrl-state=zn8fh9jdq_4

Colorado Growth Model Ratings 2014: Reading

School Rating  

% at/ above Proficient  

Growth

Percentile  

“White”  

“Economically Disadvantaged”  

“ELL”  

Students

w/ Disabilities  

1   99   61   80 %   3 %   4 %   4 %  

2   97   58   83 %   10 %   9 %   4%  

3   95   79   78 %   10 %   10 %   3 %  

4   92   51   83 %   8 %   4 %   7 %  

5   92   64   78 %   8 %   8 %   8 %  

6   90   79   74 %   6 %   5 %   6 %  

7   89   66   68 %   30 %   15 %   8 %  

8   89   65   85 %   13 %   4 %   7 %  

9   88   55   70 %   16 %   5 %   7 %  

10   88   56   56 %   30 %   5 %   3 %  

Colorado Growth Model Ratings 2014: Reading

School Rating  

% at/ above Proficient  

Growth

Percentile  

“White”  

“Economically

Disadvantaged”  

ELL  

“Students

w/ Disabilities”  

100   48   70   2 %   97 %   77 %   15 %  

101   35   36   1 %   96 %   48 %   9 %  

102   34   51   5 %   98 %   41 %   12 %  

103   34   39   4 %   95 %   48 %   10 %  

104   32   47   12 %   83 %   39 %   8 %  

105   30   36   3 %   97 %   36 %   20 %  

106   29   35   3 %   98 %   59 %   12 %  

107   28   47   3 %   97 %   67 %   10 %  

108   25   41   4 %   95 %   48 %   12 %  

109   25   42   1 %   95 %   60 %   8 %  

Colorado Growth Model Ratings 2014 : Math

School Rating  

% at/ above Proficient  

Growth

Percentile  

“White”  

“Economically Disadvantaged”  

“ELL”  

Students

w/ Disabilities  

1   96   82   78 %   10 %   10 %   3 %  

2   95   71   83 %   10 %   9 %   4 %  

3   93   61   83 %   8 %   4 %   7 %  

4   92   53   78 %   8 %   8 %   8 %  

5   91   57   85 %   13 %   4 %   7 %  

6   90   76   74 %   6 %   5 %   6 %  

7   89   63   70 %   16 %   5 %   7 %  

8   87   59   70 %   15 %   9 %   8 %  

9   87   52   68 %   30 %   15 %   8 %  

10   86   53   56 %   30 %   5 %   3 %  

Colorado Growth Model Ratings 2014: Math

School Rating  

% at/ above Proficient  

Growth

Percentile  

“White”  

“Economically

Disadvantaged”  

ELL  

Students

w/ Disabilities  

100   41   48   4 %   95 %   64 %   9 %  

101   38   40   22 %   78 %   17 %   14 %  

102   37   45   3 %   97 %   87 %   10 %  

103   37   43   4 %   95 %   48 %   10 %  

104   34   36   3 %   97 %   36 %   20 %  

105   33   40   12 %   83 %   39 %   8 %  

106   33   47   12 %   83 %   39 %   8 %  

107   32   41   2 %   97 %   77 %   15 %  

108   31   39   2 %   98 %   59 %   12 %  

109   24   34   4 %   95 %   48 %   12 %  

Tentative Timeline to implement ESEA (Colorado)

�  Enero- Abril (2016): Interpretacion de ley �  Mayo-Junio (2016): “Listening Tour” �  Julio – Sept. (2016): Escribiendo el Plan �  Sept. (2016) - Enero (2017): Modifcar el plan �  Feb. – Abril (2017): Aprobar el plan �  Implementar ESSA 2017-2018 año escolar �  We are working hard in Colorado to prepare for

2017-2018 implementation of ESSA �  ESSA addresses the authorization/ requirements NOT

the appropriations (e.g. funding levels) for various educational programs

References �  American Statistical Association (2014). ASA statement on using value-added models for

educational assessment. Retrieved from: https://www.amstat.org/policy/pdfs/ASA_VAM_Statement.pdf

�  Au, W. (2011). Neither fair nor accurate: Research-based reasons why high-stakes tests should not be used to evaluateachers.  Rethinking Schools. 

�  Darling-Hammond, L., Amrein-Beardsley, A., Haertel, E., & Rothstein, J. (2012). Evaluating teacher evaluation. Phi Delta Kappan, 93(6), 8-15. Retrieved from: http://www.kappanmagazine.org/content/93/6/8.full.pdf+html

�  Kane, J.T., & Staiger , D.O. (2002. Volatility in School Test Scores: Implications for Test-Based Accountability Systems. Brookings Papers on Education Policy. Retrieved from:

http://www.dartmouth.edu/~dstaiger/Papers/KaneStaiger_brookings2002.pdf

�  Sass, Tim R.; Semykina, Anastasia; Harris, Douglas N. (2014). Value-added models and the measure of teacher productivity Economics of Education Review,. Vol. 38, p9-23.

�  Schochet, P. Z. & Chiang, H. S. (2010). Error rates in measuring teacher and school performance based on student test score gains. Washington DC: U.S. Department of Education. Retrieved from: http://ies.ed.gov/ncee/pubs/20104004/

�  Colorado Department of Education; http://www.cde.state.co.us/

Recursos

� Read the Every Student Succeeds Act https://www.cde.state.co.us/fedprograms/essapdf �  US Department of Education http://www.ed.gov/ESSA �  Transitioning to the “Every Student Succeeds Act”

Frequently asked questions: http://www2.ed.gov/policy/elsec/leg/essa/faq/essatransitionfaqs050316.pdf