Robert Spence (2010) in his article “The Effects of Inclusion on the Academic Achievement of Regular Education Students” focuses on the influence that special need students have on regular education students when they learn in the same class. The author seeks to reveal that there is limited impact on the academic outcomes that are attained by students without special needs when they study in a classroom that is inclusive of learners who have special needs. This issue has been debated widely in the past few years. Stakeholders in the education sector have been concerned about students with particular special needs studying together with students who do not have special needs. Some scholars have held that learners studying in inclusive classes are likely to score poorly in their academic journey. However, the truth is that normal students would score the same grades whether they are in inclusive classes or in non-inclusive ones.
Summary of the Article
In the article Spence discusses the background of inclusive learning in schools, that is, the shift to learners who have special needs studying with the ones who do not (Spence, 2010). He notes that the No Child Left Behind Act was the culmination of the efforts to ensure that there was no discrimination in the classroom based on a learner’s special needs, including disability, language proficiency, race, and socio-economic status. The Act imposes pressure on school administrators to comply by allowing non-regular learners to share classes with normal students (Spence, 2010). Consequently, the inclusion raises questions whether conventional students in such settings perform optimally compared to the same learners in classes that are non-inclusive.
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Regarding the researcher’s methodology, he sought to find out the impact of inclusion on the academic excellence of students who do not have special needs. To do so, Spence uses a casual-comparative research study. In the research, learner achievement is determined by the Criterion-Referenced Competency Test (CRCT) reading and Mathematics scores of middle-school learners (Spence, 2010). This type of study is quantitative in nature and a non-experimental investigation, whereby researchers endeavor in unearthing the cause and effect relationships. The presumed cause, that is, normal students who are placed in an inclusive classroom, are an independent variable. On the other hand, the presumed effect, that is, student achievement is treated as the independent variable. Moreover, the study takes a post facto research design, that is, a quantitative study that involves studying causes after they have presumably affected the variable under study (Spence, 2010). He uses this design for two reasons: the subsets to be studied are created prior to the commencement of the study and changing the independent variable (assignment of the inclusion classes) is not possible.
Furthermore, Spence uses convenience sampling in his study. This is a sampling approach that involves selecting cases that are easy to access. In this study, convenience sampling is used to obtain the sample population, which is selected from middle-school learners within a medium-sized school system located in Southeast Georgia. The sample is the sum of the population of middle-school students without special needs studying in inclusive classes and normal students studying in classes that are non-inclusive who are taught by the same normal teacher. Learners who met the criteria from every middle-school in the jurisdiction in the academic calendars of 2007 to 2008 and 2008 to 2009 were part of the sample used in the study (Spence, 2010). The sample population has three hundred students, and over one hundred learners in each category are compared.
Additionally, the Criterion-Referenced Competency Test (CRCT) is used to determine the academic achievements of the learners. The Test is designed to determine how well learners attain, learn, and accomplish the knowledge specified in a given curriculum. In Georgia, the Test would determine how well learners acquire the knowledge prescribed in the Georgia Performance Standards (GPS). Every middle-school learner in the State has to undertake the Test close to the end of the academic year. The subjects that are tested include Science, Mathematics, Social Studies, and reading (Spence, 2010). However, in this specific study, learner achievement is measured using scaled results from CRCT score in Mathematics and reading.
Moreover, data collection in this study involves seeking permission from school principals. Since the author is a principal in one of the schools in the locality; it is not difficult to get permission from them to collect data from their schools. He collects information from Infinite Campus (school system information database). Consequently, there is no direct contact between the researcher and the learners in his quest to collect data. The names of the learners are only used in sorting them into classes and in test outcomes (Spence, 2010). A different database is created via numerical codes, which represent the names of the learners and connecting them with CRCT scores and classroom assignment results.
Similarly, the author uses inferential and descriptive statistics in the analysis of data because quantitative data is the most ideal for making comparisons between the results for the two groups. Descriptive statistics are helpful in summarizing, organizing, and displaying numerical data sets. On the other hand, inferential statistics are mathematical procedures that use probabilities and data regarding a sample to come up with conclusions about the sample population. CRCT outcomes emanating from the results obtained by the learners in math and reading from both groups are compared to determine the spectrum for the dependent variable (Spence, 2010). To remove the teacher as a probable obstacle, only learners allocated to regular teachers who presently teach in inclusive settings are used in the study. To initially equalize the test scores of the learners, he uses analysis of covariance (ANCOVA) in disaggregating the data. ANCOVA is a procedure that helps determine whether the variations between the mean results of two or more subsets on one or more dependent variables can have a statistical impact, after controlling one or more extraneous variables. In the research, ANCOVA is used to adjust previous CRCT results for students from both groups, thus, equalizing them prior to the study and offering a more generalizable conclusion. Also, quantitative data is analyzed by the Statistical Package for Social Sciences (SPSS) (Spence, 2010). Multiple displays, including tables present the findings of the study.
The author has succeeded to use various statistical methods to reveal interesting findings from the research. From the study, the research resulted into two pertinent findings. First, there is statistically significant variation between the CRCT math results between students in a middle-school who do not have any special needs and who are placed in an inclusive classroom with learners who have special needs and the academic outcome of those without special needs in non-inclusive classrooms. Normal learners who are placed in non-inclusive settings scored higher in the year 2008 to 2009 CRCT math results compared to the ones who were placed in inclusive classrooms (Spence, 2010). Second, there is a significant statistical difference between the scores obtained from the CRCT math results of normal male students who are placed in non-inclusive classrooms and those assigned to inclusive ones (Spence, 2010). Those that are placed in environments that are non-inclusive attained higher scores in CRCT math scores for the academic year 2008-2009 compared to those assigned to classrooms that were inclusive.
The preceding findings are critical in making his audience understand how other factors, including gender, may influence the outcomes of test results obtained by students in environments that are inclusive and those that study in the ones that are non-inclusive. These findings are valid since they are a reflection of the fact that students who do not have special needs may perform well in non-inclusive environments since they are not distracted from the learning process by trying to fit into the needs of those that require specialized instruction. However, the outcomes and variations in the scores of the tests may be influenced by other factors (Szumski, Smogorzewska, & Karwowski, 2017). This means that the outcomes of the study may be critiqued to reveal the flaws that may have influenced the results.
History of special education
In this article, the author discusses how special education has transformed over time due to various legislations and regulations that have been put in place. During the Twentieth Century, most children who had special needs in education were discriminated from learning in the conventional classrooms despite the fact that there have been laws making education compulsory (Spence, 2010). In many instances, parents had only two alternatives regarding such children: have them institutionalized or they remain at home. By 1930s, parent began forming advocacy groups that were meant to promote the interests of students who had special needs. As a result, special education laws were adopted to help such learners in their quest to obtain education (Spence, 2010). Laws and regulations that were meant to promote the education of such children led to the creation of self-contained special education.
Self-contained Special Education alienates the learner from the rest of the school for all academic subjects to learn in a small controlled environment with a special education teacher. During the mid-Twentieth Century, most of the special education learners were put in special schools or self-contained classrooms where they learnt with others who had special needs (Spence, 2010). Studies have revealed that there was limited academic improvement among such learners on curriculum-based or standardized measures.
A literature review shows that there are two major limitations of teaching special needs learners in self-contained classrooms. First, such students cannot observe positive student role models to assist them to have positive learning outcomes (Spence, 2010). They usually interact with other learners who have disabilities. Therefore, learners who have emotional behavior issues placed in the same class the whole day with other students who possess the same behavioral challenges do not have a learner with a positive behavior acting as a role model in the study environment. Second, subject matter discussions are reduced in such classrooms (Spence, 2010). In conventional classrooms, studies show that learners in normal education classrooms have teachers who are certified in their respective subject to teach the students, learners in self-contained classrooms hardly have an instructor who is qualified to teach in the subject area.
However, Kavale and Forness (2000) highlight two benefits that accrue to special needs students who learn in self-contained classrooms. First, such learners do not impede the learning of normal students. As much as this may seem self-serving to normal learners, parents, and teachers, the truth is that learners with severe emotional behavior or learning challenges may impede the learning of normal learners when they are placed in normal classrooms. Secondly, such learners, when placed in specialized classrooms, are able to get large daily blocks of instructional time meant for intensive personal and small-group assistance (Kavale & Forness, 2000). Therefore, a look at the limitations and advantages of placing special needs learners in specialized classrooms, the issue of placement has to be looked at depending on the learner’s specific need.
The Public Law mandated that special needs learners should be place in least restrictive environments. Since proponents of the Law felt that it was not being followed, they proposed the application of mainstreaming, which is the practice of teaching students with special needs in classrooms that have regular students during some specific portions of the school day (Spence, 2010). Therefore, such learners spend part of the school day in specialized classrooms and some time in normal classrooms. Research by Sailor and Roger (2005) shows several advantages of such an initiative to students with special needs. Such learners became more academically effective compared to when they are placed in specialized classrooms. Moreover, the students attained increased self-efficacy and confidence (Spence, 2010). Also, they learned social skills that they did not possess, understood the world around them better, and felt to belong to the regular society.
A Critique of the Article
First, it is important to note that boys who do not have any special needs are more likely to do better in their scores in math. As highlighted in the results of the study, boys in non-inclusive classes performed better than those who were assigned to classes that were inclusive. This may not be a surprise since some other factors may have contributed to this phenomenon (Szumski, Smogorzewska, & Karwowski, 2017). For instance, it is possible that the boys who were assigned to the non-inclusive classroom were typically brighter than the ones who were assigned to the other classroom. The author does not clearly spell out whether the initial performance of both groups was considered. Moreover, student improvement over time may be a reason that can influence the scores of a given test (Kavale & Forness, 2000). There is a likelihood that the good results that were recorded from the boys who were in a non-inclusive environment were as a result of personal commitment to score better grades.
Additionally, the author fails to include the results from the other subjects. It is unfortunate that the only results that he documents in his quest to compare the performance of the two groups are from math scores. It is possible that the outcomes would have been different if other disciplines, such as reading, science, and social studies, were included in the determination of the group that performed better than the other (Weiss & Lloyd, 2002). Boys may perform better in math, but they are likely to perform dismally in reading. As a result, the results of the study may have been flawed.
Moreover, the study focused on students in middle-school. This makes it possible that the best outcomes could not be attained. A better and comprehensive study has to draw samples from learners from various study levels. Therefore, the outcomes may have differed if the sample was drawn from other categories of learners. For instance, the researcher should have drawn grades three, four, and five; from lower-high school, middle-school, and tertiary institutions. This way, he would have obtained a more comprehensive outcome from the study. It is possible in lower grades students may be more concerned with their colleagues with special needs, and this may lead to poor scores in inclusive classrooms and vice versa (Weiss & Lloyd, 2002). However, as students proceed to higher levels of education, they may not be influenced by the presence of learners who need specialized attention. Consequently, their performance in either of the environments may not change in any significant way.
Comparison of the Article with Others
There have not been many studies to access the impact of inclusion of learners who are normal in classrooms where they interact with learners who need specialized treatment in their learning process. Korenich and Fox obtained data from three school districts in the states of Pennsylvania, Illinois, and Missouri (Murawski & Lee Swanson, 2001). In their study, they focused on learners who did not have any disabilities in grades three, four, and five whom they placed in inclusive classrooms with learners who had special needs. To access their academic achievements, the researchers obtained four types of data: rating from teachers on the students’ prowess in academics; results from standardized test scores; grades from the learners’ report cards for math, science, reading, science, and social studies; and learners’ work samples from math and writing. From the study results, the researchers did not find any negative consequence on the academic achievement of normal students resulting from being assigned to classrooms that include students who have special needs (Murawski & Lee Swanson, 2001). Despite the writers using a sample of elementary learners, the study compares with Spence’s study since both are quantitative in nature and accessed test scores in reading and math.
Moreover, Castro studied the academic achievement of learners who do not have any special need and are assigned to inclusive classrooms in a northern public school district in New Jersey (Sailor & Roger, 2005). In his study, he studied TerraNova test scores for a span of two years for every leaner in the jurisdiction. The scores were then compared for grade one and grade two depending on their academic environment, that is, inclusive versus non-inclusive. His conclusion was that the academic achievement of normal students in an inclusive environment with students who have special needs was not significantly better compared to the performance of the same category of students who were assigned to non-inclusive environments. Despite the fact that Castro focuses his study on elementary learners, his study compares to Spence’s in that he also applies a quantitative approach to analyze the students’ academic achievements. Additionally, the two studies analyze test scores obtained from math and reading. However, the results that Castro obtained from his research are different from the ones that were obtained by Spence. Castro found out that there was no direct effect on the academic scores obtained by ordinary learners who shared a classroom with students who had special needs (Sailor & Roger, 2005). Despite the variations in the findings, it is vital to be aware that Castro focused on elementary learners while Spence’s focus was on middle-school learners.
Additionally, Neugebauer (2008) studied the connection between the academic outcomes between students without special needs in inclusive high school social studies and science class and those of ordinary learners in non-inclusive classes in the same subjects. He used the Texas Assessment of Knowledge and Skills (TAKS) to measure academic achievement. He conducted a quantitative study whose outcomes revealed that students who do not have special needs and studying in non-inclusive classrooms scored higher in TASKS in social studies and science compared to their counterparts in inclusive settings. Despite the sample population in this research being drawn from high school learners, his study compares to Spence’s since it analyses standardized test scores and it is a quantitative study (Neugebauer, 2008). Furthermore, the study results obtained by Neugebauer are the same as the ones obtained by Spence. Math learners and boys in non-inclusive classrooms scored relatively higher compared to their colleagues in inclusive classrooms.
Each of the studies presented above play an important role in revealing how different scholars who have tried to study the relationship between the performance of normal students in inclusive classrooms and non-inclusive ones have come up with varying conclusions. However, it is true that the differences in the outcomes of the studies that are presented here are due to the role played by the variable used in the studies (Suomi, Collier, & Brown, 2003). First, the various studies rely on data obtained from learners in different grade levels. Second, the sample populations were obtained from various parts of the country, making it difficult to have a sample that has similar characteristics. Finally, the various researchers in the studies did not use the same data analysis methods. A different approach in the manner in which data is analyzed is likely to lead to the variations in the outcomes obtained from the studies. Consequently, it is true that the surroundings in which a normal learner studies may influence his or her overall performance, but it is to a negligible extent (Suomi, Collier, & Brown, 2003). There may be inconsistencies in the results obtained by different studies, but such discrepancies are not related to whether the learner was in an inclusive classroom or not; instead, the differences are as a result of the methodologies used, samples used, and results analysis methods.
In conclusion, the foregoing results of the study conducted by Spence are interesting in relation to the ongoing inclusion debate. Opponents of the inclusive education often opine that such a move has detrimental effects on the learning outcomes of ordinary students. However, it has been proved that this may be true to some extent, but that is not always the case. In Spence’s study, he highlighted that normal students score higher grades in math in non-inclusive classrooms. Despite that, he draws a conclusion that the variations are negligible. He adds that there is no much difference in reading achievement between the two subgroups. As a result, school leaders and teachers can be confident that assigning students to inclusive environments would not have detrimental effects on their reading achievement. Moreover, the findings regarding math outcomes are critical to them since they show variations in the scores. Such results can assist them as they assign learners to classrooms. Additionally, teachers and school leaders may use the findings obtained from this study to explore instructional strategies that can be used in the teaching of math, as well as how the regular teacher and the special education teacher can work together in a math setting. This research fills the literature gap in inclusive practices and how they play a role in the outcomes attained by normal learners in inclusive classrooms. This is because most of the available studies tend to focus on the positive outcomes attained by special needs students in inclusive settings.
References
Kavale, K. A., & Forness, S. R. (2000). History, rhetoric, and reality: Analysis of the inclusion debate. Remedial and Special Education , 21 (5), 279-296.
Murawski, W. W., & Lee Swanson, H. (2001). A meta-analysis of co-teaching research: Where are the data? Remedial and special education , 22 (5), 258-267.
Neugebauer, N. G. (2008). TAKS scores of general education students in secondary co-teach classes in a Texas school district . Texas A&M University.
Sailor, W., & Roger, B. (2005). Rethinking inclusion: Schoolwide applications. Phi Delta Kappan , 86 (7), 503-509.
Spence, R. S. (2010). The effects of inclusion on the academic achievement of regular education students. Retrieved from https://digitalcommons.georgiasouthern.edu/cgi/viewcontent.cgi?article=1369&context=etd
Suomi, J., Collier, D., & Brown, L. (2003). Factors affecting the social experiences of students in elementary physical education classes. Journal of Teaching in Physical Education , 22 (2), 186-202.
Szumski, G., Smogorzewska, J., & Karwowski, M. (2017). Academic achievement of students without special educational needs in inclusive classrooms: A meta-analysis. Educational Research Review , 21 , 33-54.
Weiss, M. P., & Lloyd, J. W. (2002). Congruence between roles and actions of secondary special educators in co-taught and special education settings. The Journal of Special Education , 36 (2), 58-68.
