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Inclusion and students with and without

special educational needs: an empirical

study in the Netherlands

Thesis 2 Nienke Ruijs 0301760 May 2009

Research Master Educational Sciences Department of Educational Sciences Universiteit van Amsterdam

Supervisors: Dr. Thea Peetsma Dr. Ineke van der Veen

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Preface

In the past year, I have been working on a project about inclusive education. What I thought to be a part of my first thesis for the Research Master Educational Sciences, has grown into a project covering both my theses, and which will, hopefully, lead to three publications. The first one is my first thesis: a literature review, which will be published in Educational Research Review this year. Two empirical papers are in this document. They form my second thesis, and will be submitted to scientific journals soon.

The papers are presented in the way they will be submitted to the journals. This means there is no extensive research report, or a separate introduction and conclusion. Instead, each paper can be read separately, but have a certain overlap in their content. Their main topic is different: the first paper is on inclusive education and students without Special Educational Needs, the second one on inclusive education and students with Special Educational Needs.

Presenting the papers in the way they will be submitted to the journals is also the reason why each paper has three authors: Thea Peetsma, Ineke van der Veen and me. Both papers are primarily my work. Under supervision of Thea and Ineke, I came up with the research questions, I have done literature research, I have performed the statistical analyses and I have written the papers. Thea and Ineke supervised me during the whole process, they helped me when I got stuck, encouraged me to do some additional analyses and corrected the different versions of the text to make it a better product.

I would therefore like to use this preface to thank Thea and Ineke, who, in my view, have done a great job in supervising my theses. Without them, the papers would not have had the quality they have right now. I would specifically like to thank them for letting me use the PRIMA-data, encouraging me to rewrite a literature chapter into a review study, guiding me at the statistical analyses, supporting me in splitting the empirical project into two papers,

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reading and re-reading earlier drafts, pointing out scientific sensitivities in the way I wrote things down initially and for being very flexible and generous with their time.

Amsterdam, May 2009,

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Content

Inclusive Education and Students without Special Educational Needs 5

The Presence of Multiple Students with Special Educational Needs in Inclusive 56 Education and the Functioning of Students with Special Educational Needs.

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Running head: INCLUSION AND STUDENTS WITHOUT SEN

Inclusive Education and Students without Special Educational Needs Ruijs, N.M., Van der Veen, H., Peetsma, T.T.D.

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Abstract

In the debate on inclusive education, effects on students without special educational needs (SEN) are an important topic. In earlier studies, researchers made no distinction between the effects on different groups of students without SEN. However, -often found- neutral results could be caused by positive effects for some students, and negative effects for others. In this study, we have investigated whether there is a different effect of inclusive education for intelligent and less intelligent students without SEN. Besides that, very little is known about the relation between inclusive education and the socio-emotional functioning of students without SEN. Finally, we have also investigated whether the academic and socio-emotional effects of inclusive education on students without SEN differ when children with different types of SEN are included. For this, data from over 25,000 Dutch primary school students without SEN were used. For academic achievement, no differences were found between students without SEN in inclusive and non-inclusive classes. For socio-emotional functioning some differences were found, but the practical importance of these differences is unclear.

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Inclusive Education and children without Special Educational Needs

“Primary schools loath to take special needs children” (Cassidy, 2001) “ ‘Backpack-child’ is a disaster for the class” (Lamping, 2006)

“Time to leave inclusion out? The controversy over placing children with special needs in mainstream classes is as fierce as ever, discovers Emma Seith” (Seith, 2006)

“Rather no special needs; Regular Education does not know what to do with children with disabilities” (Kooijman, 2008)

These four headlines from papers in England, the Netherlands and Scotland show that there is a fierce debate going on about the inclusion of children with Special Educational Needs (SEN). At the same time, there is an obvious international trend towards more inclusive education (Ainscow & César, 2006; Meijer, 2004; Smeets, 2007); illustrated most clearly by the Salamanca Statement (UNESCO, 1994). Farrell (2000) states that there are two types of arguments in favour of inclusive education: socio-political and empirical. The socio-political arguments mostly concern human rights: children with SEN have the right to participate in public educational services.

The empirical arguments often concern the effects on children with SEN. In general, it has been found that the academic effects of inclusive education on children with SEN are slightly positive. In most studies, it is found that SEN-students achieve just as well or even better in inclusive education (e.g. Fore, Hagan-Burke, Burke, Boon, & Smith, 2008; Lindsay, 2007; Markussen, 2004; Peetsma, Vergeer, Roeleveld, & Karsten, 2001). On socio-emotional factors, positive, neutral and negative effects of inclusion have been found (Bakker &

Bosman, 2003; Hardiman, Guerin, & Firzsimons, 2009; Nakken & Pijl, 2002; Wiener & Tardif, 2004).

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But, children with SEN are not the only important group when evaluating inclusive education. The consequences for children without SEN are just as important. In this paper, we will focus on the relation between inclusive education and the academic and socio-emotional functioning of typically developing children. Concerning academic achievement, it can be reasoned that there are negative as well as positive effects of inclusive education. On the one hand, children with SEN could take up more of the teachers attention at the expense of children without SEN, the general level of education in the class might be lowered, and children with SEN might distract the other children in the class. On the other hand, there might be positive academic effects because there is more adaptive education and there are more teacher assistants in classes with students with SEN. Regarding socio-emotional effects, it can be reasoned that children without SEN in inclusive classes become more aware and less afraid of differences between people. They might also develop fewer prejudices against and more friendships with children with SEN. On the other hand, children without SEN could copy undesirable behaviour from children with SEN.

In scientific literature, there is quite some research available on the academic effects of inclusive education on children without SEN. Over all, mixed results are found. Staub and Peck (1994) have summarized some early literature on the academic effects of inclusive education on children without SEN. They state that the available research indicates that there is no effect of inclusive education on the achievement of children without SEN. A decade later, Pijl, Nakken and Mand (2003) draw a comparable conclusion: from their literature review, there is no evidence for a detrimental effect of inclusive education on the achievement of students without SEN; some studies even find positive effects. In a recent review with 26 studies, Kalambouka et al. (2007) mostly find positive or neutral effects of inclusive

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However, most of the studies in the above cited reviews are studies on a relatively small scale. Often, findings are based on research in one or a few schools.

Dyson et al. (2004) have performed a large-scale study into the effects of inclusion on the achievement of students without SEN. On a regional level, they find no relationship between the inclusiveness of the Local Educational Authority and achievement. On the school level, a small effect was found: in schools with higher levels of inclusion, student

achievements were on average lower. Nevertheless, other background characteristics such as entitlement to free school meals or mother tongue proved to be more important, and,

according to the authors, the found effect is very small. In another large-scale study, though the amount of explained variance is very small, a slightly positive effect of inclusive

education on the achievement of typical children is found (Demeris, Childs, & Jordan, 2007). In a third large-scale study, Gandhi (2007) found no general difference in reading

performance between non-disabled students in inclusive and non-inclusive classes. When investigating more specifically, there showed to be some interaction effects with teacher courses on SEN, teacher aid and type of SEN. Some of these interaction effects indicated positive effects of inclusion, others indicate negative effects. Nevertheless, for most

comparisons, there were no differences between disabled students in inclusive and non-inclusive classes.

But, as Ruijs and Peetsma (2009) describe, a major shortcoming in earlier research is that there is no distinction between different groups of typical students in the vast majority of studies. Nevertheless, it is possible that there are different effects for different groups of typical students. On the one hand, there might be a more positive effect for intelligent children. If children with SEN require more teacher attention, teachers could make more use of independent working for the other students (Meijer, 2001), which could enable intelligent children to make more progress in inclusive education because they do not have to ‘wait’ for

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their classmates. Besides, when teachers need to deal with more different needs and

achievement levels in inclusive education, they might make more use of adaptive education (Houtveen & Van de Grift, 2001; Peschar & Meijer, 1997), which might have an adverse effect on less intelligent students (Houtveen, Booij, De Jong, & van de Grift, 1999). On the other hand, teachers might lower the general level of education to serve children with SEN (Gerber, 1995; Huber, Rosenfeld, & Fiorello, 2001). This might positively affect less

intelligent children, because they would have less difficulties keeping up with the lessons. In scientific literature, only two studies make a distinction between different groups of typical students. Dumke (1991, cited in Pijl et al., 2003) finds that there are more well-achieving and more poor-achieving students without SEN in inclusive classes. The variance in inclusive classes is higher than in non-inclusive classes, which indicates that there might be a positive effect for intelligent children and a negative effect for less intelligent children. Huber et al. (2001) on the other hand, find no differences between classes with and without children with SEN, but do find that an inclusive curriculum benefits the low-achieving students.

Although contradictory, these findings support the idea that there might be a

differential effect of inclusive education for intelligent and less intelligent students. This is a very important point to note, because –often found- neutral results can be caused by positive effects for some students and negative effects for others. When one group achieves better and another group achieves worse, the average will be neutral. In this study, therefore, we will investigate whether there is a relation between inclusive education and the academic achievement of children without SEN, and afterwards, we will investigate whether this relation differs for intelligent and less intelligent typical students.

Regarding the socio-emotional effects of inclusive education on children without SEN, far less research has been done. The available research mostly indicates positive effects of inclusive education on the contacts with and attitudes towards students with SEN: children in

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inclusive classes are having fewer prejudices about children with SEN, they are more willing to play with these children and they are having a more positive attitude towards children with SEN (Nakken & Pijl, 2002; Salend & Garrick Duhaney, 1999; Staub & Peck, 1994).

Nevertheless, Brown (1982, cited in Kalambouka, Farrell, Dyson & Kaplan, 2007) found a negative social effect of inclusive education. He found that inclusion of children with behavioural problems influenced the classroom climate and the learning environment in a negative way. However, Staub and Peck (1994) state that there is no evidence available that students without SEN learn undesirable behaviour from students with SEN. In a recent study, Wong (2008) found no differences in attitude towards people with disabilities between non-disabled students in inclusive and non-inclusive classes in a secondary school in Hong-Kong. A programme aimed at acceptance of people with disabilities, however, did positively change participants’ social acceptance of children with disabilities.

On the effects of inclusive education on other socio-emotional factors, such as self-confidence, teacher-student relation and well-being, less is known. To our knowledge, earlier studies have not investigated these factors, while inclusive education might influence these socio-emotional aspects as well. For example, typical students in inclusive education might feel better about themselves. This could be because they can use downward comparison to compare themselves to students with SEN, who generally achieve less well than themselves. This comparison might increase their well-being (Wills, 1981). Besides, there might be more acceptance for diversity in inclusive classes. On the other hand, it can be reasoned that inclusive education has a negative effect on the socio-emotional functioning of typical students: they might receive less attention from the teacher, because the SEN-students could ask more intensive teacher attention (Peck, Staub, Gallucci, & Schwartz, 2004). Furthermore, teachers might experience more stress in inclusive classes (Forlin, 2001; Forlin, Hattie, & Douglas, 1996), which could negatively affect the teacher-student relation (Yoon, 2002). In

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this study, we will therefore investigate the relation between inclusive education and the socio-emotional functioning of typical students. Because this relation might also differ for intelligent and less intelligent students, we will also make this distinction on socio-emotional functioning.

Another problem in earlier research is that most studies have not investigated whether the inclusion of children with different types of SEN causes different effects for typical students. Earlier studies have focussed on students with various types of SEN; Cole et al. (2004), for example, have investigated the effects of including children with learning disabilities and mild mental disabilities and McDonnell et al. (2003) investigated the effects of including children with intellectual or multiple disabilities. Both studies, however, have not investigated whether these different types of SEN affect typical students differently. Gandhi (2007) has made a distinction between students with different types of SEN, and indeed found a few different (interaction-) effects of the inclusion of children with different types of SEN on non-disabled children. Children with autism, for instance, seem to negatively affect

reading performance of non-disabled children, if the classroom does not have an aid. So, there might be differences in the effects of inclusion of students with different types of SEN. This seems intuitive, because a child with autism generally has other needs than a child with dyslexia, and a child with ADHD will probably behave different than a child with

internalizing problem behaviour. For this reason, children with different types of SEN might have a very different influence on typical students. In this study, we will investigate whether the relation between inclusive education and the academic and socio-emotional functioning of typical students differs when children with different types of SEN are included. For this, we make a distinction between children with externalizing, cognitive or other problems.

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1. Is there a relation between inclusive education and the achievement and socio-emotional functioning of students without SEN?

2. Does this relation differ for intelligent and less intelligent typical students?

3. Does the relation between inclusive education and the academic and socio-emotional functioning of typical students differ by the type of SEN of the included students?

Method Participants

To investigate these questions, data from the cohort study were used. The PRIMA-cohort study is a biannual study on over 55,000 students in Dutch primary education. Data are available on background variables, such as sex, parental education and ethnicity, on

achievement in language and arithmetic, on intelligence and on socio-emotional variables such as well-being, teacher-student relation and self-confidence. 42,068 students in the PRIMA-cohort study form a representative sample of Dutch primary school students. The remaining students participate in an additional sample, which is designed to obtain more information on more disadvantaged groups of students. In this study, we have only used the representative sample.

In this study, data from the sixth measurement of PRIMA were used. These data have been collected in school year 2004/2005 (Driessen, Van Langen, & Vierke, 2006). Schools were selectively approached to obtain a representative sample. Overall, 420 schools

participated in the representative sample. Within schools, students from the 2nd, 4th, 6th and 8th year of Dutch primary education participated in the study. For 10,127 of the 42,068 children (24.1%), it is unknown whether they have SEN. In missing value analysis, children for whom having SEN was unknown proved to score somewhat lower on language and behaviour and a little higher on self-reported social integration, but the effect sizes of these differences are

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very small (r=0.016 to r=0.045). Besides, there showed to be some differences on the background characteristics, but these effect sizes are small as well (η²p=0.001 to η²p=0.029). Therefore, these children were omitted from the analysis without compromising the

representativeness of the sample. As a consequence of the research questions, only children without SEN were taken into account in the analyses.

Because of the organisation of the PRIMA data, two different samples have been used in answering the research questions. In the PRIMA-cohort study, data on intelligence are available for years 4, 6 and 8. When only these years are used, about 1/4th of the data will be omitted. To avoid losing power on the effects of including children with different types of SEN, we have chosen to use two samples: one sample, without year 2, for the first two research questions and one sample, with year 2, for the third research question. Because the student-reports on socio-emotional functioning are only available for year 6 and 8, we only used these years when analyzing the student-reports.

Sample 1. In the first sample, in which we use the data on intelligence, and therefore do not take year 2 into account, there are some missing values on the background variables. There are a number of differences between children with and without missing values, but the effect sizes of these differences are very small to medium: on the continuous variables, 83.3% is below r=0.25, and on the discrete variables, all effect sizes are below η²p=0.02. Despite these differences, children with missing values were omitted from the analysis because there are significant differences on a small number of variables. After this, 19,127 children without SEN were left for the analysis of the first two research questions. On the dependent variables, there are some missing values as well, especially on the teacher-reports on socio-emotional functioning (26.0-26.7%). This substantial amount of missing values in the teacher-reports is caused by the design of the study. To avoid a heavy workload on the teacher, some teachers were asked to fill out the teacher questionnaire for a randomly selected sample of students.

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Again, there are some differences between children with and without missing values, but the effect sizes of these differences are very small to medium. On the continuous variables, 82.1% is below r=0.25, and on the discrete variables all effect sizes are below η²p=0.01. Despite these differences, analyses were run with the available cases on each variable. The exact numbers of students per analysis are mentioned in the tables, and student characteristics on this sample are summarized in Table 1.

Sample 2. In the second sample, we also analyse students in year 2. This sample was used for the third research questions on differences by type of SEN, and the missing values are comparable to Sample 1. For the background variables, 87.5% of the effect sizes of the differences are below r=0.25 and 100% is below η²p=0.02. After omitting the children with missing values on the background variables, 27,745 without SEN are left for the analyses. For the dependent variables, 87.5% of the effect sizes are below r=0.25 and 100% is below η²p=0.01. Again, analyses were run with the available cases on each variable. The exact numbers of students per analysis are mentioned in the tables, and student characteristics on this sample are summarized in Table 1.

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Insert Table 1 about here ---

Instruments

Background Characteristics. In earlier research, background characteristics such as such as sex, ethnicity and parental education proved to be important for student development (Dyson et al., 2004; Ma & Klinger, 2000; Peetsma, Van der Veen, Koopman, & Schooten, 2006). Therefore, relevant background characteristics are included in this study. Information on background characteristics was obtained through school records. The background

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school, ethnicity, parental education and urbanisation. We have controlled for differences between years by standardisation of the dependent variables within years.

In this study, ethnicity is divided into six groups: children from a Moroccan, Turkish or Surinam/Antillean background, which are the three largest minority groups in the

Netherlands, children from a native Dutch background, children from a mixed Dutch/non-Dutch background and children from other backgrounds. Parental education is defined as the highest obtained qualification of the highest educated parent. Parental education is divided into four categories: children of parents with higher education (HBO/WO), children of parents with vocational education (MBO), children of parents with lower vocational education (LBO) and children of parents with primary education. Urbanisation is divided into four categories: children in the four largest cities in The Netherlands (G4), children in the next 27 largest cities in The Netherlands (G27), children from rural areas and children from other cities and

villages.

Language and Arithmetic tests. To assess the academic functioning of students without SEN, standardized tests for language and arithmetic were used (PRIMA and CITO). In

practice, most schools already used these tests to track student achievement. Reliability of the tests proved to be good for language, KR-20≥0.80 (Driessen, 2004; Driessen & Withagen, 1999) and arithmetic MAcc=0.81 to MAcc=0.97 (Janssen & Engelen, 2002; van Kuyk & Kamphuis, 2001). Because there are large differences in age and educational attainment between years, different tests were used for each year. Student scores were standardized within years to be able to compare achievement across years. Thus, in the analyses we have used the relative position of each student compared to other students in that year.

Teacher Questionnaire on Socio-Emotional Functioning. To measure socio-emotional functioning, teacher-reports and student-reports were used. In the teacher questionnaire, teachers assessed 19 statements about each student on a five-point scale. The questionnaire

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measures six aspects of socio-emotional functioning: self-confidence (e.g. ‘This student is easily upset’), teacher-student relation (e.g. ‘This student has a difficult contact with me’), effort (e.g. ‘This student quickly thinks that his work is done’), popularity (e.g. ‘This student is popular among classmates’), well-being at school (e.g. ‘This student would rather avoid school’) and behaviour at school (e.g. ‘This student is often impudent’).

In earlier research, the reliability of this questionnaire proved to be good: the alphas of the different subscales are between 0.81 and 0.89 (Driessen, Van Langen, & Vierke, 2002). Student scores were standardised within years, because younger students usually score more positive on measures of socio-emotional functioning. Standardizing makes it possible to compare the socio-emotional functioning of children in different years.

Student Questionnaire on Socio-Emotional Functioning. Next to the teacher questionnaire, we used a student questionnaire to measure socio-emotional functioning. Because younger students are not yet able to fill out self-report questionnaires, the student questionnaire is only available for years 6 and 8. Using only this questionnaire would halve the available data and cause loss of power. Therefore, we also used the teacher-reports. To see whether the teacher observations concurred with student experiences, we also used the

student-reports.

The student questionnaire consists of 17 statements measuring three aspects of socio-emotional functioning: self-confidence on schoolwork (e.g. ‘I am one of the best students in my class’), well-being at school (e.g. ‘I feel at ease with my teacher’), and social integration in the class (e.g. ‘I have few friends in this class’; neg.). Students assessed each statement on a five-point scale, ranging from ‘this is completely untrue’ to ‘this is completely true’.

Reliability of this questionnaire proved to be satisfactory to good: α=0.75 for self-confidence, α=0.69 for well-being, and α=0.78 for social integration (Driessen et al., 2002). In this questionnaire, student scores were standardised within years as well.

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Teacher Questionnaire on Students with Special Educational Needs. To determine whether students with SEN were present in regular classes, teachers were asked to fill in a questionnaire on each student with SEN in their class. Students with SEN were defined as students with an individualised education plan, students that need a specific approach or additional help and/or students with a specific problem or disability. In the questionnaire, teachers were presented with 30 problems and were asked to report which problems the student with SEN was having. Besides, teachers were asked to report whether the student had been formally diagnosed with each of the reported problems. In this study, only the students with a formal diagnosis are considered students with SEN (n=1,839).

SEN are divided into three categories of problems: cognitive problems (n=1,147), which include mild mental retardation, language and arithmetic difficulties, dyslexia and dyscalculia, externalizing problems (n=497), which include autism, problematic effort and other externalizing problem behaviour and other problems (n=528), including physical disabilities, internalizing problem behaviour and gifted children. Gifted children were classified as having other problems, because the category cognitive problems includes

children who develop cognitively slower, while gifted children develop cognitively faster and have generally got other accompanying problems. The three categories do not necessarily exclude each other. When children have got diagnoses in different categories, they are

included in all applying categories of problems. This is because children are likely to have the needs and display the behaviour belonging to the different types of SEN. In sum, there are 229 students with diagnoses in two categories, and 52 students with diagnoses in all three categories.

To determine the relation between inclusion and functioning of typical students, the percentage of SEN-students per class was calculated. For the first two research questions, in which we use Sample 1, three groups were created: typical students without students with

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SEN in their class (n=7,467), typical students with a few (less than 10%) students with SEN in their class (n=7,585, M%=6.32%, SD%=2.10, Mn=1.34, SDn=0.53, nSEN=519), and typical students with more (more than 10%) students with SEN in their class (n=4,075, M=18.38%, SD=7.33, Mn=3.09, SDn=1.55, nSEN=914). A 10% boundary was chosen to have a reasonable number of students in both the ‘few students with SEN’ and the ‘more students with SEN’ group. The total number of students with SEN for this research question is lower than 1,839, because year 2 is not taken into account. For this sample, the total number of students with SEN is 1,433.

For the third research question, in which we use Sample 2, we first made a variable indicating whether students with SEN were present (n=15,480) or absent (n=12,265) in a class. After that, a distinction was made between the inclusion of students with three different types of SEN. One variable indicates whether there are no (n=21,243), less than 5% (n=3,324, M=4.02%, SD=0.62, Mn=1.00, SDn=0.00, nexternalizing=144) or more than 5% (n=3,178,

M=10.16%, SD=5.05, Mn=1.45, SDn=0.72, nexternalizing=353) students with externalizing problems in a class, one variable indicates whether there are no (n=16,976), less than 5% (n=3,529, M=4.12%, SD=0.61, Mn=1.00, SDn=0.00, ncognitive=151) or more than 5% (n=7,240, M=12.61%, SD=7.54, Mn=1.99, SDn=1.30, ncognitive=996) children with cognitive problems in a class, and one variable indicates whether there are no (n=21,327), less than 5% (n=3,105, M=4.08%, SD=0.64, Mn=1.00, SDn=0.00, nother=137) or more than 5% (n=3,313, M=10.99%, SD=5.87, Mn=1.47, SDn=0.75, nother=391) children with other problems in a class. Here, a boundary of 5% is used, because the number of children in classes with more children with externalizing, cognitive or other problems would get too small when using 10% as a

boundary. As can be seen from the means and standard deviations, the category less than 5% students with SEN only includes classes with one student with that type of SEN, and more than 5% means one or more students with SEN, depending on the class size.

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IQ. Student intelligence was measured by two nonverbal intelligence tests: composing figures and exclusion (Driessen et al., 2006). At composing figures, children were presented a series of five abstract figures. The first figure is a geometric shape, for example a square, from which a part has been omitted. One of the four other figures is the part that has been omitted and the question is to identify this part. This subtest requires spatial understanding. The subtest exclusion consists of series of four abstract figures. Three figures belong together and children have to choose the figure that does not belong to the other three. This subtest requires spatial understanding and the ability to reason. The scores of the tests were added to obtain one total score. The complete test consisted of 40 multiple-choice items for year 4, 41 for year 6 and 46 for year 8. The reliability of this test is satisfactory, α=0.78 for year 4, α=0.74 for year 6 and α=0.73 for year 8 (Van Batenburg & Van der Werf, 2004).

As stated earlier, the IQ test has only been administered at children in year 4, 6 and 8. Because IQ scores are already standardised, we have not standardised IQ across years. Children in year 4 do achieve somewhat better than children in year 6 and 8 (F(2,

19124)=416.1, p<0.001) , but the effect size of this difference is small to medium: r=0.20. To compare the effects of inclusive education on intelligent and less intelligent typical students, low-achieving children were defined as children scoring more than 1 SD below the mean (n=2,816), and high-achieving children were defined as children scoring more than 1 SD above the mean (n=2,843). The other students (n=13,468) are considered to be of average intelligence.

Assumptions

After analyzing missing values, common assumptions in data-analysis were checked. First, there proved to be no problematic univariate or multivariate outliers. Second, there were no

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severe deviances from normality; some variables are a little skewed, but this is no threat to the validity of the analyses. Furthermore, multicollinearity proved to be no problem.

Analyses

To investigate the research questions mentioned in the introduction, multi-level regression analyses were used. In regular regression analysis, an important assumption is that

observations are independent from each other. In this study, however, the samples consist of children within the same classes and schools. Because children in the same class and school are more similar than children from different classes and schools observations are not

independent from each other. With multi-level regression analysis, it is possible to control for these effects. In this study, we distinguish school level, class level and student level. To investigate whether multi-level regression analyses are indeed appropriate,

intraclasscorrelations and fit improvements (through χ²-difference statistics) were investigated.

Because two different samples are used in this study, the analyses were performed in two series. First, we have investigated the first two research questions, on the relation between inclusive education and the achievement and socio-emotional functioning of students without SEN, and on whether there is a different relation for intelligent and less intelligent typical students. After that, we investigated the third research question, regarding whether the academic and socio-emotional effects of inclusive education on typical students differ when students with different types of SEN are included. For all eleven dependent variables

(language, arithmetic, teacher-reported self-confidence, teacher-student relation, effort, popularity, well-being and behaviour and student-reported self-confidence, well-being and social integration), separate stepwise analyses were carried out.

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In the first series of analyses, we have used Sample 1, which is the sample without year 2. For each of the dependent variables, five models were computed. The first model (Model 0) is a reference model. This model does not contain explanatory variables, but estimates which proportion of the total variance of the dependent variable is student bound, class bound and school bound. Model 1 is a model with background variables only. Except for number of students per school, we have used dummy variables to calculate the effects of these variables. The reference groups are girls for sex, Dutch children for ethnicity, higher

education for parental education, and children in the four largest cities (G4) for urbanisation. In Model 2, IQ was added to Model 1. Here, average achieving students are the reference group. In Model 3, the presence of students with SEN was added to Model 2. Here, students in classes without students with SEN are the reference group. In the final model (Model 4) the interaction-effect of IQ and the presence of students with SEN was added to Model 3. A χ² value was calculated for each model to test whether the model differed significantly from the previous one. So, model 1 was tested against model 0, model 2 was tested against model 1, and so on.

In the second series of analyses, Sample 2, with year 2, is used. As in the first series of analyses, the first two models (Model 0 and Model 1) consist of a reference model and a model with background-variables only. In the final model (Model 2), four variables were added to Model 1: the variable indicating whether there are students with SEN present in a class, and the variables indicating whether there are no, less than 5% or more than 5% students with externalizing, cognitive or other problems in a class. On all SEN-variables, the reference groups are typical students in classes without students with SEN. A χ² value was calculated for each model to test whether the model differed significantly from the previous one.

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Differences between (intelligent and less intelligent) typical students in inclusive and non-inclusive classes

In the analysis without year 2, similarities between children from the same classes and schools are confirmed: intraclasscorrelations range from r=0.03 for student-reported self-confidence to r=0.31 for teacher-reported teacher-student relation. Eight out of the eleven

intraclasscorrelations are equal to or above r=0.10. Therefore, multi-level regression analysis is appropriate. This is supported by the fit results for class-level: for all variables,

χ²-difference statistics indicated significantly better fit at α=0.05. For school level, the same is true, except for teacher- and student-reported self-confidence1. For these measures, the fit of the empty model with school and class level is not significantly different from the fit of the model with class level only. Therefore, school level is not taken into account for self-confidence on both the teacher and student questionnaire.

Language and Arithmetic. As can be seen in Table 2, there are no differences in language and arithmetic between typical students in classes without students with SEN, in classes with less than 10% students with SEN and in classes with more than 10% students with SEN. Besides that, there shows to be no interaction effect of IQ and the presence of students with SEN on language and arithmetic. This indicates that effects of inclusive

education do not differ for intelligent and less intelligent typical students. When looking at the background variables, all variables except the number of students per school show to be related to the achievement in language and arithmetic. For example, girls score higher than boys on language, while boys score higher than girls on arithmetic, and Dutch children score higher on both tests than non-Dutch children. IQ significantly improves both models: as may be expected, intelligent children score higher on language and arithmetic than children with an average IQ, while children with a low IQ score lower on both measures than children with an average IQ.

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---

Insert Table 2 about here ---

Teacher-reports on Socio-Emotional Functioning. The presence of children with SEN is not significantly related to teacher-reported self-confidence and teacher-student relation of children without SEN: there are no differences between typical students in classes without students with SEN, typical students in classes with less than 10% students with SEN and typical students in classes with more than 10% students with SEN (Table 3). In addition, this relation does not differ for intelligent and less intelligent typical students: the interaction effect of intelligence and the presence of students with SEN does not significantly predict self-confidence and teacher-student relation of typical students. The background variables show to be less important for teacher-reported socio-emotional variables. As can be seen in Table 3, for example, non-Dutch children show somewhat more self-confidence than Dutch children, and girls have a better teacher-student relation than boys. The amount of explained variance of the background variables is quite low: 0.68% for self-confidence and 3.24% for teacher-student relation. IQ significantly improves both models: children with a higher IQ have more self-confidence and a better teacher-student relation than children with an average IQ, while children with a low IQ have less self-confidence and a less positive teacher-student relation than children with an average IQ.

---

Insert Table 3 about here ---

As can be seen in Table 4, there are no differences in teacher-reported effort and popularity between typical students in classes without students with SEN, typical students in classes with less than 10% students with SEN and typical students in classes with more than 10% students

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with SEN. This indicates that, according to the teacher, the presence of students with SEN is not significantly related to effort and popularity of typical students. However, there is a significant interaction effect of intelligence and the presence of students with SEN on effort: students with a high IQ and less than 10% students with SEN in their class show more teacher-reported effort than children with an average IQ and no students with SEN in their class (est. 0.104, SE=0.051, t=2.056, p=0.040). But, the model fit does not significantly improve, the amount of explained variance increases with only 0.04% and the effect size of this effect is d=0.106, which can be classified as a small effect (Cohen, 1988). There is no significant interaction effect of IQ and the presence of students with SEN on popularity. Most background variables show to be significant predictors of teacher-reported effort and

popularity. For example, girls show more effort and are more popular than boys, and children from parents with higher education show more effort and are more popular than children from lower educated parents. For popularity, however, the amount of explained variance is rather small: 1.67%. IQ significantly improves both models: again, children with a high IQ show more effort and are more popular than children with an average IQ, and children with a low IQ show less effort and are less popular than children with an average IQ.

---

Insert Table 4 about here ---

Finally, there show to be no differences on teacher-reported well-being and behaviour

between typical students in classes without students with SEN, typical students in classes with less than 10% students with SEN and typical students in classes with more than 10% students with SEN (Table 5). Moreover, according to the teacher, effects of inclusive education on well-being and behaviour do not differ for intelligent and less intelligent typical students: there is no significant interaction effect of IQ and the presence of students with SEN. The

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background variables show to have a significant relation with well-being and behaviour. For example, girls show more well-being and better behaviour than boys, and children from parents with higher education show more well-being and better behaviour than children from lower educated parents. IQ significantly predicts both variables: children with a high IQ show more well-being and better behaviour than children with an average IQ, and children with a low IQ show less well-being and less positive behaviour than children with an average IQ. ---

Insert Table 5 about here ---

Student-reports on Socio-Emotional Functioning. For the student-reports, there show to be no differences in social integration and well-being between typical students in classes without students with SEN, in classes with less than 10% students with SEN and in classes with more than 10% students with SEN (Table 6). Besides that, there is no interaction effect of IQ and the presence of students with SEN on social integration and well-being. This indicates that according to students, effects of inclusive education on social integration and well-being do not differ for intelligent and less intelligent typical students. Some of the

background variables show to be significantly related to social integration and well-being. For example, Dutch students score higher on social integration than students from Turkish, Mixed or other backgrounds, and children from parents with higher education score higher on well-being than children from parents with primary, lower vocational or vocational education. However, the amount of explained variance of the background variables is quite low: R²=0.98% for social integration and R²=3.25% for well-being. Intelligence significantly improves both models: children with a low IQ score lower on social integration and well-being than children with an average IQ.

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Insert Table 6 about here ---

As can be seen in Table 7, there are differences in student-reported self-confidence between typical students in classes without students with SEN and typical students in classes with more than 10% students with SEN. Students in classes with more than 10% students with SEN report more self-confidence than students in classes without students with SEN (est. 0.098, SE=0.029, t=3.411, p=0.001). While the fit of the model has significantly improved, the effect size of this effect and the increase in explained variance are small: d=0.099 and R²=0.17% (Cohen, 1988). This difference is not found for typical students in classes with less than 10% students with SEN compared to typical students in classes without students with SEN. There is no significant interaction effect of intelligence and the presence of students with SEN on student-reported self-confidence. This indicates that effects of students with SEN are not different for intelligent and less intelligent students without SEN. The

background variables show to be related to student-reported self-confidence: children from parents with higher education, for example, score higher on self-confidence than children from parents with primary, lower vocational or vocational education. Intelligence

significantly improves the model as well: children with a high IQ score higher on confidence than children with an average IQ, and children with a low IQ score lower on self-confidence than children with an average IQ.

---

Insert Table 7 about here ---

Differences between typical students in classes with students with Externalizing, Cognitive or Other problems

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As described in the method section, a different sample was used for the third research question. Except for the addition of year 2 students, this sample is very similar to the sample used for the previous research questions. Therefore, we will not extensively describe the background variables in the text. Of course, this information can be found in the tables.

In the analysis on the inclusion of students with different types of SEN, similarities between children from the same classes and schools are confirmed as again:

intraclasscorrelations range from r=0.03 for student-reported self-confidence to r=0.32 for teacher-reported teacher-student relation. Eight out of the eleven intraclasscorrelations are equal to or above r=0.10. Therefore, multi-level regression analysis is appropriate. This is supported by the fit results for class-level. For all dependent variables, χ²-difference statistics indicated significantly better fit at α=0.05. The same is true for school-level, except for

student-reported self-confidence. For teacher-reported behaviour, however, the initial analyses yielded a non-positive definite Hessian Matrix. These problems were overcome when the school-level was taken out of the analysis. Therefore, school-level is not taken into account for behaviour and student-reported self-confidence.

Language and Arithmetic. In Table 8, it can be seen that the presence of students with SEN is no significant predictor of the achievement on language and arithmetic for typical students. Furthermore, there are no differential effects for including students with different types of SEN: there are no differences between typical students in classes with no, less than 5% and more than 5% students with externalizing, cognitive and other problems. Therefore, there seems to be no relation between the inclusion of students with different types of SEN and achievement on language and arithmetic for typical students.

---

Insert Table 8 about here ---

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Teacher-reports on Socio-Emotional Functioning. For teacher-reported

self-confidence, teacher-student relation and effort (Table 9), a similar picture is found. According to the teachers, there are no differences between typical students in classes with and without students with SEN and there are no differences between typical students in classes with no, less than 5% and more than 5% students with externalizing, cognitive and other problems. Therefore, there seems to be no relation between the inclusion of students with different types of SEN and teacher-reported self-confidence, teacher-student relation and effort of typical students.

---

Insert Table 9 about here ---

There also show to be no differences in teacher-reported popularity, well-being and behaviour between typical students in classes with and without students with SEN (Table 10).

Furthermore, there are no differences between typical students in classes with no, less than 5% and more than 5% students with externalizing, cognitive and other problems. This

indicates that, according to the teachers, there seems to be no relation between the inclusion of students with different types of SEN and the popularity, well-being and behaviour of typical students.

---

Insert Table 10 about here ---

Student-reports in Socio-Emotional Functioning. For student-reported social integration and self-confidence, there again show to be no differences between typical students in classes with and without students with SEN (Table 11). Furthermore, there are no differences between typical students in classes with no, less than 5% and more than 5%

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students with externalizing, cognitive or other problems. This indicates that, according to typical students, there seems to be no relation between the inclusion of students with different types of SEN and their social integration and self-confidence. On well-being, there are no differences between typical students in classes with and without students with SEN, but there are differences for type of SEN. Children in classes with less than 5% students with

externalizing problems (est. -0.122, SE=0.055, t=-2.218, p=0.027) and children in classes with more than 5% students with other problems (est. -0.104, SE=0.053, t=-1.961, p=0.050) score lower on well-being than students in classes with no students with externalizing or other problems. However, the model fit has not significantly improved, the effect sizes of these differences are small (d=-0.123 and d=-0.105) and the increase in explained variance is very small R²=0.27%.

---

Insert Table 11 about here ---

Conclusions and Discussion

In this study, the relation between inclusive education and the academic achievement and socio-emotional functioning of students without SEN was investigated, and it was

investigated whether this relation differs for intelligent and less intelligent typical children. Further, we investigated whether the relation between inclusive education and the academic and socio-emotional functioning of typical students differs by the type of SEN of the included students.

From the results, there show to be no differences in academic achievement between typical students in non-inclusive classes, typical students in classes with a few (less than 10%) students with SEN, and typical students in classes with more (more than 10%) students with SEN. This indicates that, overall, inclusive education has no relation with the academic

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achievement of typical students. As described in the Introduction, however, this general neutral relation might be caused by differential effects for intelligent and less intelligent typical students. When the academic achievement of one group is positively influenced by inclusive education, and the academic achievement of another group is negatively influenced, the average effect will be neutral. A more important finding in this study, therefore, is that there are no indications for a different relation between inclusive education and academic achievement for intelligent and less intelligent typical students.

On different factors of socio-emotional functioning similar results are found: on the large majority of measures, there show to be no differences between typical students in non-inclusive classes, in classes with a few students with SEN and in classes with more students with SEN. Only for student-reported self-confidence, typical students in classes with more students with SEN seem to score better than typical students in non-inclusive classes. This might be because students with SEN generally perform less well than typical students. Typical students in inclusive classes, therefore, can probably compare themselves to students who function less well than themselves, which can have a positive effect on their

self-confidence. However, because the effect size and the amount of explained variance are small, the practical importance of this relation is unclear. Furthermore, there is no apparent

differential effect of inclusive education on the socio-emotional functioning of intelligent and less intelligent typical students. We did find an interaction-effect for teacher-reported effort, but because the effect size and the amount of explained variance are small, and the model fit did not significantly improve, the relevance of this effect is uncertain. From earlier research, little was known on the effects of inclusion on the socio-emotional functioning of typical students, while there might be positive as well as negative effects of inclusive education on these factors. With this study, we acquired indications that inclusive education has no relation with the socio-emotional functioning of typical students: overall, there are no meaningful

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differences between typical students in inclusive and non-inclusive classes, and possible effects do not seem to be covered by a different relation for intelligent and less intelligent typical students.

Finally, there showed to be no important differences in the academic achievement and socio-emotional functioning of typical students when including children with externalizing, cognitive or other problems. The only differences on self-reported well-being indicate that students in classes with one (i.e. less than 5%) student with externalizing problems or one or more (i.e. more than 5%) students with other problems experience less well-being than typical students in classes without students with these specific problems. This might be because students with SEN ask more teacher-attention, or affect the class climate in a negative way. However, these differences have small effect sizes, a small amount of explained variance and do not yield better model fit, so their practical importance is unclear. These results indicate that for typical students, it does not seem to matter which problems included children with SEN have: overall, there seems to be no meaningful relation between including children with different types of SEN and the academic achievement and socio-emotional functioning of typical students.

Next to the small effect sizes and explained variances of the three effects that were found, there is another reason to be very careful with interpreting these findings. In this study, we have used eleven dependent variables, on which we performed a large number of

statistical tests. It is well possible that these differences appeared because of inflated family wise error rate: when you perform many statistical tests, you can always expect that some of them yield significant results.

There are some limitations on this study. First of all, it is not possible to draw causal inferences from this study. We have performed correlational analyses on cross-sectional data. This way, it is possible to see (a lack of) differences between groups, but it is not possible to

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conclude that inclusion caused or did not cause these differences. For example, there might have been initial differences between inclusive and non-inclusive classes. To overcome this problem, experimental or longitudinal research should be done.

Besides, the students included in this study might be students with less severe types of SEN. In the Netherlands, special schools coexist next to inclusive education. Consequently, schools might include students with relatively mild SEN, while rejecting to include students with more severe SEN. Moreover, regular schools get additional funding for educating children with diagnosed SEN. This makes it attractive to indicate a child with relatively mild problems as having SEN. We were not able to compare our sample of students with SEN to students in special education. However, because we only considered children with an official diagnose as children with SEN, and children with more severe SEN are more often diagnosed, both children with mild and more severe SEN are represented in this sample.

There is one drawback of including only students with diagnosed SEN in the

definition of children with SEN: students who have SEN, but who do not have a diagnose are not classified as having SEN. This is a problem because not every student with SEN is diagnosed. Some students might not be diagnosed because of practical concerns such as waiting lists or school budgets, while others might not be diagnosed because their parents refuse to give permission for psychological testing. Therefore, it is possible that some students with SEN are classified as students without SEN in this study. But, because the diagnose definition is more objective than just asking teachers which students have SEN, we have chosen for this definition.

Further, we only made a distinction between children with cognitive, externalizing and other problems. This distinction only concerns the type of SEN a child is having, but does not indicate how severe that problem is. Cognitive problems, for example, included children with language and arithmetic difficulties, children with dyslexia and dyscalculia and children with

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mild mental retardation. There might be different effects on children without SEN when including children with mild cognitive problems or more severe cognitive problems. In our large-scaled dataset, however, it is not possible to assess the severity of SEN by the problem a child is having. For instance, there can be large differences between children with diagnosed dyslexia. Therefore, we chose to only distinguish different types of SEN.

Moreover, it is unknown how inclusive education is implemented in each school. There might be differences in the arrangements schools make to include children with SEN. These arrangements might also affect typical children. To investigate these processes, qualitative research would have been more suitable than quantitative research. Nevertheless, because all schools are Dutch schools, working under the same legislations and with the same budgetary constraints, differences between schools will not be irreconcilable. This is

supported by the small amount of variance found at school level: for the measures for which school level was significant, the variance at this level ranged from 1.0% to 10.6%, and the average was 3.04%.

Finally, in this study, the relation between inclusive education and the functioning of typical students was investigated. Possible effects on teachers and on students with SEN have not been studied. However, inclusive education might also affect teachers: they may consider inclusive education more demanding than educating typical students only. When evaluating inclusive education, these effects should be taken into account as well. The topic of inclusion and students with SEN will be covered in a forthcoming article by the same authors.

Despite these limitations, the main findings in this study still hold. We found no evidence concerning our hypothesis on the often found neutral effects of inclusive education on the academic achievement of typical students: neutral results of inclusive education do not seem to be caused by a differential effect for intelligent and less intelligent typical students. For both groups, we found no evidence for a relation between inclusive education and

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academic achievement. Furthermore: inclusive education seems to have no important relation with the socio-emotional functioning of typical students and the relation between inclusive education and the functioning of typical students does not seem to differ by the type of SEN of the included students.

In this study, it is unlikely that a lack of power covered differences between typical students in inclusive and non-inclusive classes. In educational science concerning SEN, many studies are using relatively small samples. When small differences are investigated, as is often the case in educational science, they are hard to detect with a small sample. This study

however, concerns a large-scale study. Therefore, when present, even small differences between typical students in inclusive and non-inclusive classes would have been detected. Further, the large scale of this study offers the opportunity to control for many background variables, which have often shown to affect students’ functioning at school. Another positive point of this study is that we have used teacher-reports and student-reports to investigate socio-emotional effects of inclusive education. It might be that teachers use relative judgements in the questionnaire on socio-emotional functioning, which means that they compare students to the other students in their class. When there are differences between typical students in inclusive and non-inclusive classes, these differences would not become evident, because teachers changed their standards on socio-emotional functioning. It seems like this is not the case in our data, because the student-reports yielded similar results as the teacher-reports.

The findings in this study are interesting in the light of the ongoing inclusion debate. In the introduction, we described different arguments in favour and against inclusive

education. Many of these arguments concerned the effects on typical students. For example, it is stated that inclusion might adversely affect the achievement of typical children, and that typical children might copy undesirable behaviour from children with SEN. With the findings

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of this study, we gained more support to contest these arguments. This study strengthens the scientific support in favour of inclusive education. Earlier research already indicated overall neutral or positive effects of inclusion (Kalambouka et al., 2007; Ruijs & Peetsma, 2009) This study supports this earlier research, especially by finding no evidence for an alternative explanation on neutral academic effects for typical children. The international trend towards inclusive education, therefore, seems to be more and more justified by empirical evidence.

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