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Action Research Project
Amber Wright
School of Education, Liberty University
Author Note
Amber Wright
I have no known conflict of interest to disclose.
Correspondence concerning this article should be addressed to Amber Wright
Email: awright146@liberty.edu
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Abstract
Data collection is one of the driving forces in the decision-making process for education.
Data is collected from state assessments, district assessments, and even classroom assessments
and thoroughly analyzed to determine the effectiveness of instruction for students of all abilities,
races, genders, and socio-economic classes. It stands to reason that the more trustworthy the
methods, the more accurate the data collected will be and the end result should be improved
instruction and student achievement. Data collection is even more important in the world of
special education because it is the driving force behind selecting individualized goals and for
tracking progress toward those goals. When a special education teacher struggles with proper
data collection method, there could be significant legal implications.
Keywords: Data, data collection, special education, assessments, improvement
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Action Research Project
Special education is a data driven field. Without data, a teacher is unable to measure student
progress and instructional effectiveness. This particular research project was chosen, in
collaboration with my building principal, in an effort to assist a new teacher, Mrs. MacDonald,
with collecting the data necessary to determine progress for her students as well as to assist with
writing appropriate IEP goals during annual review and/or initial identification. As a first-year
teacher, Mrs. MacDonald is frequently observed by administration and progress notes and IEP’s
are monitored by the coordinator of special education. IEP drafts are due to the CSE a minimum
of two weeks prior to IEP meetings to allow for feedback and changes prior to presenting the IEP
to the parents of the students. Every effort will be made to ensure trust, fairness, equity, and
respect are maintained between Mrs. MacDonald, the principal, and the researcher.
Action Research Question
Natalia MacDonald is a first-year special education teacher. She has struggled with proper data
collection which results in limited information about how her students are progressing toward
their IEP goals. In turn, the lack of data makes it difficult to accurately report on progress which
could become problematic if parents request proof of progress or determining if the current
instructional program is appropriate. Ensuring continued progress is essential for the provision
of a free, appropriate, public education (FAPE) which is one of the key components of special
education regulations. Mrs. MacDonald will be given explicit instruction and methods for data
collection and analysis. Her progress notes and IEP’s will be thoroughly evaluated prior to being
provided to parents. Mrs. MacDonald was given options of electronic data collection or
pencil/paper. Listed below is the question that the action research will attempt to answer.
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Will direct instruction and modeling of data collection methods result in improved
instruction and achievement for students with disabilities?
Literature Review
The Unesco IIEP Learning Portal (2020) published an article that discusses the reasons
that classroom teachers might utilize data analysis. One key was noted was for self-evaluation in
order to determine if current methods were effective. It is also important that
parents/stakeholders take stock of data that is made available to them. Having all available
information will allow all decisions to be made with the best information possible. The literature
goes further to discuss the limitations of data use to include quality concerns, access, availability
and political climate as well as ways to mitigate those limitations. While this literature was not
specific to students with disabilities, it does strongly indicate that when data is properly collected
and analyzed for any student, teachers and schools can use the analysis to alter instructional
content and/or methods in attempt to increase student achievement.
Lansford (2017) focused her research on data collection in libraries, but it is still
applicable to special education because it focuses more on the methods of data collection and the
analysis of that data that is collected. One of the keys to great decision making is usable, high
quality data and knowing how to find it, collect it, and analyze it. A breakdown at any step can
drastically impact the results. One area that is often overlooked is collaboration. Typically,
special education teachers are not working in isolation which means that collaboration is crucial
to the continued success of the students. The general education teachers, resource teachers, and
any other specialists that work with a particular student should be collaborating and sharing data
with the special education teacher to get a clearer, more complete picture of student achievement.
Is the student performing poorly in reading with the general education teacher, but excelling with
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the resource and special education teachers? Why? Collaboration allows the team to determine
the instructional methods that are most appropriate and successful for the student which is a key
piece of data. Lansford (2017) shared a quote that struck as quite powerful “If we are willing to
dig a little deeper, we can uncover some powerful data to inform our practices.”. How true this
in for life as well as for our careers! She continued to share that any changes that are brought
about as a result of data should occur individually in order to determine if they are effective.
Multiple changes at once muddy the waters and make it difficult to ascertain which change is the
most effective or causing the opposite reaction than desired.
Militello, et. al.(2013), discussed the ways that data is used and misused in education.
Data analysis is routinely used to determine school accreditation and effectiveness at the state
and district level, but it should also be used within schools to determine the most effective
teaching strategies as well as any inequities amongst various groups of students. No Child Left
Behind (NCLB), now known as Every Student Succeeds Act (ESSA) focused on ensuring an
equitable education for all students and the data revealed that inequities were occurring as well
as in improve pedagogical practices. These federal policies governing education created
accountability for school districts as entities as well as for individual teachers. The Common
Core curriculum was approved for math and English by 45 states in 2010. Virginia is one of a
handful of states that has not adopted this curriculum. The idea behind this was that if the entire
nation was following a common curriculum, it would be significantly easier to use data to
determine student success and have common standards for all American students upon
graduation. Interestingly, numerous states have begun the process to repeal the Common Core
standards in their states based upon the data that they are receiving. To date, there has not been a
correlation between the use of common core standards that the state ranking for educational
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effectiveness. This study is relevant to the proposed research question because it does show a
correlation between effectiveness of improvement efforts and data collection. The data gathered
acts as the rudder would on a boat and guides the instruction through the waters of knowledge on
toward the path of gaining achievement.
In Simpson’s (2011) research, she looked specifically at charter schools in California and
how they utilized data to drive their decision-making process specifically toward school
improvement. Simpson found that even school leaders need high quality training in how to
properly analyze data as well as how to successfully collect the information they are seeking.
She found that setting high standards was insufficient in improving student performance.
Specific goals that are also measurable, attainable, and relevant are also required. Collecting the
correct data is critical determining the true effectiveness of a program. Ensuring that all teachers,
students, and administrators understand the details will help gather the information that is needed
and relevant. Multiple sources of data help reach reliable conclusions.
Teresa Alonzo conducted a study in 2006 regarding using data-based decision making to
close the achievement gap. In this study, she found that the achievement gap is real. Students
from various races, lower socio-economic standing, and students with disabilities achieved at a
significantly lower rate than that of their peers without such barriers (2006). One of the first
steps for Alonzo was to determine, through the use of the available data, if there was an
achievement gap. Once she determined that the gap was real, the study set about using data
driven decision making in an effort to put interventions in place to close that gap. Formative,
summative, and demographic data was used to modify instructional content and practices.
Specific focus on the groups on the lower end of the achievement gap did prove effective in
increasing their level of achievement. The same could be said of students with disabilities that
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are served through an Individualized Education Plan, or IEP. The IEP targets the specific areas
of weakness with the intent of providing specialized instruction in these areas. Data should be
collected frequently regarding student progress toward these goals. Alonzo used this type of
approach with the students in her study. She found that true data driven decision making can
make an impact on students if the focus is one the individuals rather than on the policies.
There are numerous studies today that focus on data collection and improving student
achievement. The vast majority of these studies show a direct correlation between data driven
decision making and increases in student achievement. Data, although a critical component, is
not sufficient by itself to improve student achievement. Thorough analysis of that data and
implementation of quality changes are required to bring about true change.
Strategic Goals
Each study considered during the literature review indicate that while data collection is
important, proper analysis of that data is what is most important to bring change. The SMART
goal derived from the literature was:
Mrs. MacDonald will utilize her preferred new method of data collection to gather data a
minimum of once weekly. She will then engage in analysis of gathered data a minimum of once
monthly and make any adjustments to instruction and/or service times to increase student
achievement and instructional effectiveness.
Strategy Implementation and Monitoring and Data
Ms. MacDonald and I have had conferences to discuss what her concerns are about data
collection. During the conversation, we were able to figure out what the core of her concerns are.
Ms. MacDonald’s primary concern is the lack of training and experience with data collection and
how to interpret and use the data to write progress notes and IEP goals. To complete this
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research, Ms. MacDonald needs to know how to collect the data, analyze it, and use the
information for progress reporting and IEP development. I have given Ms. MacDonald
instruction and examples of quality data collection and samples of high-quality progress notes.
We have scheduled times for observations and collaboration on data analysis. While every effort
was made to be respectful of Mrs. MacDonald, she frequently appeared ambivalent to my
assistance at times, and outright hostile at other times. She was not welcoming of what she
called “interference” in her teaching. I brought this to the attention of the principal who had
observed the same behaviors. We conferenced with Mrs. MacDonald together and further
explained the purpose behind the intensive interventions with her data collection, including
potential legal ramifications. The procedures that occur during a due process hearing were
explained and the critical nature of quality data collection and analysis were described. This
appeared to only be helpful for the following week before Mrs. MacDonald began to engage in
the same ambivalent/hostile behaviors.
After meeting several times with Mrs. MacDonald, we were able to develop a data
collection system that worked well for her and allowed for fairly easy analysis. She preferred to
use a method in a spreadsheet that is formulated to calculate percentages. After showing Mrs.
MacDonald how easy it would be to use the new spreadsheet to determine the information
needed and how it should be used to analyze progress, Mrs. MacDonald was observed twice to
ensure fidelity with the data collection itself. She was given feedback and suggestions to
streamline the collection process, especially given her caseload of 13 students. After thorough
review of IEP’s and progress reports written prior to interventions and comparing them to those
written after interventions, the data supports the literature reviews a\nd showed an increased in
student achievement. Interventions will continue with Mrs. MacDonald and will be broadened to
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include the entire special education team with monthly team meetings to allow the team to learn
and grow from each other. This will also give other data collection ideas that may work best for
each individual.
Professional Development Plan
The principal, Mrs. MacDonald, and I met a final time to determine next steps. The meeting
began by commending Mrs. MacDonald for her efforts in making the changes. We then
discussed the improvements in the IEP and progress report writings and decided that we would
continue to meet regularly, at least once per month, to ensure continued progress. The principal
expressed that the plan is to include the entire special education team as we move forward into
next school year and Mrs. MacDonald appeared surprised, but pleased. While Mrs. MacDonald
was not as receptive as she could have been, she was commended for sticking with it and making
the levels of improvement that were evidenced by significantly more data driven reports. She
was also commended for having her data available at a moment’s notice and being able to
describe what it was currently showing for each student. The principal and I decided that Mrs.
MacDonald may be more willing to accept assistance if she is also given a leadership type role.
She received explicit instruction in data collection and proved to be able to follow through. We
felt that in the future, Mrs. MacDonald could use her newly learned skills to mentor other
members of the special education team using the same manner of data collection. For future
planning, a new SMART goal was developed. Mrs. MacDonald will assist other members of the
special education team by modeling quality data collection, data analysis, and assist as needed
with writing progress reports that are data driven. In order to meet this goal, Mrs. MacDonald
will need to meet with members of the team, demonstrate her preferred method of data
collection, assist the team with setting up their own spreadsheet as needed, and assist with
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analyzing data gathered by team members during the monthly team meetings. Her progress
toward the goal will be measured by the principal and the coordinator of special education during
our planned monthly meetings. When we meet in December 2021, it will be determined if Mrs.
MacDonald has accomplished her goal or if further intervention is necessary. This new growth
plan is reflective of the following national standards:
1. Profession learning that increases educator effectiveness and results for all students uses a
variety of sources and types of student, educator, and system data to plan, assess and
evaluate professional learning. (Leaning Forward: The Professional Learning
Association, Data Strand, 2021)
2. Professional learning that increases educator effectiveness and results for all students
integrates theories, research, and models of human learning to achieve its intended
outcomes. (Leaning Forward: The Professional Learning Association, Learning Design
Strand, 2021).
3. Professional learning that increases educator effectiveness and results for all students
requires skillful leaders who develop capacity, advocation, and create support systems for
professional learning. (Leaning Forward: The Professional Learning Association,
Leadership Strand, 2021)
Conclusion
This entire process was very eye opening for me. I was expecting some push back from
Mrs. MacDonald, but not to the level that I experienced. Mrs. MacDonald has not been shy to let
everyone know that one of her closest friends is the direct supervisor of the building principal
and my personal thoughts are that she feels she is above reproach due to that relationship. I have
worked hard to maintain an appropriate, professional relationship while still being firm and
ensuring that all legal requirements of her position are met.
As I am in the final few courses for the Ed.S degree, I am learning so much about
research and finding that my interests lie mainly in special education. This is not surprising since
this is where I have spent my career teaching, but the administrative side is so new to me. Given
a situation I recently encountered I would like to explore what, if any, effect hiring an advocate
may truly have on a student’s quality of education. This is certainly a topic that I intend to
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explore moving forward. This ties directly to quality data collection and data analysis because
those are the foundations for proving a quality education and progress for a student.
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References
Alonzo, T. L. (2006). Closing achievement gaps through data-driven decision making in a
Success for All school (Order No. 3237780). Available from ProQuest Dissertations &
Theses Global. (304977420). http://ezproxy.liberty.edu/login?qurl=https%3A%2F
%2Fwww.proquest.com%2Fdissertations-theses%2Fclosing-achievement-gaps-through-
data-driven%2Fdocview%2F304977420%2Fse-2%3Faccountid%3D12085
Lansford, T. (2017). GROWING THROUGH DATA: Improving Practices and Impacting Student
Achievement. Knowledge Quest, 46(2), 72-79. http://ezproxy.liberty.edu/login?qurl=https
%3A%2F%2Fwww.proquest.com%2Fscholarly-journals%2Fgrowing-through-data-
improving-practices%2Fdocview%2F1960343518%2Fse-2%3Faccountid%3D12085
Learning Forward: The Professional Learning Association. Learning Forward. (2021, July 2).
https://learningforward.org/.
Militello, M., Bass, L., Jackson, K. T., & Wang, Y. (2013). How Data Are Used and Misused in
Schools: Perceptions from Teachers and Principals. Education Sciences, 3(2), 98-120.
http://dx.doi.org.ezproxy.liberty.edu/10.3390/educsci3020098
Simpson, G. H. (2011). School leaders' use of data-driven decision-making for school
improvement: A study of promising practices in two California charter schools (Order No.
3478014). Available from ProQuest Central; ProQuest Dissertations & Theses Global;
Social Science Premium Collection. (901883434). http://ezproxy.liberty.edu/login?
qurl=https%3A%2F%2Fwww.proquest.com%2Fdissertations-theses%2Fschool-leaders-
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use-data-driven-decision-making%2Fdocview%2F901883434%2Fse-2%3Faccountid
%3D12085
Using data to improve the quality of education. Using data to improve the quality of education |
Unesco IIEP Learning Portal. (2020, November 25).
https://learningportal.iiep.unesco.org/en/issue-briefs/monitor-learning/using-data-to-
improve-the-quality-of-education.
