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Data Teams 1
RUNNING HEAD: Data Teams
DATA TEAMS
BY
JILL D. ELTISTE
Submitted to
The Department of Professional Education Faculty
Northwest Missouri State University Missouri
Department of Professional Education
College of Education and Human Services
Maryville, MO 64468
Submitted in Fulfillment for the Requirements for
61-683 Research Paper
Fall 2014
July 27, 2015
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ABSTRACT
The following study was prepared to find the overall opinion about the use of Data
Teams, and if there is a difference in opinion between administrators and teachers regarding Data
Teams. The Public School District has chosen to incorporate the use of Data Teams to better
address student learning. It has become a focus throughout the district this year, as well as a
building focus. The Data Team process is a time consuming process and requires a great deal of
time and effort on the part of teachers and administrators. It is important to note that this was the
first year that this school district chose to implement Data Teams. The overall opinion regarding
Data Teams will be shown. Additionally, survey results will be analyzed to see if there is a
difference in opinion between administrators and teachers with regards to the Data Teams. It
was found that the overall opinion about Data Teams is positive. Additionally, it was found that
there were significant differences between administrators and teachers opinion with regards to
Data Teams. 100% of administrators surveyed agreed that teachers apply the Data Team process
smoothly, but only 60% of teachers reported that teachers apply the Data Team process
smoothly. 100% of administrators surveyed agreed that teachers analyze student work to set
appropriate goals, while 87% of teachers agreed that teachers analyze student work to set
appropriate goals. 100% of administrators reported that teachers establish goals directly related
to school goals, while 80% of teachers reported that teachers establish goals directly related to
school goals. 100% of administrators reported they have evidence of the impact and efficacy of
Instructional Data Teams, and only 67% of teachers reported evidence of the impact and efficacy
of Instructional Data Teams. Because of the differences it is recommended that the policy of
using Data Teams should be monitored and reviewed.
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INTRODUCTION
Background, Issues and Concerns
Many school districts across the nation are working to address student learning by using
formative assessment data to help teachers better plan for instruction.
The Public School District is one of the districts that have chosen to incorporate the use
of Data Teams to better address students and learning objectives. It has become a focus
throughout the district this year, as well as a building focus.
Teachers and administrators are spending a great deal of time being trained in the Data
Team process and working in Data Teams. Because the process is both time consuming and the
experience is new the outcomes are yet to be seen. Many teachers are skeptical and frustrated
with Data Teams. Teachers don’t like being told what to do with their time, and nothing has
been taken off of their plate in order to accommodate for this new push. Many are asking if the
effort that they are putting forth is worth it. The following study will show the overall opinion
about the use of data teams, and if there is a difference in opinion between administrators and
teachers regarding Data Teams?
Practice under Investigation
The practice under investigation will be looking at the Data Team process.
There will be an investigation to see what the overall opinion is about the use of Data Teams,
and if there is a difference in opinion between administrators and teachers regarding Data
Teams?
School Policy to be Informed by Study
There is a big push to collect and analyze data in the school setting in order to improve
student learning. Many districts are training their administrators and teachers to use Data Teams.
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Through the Data Team process administrators and teachers are trained to use formative
assessment data to make and plan for instruction. The goal is that teachers collaborate with a
team to refine and improve instructional practices and strengthen data use for improving student
achievement. Teachers use data to determine appropriate research-based instructional strategies
to best address students and learning objectives in the classroom. Due to the amount of time it
takes to follow the Data Team process, teachers are questioning whether Data Teams are worth
the time and effort. If we can prove that Data Teams are worth the time and effort, perhaps
teachers will be more willing to commit to the Data Team process. Because this is a new process
for many districts the data from this study could inform administration and teachers as to the
overall opinion about the use of Data Teams, and if there is a difference in opinion between
administrators and teachers regarding Data Teams.
Conceptual Underpinning
Theories exist within many educational sectors that Data Teams support school
improvement. It is said that data teams have the power to reveal what is working well within a
school and what needs improvement. Data Teams are becoming more popular, but current
published research supporting the relationship between the use of Data Teams and student
achievement is hard to come by because this concept is new. School leaders are pushing for the
implementation of the Data Team process in order to see success at the building and district
level, but many teachers are questioning whether data teams are worth the time and effort..
Data Teams were designed to get educators to engage in powerful conversations about
teaching and learning based on data. These discussions need to be productive and often,
focusing on using formative assessment data to make a plan for instruction. Teachers look
closely at data and determine students strengths, then identify weaknesses. Teachers plan for and
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strengthen their instruction by selecting research based instructional strategies to best address
students and learning objectives. Teachers then create dipsticks or checkpoints throughout
instruction to see if students are making gains, and then adjust instruction as needed. The Data
Team process is informative and strategic. It is time consuming and requires all members of the
team to meet regularly and engage in conversations regarding the current data and instructional
practices. The data gleaned from the results of this survey will help the school district,
administration, and teachers get an accurate picture of what the overall opinion is about Data
Teams. This data will also help stakeholders decide if the use of Data Teams in schools is
actually helpful and worth the time and effort put forth.
Statement of the Problem
If the overall opinion is positive about the use of Data Teams, school districts need to
commit time and effort towards using and developing the Data Team process.
Purpose of the Study
The purpose of this study is to determine what the overall opinion is about the use of
Data Teams. The information garnered by this study will better inform teachers and
administrators and perhaps justify or nullify the time and effort that is currently being put forth
during the Data Team process.
Research Question(s)
RQ#1: What is the overall opinion about the use of Data Teams?
RQ#2: Is there a difference in opinion between administrators and teachers regarding
Data Teams?
Null Hypothesis(es)
HO#2: There is no difference between administrator and teacher opinion.
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Anticipated Benefits of the Study
A benefit to this study would be to determine the overall opinion about the use of Data
Teams.
Definition of Terms
Team- a number of persons associated in some joint action: a team of advisers.
Data-individual facts, statistics, or items of information
Summary
A study was conducted to find the overall opinion about the use of Data Teams and if
there is a difference in opinion between administrators and teachers regarding Data Teams? If
the chi-square shows no significant difference between administrator and teacher opinion with
regards to the use of Data Teams, administrators and teachers need to continue to use the Data
Team process. If the chi-square shows a significant number of administrators and teachers
believe that the Data Team process is not worth the time and effort, more time needs to be
dedicated to determining if the Data Team process is considered best practice in regards to
planning for student learning.
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REVIEW OF LITERATURE
The Common Core Standards have impacted the way that teachers are teaching and
students are learning. “These rigorous learning expectations have the potential to transform
education-teaching, learning, and leadership.” (Bessler, 2012) School districts across the country
are working to understand the Common Core State Standards and apply and implement the
standards. Many school districts, like mine are choosing to implement Data Teams in order to
achieve amazing gains in teaching, learning and leadership. “The Common Core State Standards
make the Data Teams process come alive because of the intentional alignment of standards
between grade levels.” (Bessler, 2012) Many school districts are turning to Data teams because
they are a means to improve learning by keeping the focus on the academic growth of students
and the achievement of learning goals. The research article, The Data Made Me Do It written by
Patte Barth (2012) looks at how school districts can use data to “highlight the right questions to
ask and lead schools to the right answers.” The article discusses the fact that money is tight and
districts are making tough decisions. Districts are being asked to identify the greatest need and
target resources to where they will provide the greatest return, or investment.
Kovaleski and Glew (2006), in their article, Bringing Instructional Support Teams to
Scale: Implications of the Pennsylvania Experience examine the statewide implementation of
instructional support teams in Pennsylvania. It discusses the challenges of bringing team-based
problem solving models to scale. History is presented and research conducted on IST is
highlighted and reviewed. The results indicate that the use of instructional support teams is
effective in reducing special education referrals and improving learning. IST analyzes group
data for the purpose of restructuring whole group instruction. IST was designed to help schools
meet No Child Left Behind.
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Through the Data Team process administrators and teachers are trained to use formative
assessment data to make and plan for instruction. The goal is that teachers collaborate with a
team to refine and improve instructional practices and strengthen data use for improving student
achievement. Data Teams improve the quality of instruction by providing research-based
interventions to help accelerate the progress of all students. “The Data Teams process helps
teams to determine if students are making adequate progress towards the rigorous demands of the
Common Core State Standards.” (Bessler, 2012) “The data-driven process is used in every Data
Team meeting (60-90 minutes).” (Bessler, 2012) The process includes five steps and is
structured so that discussions are about students and the skills they have mastered, and the skills
they are missing. Teachers discuss what instruction needs to take place, and how to go about
providing this instruction to the students. Teachers also discuss the different teaching strategies
that might be effective. Teachers collect formative data prior to the 60 minutes meeting and
come prepared to discuss “individual student and classroom results.” (Bessler, 2012) A
challenge facing most teachers is finding the time for collaboration.
The data team process is new to administrators and teachers. “The need for and
expectation to make decisions based on data is a relatively new phenomenon in education.”
(White, 2005) “Data continues to be associated more with Statistics 101 than practical
management of teaching practices to improve student achievement.” (White, 2005) How do
teachers feel about this focus on data? White reminds us that” educators in the field are the best
equipped to make decisions about curriculum content, assessment design, and instructional
delivery, especially when collaborative processes provide the benefit of multiple viewpoints and
interpretations. It is time to celebrate the teacher as expert in data analysis.”(White, 2005) “We
need to see the opportunity to benefit from great teaching and as gain for all of our students,
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delivered by all of our teachers, as a result of their collaborative efforts to improve.” (White,
2005)
The article, Working Smarter By Working Together by Honawar (2008) gives an
overview of the teacher-collaboration model. It takes a deeper look into the use of collaborative
teaching methods as a way to improve education in the United States. The challenges of the
method are discussed and the importance of applying collaborative teaching as a model for
specific needs, rather than a formula is a point that’s driven home.
In the article, Understanding Data Use Practice among Teachers: The Contribution of
Micro-Process Studies, Little (2012) says there is very little good research on what teachers
actually do when they engage in data-based decision making. She suggests that researchers
focus on the details of teachers’ work, using a “micro-process” lense to get a better sense of what
works and what doesn’t work when teachers look at assessment data. Little discusses the use of
micro-process studies to look at teachers as they worked with data. She summarizes six studies
that observed teachers as they worked with data. She pinpoints a study that compared schools
doing data analysis, both effective and ineffective schools and their characteristics in regard to
data conversations. She analyzes transcripts, describes the data-wise process, and describes
“small learning communities” working with the Teacher Leadership Model. The final study
followed eleven elementary teachers over a one-year timeframe as they looked at their students’
responses to mathematical tasks and activities. This final study captured the details of teacher
meetings through the use of audiotape. Through her work Little determines that open-ended
analysis of a small piece of student work on common instructional tasks proved more helpful
than looking at whole-class data.
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“The success of instructional Data Teams in a building depends on the full support and
active involvement of administrators. Through their words and actions, administrators set the
tone for Data Teams in the building.” (Peery, 2011) It is important that administrators believe
that all students can learn. If administrators take the proper steps to support their teachers
through the process Data Teams will be more successful. It is also necessary for administers to
support the Data Team Process by being hands-on throughout the process. There are several
ways that administrators can support Data Teams in their building. One way is to sit in on
meetings. Another way to provide support is to give feedback to teachers during the meetings.
Administrators also need to be visible throughout the school and spend time in the classrooms. It
is also important for administrators to meet with Data Team leaders on a consistent basis. (Peery,
2011)
The article, Improving Instruction Through Focused Team Supervision by William E.
Bickel and Nancy J. Artz (1984) describe approaches to focused team instructional supervision.
This team approach lets supervisors “zero in on priority areas and strengthens their relationships
with teachers.” There are five basic structures of focused team supervision: data based
instructional planning, focused attention and time, allotted team planning and working time,
regular/special education program collaboration, and collaborative supervisor/principal
relationship. This type of focus uses data to provide support and help schools identify priority
instructional areas. This helps the educators better meet the needs of the students.
In this article, My Nine ‘Truths’ of Data Analysis Thomas (2011) lists and discusses
what he has learned about using data to improve teaching and learning: 1. Focus on instruction
wisdom that come from the data. 2. Teachers should be the ones looking at the data. 3. Teachers
should work together to look at data and analyze it together. 4. Data meetings should be frequent.
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5. Teacher teams need norms. 6. Teacher teams should focus on next steps. 7. Schools should
focus on aligning the curriculum. 8. Professional learning communities need to improve. 9.
Teachers need to stay focused on the higher purpose of this work.
The book, The data teams experience: A guide for effective meetings Peery (2011) details
the data teams process and walks teachers and administrators through the steps, giving insight in
regards to the specific proven process to look at student work, apply instructional strategies, and
monitor student learning. It also looks at common problems facing Data Teams. The author
highlights several examples of successful Data Teams implementation.
The book, Beyond the numbers: Making data work for teachers & school leaders by
White (2005) begins by explaining the rearview-mirror effect: planning for future student
success based on past events. White discusses how this is harmful for educators and schools. He
then discusses the dilemma of data collection.
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RESEARCH METHODS
Research Design
A questionnaire was given to administrators and teachers at the end of the school year to
compile data concerning the overall opinion about the use of Data Teams, and the questionnaire
also aimed to determine is there a difference in opinion between administrators and teachers
regarding Data Teams? If it is determined that both administrators and teachers agree that the
Data Team process is worthwhile they will be informed of the outcome and it will be suggested
that the Data Team process be continued. The dependent variable would be administrator and
teacher opinion. The Independent variable is the use of data teams.
Study Group Description
A group of administrators and teachers working in a suburban elementary school district
were surveyed to determine overall opinion about the use of Data Teams, and is there a
difference in opinion between administrators and teachers regarding Data Teams? Of the 21
surveyed, 6 are administrators and the rest were classroom teachers or special services teachers
who are currently being trained in and are working through the Data Team process. The
administrators and teachers surveyed were all at the same level in regards to Data Team training
and had the same experience with using the Data Team process.
Data Collection and Instrumentation
Administrators and teachers will be expected to accurately report their overall opinion
about the use of Data Teams at the end of the school year through the completion of an electronic
survey. The survey instrument can be found in Appendix A.
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Statistical Analysis Methods
A chi-square was used to analyze the data given by administrators and teachers via
survey given electronically at the end of the school year to obtain the overall opinion about the
use of Data Teams, and determine is there a difference in opinion between administrators and
teachers regarding Data Teams?
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FINDINGS
A Chi-square was used to analyze the data given by administrators and teachers via
survey given electronically at the end of the school year to obtain the overall opinion about the
use of Data Teams, and determine is there a difference in opinion between administrators and
teachers regarding Data Teams. The following information, graphs and charts will show
collected data and finding based on the information taken from administrators and teachers.
Analysis of Respondents/Status
FREQUENCY PLOT
VARIABLE: Status
FRQ. CUM. % CUM. FREQUENCY PLOT
---- ---- ----- ----- -------------------------
x < 1 0 0 0 0 |
x = 1 15 15 71.4 71.4 |************************
x = 2 6 21 28.6 100 |**********
x > 2 0 21 0 100 |
TOTAL 21 100 Key for plot #1= Teacher #2= Administrator Total Respondents =21
Number of Teachers = 15 Teachers are 71.4 % of respondents
A survey was given to gather information about the use of Data Teams. 15 respondents, 71.4 %
were teachers while 6 respondents, 28.6 % were administrators.
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RQ #1
Do you believe that teachers apply the Data Team process smoothly with minimal problems?
VARIABLE: Application
FRQ. CUM. % CUM. FREQUENCY PLOT
---- ---- ----- ----- -------------------------
x < 1 0 0 0 0 |
x = 1 15 15 71.4 71.4 |************************
x = 2 6 21 28.6 100 |**********
x > 2 0 21 0 100 |
TOTAL 21 100
Key for plot #1= Yes #2= No Frequency of #1 =15 Percentage of #1 = 71.4%
Frequency of #2=6 Percentage of #2= 28.6%
In determining the overall opinion about the use of Data Teams, the respondents were asked if
they believe that teachers apply the Data Team process smoothly with minimal problems. 15
respondents, 71.4% reported that they believe that teachers apply the Data Team process
smoothly with minimal problems and 6 respondents, 28.6 % reported that they do not believe
that teachers smoothly apply the Data Team process.
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RQ #2
Do you believe that teachers apply the Data Team process smoothly with minimal problems?
Table 1
Summary of Chi Square Analysis
Source Teachers Admin. Chi Sq df p-value
Do not
Apply 40%(6) 0% (0)
Apply 60% (9) 100% (6) 3.36 1 0.06
Sign = or < 0.25
The p-value is .06 The alpha level is .25
Null Hypothesis: There is no difference between administrator and teacher opinion.
The conclusion is that we will reject the null- there is a significant difference in administrator
and teacher opinion.
9 teachers, 60%, reported that teachers apply the Data Team process smoothly with minimal
problems while 6 administrators, 100% reported that teachers apply the Data Team process
smoothly with minimal problems. 6 teachers, 40% reported that teachers do not apply the Data
Team process smoothly and 0 administrators, 0% reported that teachers do not apply the Data
Team process smoothly. The Chi-Square value was 3.36. The degrees of freedom was 1. The
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null hypothesis was: “There is no significant difference of opinion between administrators and
teachers regarding data teams.” The p-value of 0.06 is less than the alpha level of 0.25, therefore
the null hypothesis is rejected. There is a significant difference of opinion between
administrators and teachers. 100% of administrators surveyed agreed that teachers apply the
Data Team process smoothly, while only 60% of teachers reported that teachers apply the Data
Team process smoothly.
RQ#1
Do you believe that teachers use student work to analyze strengths and obstacles and set
appropriate goals?
VARIABLE: Analyze
FRQ. CUM. % CUM. FREQUENCY PLOT
---- ---- ----- ----- -------------------------
x < 1 0 0 0 0 |
x = 1 19 19 90.5 90.5 |************************
x = 2 2 21 9.5 100 |***
x > 2 0 21 0 100 |
TOTAL 21 100
Key for plot #1= Yes #2= No Frequency of #1=19 Percentage of #1= 90.5 %
Frequency of #2 =2 Percentage of #2=9.5%
In determining the overall opinion about the use of Data Teams, the respondents were asked if
they believe that teachers use student work to analyze strengths and obstacles and set appropriate
goals. 19 respondents, 90.5% reported that they believe that teachers use student work to analyze
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strengths and obstacles and set appropriate goals and 2 respondents, 9.5 % reported that they do
not believe that teachers use student work to analyze strengths and obstacles and set appropriate
goals.
RQ #2
Do you believe that teachers use student work to analyze strengths and obstacles and set
appropriate goals?
Table 1
Summary of Chi Square Analysis
Source Teachers Admin. Chi Sq df p-value
Do Not
Analyze 31.6% (2) 0% (0)
Analyze 68.4% (13) 100% (6) 0.88 1 0.35
Sign = or < 0.25
The p-value is 0.35. The alpha level is 0.25.
Null Hypothesis: There is no difference between administrator and teacher opinion.
The conclusion is that we not reject the null- there is not a significant difference in administrator
and teacher opinion. 2 teachers, 31.6%, reported that they do not believe that teachers use
student work to analyze strengths and obstacles and set appropriate goals, while 0 administrators,
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0% reported that they do not believe that teachers use student work to analyze strengths and
obstacles and set appropriate goals. 13 teachers, 68.4% reported that they believe that teachers
use student work to analyze strengths and obstacles and set appropriate goals and 6
administrators, 100% reported that they believe that teachers use student work to analyze
strengths and obstacles and set appropriate goals.
RQ#1
Do you believe that Instructional Data Teams establish goals directly related to annual school
goals?
VARIABLE: Goals
FRQ. CUM. % CUM. FREQUENCY PLOT
---- ---- ----- ----- -------------------------
x < 1 0 0 0 0 |
x = 1 18 18 85.7 85.7 |************************
x = 2 3 21 14.3 100 |****
x > 2 0 21 0 100 |
TOTAL 21 100
Key for plot #1= Yes #2= No Frequency of #1=18 Percentage of #1= 85.7%
Frequency of #2 =3 Percentage of #2=14.3 %
In determining the overall opinion about the use of Data Teams, the respondents were asked if
they believe that Instructional Data Teams establish goals directly related to annual school goals.
18 respondents, 85.7% reported they believe that Instructional Data Teams establish goals
directly related to annual school goals and 3 respondents, 14.3% reported they did not believe
Instructional Data Teams establish goals directly related to annual school goals. The overall
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opinion was that most respondents thought that Instructional Data Teams establish goals directly
related to annual school goals.
RQ #2
Do you believe that Instructional Data Teams establish goals directly related to annual school
goals?
Table 1
Summary of Chi Square Analysis
Source Teachers Admin. Chi Sq df p-value
No Goals 20% (3) 0% (0)
Goals 80% (12) 100% (6) 1.4 1 0.24
Sign = or < 0.25
The p-value is 0.24. The alpha level is 0.25.
Null Hypothesis: There is no difference between administrator and teacher opinion.
The conclusion is that we reject the null- there is a significant difference in administrator and
teacher opinion. 3 teachers, 20%, reported they did not believe Instructional Data Teams
establish goals directly related to annual school goals. 12 teachers, 80% reported that
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Instructional Data Teams establish goals directly related to annual school goals and 6
administrators, 100% reported that Instructional Data Teams establish goals directly related to
annual school goals. The Chi-Square value was 1.4. The degrees of freedom was 1.
The null hypothesis was: “There is no significant difference of opinion between administrators
and teacher regarding data teams.” The p-value of 0.24 is less than the alpha level of 0.25,
therefore the null hypothesis is rejected. There is a significant difference of opinion between
administrators and teachers.
RQ#1
Do you have evidence of the impact and efficacy of your Instructional Data Teams?
VARIABLE: Evidence
FRQ. CUM. % CUM. FREQUENCY PLOT
---- ---- ----- ----- -------------------------
x < 1 0 0 0 0 |
x = 1 16 16 76.2 76.2 |************************
x = 2 5 21 23.8 100 |********
x > 2 0 21 0 100 |
TOTAL 21 100
Key for plot #1= Yes #2= No Frequency of #1=16 Percentage of #1= 76.2%
Frequency of #2 =5 Percentage of #2=23.8%
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In determining the overall opinion about the use of Data Teams, the respondents were asked if
they have evidence of the impact of their Instructional Data Teams. 16 respondents, 76.2%
reported that they have evidence and 5 respondents, 23.8% reported that they do not have
evidence. The overall opinion was that most respondents have evidence of the impact of their
Instructional Data Teams.
RQ #2
Do you have evidence of the impact and efficacy of your Instructional Data Teams?
Table 1
Summary of Chi Square Analysis
Source Teachers Admin. Chi Sq df p-value
No Evidence 33.3 %(5) 0% (0)
Evidence 66.7 % (10) 100% (2) 2.63 1 0.11
Sign = or < 0.25
The p-value is 0.11. The alpha level is 0.25.
Null Hypothesis: There is no difference between teacher and administrator opinion.
The conclusion is that we will reject the null-there is a significant difference in teacher and
administrator opinion. 5 teachers, 33.3%, reported no evidence of the impact of their
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Instructional Data Teams while 0 administrators, 0% reported no evidence. 10 teachers, 66.7%
reported evidence and 6 administrators reported evidence of the impact of their Instructional
Data Teams. The Chi-Square value was 2.63. The degrees of freedom was 1.
The null hypothesis was: “There is no significant difference of opinion between administrators
and teachers regarding the Data Teams.” The p-value of 0.11 is less than the alpha level of 0.25,
therefore the null hypothesis is rejected. 100% of the administrators surveyed said that they have
evidence of the impact and efficacy of Instructional Data Teams, but only 66.7% of teachers
surveyed said they have evidence of the impact and efficacy of Instructional Data Teams. There
is a significant difference of opinion between administrators and teachers.
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CONCLUSIONS AND RECOMMENDATIONS
A study was conducted to determine the overall opinion about the use of Data Teams. 15
respondents, 71.4 % were teachers while 6 respondents, 28.6 % were administrators. Two
research questions were addressed: #1: What is the overall opinion about the use of Data
Teams? #2: Is there a difference in opinion between administrators and teachers regarding Data
Teams? Administrators and teachers were asked to give their overall opinion about Data Teams.
The findings of this study support the theory that Data Teams can be used to improve student
achievement. There was a significant difference of opinion between administrators and teachers
in regards to Data Teams. The study shows that there is a need for Data Teams, and the district
can use this information to make improvements to specific steps of the Data Team process. Both
administrators and teachers agree that teachers are analyzing student work. There was a
difference in opinion between administrators and teachers with regards to applying the Data
Team process smoothly, establishing goals directly related to school goals, and evidence of
impact with students. 15 respondents, 71.4 % reported that teachers are applying the Data Team
process smoothly and 6 respondents, 28.6 % reported that teachers are not applying the Data
Team process smoothly. The overall opinion was that most respondents feel as though teachers
are successful with application of the Data Team process. 19 respondents, 90.5 % reported that
teachers are analyzing student work and 2 respondents, 9.5 % reported that they do not believe
that teachers are analyzing student work. The overall opinion was that most respondents feel as
though teachers are analyzing student work. 18 respondents, 85.7 % reported that teachers
establish goals directly related to school goals and 3 respondents, 14 % reported that teachers do
not establish goals directly related to school goals. 5 respondents, 23.8 % said they had no
evidence of the impact of data teams and 16 respondents, 76.2 % reported that they had evidence
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of the impact of data teams. The overall opinion was that most respondents had evidence of the
impact of data teams.
Even though there was a significant difference in opinion between administrators and
teachers believe that the district can view this as a credible measure. The data shows that the
majority of those surveyed believe that Data Teams are worthwhile. There are differences in
opinion, and these differences should be addressed. The district should take time to investigate
these differences and see what support can be provided to teachers with Data Teams. It is
important to note that this was the first year that Data Teams were implemented in this school
district. I believe that this survey provides accurate information in regards to the Data Team
process at this stage of implementation. The district can now use this data to take steps to
address the areas that need improvement. The district can be confident that by addressing these
areas the administrator and teacher experience will be improved with regards to the Data Team
process.
The outcomes reported from this study show that the overall opinion regarding Data
Teams is positive. The findings show there is a significant difference in opinion between
administrators and teachers with regard to Data Teams. 100% of administrators surveyed agreed
that teachers apply the Data Team process smoothly, but only 60% of teachers reported that
teachers apply the Data Team process smoothly. The Chi-Square Analysis results indicated that
the p-value 0.06 is less than the alpha level of 0.25; therefore the null hypothesis is rejected.
There is a significant difference of opinion between administrators and teachers with regards to
application of the Data Team process. 100% of administrators reported that teachers establish
goals directly related to school goals, while 80% of teachers reported that teachers establish
goals directly related to school goals. The Chi-Square Analysis results indicated that the p-value
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0.24 is less than the alpha level of 0.25; therefore the null hypothesis is rejected. There is a
significant difference of opinion between administrators and teachers with regards to teachers
establishing goals directly related to school goals as part of the Data Team process. 100% of
administrators reported they have evidence of the impact and efficacy of Instructional Data
Teams, and only 67% of teachers reported evidence of the impact and efficacy of Instructional
Data Teams. The Chi-Square Analysis results indicated that the p-value 0.11 is less than the
alpha level of 0.25; therefore the null hypothesis is rejected. There is a significant difference of
opinion between administrators and teachers with regards to the evidence of the impact and
efficacy of Instructional Data Teams.
The research points to a significant difference in opinion between administrators and
teachers with regards to Data Teams. Teachers do not see themselves as statistical number
crunchers and the Data Team process relies a great deal on looking at numbers. This process is
new. It takes time for teachers to “buy in.” Teachers need more time and they need more
training. A drawback to using Data Teams is time. Teachers value their time and are struggling
with Data Teams because of the amount of time that is spent working on one standard. Teachers
pride themselves on doing things well, and most teachers do not feel as though they do
something well until they have perfected it. With that being said, keep in mind that this was the
first year of implementation. It’s no wonder that the teachers’ opinions are not on par with the
administrators. In this district the administrators are data driven. They are comfortable using
numbers, and are simply more comfortable with the Data Team process. The administrators
might also be more optimistic about teacher performance. If the study were to be reviewed or
changed, a larger number of teachers and administrators would be surveyed to collect a larger
sample from the district.
Data Teams 27
It is important that this district conduct some further studies that could help determine if
Data Teams are worth the time and effort. One area they could look at would be the relationship
between using Data Team and students achievement scores. When state testing results are
released the district could compare scores and possibly show a connection between the use of
Data Teams and student achievement. It will also be important for the district to continue to
study administrator and teacher opinion with regards to Data Teams, especially after the district
completes another year of Data Team implementation.
Professional development is an area that could be addressed to help bridge the opinion
differences between administrators and teachers. The district should provide opportunities for
teachers to receive more training with the data team process and possibly take part in book
studies to help teachers learn more about the methods and practices needed when working in
Data Teams. Administrators should survey the teachers to find out how they feel about Data
Teams, then address the areas of concern and celebrate the successes.
Data Teams 28
REFERENCES
Barth, P. (2012). 'The Data Made Me Do It'. American School Board Journal, 199(2), 28.
http://search.ebscohost.com. (AN70550212)
Besser, L. (2012). Leveraging Data Teams and Professional Learning Communities for Success
on the Common Core. In Navigating assessment and collaboration with the common core
state standards (pp. 53-79). Englewood, CO: Lead Learn Press.
Bickel, W.E., & Artz, N.J. (1984) Improving Instruction Through Focused Team Supervision.
Educational Leadership, 41(7), 22. http://search.ebscohost.com. (AN 8524268)
Honawar, V. (2008). “Working Smarter By Working Together”. Education Week, 27(31), 25-
27. http://search.ebscohost.com. (AN31660387)
Kovaleski, J. F., & Glew, M. C. (2006). Bringing Instructional Support Teams to Scale:
Implications of the Pennsylvania Experience. Remedial & Special Education, 27(1), 16.
http://search.ebscohost.com. (AN19505132)
Little, J. (2012). Understanding Data Use Practice among Teachers: The Contribution of Micro-
Process Studies. American Journal Of Education, 118(2), 143-166.
http://search.ebscohost.com. (AN71054927)
Peery, Angela (2011). The data teams experience: A guide for effective meetings. Englewood,
CO: Lead Learn Press.
Thomas, R. S. (2011). My Nine ‘Truths’ of Data Analysis. Education Week, 30(35), 36, 29.
White, S. (2005). Beyond the numbers: Making data work for teachers & school leaders.
Englewood, CO: Advanced Learning Press.
Data Teams 29
APPENDIX A
Please rate the degree to which you agree with the
following statements regarding Data Teams
Agree Disagree
1. Teachers apply the Data Team process smoothly with
minimal management problems
2. Teachers use student work to analyze strengths and
obstacles and set appropriate goals
3. Instructional Data Teams establish goals directly related
to annual school goals
4. Do you have evidence of the impact and efficacy of your
Instructional Data Teams?