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Statement of the problem
Virtual learning was once an uncommon concept that has become an accepted method in
American education (Pape, Adams, & Ribeiro, 2005). When virtual schools began to develop in
the 1990’s, they generally served gifted and talented (GT) students offering accelerated and
advanced placement courses for enrichment. Since that time, virtual schools have continued to
develop and offer a variety of courses to students with a range of different educational needs.
Students with disabilities are becoming more attracted to virtual schools and have shown
increased enrollment (Hassel & Terrell, 2004; Rhim & Kowal, 2008).
Interest of students with disabilities in virtual schooling in combination with mandates to
close achievement gaps and increase graduation rates have drawn the attention of virtual schools
to address the needs of students with disabilities (Muller, 2010; Repetto, Cavanaugh, Wayer, &
Liu, 2010). Repetto, Cavanaugh, Wayer, & Liu (2010) addressed virtual high schools and
outcomes of students with disabilities by discussing five issues, referred to as the five Cs (i.e.,
“connect, climate, control, curriculum, and care”), associated with the high dropout rate among
students with disabilities and discussed ways virtual schools could improve outcomes for these
students (p. 93).
According to Repetto, Cavanaugh, Wayer, & Liu (2010), the number of students with
disabilities enrolled in virtual schools is unknown because of the lack of data collected on these
students. It is estimated that the population of students with disabilities enrolled in virtual
programs is similar to the traditional school population. The United States Department of
Education reported that 13.6% of students served in traditional school programs had a disability
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during the 2006-2007 school year (U.S. Department of Education, 2009). Much of the data
collected by virtual school programs is student reported. Many virtual schools merely require
students to report the presence of an Individualized Education Program (IEP). Because a great
majority of virtual schools are supplemental to traditional schools, they do not get a copy of the
IEP document or require disability specific information (e.g., disability type) to be reported. To
best serve students with disabilities in virtual schools, disability specific data must be researched
(Kim-Rupnow, Dowrick, Burke, 2001; Muller, 2010; Repetto, Cavanaugh, Wayer, & Liu, 2010).
According to the National Education Technology Plan, housed under the No Child Left
Behind Act (NCLB), virtual schooling was recommended as a school choice option for students
with disabilities (Hassel & Terrell, 2004; Rice, 2006). In order to develop evidence-based
practices for students with disabilities further research is needed to learn how to help these
students successfully complete virtual school courses (Repetto, Cavanaugh, Wayer, & Liu,
2010). Virtual schools will need to take part in a system change that implements best practices
for serving students with disabilities in a digital setting. (Repetto, Cavanaugh, Wayer, & Liu,
2010). Current research suggests the number of students with disabilities enrolling in virtual
school courses will continue to increase (Repetto, Cavanaugh, Wayer, & Liu, 2010; Hassel &
Terrel, 2004; Rhim & Kowal, 2008). Thus, it is important for researchers to recognize this and
develop quality virtual school programs for these students.
Research Design and Theoretical Framework
The research design for the present study consists of a qualitative framework using
quantitative data. The nature and novelty of this study call for a unique design. Research has
begun to recognize the importance of serving students with exceptionalities in virtual schools,
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but has neglected examination of how these students have performed in virtual settings to date
(Hassel & Terrel, 2004; Kim-Rupnow, Dowrick, Burke, 2001; Muller, 2010; Rhim & Kowal,
2008; Repetto, Cavanaugh, Wayer, & Liu, 2010). In order to explain the performance of students
with exceptionalities in virtual schools, it is first necessary to know how these students are
performing. Study results will allow for development of grounded theory. Figure 1 provides a
diagram of the research design and potential theoretical explanation.
Three potential outcomes are possible. Students with exceptionalities may perform
similar to, better than or worse than students without disabilities. Theoretical possibilities for
these outcomes are discussed in following sections. In addition to student outcomes, pace
requests will be examined. Florida Virtual School (FLVS) students select one of three paces (i.e.,
traditional, extended or accelerated) when they enroll in a virtual course. Research shows that
extended time benefits students with disabilities (Alster, 1997; Elliott, & Marquart, 2004;
Runyan, 1991; Sireci, Scarpati, & Shuhong, 2005; Zuriff, 2000). The present study will
determine if subjects with exceptionalities request additional time and if they actually used the
additional time requested. The relationship between pace and final course grade will be
examined. Possible theoretical explanations have been considered for each potential outcome.
Students with exceptionalities perform lower and experience more academic struggles
than students without exceptionalities in traditional school settings (Benz, Lindstrom, &
Yovanoff, 2000; Osgood, Foster, Flanagan, & Ruth, 2007; Reschly & Christenson, 2006;
Kaufman, Alt, & Chapman, 2001). Results indicating that students with exceptionalities perform
as well as or better than students without exceptionalities would show that virtual schools may
better meet the needs of students with exceptionalities. The cognitive load theory and Maslow’s
hierarchy of needs are two theories that may provide an explanation for such an outcome.
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Should results indicate that students with exceptionalities perform worse than students
without exceptionalities, there are three theories that may provide an explanation. Readiness,
transactional distance, and self-efficacy theories provide possible explanations for low
performance among students with exceptionalities in virtual schools. Theories in support of
virtual schools for students with exceptionalities are discussed in following sections.
Cognitive Load Theory
The cognitive load theory was developed by John Sweller in 1988. Paas, Renkl, and
Sweller (2003) summarized cognitive load as, “working memory, in which all conscious
cognitive processing occurs, can handle only a very limited number-possibly no more than two
or there-of novel interacting elements” (p.2). The ultimate goal of cognitive load theory is to
provide guidelines for presenting an amount of information that will promote optimal learning
(Sweller, Van Merrienboer, and Pass, 1998, p. 251). Cognitive load refers to the load put on the
working memory during the learning process. The heavier the cognitive load that has to be
learned in a short amount of time, the more challenging it is for an individual to process the
information in short term memory. In order for optimal learning to occur, cognitive load must be
According to Chandler and Sweller (1992), cognitive load can be made heavier by
irrelevant tasks. An example he used was taking a test written in another language. The cognitive
load for such a task would be multiplied for the test taker as they would spend more time
processing and translating the questions rather than the responses to the questions. The test being
in another language is an unnecessary contributor to cognitive load. Cognitive load can often be
reduced significantly through careful consideration of the actual necessity of each required task.
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Cognitive load theory relates directly to this study by helping to explain and predict the
potential benefits and outcomes of virtual schooling for students with exceptionalities.
Traditional school settings impose a heavy cognitive load on students. In order to arrive at school
by a specific time, students must complete a variety of tasks (e.g., setting an alarm, preparing and
selecting clothing, completing a hygiene routine, selecting, preparing and eating a meal, planning
for, preparing and selecting a meal to take, transportation considerations, etc.). These tasks often
impose a heavier than normal cognitive load for students with exceptionalities who have slower
Once students arrive at school, they may have already reached cognitive overload. They
have to find their lockers and make sure they have all needed supplies, and arrive at the correct
classroom before it begins. The strict schedule of traditional school settings often do no allow
students to spend as much time as needed on academic tasks. Additionally, students are forced to
take classes that a school offers at the time of day that works out for scheduling purposes. This
may present challenges for students with exceptionalities who may struggle in math and find
themselves more alert in late afternoon, but are required to take math first in the morning. The
traditional school setting requires many cognitive tasks that may overload students with
Virtual school environments may reduce the cognitive load of students with
exceptionalities by requiring less cognitive tasks in order to attend. Virtual schools allow
flexibility of schedule, pace, and course selection. Students are given the option to take classes
any time during the day and in any order they prefer. Virtual courses allow students to take as
many necessary breaks as needed and review information as many times as a student needs.
Additionally, virtual schools often offer courses that are not available in traditional school
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settings. It seems that virtual schools may reduce cognitive load which may help improve the
outcomes of students with exceptionalities.
Maslow’s Hierarchy of Needs
In addition to reducing cognitive load to improve learning outcomes, Abraham Maslow’s
hierarchy of needs suggests students physiological, safety, belongingness and love, and esteem
needs be met before higher order skills such as academic learning are able to occur. Maslow’s
higherarchy of needs in Figure 2 describes five levels of human need that must be met before an
individual reaches self-actualization (Maslow, 1943). One set of needs must be met before the
next set of needs can be met. The first domain, physiological needs, includes the basic life needs
such as food, drink, sleep, and shelter. The second domain, safety needs, includes security and
psychological safety. Maslow suggests that meeting one’s safety needs are secondary to meeting
one’s physiological needs. For example, an individual is not going to care about their security if
they are starving and homeless. An individual’s need to be eat and have shelter are more
concerning than their personal safety.
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Figure 2. Maslow’s Hierarchy of Needs
Education researchers have applied Maslow’s hierarchy of needs to school settings
suggesting that education must first meet the basic needs of students before they are expected to
learn. Virtual school settings may help meet some of the basic needs of students with
exceptionalities that help to improve their outcomes. The scheduling constraints of traditional
school settings impact the physiological needs of students of students. The hours of traditional
school settings often require students to arrive early to school and may not allow students to get
adequate sleep. The lunch schedules of traditional high schools may have students eating lunch
too early or too late leaving them hungry at some point during the school day. Often classrooms
can be too cold or too hot, impacting student learning. Learning is effected by lack of sleep,
hunger and being uncomfortable.
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Once physiological needs are met, safety needs are of second importance according to
Maslow. There are many safety issues related to traditional school settings. Students who ride a
school bus wait at bus stops that are not always safe to then get on a school bus where there is
much potential for bullying. Throughout the school day there are many opportunities for student
safety to be threatened by other students (e.g., lunch room, during transitions between classes,
and waiting for the bus in morning and afternoon). Students with exceptionalities may have
potential to struggle with safety concerns more than students without exceptionalities. They may
be bullied or picked on more easily because of their exceptionally low or high intelligence.
Students with physical impairments may fear for their safety in navigating the school or in the
case of an emergency. Students with quadriplegia for example, have to depend on another
capable person to complete every physical task. Individuals with quadriplegia would have to
have help during emergency situations (e.g., fire, bomb threat, or shootings). This dependency
can threaten the safety of students with exceptionalities. According to Maslow’s theory, students
cannot learn if they do not feel safe. Virtual schooling removes these threats by allowing students
to learn in an environment where they feel safe.
Belongingness and love needs are the third tier of Maslow’s hierarchy that suggests
students must feel a sense of belonging and acceptance before learning can occur. This has been
a significant issue for students with exceptionalities for decades. In cultures worldwide,
individuals with exceptionalities are outcasts and misfits because of their differences. Fitting in
and feeling accepted maybe one of the most unmet need of students with exceptionalities. These
students receive different work in different classrooms. They have different needs and often
behave differently. Peers and teachers alike can tend to focus on and highlight these differences.
Traditional school settings often unknowingly highlight the differences of students with
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exceptionalities. These students never achieve a sense of acceptance or belonging. According to
Maslow, they are not able to learn effectively until this occurs. The set-up of virtual schools
lowers the visibility of these differences. This is discussed further in the review of literature.
Finally, the esteem needs of students must be met before learning can take place
according to Maslow. Esteem needs include feelings of competence, approval and recognition.
Students with mild disabilities often exert all of their energy attempting to keep up with the rest
of their class members. Many times, they barely get by in order to move on to the next level and
often lag behind academically, never achieving competence, approval or recognition. Gifted and
talented students are often ostracized for their advanced skills rather than recognized and
approved for their accomplishments. The decreased visibility of exceptionalities in virtual school
settings may help these students develop a sense of belonging, approval and acceptance in the
virtual environment. The immediate feedback and availability of instructors allows for more
opportunities for students to gain a sense of belonging and approval.
Although most traditional high schools make every effort to meet the needs of both
students with and without exceptionalities, it is realistically impossible for them to do so. The
principles and set-up of virtual schooling seem to naturally meet the physiological, safety,
belongingness and love, and esteem needs of students with exceptionalities.
The combination of Sweller’s Cognitive Load Theory and Maslow’s Hierarchy of Needs
serve as a potential theoretical explanation for sucessuful outcomes of students with
exceptionalities in FLVS. The set-up of virtual schooling may reduce the cognitive load of
students with exceptionalities by removing unmeaningful cognitive tasks while allowing students
CARRIE ALLDAY THEORETICAL FRAMEWORK 10
to give their best cognitive efforts towards academic learning. The set-up of virtual schooling
may also help meet Maslow’s hierarchy of needs allowing students to learn academic content
and skills. The combination of these theories as a theoretical perspective support the notion that
virtual schooling may benefit students with exceptionalities and improve their outcomes by
reducing cognitive load and meeting students needs.
Alster, E. (1997). The effects of extended time on algebra tests scores for college students with
and without learning disabilities. Journal of Learning Disabilities, 30, 222-227.
Benz, M., Lindstrom, L., & Yovanoff, P. (2000). Improving graduation and employment
outcomes of students with disabilities: Predictive factors and student perspectives.
Exceptional Children, 66(4), 509-530.
Chandler, P., & Sweller, J. (1992). The split-attention effect as a factor in the design of
instruction. British Journal of Educational Psychology, 62, 233-246.
Elliot, S., & Marquart, A. (2004). Extended time as a testing accommodation: Its effects and
perceived consequences. Exceptional Children, 70, 349-367.
Hassel, B., & Terrell, M. (2004). How can virtual schools be a vibrant part of meeting the choice
provisions of the No Child Left Behind Act? U.S. Department of Education Secretary’s
No Child Left Behind Leadership Summit: Increasing Options through e-learning.
Washington, D.C.: Author
Kaufman, P., Alt, M., & Chapman, C. (2000). Dropout rates in the United States, 2000:
Statistical analysis report. Retrieved from ERIC database. (ED460174)
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Kim-Rupnow, W., Dowrick, P., & Burke, L. (2001). Implications for improving access and
outcomes for individuals with disabilities in postsecondary distance education. The
American Journal of Distance Education, 15(1), 25-40.
Maslow, A. (1943). A theory of human motivation. Psychological Review, 50(4), 370-396.
Muller, E. (2010). Virtual K-12 public school programs and students with disabilities: Issues and
recommendations. Alexandria, VA: Project Forum at the National Association of State
Osgood, D., Foster, E., Flanagan, C., & Ruth, G. (2007). On your own without a net: The
transition to adulthood for vulnerable populations. Chicago, IL: University of Chicago
Paas, F., Renkl, A., & Sweller, J. (2003). Cognitive load theory and instructional design: Recent
developments. Educational Psychologist, 38(1), 1-4.
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outcomes for students with disabilities. The Quarterly Review of Distance Education,
Reschly, A., & Christenson, S. (2006). Prediction of dropout among students with mild
disabilities: A case for the inclusion of student engagement variables. Remedial and
Special Education, 27(5), 276-292.
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Rhim, L., & Kowal, J. (2008). Demystifying special education in virtual charter schools.
Alexandria, VA: National Association of State Directors of Special Education. Retrieved
September 1, 2010 from www.uscharterschools.org/specialedprimers
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Runyan, M. (1991). The effect of extra time on reading comprehension scores for university
students with and without learning disabilities. Journal of Learning Disabilities, 24, 104-
Sireci, S., Scarpati, S., & Shuhong, L. (2005). Test accommodations for students with
disabilities: An analysis of the interaction hypothesis. Review of Educational Research,
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive
Science. 12(2), 257-285.
Sweller, J., Van Merrienboer, J., & Paas, F. (1998). Cognitive architecture and instructional
design. Educational Psychology Review, 10, 251-296.
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