Leave No Child or Teacher Behind

Fort Lauderdale, Florida - It is remarkable the work that the U.S. Department of Education (DOE) makes to achieve the vision of not leaving a child behind. But is this what is really happening? Are we preparing our children accordingly in education for global competitiveness? The mission of the U.S. Department of Education is to promote student achievement by fostering educational excellence and to ensure that every child gets equal access to the best education possible. This effort is federal mandated by the No Child Left Behind Act of 2001 (NCLB) and the Obama Administration's blueprint for reauthorizing the Elementary and Secondary Education Act. The NCLB Act requires that schools close academic gaps between economically disadvantaged students and students who are from different racial, and ethnic backgrounds as well as students with disabilities. 

When I think about the “No Child Left Behind” Act, I am reminded of the heroic stories of the US soldiers described in the book of “Leave No Man Behind [LNMB]: The Saga of Combat Search and Rescue," written by George Galdorisi and Thomas Phillips in 2008. The NCLB title should inspire every administrator and educator to rescue and help each child in the classroom just as the LNMB moved our soldiers to rescue their fellow American soldiers who may have fallen injured and left behind during a combat mission.  

Once I read the title of the act “No Child Left Behind”, one would draw a fast conclusion that we are providing and exhausting all possible resources to help each child within their learning careers, according to the skills and abilities that they have been born with. Yet, the question remains, are we? The intention of this law is to improve each child’s learning growth. But is this really what is happening? In order to accomplish the U.S. Department of Education’s vision, the NCLB Act supports that each states’ public education enforces more rigors and accountability through the incorporation of high standards, standards based instruction, annual standardized assessments, teacher performance, and the establishment of measurable objectives. 

What perplexes most administrators is what types of resources can be used at the schools to ensure that the schools do not leave any child behind? The NCLB Act emphasizes the importance of using data to improve learning methods and meet student needs. Therefore, the incredible amount of testing data that we produce every year is the best leading source that we have available. The correct selection of data and technology may lead us to achieve the expected students learning results.

It has been proven that by using modern technology and the ingenuity of well-educated scientists and engineers, that we can reach the Moon, build a Space Station and connect the world electronically through the Internet, providing even more evidence that we, as society, can overcome the greatest of insurmountable tasks. We see stronger evidence of the effective use of data interpretation and analysis when used by award winning scientists who provide factual data of Einstein’s predictions of the theory of relativity and the gravitational waves; where the scientific community uses and relates this data with the origins of the universe.  If we, as society, can reach space and decipher the secrets of the universe, then we have proven that we have the factual potentiality to achieve better student academic outcomes. 

Now that the educational sector has sufficient student’s testing data, we can effectively analyze the data and use the outcomes to address each student’s yearly growth. Using data on student progress is crucial for schools and educators to make decisions regarding future growth, strategies implementation, and changes in learning intervention. Teacher evaluation tools such as those offered by Point2Check.com have helped to simplify this process. The Coach One Teacher Evaluation system is a comprehensive, but easy to use tool that collects, harnesses and calculates student data through simple algorithms, which provides insight into each student’s growth outcome. The Coach One Teacher Evaluation system is designed to calculate each student’s yearly growth, making it possible to match students with growth deficiencies, with highly effective teachers while providing vertical growth data from the classroom to the state. 

The effective use of data will drive the changes in academic rigor and support the alignment of the standard-based reform. The Coach One System can be most reliable by empowering and aligning schools to meet NCLB requirements. Schools should address each child’s growth data and implement learning strategies based on the child’s needs. The emphasis is on the child’s growth and not the end scores of the child’s assessments, thus, it will drive improvement in learning. For example, a student’s end of the year assessment score that goes from 60% to 75% shows a 15% growth; while a student that goes from 80% to 81% reflects only 1% growth. These two students reflect big learning gain differences that show significant growth between them.  However, the first one shows greater growth than the second one, even if the second one has a better end of the year score.

It is clear that most states are reporting growth as is evidenced by the Adequate Year Progress (AYP) or Annual Measurable Objectives (AMOs) which is used as a yearly target in measuring the growth within reading and mathematics for each subgroup. This data is used in multiple states such as Florida and Washington State. If this data (per student basic and not subgroup) is used by schools and districts to track the annual growth of each child, then the school system will not leave any child behind. We are in urgent need of an educational evaluation system that can show great improvement and not one that only reports high scores as a measure of growth. Effectively, it can be compared to the growth of a business. A business is not only measured by how much you sell during the course of a year but also in the percentage of profit. The truly successful business is evidenced by its effective growth in terms of profit and not just the end of year sales.

In conclusion, in order to provide the effective education of each child, the state-districts-schools must establish a system to measure, track, and relate the data of both: Individual student academic growth and teacher’s academic growth performance.  The school can use historical data to address each student's growth, as well as a way to identify and assist each teacher's yearly performance growth. Creating a school environment in which students’ growth is expected to be achieved at high levels and where students are encouraged and supported in doing so is a critical means for preparing our students for the challenges of the future. Schools need to effectively analyze their data and change their practices and structures in order to provide sufficient intervention and support to all students. These interventions will lead the school to successfully achieve academic rigor. Ultimately, the student and teacher growth data should be used to fulfill the requirement of the law by not matching ineffective teachers with students who did not show adequate growth during the year. Multiple research studies agree that students’ learning is adversely affected when students do not have an effective teacher. Therefore, using accumulated growth data makes it possible to not only leave any child behind but to leave no teacher behind as well.

by Raul Baez Hernandez, M. Ed

The Meaning Of Highly Effective Teacher

Can F schools have highly effective teachers?

At the beginning of the school year in an F school, a colleague teacher of mine told me that she did not want to teach the students that achieved a lower average grade because she did not want to receive a bad teacher performance evaluation score. Indeed, her students’ average grade was at the lower end of the grading spectrum. She was mad because the administrators assigned me 18 high achiever students with a reading average grade of 83%, whereas her class reading average grade was 35%, based on the District 1^st grade previous year’s test.

To my surprise, at the end of the year she achieved a highly effective performance score on her evaluation, whereas I got a rating of “unsatisfactory performance.” That was a contradiction that we could not understand, and so we decided to ask an administrator about this discrepancy. The administrator gave us the following explanation based on student growth.

He indicated that student growth was the key to determine teacher performance. The school used the Florida Annual Measurable Objectives (AMOs), which reflect the expected growth that each school-teacher should achieve at the end of the year according to the state. The administrator said that the expected school AMOs for the current school year was as follows: (a) for Reading, the state expected that our students increase 4 points and (b) for mathematics, the expectation was a 3-point increase. Table 1 data was also provided by the school administrator. He said that both of us were teaching 18, 2^nd grade reading and mathematics students. For confidentiality, we will use the following classification to identify the teachers: (a) “LGT” for the lower grade teacher and (b) “HGT” for the higher grade teacher.

Table 1: Student Growth Data                                        

	Previous Year’s District Score 2012-2013		Expected State AMOs 2013-2014		Expected End-of-Year Score 2013-2014		Actual End-of-year Score  2013-2014
Teacher	Reading	Math	Reading	Math	Reading	Math	Reading	Math
LGT	35	37	4	3	39	40	51	53
HGT	83	86	4	3	87	89	84	86

The expected growth was calculated for each teacher using the following mathematical expression: Expected end-of-the-year growth = (Previous year’s score in a district test + Expected school annual measurable objective). Then at the end of the year when the students were graded on the end-of-the-year district test, the resulting score was compared with the expected end-of-year score.

Based on Table 1, using both subject scores, the LGT students obtained a 52% average score, whereas the students of the HGT students achieved 85%.The score of the students reveal that the HGT has the high achiever score. However, the end-of-the-year score for 2013-2014 indicates that the LGT showed higher student academic growth—in fact, better than expected end-of-the-year scores in both subjects. The HGT did not achieve the expected scores for either subject.

Consequently, the LGT showed better teaching performance and maximum student learning growth that was above expectations. Therefore, using Table 2, the LGT is highly effective based on student growth, not based on student average scores.

The administrator used the following table to determine the performance of both teachers.
In the mathematical equations, “P” = Previous, “S” = State Expectations, and “E” = End of the year.

Table 2 Educators Performance: AMOs Model Relationship

Rating	Score	Performance Level	Above State Expectation	Mathematical Relationship For End-of-year
4	4	Highly Effective	Y	E ≥ S + 1.01
3	3	Effective	Y	E ≥ S < S + 1.00
3	3	Effective	N	E  ≥ (S) -1
2	2	Needs Improvement	N	E  ≤ S -1.01 And E ≤ S -2
2	2	Developing (3 years or less experience)	N	E  ≤ S -1.01 And E ≤ S -2
1	1	Unsatisfactory	N	E ≤ S – 2.1

Annual Measurable Objectives Model

The Annual Measurable Objectives (AMOS) method can improve the alignment between state yearly student learning growth expectations, state standards, state assessments, and classroom instruction, while promoting the professional growth of teachers and standards-based instruction. Aligning teacher performance with state expected growth will help achieve state expectations according to NCLB Act (2001).

Student growth is a positive change in a student’s or group of students’ knowledge or skills, as evidenced by a learning gain from one year to the next by comparing two years of assessment data. It is the relationship between two student assessments at different points in time. The measurement model is the process in which two developmental assessment scores of a student are compared to identify a change in a student’s knowledge or skills over time.

The developmental test measures the knowledge that students could learn at a certain specific developmental age. The developmental knowledge is aligned with the content standards specific to the state or the district. This is the rationale used to compare the results of the two tests during two developmental ages of the students.

This model takes the mean from the final students’ assessment of the previous year and adds it to the students’ expected state target growth expectation. The school growth expectation comes from the target Annual Measurable Objectives (AMOs) or AYP of the state or district learning growth goal.

Baez, R. H. (2014). Coach One evaluation system. Point to check data.

All Data Are Not Created Equal

Weighting the Educator Student Growth Performance Score

 Purpose: To adjust the Student Growth based on the number of students.

By analyzing multiple evaluation systems, we discovered that the evaluation method used to calculate teacher performance is not adequate. The intent behind this article is to offer a different   method to deal with data when there is a combination of performance factors. This process will equalize the contribution that students’ growth has on the final results when calculating the total student growth associated with the determination of the educator’s final student growth performance. This situation happens when an educator has mixed sections with different numbers of students or when a teacher is teaching multiple subjects that have various numbers of students in each class. This method will give the right weight that the amount of students has when calculating the final results of the educator’s student growth performance.  The data is corrupted if the evaluation system does not take into consideration this adjustment. Such corruption is a threat that adds a fatal error to the calculation of the educator’s student growth performance and needs to be corrected before the final student growth performance is reported.

 Case scenario—Mr. Thomas’ mixed classes:

Mr. Thomas is teaching the same subject (reading), but he has two classes, a 4^th grade class and a 5^th grade class. The classes have a different number of students. After calculating the student growth using the Value Added Model (VAM) data, each group had a different student growth performance as follows:

Grade	Subject	Number of Students in Class	VAM Student Growth Measure (SGM) Performance
4	Reading	4	60
5	Reading	14	98

Threat to the final performance evaluation

The common error happens when a mixed SGM result of either data sets (or multiple data sets) is treated as if they contributed equally to the final average results.  As an example,  using the previous SGM to calculate the final student growth performance, and treating the data as if both SGM contribute equally, the result is (60 + 98) / 2 = 79. Based on this calculation, Mr. Thomas’ final student growth performance score is 79. This calculation has a fatal error that requires weighting the data according to the number of students in each class.

Weighted data procedure

The student growth of 14 students does not contribute equally to the final performance when it is compared with the student growth of 4 students.  It’s not the influence of the teacher that’s the concern here, but rather the contributory value given to the two sets of data. The data must be weighted in order to obtain the correct final performance value. In order to obtain the final performance value, the following steps should be used to correctly evaluate Mr. Thomas’ student growth performance.

I- Determining the contribution factor

1) Add the total students in each class. (4 + 14 = 18) This number represents 100% of the students or total students.

2) Divide the number of students in each class by the total number of students as a method to determine the contribution factor for each group of students:

                         (a) 4^th-Grade Class (4/18 = .22)

   (b) 5^th-Grade Class (14/18 = .78)

II- Implementing the contribution factor

3) Now take the SGM Performance for each grade level (or subject) and multiply it by the contribution factor in order to obtain the real contribution that each group of students has on the educator’s final performance:

(a) 4^th-grade class contribution: (60 X .22 = 13.2)

(b) 5^th-grade class contribution: (98 X .78 = 76.44)

4) The addition of both (or multiple) contributions is the correct final student growth performance for Mr. Thomas. This method will eliminate the un-weighted error.

                         (a) (13.2 + 76. 4 = 90): Now based on this calculation, 
                               Mr. Thomas’ final student growth performance score is 90

Contribution Factor for Final Performance Summary

SGM Contribution for each grade or subject	(Multiply by the) Contribution Factor	Total student growth contribution per class
60	.22	13.2
98	.78	76.44
	Weighted Performance Score	89.6

Citation required: Raul Baez Hernandez (2014). Weighting the educator student growth performance score. Coach One Evaluation System