Posts Tagged ‘IEP’

Data: The DNA of Education-based Decision Making

Thursday, March 12th, 2009

Policy makers, administrators and educators at all levels need sound data with which to make decisions.  Quality data enable decisions to be made with greater accuracy.  But the growing need for student achievement in the current standards-based environment has placed increasing demands on all of those involved with K to 12 education to obtain sound data with which not only to more fully understand their school systems but also to improve the quality of education. 

 

While there seems to be no lack of school-based data, what seems to be missing is data that are generally agreed upon to be sound or of good quality.  But discussions of data quality and their use with models usually brings to mind the adage of “garbage-in, garbage-out” because the quality of decisions made, the outcomes, is directly related to the quality of data used, the inputs.  According to Kowalski, Lasley, and Mahoney (2008) “unless those entering the data use exactly the same metrics, measures, or procedures, the realities of one school can be quite different from the realities of another, even though the data may look similar.  Because all fifty states use different tests, measures, and approaches, a real absence of common metrics exists and that void makes it difficult for educators, even psychometrically astute ones, to make good judgments based on published data.”  

 

The key to school improvement is improved data-relevance.  Therefore, it is crucial to understand how data are collected, aggregated, analyzed, reported and used.  But this may sound easier than it is because data come in many forms, at many levels, and is often unconnected or is connected from the individual district, school, classroom, teacher and student.  There are also different methods for data collection, aggregation, analysis and reporting. 

 

DNA is defined as the location where your body’s cells store coded information and the pairing of the DNA bases in the middle of the two strands or helices helps to keep the coded “data” intact.  Because data, like DNA, are so intertwined in the formulation of educational policy such as decision-making for funding formulas, the double helix that forms the structure of DNA might be the best way to depict our five-level model.  The DNA diagram below depicts how its coded “data” or information flows vertically, up and down its two congruent helices, as well as horizontally, across the base pairs. 

 

 

 

 

In our model the vertical dimension relate each level to the one above and below it.  The vertical dimension represents the ways in which the data bubble up and down between and among the various levels.  Using DNA’s double helix to exemplify our model, individual student test score data move up from the student in the classroom for collection at the school level before being aggregated at the district level and reported to the state Department of Education where the data are analyzed and transmitted to the federal level for nation-wide use.  The federal data, in turn, are disseminated back to the individual states for their use and, in turn, the states provide the information to their school districts for policy making purposes among other things.  The districts share the information with the schools within the district so that improved curriculum, operational and program student-centric decisions can be made. 

 

Just as the “base pairs” of DNA intersect the two “sugar phosphate backbones” or its two helices, our model’s horizontal dimensions form the important intersections with its two helices or data flow “backbones.”  Our model’s horizontal dimensions include the relationships, comparisons and uses within a level such as:  

 

  • Federal level:  Comparisons of the American educational system with those of other nations.
  • State level:  Comparisons of school systems between and among states.
  • District level:  Comparisons of local education authorities (LEA) or school districts with one another especially ones that share similar characteristics. 
  • School level:  Comparisons of different schools either within a state or across a number of states. 
  • Student level:  Comparisons of students according to various factors such as socio-economic status, race, gender, subject matter, and grade level. 

 

The dimensions and intersections of our model resemble those of DNA as data flow vertically, up and down the two congruent helices, as well as horizontally, across the levels as shown below for our model: 

 

 

 

 

 

 

School

Student

State

District

Federal

 

 

This study poses a five-level model for data building and data use that is intended not only to help gather the right types and “levels” of information but also to put the information where it is needed most and best used.  It examines the five key levels of education-based decisions as highlighted above, identifying the availability and limitations of data at those levels as well as how the data analysis might affect education at that level and throughout the system.  While decision-making depends on data, it is important to explain the limitations at each level and what might be done (for good or for bad) by creating more information at that level. 

 

 

Level 1:  Federal Data and Decision Making:  

 

The United States is beginning to create a national system of schools, with national accountability and nationally as well as internationally comparative data.  This is further necessitating more national standards, alignment of curriculum across the states, and new reliable data on how America’s schools are performing.  All nations of the world have information on their schools and many provide comparative studies.   

 

Federal level data are actually an aggregation of state level data such as data collected according to the No Child Left Behind (NCLB) Act, the National Assessment of Education Progress (NAEP) often referred to as “The Nation’s Report Card” and other state-level achievement tests.   “The Nation’s Report Card” is an aggregation and an analysis of the NAEP test results and the NCLB Act requires the NAEP testing of all students nation-wide in the near future.  NAEP provides a measure of how students in grades 4, 8 and 12 nation-wide are performing in mathematics, science, and language arts. 

 

The National Center for Education Statistics (NCES) holds a wealth of information on schools and student performance nation-wide particularly student demographic data and school district financial data.  The NCES also provides analyses of its data in such publications as the Education Statistics Quarterly, the annual Conditions of Education report, the Nation’s Report Card, the Digest of Education Statistics, and reports on selected current educational issues.

 

Level 2:  State Data and Decision Making:

 

States, through their departments of education, collect, aggregate and report data to the federal level as well as other levels through measures such as the NCLB, NAEP, and in New Jersey, the New Jersey Assessment of Skills and Knowledge (NJASK.)  The NJASK is a state assessment of public school student achievement in grades three to seven which is administered by the New Jersey Department of Education.  The NJASK is defined by the New Jersey Core Curriculum Content Standards (CCCS) in language arts, mathematics and science that was implemented to help meet the requirements of NCLB.  The NJASK test is given for up to two hours per day covering a three to five day time frame.  The questions are either multiple choice or ones requiring a written response. 

 

The New Jersey CCCS provide local school districts with benchmarks for student achievement of the skills the State of New Jersey expects its public school students to acquire during their K to 12 education in nine content areas.  These benchmarks set the levels which students should attain in the following areas: 

 

  • Visual and performing arts
  • Health and physical education
  • Language arts literacy
  • Mathematics
  • Science
  • Social studies
  • World languages
  • Technology
  • Career education, consumer, family, and life skills

 

The CCCS are “outcome statements” that form the basis of “strands” and “Cumulative Progress Indicators” (CPI).  Strands are defined as tools to help teachers identify content and skills.  Each strand is composed of a number of CPIs.  The CPIs provide the specific content and skills to be taught at the appropriate grade levels. 

 

Level 3:  District Data and Decision Making:

 

In all states except Hawaii, the Local Education Authority (LEA) or school district is the major decision-making setting.  The overwhelming majority of districts elect boards of education who in turn hire the superintendent as well as other staff and operate the school system within the LEA or district.  Hence, data gathered, analyzed and acted upon at the district level are critical to the system of control and accountability. 

 

Districts play a central role in collecting data as well as in using data to improve student achievement.  While nearly all districts nation-wide generate some sort of district “Report Card,” districts in New Jersey are key to the process of collecting, aggregating, reporting and using data through such measures as the: 

 

  • Grade Eight Proficiency Assessment (GEPA)
  • High School Proficiency Assessment (HSPA)
  • Advanced Placement (AP) program and tests
  • New Jersey Quality Single Accountability Continuum (NJQSAC)

 

A variety of tests are used to assess public school student achievement as well as to help improve public education through data collection in New Jersey school districts.  The GEPA is a standardized test administered to all New Jersey eighth graders on several subjects and is very similar to the HSPA.  As such, the GEPA is often referred to as the “preparation test” for the HSPA.  The HSPA is a standardized test administered during a four day period to all New Jersey high school students in their eleventh grade or junior year on language arts literacy and mathematics.  Public school students must pass the HSPA exams to graduate from high school in New Jersey.  The Advanced Placement (AP) program provides high school students with a way in which to earn college level credit depending how well they perform on the subject matter exams given for the AP level courses they attend. 

 

The system for monitoring and evaluating New Jersey’s public school districts is the New Jersey Quality Single Accountability Continuum (NJQSAC) which is often referred to as the “QSAC.”  QSAC replaced the Quality Annual Assurance Report (QAAR) beginning with the 2006-07 school year.  As a result it shifted the focus from primarily compliance to district, individual school and student improvement.  The QSAC combines a wide range of state monitoring requirements with those of the federal government into a “single” system of monitoring and evaluating school districts.  All New Jersey school districts must perform an annual self-assessment according to five key components:   

 

  • Instruction
  • Personnel
  • Financial management
  • Operations
  • Governance

 

The QSAC addressed the problem of a large number of significantly different and often conflicting state and federal monitoring and evaluating requirements.  The QSAC simplified the monitoring of district performance by forging one set of standards for all school districts as well as enabling districts to make their own adjustments more readily.  It also enables more informed school district comparisons through the use of a “continuum” on which all districts are rated. 

 

Level 4:  School Data and Decision Making: 

 

The school is the primary working unit for education and as such it is also the primary decision-making unit.  Many educators, central office staff and policy makers tend to believe that those closest to the classroom because of their daily access to students and their performance have a more in depth understanding of school-centric and student-centric data.  Therefore, those at the school level may be better positioned to make more informed decisions concerning educational programs and services than those at other levels especially at the state and federal Departments of Education.   Examples of school level measures include school “Report Cards” and Annual Yearly Progress (AYP).  

 

Level 5:  Student Data and Decision Making: 

 

Ultimately, the level of decision-making and analysis is the student:  the child is taught, supported, tested and reviewed in many ways.  Data are collected on students according to many factors including but not limited to subject matter, grade level, socio-economic status, race, gender, Limited English Proficiency (LEP), Advanced Placement as well as special education and Individual Education Plans (IEP).  

 

 

_______________________________

References

Kowaski, T. J., Lasley II, T. J., & Mahoney, J. W. (2008), Data-Driven Decisions and School Leadership: Best Practices for School Improvement, Boston: Allyn & Bacon.

State of New Jersey, Department of Education, web site. United States Library of Medicine, DNA Double Helix diagram.  

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Posted in Advanced Placement (AP), Annual Yearly Progress (AYP), data-based decision making, decision making, Grade Eight Proficiency Assessment (GEPA), High School Proficiency Assessment (HSPA), LEA, Local Education Authority (LEA), National Assessment of Education Progress (NAEP), National Center for Education Statistics, New Jersey Assessment of Skills and Knowledge (NJASK), New Jersey Core Curriculum Content Standards (CCCS), New Jersey Quality Single Accountability Continuum (NJQSAC), NJQSAC, No Child Left Behind (NCLB) Act | No Comments »

New Jersey’s Under-funded Education Mandates Hurt Public Education

Wednesday, December 31st, 2008

Under-funded state special education mandates are perhaps the primary reason why the cost of public school education continues to increase at a rate higher than the rate of inflation, causing property taxes to rise disproportionately to incomes in New Jersey.  According to the Garden State Coalition of Schools (GSCS, 2008), in New Jersey “mandates drive 70% of district expenses” and of these mandates, those for special education represent the fastest growing financial challenge confronting school districts.  Furthermore, these under-funded state mandates have heightened the pressure on school districts to fund operating budgets by reducing programs and services for regular education in order to fund mandate-protected programs and services, primarily special education.

 

School districts are required by state and federal laws to provide the special education programs and services included in a student’s Individual Education Plan (IEP); therefore, special education budgets cannot be cut and the under-funded portion of special education’s costs must be made up from other budgetary sources.  To offset the increased costs of under-funded special education mandates, school districts are increasingly forced to significantly reduce programs for regular education students because property tax increases have been limited largely through other state legislation.  Under-funded state special education mandates not only have sharply increased the competition between regular and special education programs for funding within a school’s budget but also have created sharp divisions within a school’s community because they pit the parents of special and regular education students against each other in the fight for funding.

 

In 2005, New Jersey state aid covered less than one-third of state mandated special education programs and services while the federal Individuals with Disabilities in Education Act (IDEA) is funded at approximately five percent of its cost to school districts nationwide.  Since January 2008, special education financial aid has been further and significantly reduced for most districts statewide based on the new state funding formula that reduces a school district’s special education aid calculation to the extent that its classification rate is above the state average.  In addition, wealthy districts have been losing entitlement aid for at-risk children, particularly special education as these and other categorical financial aid funds are now subjected to the formula’s wealth-equalizing local share calculation. 

 

All of this comes at a time when the costs for special education are skyrocketing.  Increased costs for mandated preschool programs including intensive services for autistic students and lower special education student to teacher ratios are a major part of the problem.  But more importantly there are also increasing numbers of costly out-of-district placements as well as parental lawsuits against public school districts for the purpose of obtaining private school placements for their children at the public’s expense.  

 

New Jersey has the highest proportion of special education students in out-of-district placements as well as the fourth highest classification rate for special education eligibility in the country.  Many of New Jersey’s school districts find that out-of-district placements can consume as much as 50% of the special education budget despite covering approximately ten percent of special education enrollment.  The students placed in out-of-district schools tend to be the most expensive because they are usually the ones most in need of special education programs and services.  Depending on the student’s disability, the annual cost of sending a student to an out-of-district private school can range from roughly $70,000 to over $250,000 especially for the most educationally and physically challenged students.  

 

The legal costs arising from parental special education-based law suits are another major expense for schools.  As parents have become more knowledgeable about what constitutes special education programs and services, they have increased their demands to have their children receive not only more intensive services as well as increasing their children’s classification but also more placements in private schools which have resulted in more parents suing school districts for these additional benefits.  New Jersey’s legal system, however, operates according to a fee shifting principle in which a school district losing in an administrative court not only must pay all of the judgment costs but also all of the plaintiff’s legal costs including those for their attorneys and expert witnesses regardless of the length of the trial.  Moreover, litigation for special education proceedings often takes longer than civil law suits – increasing both legal fees and court costs.  In addition, there is the cost resulting from the amount of time required of teachers, child study teams and administrators to appear in court rather than in school.  While school districts do settle a number of cases rather than run the risk of potentially more expensive outcomes, these settlements fuel the cost of providing special education.  Holding New Jersey school districts harmless from such law suits would be another way in which to enable school districts to allocate more of their scarce resources to student instruction.

 

The State of New Jersey requires special education programs for children with educational disabilities ages three to five, particularly autistic children.  While the only difference for preschool aged children is the state requirement to have a speech pathologist on the child study team, the same IEP, evaluation, eligibility, due process and “least restrictive environment” requirements apply for all special education students regardless of age.  These mandated pre-school programs put an additional expense burden on local school districts as long as the mandates continue to come without the requisite funding from the state. 

 

The special education students to teacher ratios are set by the State of New Jersey and they are, necessarily, lower than the student to teacher ratios for regular students.  These staffing ratios are based primarily on the student’s IEP, classification, and intensity of services required.  The student to teacher ratio for a class for children with the lowest level of disabilities having one teacher has a maximum of eight while the maximum is twelve for a class with one teacher and one aid.  Although ratios usually range from four to seven depending on the severity of the student’s disability, class sizes exceeding six students require two aids in addition to the teacher.  However, classes for children with autism and other profound cognitive disabilities are limited to a ratio of three to one.  While providing a good education for students with special needs, without the requisite state funding for these mandated levels, the higher costs of such low student to teacher ratios are often offset by higher student to teacher ratios for regular education.  Because smaller class sizes have been shown to improve learning for all students, the under-funded state mandates for special education can have a deleterious effect on regular student education.

 

When the State of New Jersey requires its public schools to pay for an ever increasing proportion of special education costs through its under-funded mandates, the state is not only forcing property taxes to grow faster than the rate of inflation but also pressuring districts to find the missing funds by reducing the regular education budget.  Such forced cuts to the regular education budget cause school districts to reduce the number of regular education teachers which results in much larger class sizes for regular education students.  Because larger class sizes have been shown to lead to lower test scores which make it more difficult for students and schools to achieve adequate yearly progress (AYP) as required by the No Child Left Behind (NCLB) Act.  As a result, school districts are much more likely to be subjected to many of the NCLB’s more stringent financial penalties.  This will further reduce the financial resources available to support quality education. 

 

Unless the people of New Jersey wish to have not only higher property taxes but also a downward spiral in the quality of their public education, then the State of New Jersey should pay the costs of its mandated school programs and services particularly special education.  If all of New Jersey’s special education mandates were fully funded the quality of the education of all of New Jersey’s public school students, both regular and special, would be the greatest beneficiary. 

 

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References:

Garden State Coalition of Schools (2008). Garden State Coalition of Schools Legislative FYI 5-16-08 http://www.gscschools.org  May 16, 2008. 

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Posted in home rule, IDEA, lean manufacturing, mandates, New Jersey, No Child Left Behind Act, property taxes, school finance, school reform, special education, state mandates | No Comments »