Review

 

Be sure to include the following information 

• The setting of the assessment being covered (What kind of school, who is taking it?)
• The aspect of assessment the article is covering (is it the development of the assessment, the results, how students react to assessments, etc..)
• What the author(s) hypothesis was, or what they wanted to know
• The method the author(s) used
• What the author(s) found during this research
• How did this research add to the professional body of knowledge
• Any other information you found interesting
• Your own personal reflection on the article

28 Educational Research Quarterly December 2020

11(1), 71-85.
Yılmaz, E. & Aslan, H. (2013). Examination of relationship between

teachers’ loneliness at workplace and their life satisfaction.
Pegem Journal of Education & Instruction, 3 (3), 59-69.

An Evaluation of Assessment Equity for Special Education
Students in Texas

Mistie Dakroub

Randy Hendricks Craig Hammonds
University of Mary Hardin-Baylor

The use of standardized assessments to monitor the success and productivity of
public school systems in the United States is arguably a necessary component of
state accountability systems. This research study is not intended to challenge the
compulsion of accountability via testing, but the results of this study do raise
questions regarding the equity of the assessment process required by the state of

Vol. 44.2 Educational Research Quarterly 29

Texas for its public school system. The demographics of the Texas public school
student population includes a subgroup of special education (SPED) students who
are currently charged with performing on state standardized tests at the same level
as their general education counterparts. These SPED students previously
participated in an assessment at a slightly lower rigor level than the cohort test,
with fewer questions to complete. Texas policymakers removed this mid-level
assessment, referred to as the STAAR Modified (STAAR M) test after 2014,
and moved forward with one testing option for most SPED students. This option
assesses not only SPED students, but also general education students (Texas
Classroom Teachers Association, 2013). This study calls into question the need
for a tiered testing system for SPED students who function in the mainstream
population but require significant instructional accommodations or curricular
modification. This quantitative study employs the use of a readability analysis
tool to assess the 2014 STAAR and the 2014 STAAR M to determine
assessment readability levels for grades three through eight in the subjects of
reading, social studies, and science. In addition, an analysis of passing percentages
was conducted for SPED and non-SPED students tested in the same grade levels
and subjects for 2012-2015; 2015 represents the first year that STAAR M
assessments were not available to the SPED population. The data from the
readability and passing percentage analyses were used to evaluate the degree of
assessment equity for the Texas SPED student population after the elimination
of the STAAR Modified assessment option.

The Special Education Instruction
Assessment Divide in Texas

In 2012, Texas policymakers significantly increased the rigor
of the state’s public school accountability system by implementing
the State of Texas Assessment of Academic Readiness (STAAR)
testing program. This new testing program had three major testing
options for students: The STAAR Alternate (STAAR Alt) test, which
was intended for special education (SPED) students with more severe
and profound disabilities; the STAAR Modified (STAAR M) test,
which was for SPED students with significant curricular
modifications or instructional accommodations in the mainstream

30 Educational Research Quarterly December 2020

classroom setting; and the STAAR test, which was the mainstream
assessment for non-SPED Texas students. In 2015, Texas
policymakers removed the STAAR M option for SPED students
(Texas Education Agency, n.d.a). Since the current testing program
limits the STAAR Alt to the most severely disabled students, this
change potentially widens the assessment achievement gap between
the majority of SPED students and their mainstream peers. The
SPED students most adversely affected by the restructuring are those
capable of attending mainstream classes but not skilled enough to
function at the same academic level as their non-disabled cohort.

Special education teachers and campus administrators labor
under the expectation that students in special education programs
receive student-centered instruction tailored to each student’s
individual needs. Educators must follow the individual education
plan (IEP) for each student, but this does not necessarily align with
state assessment expectations. State testing based solely on the
cohort grade level does not take into account the specific needs of
the special education student nor his or her IEP. The
accommodations that a special education student can receive on the
STAAR test include adjustments such as extended time, small group
testing environment, and, in some cases, having the assessment read
aloud. Some students also qualify for vocabulary assistance, but they
must take the online version of the STAAR in order to access that
particular accommodation (Texas Education Agency, n.d.b). All of
these systems assist special education students, but they still leave a
potential gap between the level of instruction and the level of
assessment. Students who achieve below grade level by two or three
grades must be instructed at that level and remediated up to the
cohort grade level. However, upward remediation typically does not
happen in one year, and for some students it never happens. The
assessment of all students should mirror the level of instruction they
have received during the academic school year. However, currently
in Texas, the vast majority of special education students are held to

Vol. 44.2 Educational Research Quarterly 31

an equivalent standard on the mandated STAAR assessments as their
non-disabled peers with only minor accommodations or assistance
(Chomsky & Robichaud, 2014; Dodge, 2009), resulting in instruction-
assessment misalignment for many SPED students. Given this
instruction-assessment misalignment, the instructional expectation
for many special education students may not reach the rigor of state-
mandated assessments.

As the expectation in the United States to educate all students
has grown, so has the need for best practices in educating students
with diverse learning needs (Katsiyannis, Yell, & Bradley, 2001).
Identified special education students have been exposed to a wide
variety of educational environments since the 1975 inception of the
Education of all Handicapped Children’s Act (EAHCA), which was
the first federal law requiring special education services. Laws
supporting the education of SPED students have progressed to keep
public schools from isolating SPED students from the mainstream
population; however, the Texas accountability system in the late
1990s and turn of the 21st century excluded scores of special
education students from the school rating system. Thus, the
expectations for special education students on state assessments
progressed from no to little accountability in the state’s earlier testing
program to the current system based on results of either the STAAR
or STAAR Alt (Duckworth, Tsukayama, & Quinn, 2012; LaVenture,
2003).

The present system allows school districts to declare a small
percentage of students eligible for the STAAR Alt assessment, which
is intended for special education students with severe and profound
disabilities. School districts who over-identify special education
students in the STAAR Alt assessment category receive automatic
failures for the number of students over the allotted percentage of
expected testers. Currently, each school district is limited to 1% of
the student population taking the STAAR Alt test, which means that
the STAAR Alt testing population exceeding 1% are counted as

32 Educational Research Quarterly December 2020

automatic failures in the accountability system. This practice forces
school district administrators to push students out of STAAR Alt and
into the standard STAAR assessment category, even with full
knowledge that for some special education students the IEP required
is not aligned with the academic rigor of the standard STAAR test
(Greer & Meyen, 2009; Texas Education Agency, n.d.c).
As mandated by federal law, the state of Texas has required
the standardized assessment of all students, including SPED students,
since No Child Left Behind (Cho & Kingston, 2011). Currently,
Texas testing, ostensibly established based on the vocabulary level of
the mainstream students in each grade, does not take into account the
wide-ranging levels of SPED students. The researchers of this study
assumed that readability analysis, using a calibration system that takes
into account vocabulary and sentence structure to determine the
grade level of a written piece, would be an essential part of test item
selection to ensure that SPED students do not struggle to
comprehend questions and passages that are above the tested grade
reading level. In order to confirm that assumption, two separate
emails were directed to the Texas Education Agency. One email
specifically asked about the calibration tools used to determine the
readability level of STAAR tests; the second email involved a similar
inquiry. The question was posed to two different departments in an
effort to ensure that the response was as accurate as possible. The
email responses both housed the same answer. STAAR tests are not
calibrated to determine reading level by an official calibration tool.
Given that SPED students are often two and three grades below their
peers in reading level, the need to ensure that SPED students are
assessed equitably in regards to reading level seems pedagogically
sound (Gillies, 2014; Welch, 1998).

The purpose of this study was to assess the impact that the
elimination of the STAAR M test had on the SPED student testing
population in Texas, specifically the year following the last
administration of the modified test. Students receiving special

Vol. 44.2 Educational Research Quarterly 33

education services have federal guidelines that protect the educational
environment that schools must provide for them. Students who
perform below grade level on diagnostic testing and qualify for
special education services have a right to instruction at their
developmental level. Special education teachers must then work with
that student to bring him or her up to grade level, or as close to grade
level as feasible in the academic year. However, mainstream special
education students in Texas are assessed with the cohort group that
matches the grade level as opposed to the academic ability of
individual students. The lumping of special education students with
mainstream students for testing purposes creates a chasm between
the instructional experiences and assessment practices for special
education students in the state of Texas (Bock & Erickson, 2015;
Gillies, 2014). Given the high stakes associated with the Texas
testing system, the need for adequate and appropriate assessment for
special education students is a real and valid area for research (Gillies,
2014; Roach, Beddow, Kurz, Kettler, & Elliott, 2010).

Methodology and Findings

All data for this study were collected from the Texas
Education Agency (TEA) and analyzed using SPSS statistical
software. This causal-comparative, quantitative study was designed
to address four research questions related to the readability levels of
the 2014 modified and non-modified STAAR tests, as well as the
passing rates disaggregated by the 20 educational regions across
Texas over the span of 2012 through 2015 for SPED and non-SPED
students taking the STAAR and STAAR M assessments. More
specially, the following research questions served to guide the study
design and data analysis.

R1: Is there a statistically significant difference between
readability levels of the passages/questions from the 2014 STAAR M
assessments in grades three through eight in reading, science, and
social studies compared with the readability analysis levels of the

34 Educational Research Quarterly December 2020

passages/questions from the 2014 standard STAAR assessments in
grades three through eight in reading, science, and social studies?

R2: Is there a statistically significant difference between
passing rates for special education students who took the modified
3rd through 8th grade reading STAAR tests across the years 2012,
2013, 2014 and SPED students who took the standard STAAR test
in 2015 compared to the passing rates of non-SPED students who
took the standard 3rd through 8th grade reading STAAR test across
the years 2012, 2013, 2014 and 2015?

R3: Is there a statistically significant difference between
passing rates for special education students who took the modified 5th
and 8th grade science STAAR test across the years 2012, 2013, 2014
and SPED students who took the standard STAAR test in 2015
compared to the passing rates of non-SPED students who took the
standard 5th and 8th grade science STAAR tests across the years 2012,
2013, 2014 and 2015?

R4: Is there a statistically significant difference between
passing rates for special education students who took the modified 8th
grade social studies STAAR test across the years 2012, 2013, 2014
and SPED students who took the standard STAAR test in 2015
compared to the passing rates of non-SPED students who took the
standard 8th grade social studies STAAR test across the years 2012,
2013, 2014 and 2015?

Reading level analysis of the questions and passages of the
2014 regular and modified STAAR tests was conducted to determine
the degree that each was aligned with the designated grade levels for
reading, science, and social studies assessments in grades three
through eight. The 2014 STAAR assessment was chosen for the
readability analysis since it represents the last year the modified tests
were administered. If the non-modified and modified versions of the
STAAR assessments significantly differ in regards to readability level,
an argument can be made that any decline in SPED passing rates
after the elimination of the modified tests are likely the result of a

Vol. 44.2 Educational Research Quarterly 35

misalignment between SPED students’ readability levels and the
readability levels of the standard STAAR assessments as opposed to
instructional deficiencies. The researchers used the calibration system
ReadablePro to determine the readability score for each question or
passage assessed. Each readability passage or question analysis
resulted in five separate indices scores, which comprise the
ReadablePro calibration algorithm. The five indices scores were then
averaged to determine an overall readability score. Individual indices
included the Flesch-Kincaid, Gunning’s Fog, Coleman-Liau, Simple
Measure of Gobbledygook (SMOG), and the Automated Readability
Index (ARI) (Readability Formulas, n.d.; ReadablePro Features, n.d.).
As an example, Table 1 provides a breakdown of the results for the
non-modified STAAR 3rd grade reading and the modified STAAR 3rd
grade reading tests from 2014. The overall readability score,
expressed as a grade level, is 7.0 and 4.1 for the non-modified and
modified tests respectively. In this case, the non-modified test was
found to be 4.0 grade levels above the designated grade level while
the modified test was found to be 1.1 grade levels above.

Table 1. Example of Readability Score Determination for 3rd Grade Reading

Testing
Format

Flesch-
Kincaid

Gunning’s
Fog

Coleman-
Liau

SMOG ARI Readability
Score

Non-odified 5.9 7.6 7.3 8.9 5.3 7.0
Modified 2.7 4.4 4.8 6.3 2.1 4.1

One-way ANOVA procedures were conducted to address
research questions two through four. The dependent variables for
the ANOVA analyses were the passing rates for the student cohorts
taking the different STAAR assessments, with the unit of analysis
being the 20 education regions within the state of Texas. The
independent variables included the combination of student
classification (SPED or non-SPED) and the year of the test (2012
through 2015), with resulted in eight student cohort comparisons per

36 Educational Research Quarterly December 2020

analysis: four SPED cohorts (2012-2015) and four non-SPED
cohorts (2012-2015). The ANOVA analyses were designed to
determine if passing rates for SPED students mirror the passing rates
for non-SPED students over time. If the modified version of
STAAR is unnecessary for appropriate SPED assessments, then the
passing rates for SPED students should follow the same pattern as
the passing rates for non-SPED students over the same years of
assessments. If, however, the elimination of the modified version of
STAAR resulted in an instruction-assessment misalignment, the
SPED passing rates after the elimination of modified assessments
would be expected to show a marked departure from the previous
trend (Office of Qualifications and Examinations Regulation, 2016).

In conducting the ANOVA procedures, the researchers first
reviewed the results of Levene’s test to verify the assumption of
homogeneity of variances. When Levene’s test was significant (p ≤
0.05), indicating a lack of homogeneity of variances, the researchers
used the Welch’s F statistic as the test for an overall significant
difference between means and the Games-Howell post hoc test to
identify the specific group means that differed significantly (Northern
Arizona University, n.d.). When Levene’s test was not significant, the
researchers used the traditional ANOVA F statistic and Tukey’s HSD
as the overall significance test and post hoc test respectively. The
researchers used an alpha level of .05 for all analyses. Partial eta

squared (ɳp
2) was calculated as the measure of effect size for all

significant F values; partial eta squared values of .01, .06. and .14
correspond to small, medium, and large effect sizes respectively
(Stern, 2011). In addition, when a significant pairwise difference was
found between the 2015 SPED student group and any of the other
student groups, effect size was determined by calculating Hedges’ g.
Hedges’ g values of 0.2, 0.5, and 0.8 demonstrate small, medium, and
large pairwise differences respectively (Lakens, 2013).

Readability Analysis

Vol. 44.2 Educational Research Quarterly 37

A paired sample t test was conducted to analyze the
readability of the 2014 STAAR M and 2014 STAAR assessments.
Thirty-three data points were collected from both test versions in
grades three through eight in the subjects of reading, social studies,
and science. The analysis revealed a significant difference in the
readability for the non-modified (M = 1.86, SD = 2.88) and the
modified assessments (M = .076, SD = 2.02); t(32) = -3.10, p < .004). This finding is consistent with the need for a lower readability level for the modified test but also indicates that both assessments are typically above the assigned grade level, with the non-modified test being 1.86 grade levels above and the modified test at 0.76 grade levels above. Table 2. Results of Paired-Samples t Test Analysis for Modified and Non-

Modified Readability Levels

M

n

SD

t

df p

Non-modified 1.86 33 2.875 3.100 32 .004
Modified .076 33 2.022

NOTE: The mean (M) represents the average deviation from assigned grade levels.

Passing Rate Analyses

One-way ANOVA procedures were conducted to assess
research questions two through four. In order to facilitate the
reporting of results, the findings are grouped based on subject: (a) 3rd
through 8th grade reading and b) 5th grade science, 8th grade science,
and 8th grade social studies. A line graph is provided for each analysis
following the explanation to illustrate the results; individual ANOVA
tables are included in the appendix.

Reading Grades Three through Eight.
As delineated in Table 3, the results of the one-way ANOVA

analyses for the reading assessments were significant in all six cases,
with large partial eta squared values for each. In addition, the post-

38 Educational Research Quarterly December 2020

hoc procedures indicated that the passing rate for the 2015 SPED
group was significantly less than the other seven student groups in all
six analyses. The Hedge’s g values for the 2015 SPED pairwise
comparisons to the other student groups ranged from 2.30 to 6.44,
which represents a large effect in all instances. As shown in the line
graphs depicted in Figure 1, the elimination of the modified test in
2015 resulted in a precipitous decline for the 2015 SPED cohort on
the reading STAAR tests in grades three through eight.

Table 3. One-way ANOVA Results for Reading Grades Three through Eight

Grade Levene’s F p ɳp

2 Post-Hoc 2015 SPED
Pairwise Comparisons

Hedge’s g
Range

3rd

p = .134

68.450

< .001

.76

All significant (p < .001)

3.29 – 5.16

4th p = .178 77.417 < .001 .78 All significant (p < .001) 3.84 – 6.39 5th p < .001 72.094 < .001 .81 All significant (p < .001) 2.24 – 4.43 6th p = .003 66.162 < .001 .85 All significant (p < .001) 4.14 – 6.33 7th p = .011 75.218 < .001 .85 All significant (p < .001) 4.19 – 6.44 8th p < .001 116.70 < .001 .85 All significant (p < .001) 2.30 – 6.17

Figure 1. Passing rate comparisons for SPED and non-SPED students for reading grades three through eight.

Science Grades Five and Eight and Social Studies Grade
Eight.

As shown in Table 4, the one-way ANOVA procedures for
the two science and one social studies analyses resulted in significant
differences and large effect sizes for all three. In addition, the post
hoc procedures indicated significantly lower passing rates for the
2015 SPED group in all comparisons to other student groups.
Hedge’s g pairwise effect size values ranged from 2.15 to 8.83, which
exceeds the .8 large effect threshold in every case. The findings for
the two science and one social studies assessments demonstrate
consistency with the reading assessments: The elimination of the
modified test after 2014 resulted in a precipitous decline in passing
rates for the SPED testing population in 2015 on the two science
assessments in grades five and eight and the one social studies
assessment in grade eight (Figure 2).

Table 4. One-way ANOVA Results for Science Grades Fifth and Eight and
Social Studies Grade Eight

Assessment Levene’s F p ɳp

2 Post-Hoc 2015 SPED
Pairwise Comparisons

Hedge’s g
Range

5th Science p = .145 89.944 < .001 .81 All significant (p < .001) 2.15 – 5.09 8th Science p = .124 130.926 < .001 .86 All significant (p < .001) 6.08 – 8.03 8th SS p = .833 77.341 < .001 .78 All significant (p < .001) 5.15 – 8.83

Figure 2. Passing rate comparisons for SPED and non-SPED students for reading grades three through eight.

20

30

40

50

60

70

2012 2013 2014 2015

8th Grade Social Studies

SPED NSPED

Conclusions and Recommendations
This study was designed to assess the suitability of the

standard STAAR test as a pedagogically appropriate assessment for
Texas SPED students. State policymakers determined that the tiered
testing system of STAAR, STAAR M, and STAAR Alt would be
minimized to only offering the STAAR and STAAR Alt tests
beginning in the year 2015 (Texas Classroom Teachers Association,
2013). SPED students who had previously taken the STAAR M,
which had fewer questions, fewer answer choices, and often was at a
lower reading level, would now take the STAAR test with their peers.
This decision was based on federal mandates, but no significant
changes were made to the STAAR test in anticipation of adding the
SPED students to the testing cohort. The problem with this system
is that the expectation and structure of the STAAR test do not match
the instructional expectation for SPED students. SPED students are
entitled to instructional accommodations and curricular modifications
as a means to bridge the students’ learning gaps over time, commonly
over the span of multiple academic years (Fuchs & Fuchs, 2016).
The standard STAAR test fails to take this factor into account.

The data resulting from this study show a plummet in scores as
SPED students who previously achieved closer to their cohort counterparts
at each grade level and subject area took a distinct dip in performance in
2015, indicating that the STAAR M assessment was a more appropriate
assessment option for students with disabilities. The findings on the
readability analysis of the STAAR and STAAR M assessments in 2014, the
last year the STAAR M was administered, show that the readability level for
the STAAR and STAAR M were both above grade level in readability. The
STAAR M readability was slightly above grade level, instead of rating
slightly below, as would be expected for students with SPED
accommodations and modifications for learning disabilities (Hart, 2015).

Upon completing this study, the researchers recommend that
Texas policymakers consider reinstating the three-tiered assessment format
that takes into account students who qualify for SPED but are not severe
and profound enough in their disabilities to qualify for the STAAR Alt
assessment. This would also require federal bureaucrats at the U.S.
Department of Education to acknowledge the legitimacy of a middle tier

Vol. 44.2 Educational Research Quarterly 43

assessment for SPED students in the mainstream classroom setting. If a
return to the three-tiered assessment format is deemed unacceptable,
policymakers should ensure that the standard STAAR assessments are at
least closer to actual grade level readability as determined by a legitimate
calibration process. The need for accountability in Texas public schools was
never a question in this research study, but the need for greater assessment
equity for special education students is indicated based on the study
findings; fundamental fairness would seem to demand it.

References
Bock, A., & Erickson, K. (2015). The influence of teacher

epistemology and practice on student engagement in literacy
learning. Research & Practice for Persons with Severe Disabilities,
40(2), 138–153. https://doi.org/10.1177/1540796915591987

Cho, H.-J., & Kingston, N. (2011). Capturing implicit policy from
NCLB test type assignments of students with disabilities.
Exceptional Children, 78(1), 58–72. http://0-search.
ebscohost.com.umhblib.umhb.edu/login.aspx?direct=true&d
b=eue&AN=508487883&site=ehost-live

Chomsky, N., & Robichaud, A. (2014). Standardized testing as an
assault on humanism and critical thinking in education.
Radical Pedagogy, 11(1), 3–3. http://0-search.ebscohost.
com.umhblib.umhb.edu/login.aspx?direct=true&db=eue&A
N=94334249&site=ehost-live

Dodge, A. (2009). Heuristics and NCLB standardized tests: A
convenient lie. International Journal of Progressive Education, 5(2),
6–22. http://0-search.ebscohost.com.umhblib.umhb.edu/
login.aspx?direct=true&db=eue&AN=51837750&site=ehost
-live

Duckworth, A. L., Tsukayama, E., & Quinn, P. D. (2012). What No
Child Left Behind leaves behind: The roles of IQ and self-
control in predicting standardized achievement test scores
and report card grades. Journal of Educational Psychology, 104(2),
439–451. https://doi.org/10.1037/a0026280

44 Educational Research Quarterly December 2020

Fuchs, D., & Fuchs, L. S. (2016). Responsiveness-to-intervention: a
“systems” approach to instructional adaptation. Theory Into
Practice, 55(3), 225–233. https://doi.org/10.1080/
00405841.2016.1184536

Gillies, R. M. (2014). The role of assessment in informing
interventions for students with special education needs.
International Journal of Disability, Development & Education, 61(1),
1–5. https://doi.org/10.1080/1034912X.2014.878528

Greer, D. L., & Meyen, E. L. (2009). Special education teacher
education: a perspective on content knowledge. Learning
Disabilities Research & Practice (Wiley-Blackwell), 24(4), 196–203.
https://doi.org/10.1111/j.1540-5826.2009.00293.x

Hart, S. (2015, August 17). Why are so many Texas students
struggling with STAAR? Retrieved September 28, 2018, from
https://www.texasmonthly.com/the-daily-post/why-are-so-
many-texas-students-struggling-with-staar/

Katsiyannis, A., Yell, M. L., & Bradley, R. (2001). Reflections on the
25th anniversary of the Individuals with Disabilities
Education Act. Remedial & Special Education, 22(6), 324.
http://0-search.ebscohost.com.umhblib.umhb.edu/ login
.aspx?direct=true&db=a9h&AN=5599353&site=ehost-live

Lakens, D. (2013). Calculating and reporting effect sizes to facilitate
cumulative science: A practical primer for t-tests and
ANOVAs. Frontiers in Psychology, 4, 863.

LaVenture, S. (2003). The Individuals with Disabilities Education Act
(idea): Past and present. Journal of Visual Impairment &
Blindness, 97(9), 517–518. http://0-search.ebscohost.
com.umhblib.umhb.edu/login.aspx?direct=true&db=a9h&A
N=10818925&site=ehost-live

Northern Arizona University. (n.d.). Understanding the One-Way
ANOVA. http://oak.ucc.nau.edu/rh232/ courses/EPS525/
Handouts/Understanding%20the%20One-way%20ANOVA.
pdf

http://0-search.ebscohost.com.umhblib.umhb.edu/

Vol. 44.2 Educational Research Quarterly 45

Office of Qualifications and Examinations Regulation. (2016).

Investigations into the sawtooth effect in GCSEs, AS and A levels.
https://assets.publishing.service.gov.uk/
government/uploads/system/uploads/attachment_data/file/
549686/an-investigation-into-the-sawtooth-effect-in-gcse-as-
and-a-level-assessments

Readability Formulas. (n.d.). Retrieved from http://www.
readabilityformulas.com/free-readability-formula-tests.php

ReadablePro Features. (n.d.). Retrieved from https://readable.com/
features/#readability

Roach, A. T., Beddow, P. A., Kurz, A., Kettler, R. J., & Elliott, S. N.
(2010). Incorporating student input in developing alternate
assessments based on modified academic achievement
standards. Exceptional Children, 77(1), 61–80. http://0-
search.ebscohost.com.umhblib.umhb.edu/login.
aspx?direct=true&db=eue&AN=508188951&site=ehost-live

Stern, L. (2011). Statistics for the behavioral sciences. a visual approach to spss
for windows: a guide to spss (2nd ed.). Boston, MA: Pearson
Education.

Texas Classroom Teachers Association. (2013, August 23). USDE
directive eliminates STAAR Modified. https://tcta.org/node/
13637-usde_directive_eliminates_ staar_modified

Texas Education Agency. (n.d.a). STAAR modified resources archives.
https://tea.texas.gov/student.assessment/special-ed/staarm/

Texas Education Agency. (n.d.b). Accommodation resources. Retrieved
from https://tea.texas.gov/accommodations/

Texas Education Agency. (n.d.c). STAAR alternative participation
requirements https://tea.texas.gov/student.assessment/ special-
ed/staaralt/partreqs/

Welch, M. (1998). The idea of collaboration in special education: an
introspective examination of paradigms and promise. Journal
of Educational & Psychological Consultation, 9(2), 119. http://0-

46 Educational Research Quarterly December 2020

search.ebscohost.com.umhblib.umhb.edu/login.aspx?direct
=true&db=a9h&AN=7437003&site=ehost-live

Appendix A: ANOVA Tables for 3rd through 8th Grade Reading

Table 1. ANOVA Results for 3rd Grade Reading

SS df MS F p

ɳp
2

Between 10843.975 7 1549.139 68.450 <.001 .76

Within 3440.000 152 22.632

Total 14283.975 159

Table 2. ANOVA Results for 4th Grade Reading

SS df MS F p ɳp
2

Between 14425.144 7 2060.735 77.417 <.001 .78

Within 4046.050 152 26.619

Total 18471.194 159

Table 3. ANOVA Results for 5th Grade Reading

F df1 df2 Sig.

ɳp
2

Welch’s
test

72.094

7

64.860

<.001

.81

Table 4. ANOVA Results for 6th Grade Reading

F df1 df2 Sig.

ɳp
2

Welch’s
test

66.162

7

64.909

<.001

.85

Vol. 44.2 Educational Research Quarterly 47

Table 5. ANOVA Results for 7th Grade Reading

F df1 df2 Sig.

ɳp
2

Welch’s
test

75.218

7

64.894

<.001 .85

Table 6. ANOVA Results for 8th Grade Reading

F df1 df2 Sig.

ɳp
2

Welch’s
test

116.700

7

64.412

<.001 .85

Appendix B: ANOVA Tables for 5th science, 8th science,

and 8th Social Studies

Table 1. ANOVA Results for 5th Grade Science

SS df MS F p ɳp
2

Between 17926.194 7 2560.885 89.944 <.001 .81

Within 4327.750 152 28.472

Total 22253.944 159

Table 2. ANOVA Results for 8th Grade Science

SS df MS F p ɳp
2

Between 32065.794 7 4580.828 130.926 <.001 .86

Within 5318.150 152 34.988

Total 37383.944 159

Table 3. ANOVA Results for 8th Grade Social Studies

48 Educational Research Quarterly December 2020

SS df MS F p ɳp
2

Between 20874.494 7 2982.071 77.341 <.001 .78

Within 5860.750 152 38.558

Total 26735.244 159

Teacher Effects, Student School Attendance and Student

Outcomes: Comparing Low and High Performing Schools in
North Carolina

James S. Etim Alice S. Etim Zachary D. Blizard

Winston Salem State University

Introduction
The No Child Left Behind Act (2002) stipulates that states

assess students during their K-12 educational experience at various
points as a way of measuring student learning. In North Carolina, the
State has the NC Schools Report Card that documents to the public,
parents and educators the state of education in the schools annually.
A major goal of school districts and schools is to ensure student
success, including high level of pass on the state achievement tests.
Educational planners, policy makers, teachers, parents and other
interested parties are engaged in studies and strategies on how to
improve the student performance in schools and the overall quality
of education.

In a globalized economy, one societal goal for educational
institutions is to prepare students for college and the world of work.
In line with this, the focus of the Common Core Standards is the
preparation of students for college and careers. Education has been
called the great equalizer (Spring 2016) and the benefits of education
have been documented by several scholars (Baum and Payea, 2005;
Cattan and Crawford, 2013). Baum and Payea (2005) pointed out that
“There is a correlation between higher levels of education and higher
earnings for all racial/ethnic groups and for both men and women.

Copyright of Educational Research Quarterly is the property of Educational Research
Quarterly and its content may not be copied or emailed to multiple sites or posted to a listserv
without the copyright holder’s express written permission. However, users may print,
download, or email articles for individual use.