A Study Utilizing Resource Classrooms with a Technological ......A Study Utilizing Resource Classrooms with a Technological Course Management System to Improve Literacy and Math in

Running Head: RESOURCE AND CMS TECHNOLOGY 1

A Study Utilizing Resource Classrooms with a Technological Course Management System to

Improve Literacy and Math in Special Education

Julious Morris

University of St. Thomas

Research Professor: Dawn Bradford, Ed.D.

Program Directors: Catherine Barber, Ph.D.

May 2012

RESOURCE AND CMS TECHNOLOGY 2

Table of Contents

Abstract 4

Chapter 1: Introduction 5

Special Education Law 5

Disabilities & Education 5

Resource Classrooms 6

Definition of Key Terms 8

Chapter 2: Literature Review 9

One-to-one Laptop 9

Learning Styles 10

Reading/Literacy Resource Classroom 11

Math Resource Classroom 11

Chapter 3: Method 13

Participants & Sampling 13

District & School Demographics 13

Teacher Demographics 13

Teacher Background 14

Participants 14

Measures 15

Assessment Tools 15

Procedures 16

Data Analysis Plan 17


Chapter 4: Results 18

Implementing the Study 18

Presentation of Results 18

Data Analysis 18

Chapter 5: Conclusion 21

References 23

Appendix 26


Abstract

This study investigated the use of the special education resource classroom along with the

use of one-to-one technology to help improve student literacy and math word problem solving.

The seven participants, with varying disabilities, in this study were in the 6th

to 8th

grades and

were placed by Admission, Review, Dismissal (ARD) committee decision in the special

education setting of the resource classroom. The researcher found that the participants in the

study were reading two or more years below grade level and performed poorly on math word

problems. During this study, the teachers were to utilize their interactive white boards along

with the district Classroom Management System (CMS) training site to enhance their instruction

in the resource classroom. The participants in the study were to utilize their issued laptops along

with the use of the district training site to improve their reading and math problem solving skills,

particularly in word problems. The study revealed that students were assessed with modified

curriculum and had taken the modified version of the Texas Assessment of Knowledge and

Skills (TAKS) state assessment the prior year. In comparison with the new State of Texas

Assessments of Academic Readiness (STAAR) requirements, the researcher found that the

results from numerous math assessments developed and administered with the new requirements

proved to be quite difficult for the participants. During the course of the study the participating

teachers had not utilized his/her interactive white boards and the district CMS training site to

enhance the participants learning. The study also showed that the participants were too

preoccupied with other things on the laptops. The scores from assessments revealed the

participants’ ability to complete math word problems was not successful. Recommendations on

addressing solutions to enhance this study better are provided.


Chapter 1

Introduction

Special Education Law

Public Law 94-142 – Education for All Handicapped Children, later renamed Individuals

with Disabilities Education Act (IDEA), guarantees a “free appropriate public education (FAPE)

to all children with disabilities” (Protigal, 1999). Since the enactment of IDEA, children can be

identified and receive special services from birth to age 21. When looking at the educational

aspect, children identified with a disability as early as age 3 can receive educational services.

Special Education in the United States has shown an increase in numbers of children identified

under IDEA with one or possibly more of the 13 disabilities listed in Figure 1 (see Appendix).

The 25th

Annual Report to Congress on the Implementation of Individuals with Disabilities Act,

Vol. 1, 2003, showed a remarkable increase in children served under IDEA, Parts B and C, over

a 10-year period from the 1992-1993 to 2001-2002 school years. To be age specific, the report

showed the age group 3-21 grew from “5,080,651” to “6,487,260” in the 10-year period (U.S.

Department of Education, 2003). Many changes in education have taken place since the

enactment of IDEA and the current implementation of the No Child Left Behind (NCLB) Act of

2001.

Disabilities & Education

Children that qualify for special education services under IDEA, as seen in Figure 1 (see

Appendix), can be identified with a specific learning disability which is broken down into

various disorders, such as basic reading skills to math calculations, or a child can be identified as

having a mild to severe intellectual disability, formerly known as mental retardation. In


addressing how these children learn, administrators, teachers, and special education teachers

need to know how to approach and adapt their teaching of these children. Regular and special

education teachers are always looking for ways to help their students. The goal of special

education is that children are in the Least Restrictive Environment (LRE) by being educated with

their peers in the regular classroom, commonly called an inclusion or mainstream setting, yet at

times these students’ levels are severe enough that they can be one or more grade levels behind

their peers. Even with accommodations or modifications in the regular classroom, the student

would not learn the concepts that are being taught. At this point, parents and educators look at

student success in the regular classroom and may decide that a more restricted environment of a

special education resource classroom would be more suitable for the student.

Resource Classrooms

“The goal of the resource room is to plan, develop, and provide educational strategies that

meet the unique and varied learning needs of an individual with a disability” (Phillips, 2008). A

resource classroom usually contains a small group of students who can receive specialized

instruction to help raise the students’ academic levels of his/her peers. In a report by Kerri

Phillips, titled The Resource Room in Special Education wrote,

The resource room was originally developed as a way to provide education to individuals

who had difficulty learning in the regular educational classroom. The typical resource

room is a separate classroom where a teacher certified in special education teaches a child

daily for brief periods of time (Blosser & Neidecker, 2002; Fletcher-Janzen, & Reynolds,

2000).

As students are being placed in a more restrictive environment of a resource classroom, the job

of the special education teacher now plays an important role of specializing student instruction.


In today’s technological era, students are growing up with technology as part of their lives, and

teachers are trying to adapt their lessons and teaching to utilizing such technology. School

districts are trying to address this issue by providing teachers with the needed technology in

his/her classrooms. The Technology Immersion Pilot (TIP) in Texas pioneered an entirely new

concept in educational technology—total immersion of faculty and students in technology (TIP,

2009). Alvin ISD in Alvin, TX, has incorporated the project by implementing a one-to-one

laptop initiative for all students in grades 6th

to 8th

, and all core subject teachers will have an

interactive white board in his/her classroom, which includes the special education teachers’

classrooms. The current mathematics textbook being used in the Alvin ISD district incorporates

technology by offering compact discs containing video demonstrations of mathematical concepts

and is readily available to the teachers to show in their classroom which, it is hoped, will

enhance the concept being taught. The job now of educators is to find ways of teaching students

while utilizing this technology. While examining a resource classroom, the question being raised

on a junior high campus, grades 6th

to 8th

, in Alvin ISD was what can be done to help reach these

struggling students in the resource classroom all the while utilizing technology? This study will

show that utilizing the technology will help students in a resource classroom improve student

literacy (reading/writing) and math levels, especially in the areas of solving word problems.


Definition of Key Words

IEP – Individualized Education Plan

IDEA – federal program for individuals with a disability.

FAPE – all children be given free education no matter their disability.

NCLB – federal legislation that identifies/controls student achievement and progress in schools.

Learning disability – child may have a deficit in the area of basic reading, reading

comprehension, reading fluency, written or oral expression, math problem solving, math

calculations, and/or math reasoning.

Intellectual disability – child has mild to moderate cognitive deficits.

LRE – consideration of educating the handicapped student with regular education peers.

Inclusion/ mainstream – student with disability is in the regular classroom with support of a

special education teacher or paraprofessional.


Chapter 2

Literature Review

One-to-One Laptop Programs

Many school districts across the country are implementing some sort of one-to-one

computing program with students in grades 6 to 8 with support of numerous studies on the

effectiveness of these programs. The programs have their pros and cons as noted by Bryan

Goodwin (2011) in his article Teaching Screenagers: One-to-One Laptop Programs Are No

Silver Bullet. Goodwin (2011) states,

“…some school systems that ushered in one-to-one laptop programs amid great fanfare

have begun to scrap them because of budget cuts (Lemagie, 2010); mushrooming

maintenance costs (Vascellaro, 2006); and concerns about how students are using the

computer” (Hu, 2007).

Goodwin (2011) goes on to list some encouraging information with the one-to-one programs

such as,

More engaged learners. A four-year study of 5,000 middle school students in Texas

found that those engaged in laptop immersion programs were less likely to have

disciplinary problems (but slightly more likely to be absent from school) than students in

schools without laptops (Shapley et al., 2009).

Better technology skills. The Texas study also found that the technology skills of

students in the laptop programs improved significantly – so much so that after three

years, low-income students in the laptop schools displayed the same levels of technology

proficiency as wealthier students in the control schools (Shapley et al., 2009).


Cost efficiencies. Proponents of one-to-one programs also assert that such programs

create savings in other areas, including reduced costs for textbooks, paper, assessments,

and paperwork, as well as a reduction in disciplinary actions (Greaves, Hayes, Gielniak,

& Peterson, 2010).

“There is strong evidence that student engagement increased dramatically…” and “… student

research skills and collaboration were enhanced by the improved educational access and

opportunities afforded by the 1:1 pilot program” (Bebell & Kay, 2010). The utilization of the

one-to-one program requires teachers to find ways to enhance their instruction in the classroom

when utilizing this technology. One of the ways that special education teachers are utilizing

technology is through the use of interactive websites that students can use on their laptops all the

while addressing the students’ different learning styles as well.

Learning Styles

Special education teachers look at learning styles to help their students in all settings. It

has been known by educators for years that children do learn by various modalities, and a leader

of addressing this is Neil D. Fleming with the support of David Baum. Fleming & Baum (2006)

address these modalities through their studies and further report that people do learn Visually,

Auditory, Reading/writing, or Kinesthetically (VARK) or a combination of the four categories.

According to Fleming and Baum (2006), who developed the VARK questionnaire, stated that “it

is, technically, not a learning styles’ questionnaire, as it provides feedback only on one’s

preferred modes for communicating” (Fleming & Baume, 2006). Teachers and students can

understand further by “knowing one’s learning style [which] can be beneficial if learners take the

next step, and consider how and when they learn, as part of a reflective, metacognitive process,

with action to follow” (Fleming & Baume, 2006).


Reading/Literacy Resource Classroom

Literacy is a very important factor when educating students today. It is not only the

reading classroom with some writing involved, it is now heavily linked to the writing process

that becomes cross curricular, hitting all subject areas which is a literacy classroom. Savilla

Banister from Bowling Green State University studied the use of technology and how it could

affect literacy in today’s society, titled Web 2.0 Tools in the Reading Classroom: Teachers

Exploring Literacy in the 21st Century. Bannister (2008) reported that for reading specialists,

dedicated to student growth and achievement in reading and writing effectively across the

subject areas, the newest evolution of the World Wide Web provides opportunities for students

to challenge their literacy skills. Teachers are now incorporating the use of the web to deliver

instruction and to enhance student literacy skills. English teachers who currently support the use

of audio podcasts for part of their instruction of reading as reported by Banister (2008) states by

acquiring and listening to these podcasts, their awareness and comfort with the medium

increased. The possibilities of podcasting and vodcasting for students in the resource classroom

has not been explored at this point in time, but the potential for student growth is very promising

when utilizing technology with literacy.

Math Resource Classroom

The possibilities when using the technologies of the one-to-one laptop program in the

special education reading (literacy) classroom are hoped to be a benefit to the teacher and the

student. In the subject of mathematics, however, students learning mathematical concepts could

also benefit from the use of such technology.


“The use of video and audio provides opportunities for all sensory perceptions – auditory,

visual, and kinesthetic – to be engaged during the learning process (Saylor 2004). These

new technologies provide opportunities to improve the educational process” (Franklin &

Peng 2008).

Textbook companies are addressing technology use with mathematics by the issue of videos

which mirror important concepts in the textbook to enhance the learning of the students and the

ease of teacher use in the classroom. Franklin and Peng (2008) studied the use of the iPod

Touch and videos that were pushed out through Really Simple Syndication (RSS) feeds to the

students “that allow students to subscribe and have information sent directly to their devices to

be read as needed 24/7 (i.P.O.C. 2006).” Technology of this magnitude has unlimited potential

to help special education teachers reach their students not only at school but at home as well.

“Schools at all levels are beginning to use iPods and other mobile devices as a means of

delivering coursework and content” (Franklin & Peng 2008). Not only were videos pushed out

to the student but the students in the study made videos themselves about the particular

mathematical concept being taught. The results from Franklin & Pengs’ 2008 study had some

interesting results. One teacher reported that “the iPod was so much fun for the students and

provided ownership to the math concepts being developed into movies. All of the students

talked about how hard it is to explain math to someone” (Franklin & Peng 2008). Teaching

mathematical concepts to students can prove to be a difficult task at times to regular students, yet

when one thinks about how a special needs student learns, this task can be most unbearable.

With the help of technology, one-to-one laptop programs, and knowing how special needs

students learn can be the most beneficial mechanism that a special education teacher can use

today, especially when students are lower than their peers.


Chapter 3

Method

Participants and Sampling

District and School Demographics. Alvin Independent School District is located in

Alvin, Texas, and covers 250 square miles in northern Brazoria County. It serves the

communities of Alvin, Manvel, Iowa Colony, Liverpool, Amsterdam, and parts of Rosharon,

Arcola, and Pearland. The district currently educates over 18,000 students, and the district's

ethnic composition is 44.5% Hispanic, 34% White, 12% African American, 8% Asian, and 1%

other.

The campus where this study will be conducted has a current enrollment of 670 students.

The campus ethnic breakdown is 0.15% Native Hawaiian or Other Pacific Islander, 2.39%

African American, 0.45% American Indian or Alaska Native, 1.9% Asian, 62.69%

Hispanic/Latino, 32.39% White, and 0.75% two or more races. The current special education

count for the campus is 74, which is 11% of the campus receiving special education services. Of

the 74 students in special education, 12 or 16% of these students are in the resource classroom

less than 50% of the day.

Teacher Demographics. There are two teachers being utilized for this study; both

teachers are currently employed by Alvin ISD. Both teachers’ current assignments are special

education inclusion support, co-teaching, and resource classes. Teacher A teaches English

Language Arts/Reading, and teacher B teaches Math. Teacher A is currently teaching two

resource classes during the school day for 50 minutes per class, co-teaches three periods, one

conference period, and one inclusion period during the school day. Teacher B currently teaches


two resource classes during the school day for 50 minutes per class, co-teaches two periods, one

period for conference, and teaches athletics one period.

Teachers Background. Teacher A (female) has a B.A. degree in Anthropology, an M.S.

in Education Management, and is certified to teach Secondary English 6-12, holds a Gifted and

Talented (GT) rider, Special Education PK-12, and Principal PK-12. Teacher A has taught for

12 years in Language Arts grades 7 and 8. She is currently teaching two special education

resource classes in Language Arts grades 6 to 8, and her philosophy is that children in the

resource classroom need some help from a teacher who has the training, experience, and desire

to do exactly what each individual needs to move the students’ forward in the language arts, but

especially in reading.

Teacher B (male) has a B.S. degree in Human Performance and is certified in Physical

Education EC-12, Health EC-12, Special Education EC-12, and is currently waiting for

certification in Math 4-8. Teacher B is currently teaching two special education resource math

classes grades 6 to 8. Teacher B’s philosophy about the resource classroom is that there is a

need for accommodating students with the need for a positive math enrichment program. The

goal is to fill the gaps and assist students at their level of learning.

Participants. The participants in this study are students who have been placed in a more

restricted environment of the resource classroom. There are currently 10 students receiving

special education resource instruction in Language Arts/Reading and 12 students in Math. Of

the total students in the resource classes, permission for participation in the study was only

obtained from eight parents, and during the study one student was removed due to his/her

withdrawal. The participants’ disability range from Intellectually Disabled, Autism, to Specific

Learning Disabilities with various related services they receive, as seen in Table 1 (see


Appendix). In Table 2 (see Appendix), you will see the educational placement of the

participants in the study from his/her Individualized Education Plan (IEP) placement

determination. The students who are scheduled for the resource classroom are divided by grade,

each teacher teaches a class of 6th

graders, and then the second class is a combination of 7th

and

8th

graders due to changes in curriculum requirements from 6th

grade to 7th

grade. Each student

has been issued a laptop mini for use in all of their core subject areas and has access to the

internet and Moodle, the current district training site.

Measures

Assessment Tools. At the beginning of the study, the students completed a

Developmental Reading Assessment (DRA). The DRA it is a set of individually administered

criterion-referenced reading assessments for students in kindergarten through Grade 8. Modeled

after an informal reading inventory, the DRA is intended to be administered, scored, and

interpreted by classroom teachers. (Natalie Rathvon, PhD., n.d.) This gave a further

understanding of student reading comprehension as a predictor for student accuracy on solving

word problems. Students’ scores on the prior year’s TAKS-Modified test were used as the

starting point of the analysis. These scores were the indicator of where the students should be at

his/her grade level 6th

– 8th

in Reading and Math. Throughout the course of the year students

were given various assessments to measure their progress in reading and math. All students

received accommodations as noted in their current IEP. As a final assessment, the students

completed a Simulated STAAR assessment in Reading and Math. The new STAAR assessment

“tests content students studies that year, as opposed to testing content studied over multiple

years” (TEA, 2010)


Procedures

This study began with gaining permission for the students to participate in the study. Of

the 12 students who were placed in the resource classroom, only 7 students were participants of

the study. The resource teachers were eager to participate and support the study. Each student in

the study had previously been issued a laptop mini to be used in their academic classes and was

to participate in the district training site Moodle. Moodle is a Course Management System

(CMS), also known as a Learning Management System (LMS) or a Virtual Learning

Environment (VLE). This web application allows educators to create effective online learning

sites through the utilization of forums, glossaries, wikis, assignments, quizzes, choices (polls),

and databases. (Moodle, 2012) Teachers of this study were to utilize this site by creating

projects and lessons on various topics to support his/her lessons with the use of links to various

sites that students, who enroll in the class, can access 24/7. This encourages students to add to

the total course experience for others. (Moodle, 2012) Each of the participants completed a

DRA, Reading and Math simulation assessment, and several Math Unit Tests. Through these

assessments, the reading and math objectives are aligned with the Texas Essential Knowledge

and Skills (TEKS) for the particular grade levels which are aligned with the National Standards

for reading and math. During the study, the students were to utilize their laptops to access

lessons through the district training site which supported what was being taught in the resource

classroom. It is noted, this is the first year for this campus to have resource classes in many

years. Data collection of student scores was gained through the website utilized by the district

called Eduphoria, a web application from School Objects, which is a database warehouse site

that houses all students’ assessment scores in the district.


Data Analysis Plan

During this study, several instruments were used to assess the participants. For the

purpose of this study, the participants were assessed with the Developmental Reading

Assessment (DRA) in the fall and previous Texas Assessment of Knowledge and Skills-

Modified (TAKS-Modified) scores on the Reading and Math. These scores are being reported as

part of the data to establish a baseline for further assessments. The students were given a

simulated State of Texas Assessment of Academic Readiness-Modified (STAAR-M) assessment

in Reading and Math, and the data are being used for reporting purposes. The participants were

also given Math Unit Tests in which the majority of the tests consist of word problems and were

modified at the appropriate grade level. A Math Unit Test sample could not be obtained due to

district copyright, and permission was not obtained. Since the STAAR test does not have

computation or vocabulary questions, the TEKS that are connected to these problems closely

meet the intent of the TEKS. The ultimate goals of these assessments demonstrate an authentic

assessment of progress. The statistical information of the assessments that were given is

presented in the next chapter.


Chapter 4

Results

Implementing the Study

Analysis was composed of identifying areas associated with comprehension of material

that is being taught with the support of the resource classroom. Reading comprehension was

analyzed by the number of questions correct in all reading objectives. Math was an analyses of

the students’ correct answers of word problems and a further breakdown of the six math

objectives. The study looked at the use of the CMS training site Moodle that the teachers were

to utilize to enhance their classroom teaching for the students in the resource classroom. Data

were gathered on numerous Math Unit Tests taken by the participants.

Presentation of Results

Figure 2 and Table 3 (see Appendix) display the results of the participants’ fall reading

levels gained from the DRA assessment. Figure 2 illustrates the participants’ scores to be

significantly low compared to where they should be for their grade level. Table 3 shows the

equivalent grade level for their scores, which shows that the participants are reading two or more

years below grade level. This information is an important factor of how the students performed

on the Reading and Math assessments.

Data Analysis

Data that are collected on the participants was from the students’ current IEP and scores

from TAKS-Modified assessments, STAAR-Modified simulation assessments, and Math Unit

Tests-Modified that each participant in the study had completed. Figures 3 and 4 (see Appendix)

show his/her previous school years TAKS assessment percentage scores in comparison with the

STAAR simulation percentage scores for Reading and Math. The STAAR simulation

Table 3: DRA Levels


assessments are based on the new state requirements and administered according to new

regulations. To further analyze this data, the objectives for the math assessments are displayed

in Figures 5 through 9 (see Appendix). The information gathered on each of the participants in

the study was gained through the Eduphoria-School Objects website, which houses the database

of student scores for all assessments taken within the district. The assessments were by order of

particular objectives for each assessment. The information was input into a spreadsheet to

further analyze the data and to gain the average, median, standard deviation, and t-scale for each

objective represented in the Math Unit Tests. As seen in Figures 3 and 4 (see Appendix), one

can see the students’ performance on their TAKS-Modified assessments, which assesses

students’ minimal skills, as compared to the STAAR-Modified simulation assessments, which

shows significant differences of student performance.

The data show that with the difference of requirements of the Reading TAKS-M to the

STAAR-M simulation this difference to be considered extremely statistically significant with a

two-tailed P value of 0.05, with an average of the TAKS-Modified tests to be 62.14%, and a

standard deviation and a t-scale score of σ=13.85. This is compared to the STAAR-Modified

simulation tests, with an average of 43%, with a standard deviation of σ=5.10, for an overall

t-scale score of t=3.43, with a difference df=12, and the standard error of difference of 5.58. The

mean of the TAKS-M to the STAAR-M simulation equals 19.14 with an interval difference from

6.99 to 31.30.

As for the Math TAKS-M to the STAAR-M simulation difference, it is considered to be

extremely statistically significant with a two-tailed P value equal to 0.0007. Results of an

average of the TAKS-Modified tests were 60.43%, and a standard deviation of σ=14.68. This is

compared to the STAAR-Modified simulation test, which had a mean of 26.43 with a standard


deviation of σ=13.39. An overall t-scale score of t= 4.53 showed a difference of df=12 and the

standard error of difference of 7.51. The mean of TAKS-M to STAAR-M simulation equals

34%, with a 95% confidence interval difference from 17.63 to 50.37.

The participants in the study completed seven math unit tests with the following

statistical information. Figure 6 (see Appendix) displays the students’ scores for Objective One

to have a mean score of 48%, with a median score of 44%, and a standard deviation of 0.1.

Objective Two, Figure 7 (see Appendix), had a mean score of 51%, with a median score of 45%,

and a standard deviation of σ= 0.26. On Objective Three, Figure 8 (see Appendix), had a mean

score was 72%, with a median score of 71%, and a standard deviation of σ= 0.26. Figure 9

(see Appendix) displays Objective Four with a mean of 49%, with a median of 72%, and a

standard deviation of σ=0.42. Objective Four was only assessed on two of the seven

participants. Objective Five was only assessed on one participant in the study, therefore no

relevant data are presented. Objective Six, Figure 10 (see Appendix), had a mean score of 64%,

and a median of 67%, and a standard deviation of σ=0.37. In comparison of the students’

scores from the first math unit test to the seventh test, the following statistical information to be

considered to be not statistically significant from a two-tailed P value was equal to 0.68. The

mean of the first test was 48%, with a standard deviation of σ=9.87 compared to the seventh

tests, with a mean of 54.86%, standard deviation of σ=41.66. The mean of the first test to the

seventh test was equal to -6.86 with a 95% confidence interval difference from -42.11 to 28.40,

with a t-scale score of t=0.42, with a difference of 12, and a standard error of difference of 16.18.


Chapter 5

Conclusion

This study was to show that utilizing the CMS technology would help students in a

resource classroom improve student literacy (reading/writing) and math level, especially in the

areas of solving word problems. This study can be of use for special and regular education

teachers as well as campus principals and district administration.

Throughout the study, the resource teachers were to utilize the CMS site Moodle, in

conjunction specifically with the students’ laptop minis, to coincide with their lessons to help the

student improve on assessments, especially in the areas of reading math word problems. The

researcher found that the teachers had great difficulty integrating the technology with their

lessons. The teachers’ interactive white boards were not properly installed until half of the study

was implemented. The participants themselves did not utilize the laptops to the degree they were

meant to be used. One example was that upon the researchers’ observation, the participants were

playing games instead of working on skills to improve their reading ability and math problem

solving skills.

Therefore, the study did reveal that with the support of the resource classroom, one-to-

one laptops, and the utilization of the CMS technology students’ scores showed no improvement

when it came to reading and math assessments. The researcher also found that the new STAAR

assessment requirements are very difficult, and the scores showed this could be a true indicator

of the participants’ ability. The lack of teacher experience in teaching a resource class could

have been a factor. The researcher would recommend that professional development for the

teachers is warranted in utilizing technology in the classroom. The researcher also noted that


results could have been a factor of the teachers’ instructional methods in the classroom. The

research would warrant that further study could be conducted to see if the teachers’ instructional

methods and use of technology could efficiently prepare the students in the resource classroom

for stronger performance on the new regulations of the STAAR assessments.


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Appendix

List of Tables and Figures

Figure 1: Categories of Disabilities under IDEA

Table 1: Student Demographics

Table 2: Participants Placement

Figure 2: Fall DRA Level at a Glance

Table 3: Fall DRA Level Equivalents

Figure 3: TAKS to STAAR Simulation Scores Reading

Figure 4: TAKS to STAAR Simulation Scores Math

Figure 5: Math Unit Tests Objective 1






Figures 1: Categories of Disabilities under IDEA

Categories of Disabilities under IDEA

1. Autism 2. Deaf-Blindness 3. Deafness 4. Emotional Disturbance 5. Hearing Impairment 6. Intellectual Disability (Mental Retardation) 7. Multiple Disabilities 8. Orthopedic Impairment 9. Other Health Impairment 10. Specific Learning Disability 11. Speech or Language Impairment 12. Traumatic Brain Injury 13. Visual Impairment (including Blindness)

Adapted from NICHCY Web


Student Grade Gender Disability Related Service SES ESL

A 8 M AU, OHI (ADHD) Counseling N N

B 8 M AI None Y N

C 7 M ID, SI Occupational Therapy Y N

D 7 M LD (RC, LC, OE) None Y Y

E 7 F LD (MP, OE) None Y N

F 8 M AU, SI PASS Y N

G 6 M LD (BR,RC,RF,WE) None N Y

Disability: AU-Autism; OHI-Other Health Impairment; SI- Speech Impairment; LD-Learning Disability

Qualifying Areas of LD: BR-Basic Reading; RC-Reading Comprehension, RF-Reading Fluency; OE-Oral Expression, WE-Written

Expression, LC-Listening Comprehension, MC-Math Calculations, MP-Math Problem Solving

Table 1. Student Demographics


Student Grade Gender Educational Placement Type Resource Class

A 8 M 42-at least 21% & < 50% Reading & Math

B 8 M 42-at least 21% & < 50% Reading & Math

C 7 M 42-at least 21% & < 50% Reading & Math

D 7 M 42-at least 21% & < 50% Reading & Math

E 7 F 41-less than 21% Math

F 8 M 41-less than 21% Math

G 6 M 42-at least 21% & < 50% Reading & Math

Table 2. Participants’ Placement


80 80

70 70 70

80

60

50

42 39 40

46

40 37

S1 S2 S3 S4 S5 S6 S7

DRA Levels

Required Reading Level Fall DRA Level

Figure 2: Fall DRA Level at a Glance


Student Grade Required

Reading Level DRA Level Grade Equivalent

A 8 80 50 5th

grade

B 8 80 42 4th

grade mid-year

C 7 70 39 3rd

grade end of year

D 7 70 40 4th

grade beginning of year

E 7 70 46 4th

grade end of year

F 8 80 40 4th

grade beginning of year

G 6 60 37 3rd

grade end of year

Table 3: Fall DRA Level Equivalents


34%

76%

59% 59%

71% 68% 68%

48%

40% 44%

33%

47% 45% 44%

1 2 3 4 5 6 7

Reading Assessments

Reading TAKS Score Reading STAAR Simulation Score

Figure 3: TAKS to STAAR simulation scores Reading


42%

55%

62%

76%

43%

79%

66%

36%

30% 34%

40%

23%

0%

22%

1 2 3 4 5 6 7

Math Assessment

Math TAKS Score Math STAAR simulation Score

Figure 4: TAKS to STAAR simulation scores Math


49%

36%

43%

55%

66%

44% 43%

48% 44%

0.10

S1 S2 S3 S4 S5 S6 S7 Average Mean St. Dev.

Math Unit Tests

Obj 1

Figure 5: Math Unit Test Objective 1


45%

53%

30%

96%

22%

37%

73%

51% 45%

0.26


Math Unit Tests

Obj 2



76%

31%

100% 100%

62% 65% 72% 71%

0.26


Math Unit Tests

Obj 3



72% 75%

0%

49%

72%

0.42


Math Unit Tests

Obj 4



0%

67%

50%

100% 100%

67% 64%

67%

0.37


Math Unit Tests

Obj 6


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