Analysis of inclusive education in the academic performance of students with special needs: Advantages and disadvantages.

Achievement Goals, School Achievement, Self-Estimations of School Achievement, and Calibration in Students With and Without Special

Education Needs in Inclusive Education

Susanne Schwab University of Graz

Marco G.P. Hessels University of Geneva

This study focuses on the goal orientation of students with and without special education needs (SEN) in inclusive schools. Participants were 186 students (110 boys; 76 girls) from Grade 7 (mean age = 13.83). Of these, 93 were diagnosed as having SEN, while the other 93 were mainstream students matched on IQ. Students without SEN scored significantly higher in mastery-goal orientation, while students with SEN had a significantly higher performance-avoidance orientation. Two-step regression analyses showed that SEN was the only variable to predict differences in both mastery orientation and performance-avoidance orientation, while actual school achievements in German and Mathematics, self-estimations of school achievement in these school domains, as well as calibration (all entered in Step 1) were not significant.

Keywords: special education needs, achievement goals, inclusive education, calibration

Inclusion in Austria

On the way to a comprehensive society, school integration is one of the most important components. School integration is rising not only in Austria, but also in many other European countries. In Austria, about 51.2% of the pupils with special educational needs (SEN) are taught in mainstream classes (Buchner, Feyerer, & Flieger, 2009) and this percentage will further increase in the next few years. In Austria, contrary to other German-speaking countries, since 1993 the choice between inclusive education in a regular school and edu- cation in a special school mainly depends on the parents’ decision. The particular roles and responsibilities of parents have been emphasized in education acts granting them an essential role in decision making with regard to the type of schooling their children will receive (Gasteiger-Klicpera, Klicpera, Gebhardt, & Schwab, 2012). Most of the pupils with SEN in integrative settings in Austria have learning disabilities regarding one or more subjects (e.g., German or Mathematics). This type of disability is similar to the Inter- national Classification of Functioning, Disability and Health, Category B, Students with Learning Difficulties (WHO, 1993).

© 2014 Scandinavian Journal of Educational Research

Susanne Schwab, Department of Education, University of Graz; Marco G.P. Hessels, Department of Special Education, University of Geneva.

Correspondence concerning this article should be addressed to Susanne Schwab, University of Graz, Department of Education, Special Education Unit, Merangasse 70/II, Graz, A-8010 Austria. E-mail: [email protected]

Scandinavian Journal of Educational Research, 2015 Vol. 59, No. 4, 461–477, http://dx.doi.org/10.1080/00313831.2014.932304

According to Haeberlin (2013), the term inclusive education is used to emphasize that it is not merely an organizational change of the special education system. In German-speaking countries, inclusion is understood as an optimized form of integration in which all children are regarded as individuals with different initial positions. Differences are considered enrich- ment (Sander, 2005). However, in Austria, much still has to be accomplished for the school system to really become inclusive: schools that acknowledge diversity among students and that offer equal opportunities to all.

Currently, integration research is mostly focused on the (presumed) positive impact of integration classes in comparison to special classes, or on comparing students with and without SEN in mainstream education. The positive impact of integration on the school achievement of students with and without disabilities has been shown in several studies (e.g., Bless & Mohr, 2007; Ruijs & Peetsma, 2009). Many studies have analyzed the causes of school success or failure. These may be due to general and/or specific cognitive abilities (Deary, Strand, Smith, & Fernandez, 2007; Fraser, Walberg, Welch, & Hattie, 1987; Gustafsson & Undheim, 1996; Resing & Drenth, 2007; Rindermann, 2006; Snow & Yalow, 1982; Spinath, Freudenthaler, & Neubauer, 2010), but meta-cognitive skills (e.g., Bjorklund, 2005; Lucangeli & Cornoldi, 1997; Spinath, 2011; Swanson, 1993; Veenman, Kok, & Blöte, 2005), learning strategies, or motivational factors (Berger, 2008, 2009; Bjorklund, Miller, Coyle, & Slawinski, 1997; Fuchs et al., 2003; Pressley & Levin, 1987; Sideridis, 2007; Sideridis & Scanlon, 2006; Steinmayr & Spinath, 2007) may also be involved. This implies that, to explain the school achievement of children with and without SEN, various behaviors of the children have to be taken into account. Learning styles, motivation, and performance-goal orientation have been shown to play an important role in classroom learning in SEN children, especially in the genesis and persistence of learning disorders (Botsas & Padeliadu, 2003; Helmke & Schrader, 2006; Matthes, 2006; Sideridis, Morgan, Botsas, Padeliadu, & Fuchs, 2006; Spinath, Stiensmeier-Pelster, Schöne, & Dickhäuser, 2002; Wilbert, 2011).

Motivation and Goal Orientation

When examining the research literature, we find abundant evidence that students with and without special education needs: (1) have different academic and social self-concepts (Bless & Mohr, 2007; Kistner, Haskett, White, & Robbins, 1987; Elbaum, 2002; Elbaum & Vaughn, 2001; Schwab, Gebhardt, & Gasteiger-Klicpera, 2013; Zisimopoulos & Galanaki, 2009), (2) regulate their learning processes differently (Grolnick & Ryan, 1990), and (3) make different causal attributions regarding their successes and failures (Licht, Kistner, Ozkaragoz, Shapiro, & Clausen, 1985; Waheeda & Grainger, 2002; Zisimopoulos & Galanaki, 2009; see also Wilbert, 2011). Ring and Reetz (2000) showed, for example, that students with learning dif- ficulties exhibit a general tendency to attribute success to external factors, while attributing failure to ability, whereas the opposite prevails in students without learning difficulties. Furthermore, it is generally demonstrated that SEN learners show increased failure orientation (Matthes, 2006), as well as a lower academic self-concept (Haeberlin, Bless, Moser, & Klaghofer, 1999), and, as a consequence, show less effort in cognitive tasks (see also Venetz, Tarnutzer, Zurbriggen, & Sempert, 2010). Students with and without learning diffi- culties also have different goal orientations (Venetz et al., 2010).

Commonly, two general goals of learning orientation are distinguished: (1) task- involvement and (2) ego-involvement, which can be referred to as learning or mastery

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orientation and performance orientation (see Elliott & Dweck, 1988; Elliot & Harackiewicz, 1996; Linnenbrink & Pintrich, 2002). Some authors argue that the dual Achievement Goal Theory should be replaced by more a complex, multiple-goal model (Senko, Hulleman, & Harackiewicz, 2011). Kaplan and Maehr (2007), for example, also include a third com- ponent of goal orientation, namely work avoidance. While mastery orientation (often referred to as the learning motive) deals with understanding the tasks and improving com- petence, and focuses on self-improvement based on self-referenced standards, performance orientation (the achievement motive) refers to the person’s performance in comparison to others (Elliot & Harackiewicz, 1996; Spinath & Schöne, 2003). According to the perform- ance orientation, one either likes to demonstrate one’s skills (performance approach) or hide one’s incompetence (performance-avoidance approach) (Elliot, 1999), but both approaches appear moderately-to-highly correlated (Linnenbrink-Garcia, Middleton, Ciani, Easter, O’Keefe, & Zusho, 2012; see also Murayama, Elliot, & Yamagata, 2011). Nowadays, four learning goals are generally distinguished in the literature, namely mastery orientation, performance-approach orientation, performance-avoidance orientation, and work-avoidance orientation.

In Germany, Wilbert (2011) showed that the “Skalen zur Erfassung der Lern-und Leis- tungsmotivation” (SELLMO-S: Spinath et al., 2002), an instrument that measures the four achievement goals, functioned adequately in a group of children with learning disabilities. Tarnutzer (2011), using the SELLMO-S, demonstrated that students with low achievement scores reported a higher performance-avoidance orientation and (for some of the students) a higher tendency of work avoidance. Fulk, Brighamd, and Lohman (1998), using Nicholls’ (1989) Motivational Orientation Scale, concluded that students with learning diasabilities (LD) had a higher work-avoidance orientation than a group of average achievers.

Motivation and the Relationship with Achievement and Metacognition

A strong focus on the learning motive is associated with high success, while a high achievement-motivation orientation has a negative effect on performance (Bell & Kozlowski, 2002). Although mastery orientation seems to lead to higher success compared to perform- ance orientation (e.g., Ames, 1992), studies have also shown that both a mastery and a per- formance orientation can be beneficial (e.g., Harackiewicz, Barron, Pintrich, Elliot, & Thrash, 2002). In their meta-analytic review, Hulleman, Schrager, Bodmann, and Harackiewicz (2010) showed that having performance-approach goals was positively correlated to perform- ance outcomes, whereas mastery goals were only related to performance outcomes when the scales did not contain goal-relevant language.

Law, Elliot, and Murayama (2012) showed that perceived competence moderates the relationship between performance-approach and performance-avoidance goals. However, regardless of the fact that a considerable overlap exists between the two goals, research has made clear that they are related to different antecedents and consequences (Law et al., 2012). Huang (2012) analyzed 151 studies and concluded that approach motivations were related to higher academic achievement, whereas avoidance motivations were related to lower academic achievement.

Research has further shown that interactions exist between motivation and metacognition (Berger, 2008, 2009; Borkowski, Chan, & Muthukrishna, 2000; Efklides, 2011; Miller, Greene, Montalvo, Ravindran, & Nichols, 1996; Pintrich, 2000; Weinert & Kluwe, 1987). However, only few studies address the relationships between achievement goals and

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metacognition (Vrugt & Oort, 2008). Schraw, Potenza, and Nebelsick-Gullet (1993) showed that students who scored high on the learning dimension obtained higher achievement scores and exhibited more metacognitive knowledge than students with low scores on the learning dimension, whereas performance-approach goals were not related to metacognitive knowl- edge. Metaknowledge, that is, the knowledge someone has about his or her own cognitive functioning (e.g., the domains in which one is strong or weak), about school tasks, (e.g., why a certain task is difficult), and about strategies that can or cannot be applied in different task-solving situations (Flavell & Wellman, 1977), as well as metacognitive strategies such as anticipation, planning, and control (Berger, 2009; Bosson et al., 2010; Hessels, Hessels- Schlatter, Bosson & Balli, 2009), are reported to be deficient or underdeveloped in students with learning difficulties (Swanson, 1993).

According to Ford, Smith, Weissbein, Gully, and Salas (1998), mastery orientation was positively related to metacognitive activity. Furthermore, Vrugt and Oort (2008) illustrated that mastery goals had a positive correlation with metacognitive behavior, whereas perform- ance-avoidance goals had a negative correlation with metacognitive behavior (for effective self-regulatory students). Performance-approach goals appeared unrelated to metacognition (Vrugt & Oort, 2008). Dupeyrat and Mariné (2005) also confirmed that metacognitive control is positively related to a mastery approach and negatively related to performance- avoidance and work-avoidance goals. All in all, the relationship between metacognitive control and performance-approach goals is not clear: performance-approach goals and meta- cognitive control are sometimes positively related, sometimes unrelated, and sometimes negatively related (Middleton & Midgley, 1997).

The metacognitive awareness a person has of his or her own processes of learning is related to the concept of calibration (e.g., Pieschl, 2009; Schraw, 2009; see also Labuhn, Zimmerman, & Hasselhorn, 2010). Calibration is defined as the consistency between the students’ perceived performance and their actual performance (e.g., Pieschl, 2009; Schraw, 2009). Several studies have already shown that the accuracy of prediction of school success is correlated to achievement (e.g., Labuhn et al., 2010; Schraw et al., 1993). Regard- ing goal orientation and the perceived ability in mathematics, Berger (2009) showed signifi- cant positive correlations with mastery-challenge goals and weak positive correlations with performance-approach goals. Negative correlations were found with performance-avoidance and work-avoidance goals. The correlation between mastery-approach goals and perceived ability was not significant (Berger, 2009). Bipp, Steinmayr, and Spinath (2012) recently argued that goal orientations affect the perception of one’s own intelligence. They showed that persons with a high performance-approach orientation overestimated their intelligence, while persons with high performance-avoidance orientation underestimated their intelligence.

Objectives

Teaching, especially inclusive teaching, has to assure that every student can profit opti- mally from the lessons. Teachers will reach this goal only if they focus on the students’ differ- ent learning and performance requirements, as well as the motivation of the individual students. Goal orientation has been investigated regularly during the past years and quite some knowledge about it has accumulated, but little is known about goal orientation and SEN. Some studies have shown group differences between students with and without SEN (Fulk et al., 1998; Tarnutzer, 2011), but they did not control for external variables such as

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intelligence or achievement. Therefore, it is unclear to what the group differences were related and if these were really due to SEN.

The present study analyzes the goal orientations (mastery-goal orientation, performance- approach orientation, performance-avoidance orientation, and work-avoidance orientation) from students with and without SEN. As we assume that students with SEN have a higher performance-avoidance orientation and a higher work-avoidance orientation than students without SEN, we will investigate the differences between students with and without SEN on the four scales of goal orientation (mastery orientation, performance-approach orientation, performance-avoidance orientation, and work avoidance). If differences are found between the groups, we will further investigate whether these differences are mediated by other vari- ables such as school achievement in German and Mathematics, self-estimations of one’s own achievement in these school domains and calibration, or whether the group differences hold after controlling for these variables.

Methods

Participants

Participants were 186 (110 boys; 76 girls) seventh graders (mean age = 13 years 10 months, SD = 1 year 1 month) from 27 Austrian school classes, located in rural, urban, and suburban areas of Styria, Lower Austria, Vienna, and Upper Austria. These schools were randomly selected from schools teaching in inclusive classes. Informed consent was obtained from all parents whose child(ren) participated in the study. The sample was first of all composed of 93 students (55 boys, 38 girls) with SEN. Furthermore, 93 (55 boys, 38 girls) typically developing students without SEN were drawn from a pool of approxi- mately 900 students. These students were matched on IQ and gender with the SEN students on a one-to-one basis, that is, for each student with SEN, a student without SEN, but of the same gender and approximately the same IQ, was randomly selected from the total sample. Mean IQ scores were 81.3 (SD = 10.2) and 79.4 (SD = 9.9) for the group without SEN and the group with SEN, respectively. While the mean age of students without SEN was 13 years and 8 months, students with SEN were slightly older (14 years and 0 months; t175.92 = −3.34, p < .01). About 16.1% of the participants had a migration background. Students with SEN were all diagnosed as having a developmental disorder of school achievement (they had serious problems with reading, writing or numeracy and needed more time to process new infor- mation, but no other diagnosed disability such as, e.g., behavioral disorders or attention deficit hyperactivity disorder), they benefited from smaller class sizes and were accompanied by a special education teacher in the inclusive classes.

Procedure

Students first had to complete the goal orientation scales and then to fill out the self- estimations of their achievement. Beforehand, the teachers were asked which students might have problems filling out the questionnaires. Two assistants monitored all students (including those without SEN) and were ready to intervene if they observed students strug- gling with the questionnaires, also those that had not been listed beforehand by the teachers for needing assistance. The help provided was neutral and consisted of reading decoding only. No explanations about concepts or items were given. Next, the students had to complete

ACHIEVEMENT GOALS, ACHIEVEMENT AND CALIBRATION 465

the intelligence and achievements tests. Finally, the teachers were asked to complete a ques- tionnaire and to include the grades the students had obtained in German and Mathematics during the previous school year.

Measures

Goal orientation.

Goal orientations were assessed with the learning and achievement orientation scales SELLMO-S (Spinath et al., 2002). This instrument consists of 31 items that measure four goal-orientation scales: (1) the mastery-goal orientation scale (example: “In school I want to learn something interesting”; 8 items; α = .74), (2) the performance-approach orientation scale (example: “In school I want the others to think I am clever”; 7 items; α = .82), (3) the performance-avoidance orientation scale (example: “In school I want to make sure the others do not see that I do not understand”; 8 items; α = .92), and (4) the work-avoidance orientation scale (example: “In school I want to work the least possible”; 8 items; α = .89). Wilbert (2011) confirmed the reliability as well as the factorial structure of the instrument in a sample of students with disabilities. The rating scale system ranged from 1 = totally disagree to 5 = totally agree. Mean scale scores were computed for each student (scale total score divided by the number of items).

Self-estimates of achievement.

In line with a more often used one-item measure in this research field (see, e.g., Spinath et al., 2010; Tanzer, 1995) participants were asked to estimate their test scores on the basis of this wording: “How do you assess your talents in German (reading and writing)” and “How do you assess your talents in Mathematics?” The rating scale system ranged from 1 = low to 5 = high.

Intelligence and school achievement.

The Culture Fair Intelligence Test (CFT 20-R: Weiß, 2008) was used to estimate the stu- dents’ intelligence. This group administered intelligence test is language free and measures basic fluid intelligence, and is not confounded with scholastic abilities. Finally, we used German and Mathematics grades of the previous school year as an indicator of school per- formance. In Austria, grades range from 1 to 5, with 1 indicating outstanding and 5 insuffi- cient performance. To facilitate reading and interpretation, grades were inversed so that higher numbers represented better performance.

Calibration.

Calibration was defined as the absolute difference between self-estimated achievement and actual achievement. This means that a score of 0 indicates that the self-estimation corre- sponds perfectly to actual achievement and that the higher the calibration score, the greater the discrepancy is between the two.

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Results

The descriptive statistics show that some minor deviations from the normal distribution exist. This only concerns the skewness of mastery-goal orientation and performance-avoid- ance orientation in both groups, the skewness in German calibration in students without SEN, and the kurtosis of performance-avoidance orientation in SEN students. Nevertheless, para- metric analyses were performed, following Tabachnick and Fidell (2006), who affirm that with sufficiently large groups per cell, parametric analyses are relatively robust against such deviations from normality. Moreover, residual analyses always confirmed the appropri- ateness of the analyses.

Goal Orientations

The group differences in goal orientations were examined using multivariate and univari- ate analyses of variance. Status (with or without SEN) and gender were used as independent variables. The multivariate analysis results showed a significant group effect on the goal orientation scales (F [4, 179] = 4.31, p ≤ .01, η2 = .09, power = .93). The univariate analyses showed that only significant differences existed for the scales mastery-goal orientation and performance-avoidance orientation (see Table 1). While students without SEN have a greater mastery-goal orientation (F [1, 182] = 5.45, p ≤ .05, η2 = .03, power = .63), students with SEN show a higher performance-avoidance orientation (F [1,182] = 8.52, p ≤ .01, η2 = .04, power = .84). Both effect sizes are small (Cohen, 1992). For the performance-approach orientation (F [1, 182] = 2.49, n.s.), as well as for the work-avoidance orientation (F [1, 182]

Table 1 Means and standard deviations for students with and without SEN, as well as univariate F-tests for differences for all variablesa

Without SEN With SEN

M SD M SD F (1.184)

Goal orientation Mastery goal 3.73 .60 3.50 .70 5.45*

Performance approach 3.32 .72 3.15 .70 2.49

Performance avoidance 2.52 .89 2.90 .86 8.52**

Work avoidance 2.85 .81 2.93 .81 0.48

Achievement

German 3.55 .98 3.03 .95 13.26**

Mathematics 3.54 .93 3.08 .97 11.05** Self-estimation

German 3.49 .92 3.27 .99

Mathematic 3.23 .98 3.09 1.06

Calibration

German 0.72 0.77 0.97 0.76

Mathematics 0.85 0.74 0.98 0.79 IQ 81.26 10.23 79.43 9.87 2.16

Note: aexcept for self-estimations and calibration, since no significant multivariate effect existed; * p ≤ .05; ** p ≤ .01.

ACHIEVEMENT GOALS, ACHIEVEMENT AND CALIBRATION 467

= 0.48, n.s.), no significant differences were found. There was no significant main effect for gender (F [4, 179] = 1.81, n.s.) and no significant interaction effect between SEN status and gender (F [4, 179] = 0.24, n.s.).

Achievement, Self-Estimation of Achievement, and Calibration

Table 1 presents the means and standard deviations for school achievement, self- estimations of school achievement, calibration, and IQ in both groups. When the multivariate analyses were significant, univariate analyses of variance were performed to examine where the effects could be found. The results of these analyses are also presented in Table 1.

Consistent with previous research, the multivariate analysis showed a significant differ- ence between the groups regarding school achievement (F [2, 183] = 7.22, p ≤ .01, η2 = .07, power = .93). The results of the univariate analyses presented in Table 1 show that students without SEN attained a significantly higher level of school achievement in German (means scores of 3.55 versus 3.03, η2 = .07) and Mathematics (means of 3.54, versus 3.08, η2 = .06) than students with SEN. The multivariate analysis of variance of self-estimation in German and Mathematics shows that the groups were not significantly different (F [2, 183] = 1.48, n.s.). Students with SEN were also not different from students without SEN on calibration in German and Mathematics achievement (F [2, 183] = 2.73, n.s.). Obviously, as the groups were matched, mean IQ scores did not differ between groups.

Prediction of Goal Orientations

Hierarchical multiple regression analyses were done with mastery-goal orientation and performance-avoidance orientation, respectively, as the dependent variables. In each analysis, the two components of school achievement (German and Mathematics), the two self-estimations of these achievements variables, as well as the two calibrations, were entered as one block in Step 1 (Stepwise method), followed by SEN status in Step 2. Gender was excluded from the analysis as it showed no significant relationship in the multivariate analysis of variance. Intelligence was also excluded as it showed no signifi- cant correlation with any of the learning goals. Results are summarized in Tables 2 (mastery- goal orientations) and 3 (performance-avoidance orientation), showing the β’s, T-values, and significance for all the variables after Step 1 and Step 2, as well as the total R2 and the R2

change. Table 2 shows that the final regression model explains 4.9% of the variance in mastery

goal achievement (F [1, 183] = 4.67, p ≤ .05). However, although self-estimation of German achievement was introduced as significant predictor in the first step, the final model shows that only SEN contributed significantly to the prediction of the mastery goal orientation.

Regarding performance-avoidance orientation, Table 3 shows that the final regression model explains 5.5% of the variance (F [1, 183] = 5.29, p ≤ .01). Similarly to the findings for the mastery-goal orientation, German achievement was introduced as a significant predic- tor, but only SEN emerged as significant predictor of performance-avoidance orientation in the final model. All in all, both regression analyses show that SEN is the only explaining vari- able and that group differences cannot be explained by other variables.

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Table 2 Prediction of students’ mastery-goal orientation by measures of achievement, self-estimation of achievement, calibration, and intelligence (Step 1) and their SEN status (Step 2)

β t p R2 ΔR2

Step 1

German achievement .09 1.11 .27

Mathematics achievement .04 .53 .60 Self-estimation German .16 2.18 .03 Self-estimation Mathematics .10 1.33 .18

Calibration German .09 1.30 .20

Calibration Mathematics .02 0.27 .79 .025 .025a

Step 2

German achievement .05 .64 .52 Mathematics achievement .01 .07 .94

Self-estimation German .14 1.94 .05

Self-estimation Mathematics .09 1.25 .21

Calibration German .12 1.69 .09

Calibration Mathematics .03 0.45 .66

SEN −.15 −2.12 .04 .049 .024b

Note: a F [1, 184] = 4.77, p = .03; b F [1, 183] = 4.67, p = .04. Significant p-values printed bold.

Table 3 Prediction of students’ performance-avoidance orientation by measures of achievement, self-estimation of achievement, calibration, and intelligence (Step 1) and their SEN status (Step 2)

β t p R2 ΔR2

Step 1 German achievement −.15 −2.09 .04 Mathematics achievement .03 .31 .76

Self-estimation German −.04 −.46 .65 Self-estimation Mathematics −.08 −1.08 .28 Calibration German .06 .84 .40

Calibration Mathematics .06 .79 .43 .023 .023a

Step 2 German achievement −.10 1.40 .16 Mathematics achievement .05 .51 .61

Self-estimation German −.03 −.37 .71 Self-estimation Mathematics −.07 −.94 .35 Calibration German .04 .55 .59

Calibration Mathematics .04 .54 .59

SEN .18 2.47 .01 .055 .032b

Note:a F[1, 184] = 4.36, p = .04; b F[1, 183] = 5.29, p = .01. Significant p-values printed bold.

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Discussion

The aim of the present study was to expand our knowledge about the goal orientations in students with and without SEN in inclusive classes, as well as the relevance of other variables such as school achievement, self-estimation of school achievement, and calibration in relation to students’ goal orientations. Before we discuss the results, we think it is important to keep in mind that the participants in this study were randomly drawn from a large pool and that the students with and without SEN were matched on their intelligence scores (mean IQ around 80) and gender. This is a new approach, which has the advantage that a more correct comparison of students with and without SEN can be made. A disadvantage may be the limited comparability with other studies, using randomized samples of regular students.

The goal-orientation scales first of all showed that students without SEN scored higher in mastery-goal orientation, whereas students with SEN had higher performance-avoidance orientation. The latter confirms our hypothesis and concurs with Tarnutzer’s (2011) results, which also found that students with low achievement scored higher in perform- ance-avoidance orientation. It must be acknowledged, though, that the effect sizes are rela- tively small. Unlike Fulk et al. (1998) and Tarnutzer (2011), we did not find significant differences in the work-avoidance orientation. This might be explained by the fact that our groups were matched on intelligence: both groups have a mean IQ that is below average. In this research we found no relationship between IQ and goal orientations.

Next, we looked for group differences in school achievement, self-estimations of school achievement, and calibration. First of all, students without SEN attained higher levels of school achievement than students with SEN, in both German and Mathematics. Nevertheless, we found no differences in the self-estimations of school achievement, but students without SEN showed a tendency for more accurate estimations of their own achievements. A limit- ation of this study is that our estimation of school achievement was based on the students’ grades in German and Mathematics at the end of the previous school year and not on Math- ematics and German tests, which could have provided more objective measures. In this context, it is also important to mention that SEN students showed a tendency to overestimate their own achievement (cf. Hessels et al., 2009), whereas children without SEN rather under- estimated their own achievement. Even though students with SEN had lower achievement scores, they estimated their achievement at nearly the same level as that of the students without SEN. This overestimation may either be related to motivational/emotional variables, such as preserving self-image (“I am not a weak student”), or to less developed metacognitive competences (metaknowledge), that is, students with SEN are less able to correctly evaluate their performance (Swanson, 1993). However, it must be remembered that the differences with the group without SEN are small. It should also be mentioned that ability estimate is influenced by peers. If a student is in a good school, for example, the ability estimate tends to be lower as their peers are academically competent. Basically, this means that it is difficult to compare ability estimates of students from different schools and classrooms. However, our sample does not allow, for example, a multi-level treatment of the data to take classroom differences into account.

An important goal of this research was to investigate, when group differences in goal orientations were to be found, whether these would still hold when controlling for differences in achievement, self-estimations of achievement, and/or calibration. To answer this question, we conducted two separate regression analyses, one for mastery-goal orientation and one for performance-avoidance orientation, in which all variables except SEN status were included

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as potential predictors in Step 1. Students’ SEN status was subsequently entered in Step 2. The results of both analyses showed that only SEN status significantly augmented the amount of variance explained. Apparently, differences in goal orientations between students with and without SEN cannot be explained from other variables such as achievement, self- estimations of achievement, or calibration. This implies that being identified as a student with SEN may play an important role in goal orientations. Although it could be argued that the explained variance of both models is rather modest, the aim of this study was not to determine what the most important predictors are and to explain as much as variance in the goal orientations. Rather, it was important to demonstrate that being diagnosed as having SEN, by itself, may play an important role in students’ goal orientations. The fact that low amounts of variance are explained, in our view, finds its origin in the fact that the groups are matched on intelligence. Since most of the SEN students have an IQ that is below average, the matched group without SEN automatically falls into this lower range. This most likely means that these students also have lower academic success (although still somewhat higher than students with SEN), which further implies that the differences in goal orientations may be reduced, compared to a randomized sample of regular students. The greater standard deviations found in sample used for creating the reference norms, as reported in the SELLMO-S manual (Spinath et al., 2002), seem to concur with this idea.

Regardless of the relatively low explained variance, it must be concluded that differences in goal orientations exist between student with and without SEN. Further research should aim to find out why this is the case. Is it because students know that they are different, or know that they are the weak students? Or is it because teachers treat students with SEN differently from students without SEN? Hence, student motivation should not only be seen from the per- spective of the student, but also from the perspective of the teacher. Does the teacher exhibit behaviors towards the students and provide reinforcements that foster motivation for learning in students with special educational needs? This implies that the development of professional skills, the commitment to education as well as the personal development of teachers should also be taken into account in further research (see, e.g., Pekrun, 2009).

Furthermore, the chance of being diagnosed with a developmental disorder of school achievement may also depend on other factors than learning problems, such as parental support and general attitudes with regard to schooling (e.g., Pels, 1991), other motivational aspects of the learner, or various aspects of the school culture. Additionally, it must be recog- nized that the diagnostic procedure of special educational needs in Austria is highly criticized for its unstandardized nature. The assessment of LD is largely based on expert opinions pro- vided by special education teachers who are not obliged to use standardized tests or protocols (Gebhardt, Krammer, Schwab, Rossmann, & Gasteiger-Klicpera, 2013; Schwab, 2014).

A final methodological consideration concerns the direction of the effects. In the present article, we hypothesized that being labeled as having SEN would influence learning goals. Indeed, the effect could also be thought of in the opposite direction. For example, if a pupil shows a lot of work avoidance in the classroom, he or she might have a greater chance of being referred for the assessment of a possible learning disability. To be able to clarify the cause-and-effect relationship between these variables, a longitudinal study that started at the beginning of primary school would be necessary. Also, larger samples would allow for building structural equation models that would allow for stronger conclusions than the present approach.

In conclusion, even when the present results concern only Austria, likewise results could be found in other countries that are also changing to more inclusive school systems. An

ACHIEVEMENT GOALS, ACHIEVEMENT AND CALIBRATION 471

important factor in this context may be the way in which resources are attributed. In Austria, these are intimately related to the label that is attributed to a pupil. More research is needed about the influence of attributing such labels on the behavior of pupils and that of teachers, as these will be very important for the pupil’s school career.

References

Ames, C. (1992). Classrooms: Goals, structures, and student motivation. Journal of Educational Psychology, 84, 261–271. http://www.unco.edu/cebs/psychology/kevinpugh/motivation_ project/resources/ames92.pdf

Bell, B. S., & Kozlowski, S. W. J. (2002). Goal orientation and ability: Interactive effects on self- efficacy, performance, and knowledge. Journal of Applied Psychology, 87, 497–505. doi: 10. 1037/0021-9010.87.3.497

Berger, J. L. (2008). Motivation, métacognition et aptitudes cognitives chez les apprenants de la for- mation professionnelle initiale [Motivation, metacognition, and cognitive aptitudes of learners in initial vocational education]. (Unpublished doctoral dissertation) University of Geneva, Geneva, Switzerland.

Berger, J. L. (2009). The influence of achievement goals on metacognitive processes in math problem solving. Journal of Cognitive Education and Psychology, 8, 165–181. doi: 10.1891/1945–8959. 8.2.165

Bipp, T., Steinmayr, R., & Spinath, B. (2012). A functional look at goal orientations: Their role for self-estimates of intelligence and performance. Learning and Individual Differences, 22, 280–289. doi:10.1016/j.lindif.2012.01.009

Bjorklund, D. F. (2005). Children‘s thinking: Cognitive development and individual differences (4th ed.). Belmont, CA: Wadsworth/Thomson Learning.

Bjorklund, D. F., Miller, P. H., Coyle, T. R., & Slawinski, J. L. (1997). New themes in strategy devel- opment. Developmental Review, 17, 411–441. http://www.ingentaconnect.com/content/ap/dr/ 1997/00000017/00000004/art00440;jsessionid=4mdmpja89g5tb.alice

Bless, G., & Mohr, K. (2007). Die Effekte von Sonderunterricht und gemeinsamem Unterricht auf die Entwicklung von Kindern mit Lernbehinderungen [The effects of special class education and inclusive education on the development of children with learning disabilities]. In J. Walter & F. B. Wember (Eds.), Sonderpädagogik des Lernens. Handbuch Sonderpädagogik Band 2 [Special pedagogy of learning. Handbook Special Education, Volume 2] (pp. 375–383). Bern: Hogrefe.

Borkowski, J. G., Chan, L. K. S., & Muthukrishna, N. (2000). A process-oriented model of metacog- nition: Links between motivation and executive functioning. In G. Schraw (Ed.), Issues in the measurement of metacognition (pp. 1–41). Lincoln, NE: Buros Institute.

Bosson, M. S., Hessels, M. G. P., Hessels-Schlatter, C., Berger, J. L., Kipfer, N., &, Büchel, F. P. (2010). Strategy acquisition by children with learning difficulties in a metacognitive training. Australian Journal of Learning Difficulties, 15, 13–34. doi: 10.1080/19404150903524523

Botsas, G., & Padeliadu, S. (2003). Goal orientation and reading comprehension strategy use among students with and without reading difficulties. International Journal of Educational Research, 39, 477–495. doi:10.1016/j.ijer.2004.06.010

Buchner, T., Feyerer, E., & Flieger, P. (2009). Report on the social inclusion and social protection of disabled people in European countries (pdf). Retrieved from http://www.disabilityeurope.net/ content/pdf/AT%20social%20inclusion%20report.pdf

Cohen, J. (1992). Statistics a power primer. Psychology Bulletin, 112, 155–159. http://classes. deonandan.com/hss4303/2010/cohen%201992%20sample%20size.pdf

Deary, I. J., Strand, S., Smith, P., & Fernandez, C. (2007). Intelligence and educational achievement. Intelligence, 35, 13–21. doi:10.1016/j.intell.2006.02.001

472 SCHWAB AND HESSELS

Dupeyrat, C., & Mariné, C. (2005). Implicit theories of intelligence, goal orientation, cognitive engagement, and achievement: A test of Dweck’s model with returning to school adults. Contemporary Educational Psychology, 30, 43–59. doi:10.1016/j.cedpsych.2004.01.007

Efklides, A. (2011). Interactions of metacognition with motivation and affect in self-regulated learning: The MASRL Model. Educational Psychologist, 46, 6–25. doi: 10.1080/00461520. 2011.538645

Elbaum, B. (2002). The self-concept of students with learning disabilities: A meta-analysis of compari- sons across different placements. Learning Disabilities Research & Practice, 17, 216–226. doi: 10.1111/1540-5826.00047

Elbaum, B., & Vaughn, S. (2001). School-based interventions to enhance the self-concept of students with learning disabilities: A meta-analysis. Elementary School Journal, 101, 303–329. http:// nichcy.org/research/summaries/abstract18

Elliot, A. J. (1999). Approach and avoidance motivation and achievement goals. Educational Psychologist, 34, 169–189. doi:10.1207/s15326985ep3403_3

Elliot, A. J., & Harackiewicz, J. M. (1996). Approach and avoidance achievement goals and intrinsic motivation: A mediational analysis. Journal of Personality and Social Psychology, 70, 461–475. http://www.psych.rochester.edu/research/apav/publications/documents/1996_ ElliotHarackiewicz_ApproachandAvoidanceAchievementGoalsandIntrinsicMotivation.pdf

Elliott, E.S., & Dweck, C.S. (1988). Goals: An approach to motivation and achievement. Journal of Personality and Social Psychology, 54, 5–12. doi: 10.1037/0022-3514.54.1.5

Flavell, J. H., & Wellman, H. M. (1977). Metamemory. In R. V. Kail & J. W. Hagen (Eds.), Perspectives on the development of memory and cognition (pp. 3–33). Hillsdale, NJ: Lawrence Erlbaum.

Ford, J. K., Smith, E. M., Weissbein, D. A., Gully, S. M., & Salas, E. (1998). Relationships of goal orientation, metacognitive activity, and practice strategies with learning outcomes and transfer. Journal of Applied Psychology, 83, 218–233. doi: 10.1037/0021-9010.83.2.218

Fraser, B. J., Walberg, H. J., Welch, W. W., & Hattie, J. A. (1987). Syntheses of educational pro- ductivity research. International Journal of Educational Research, 81, 147–252. doi: 10.1016/ 0883-0355(87)90035-8

Fuchs, L. S., Fuchs, D., Prentice, K., Burch, M., Hamlett, C. L., & Owen, R., et al. (2003). Explicitly teaching for transfer: Effects on third-grade students’ mathematical problem solving. Journal of Educational Psychology, 95, 293–304. http://www.deepdyve.com/lp/psycarticles-reg/explicitly- teaching-for-transfer-TchQgFJFqM

Fulk, B. M., Brigham, F. J., & Lohman, D. A. (1998). Motivation and self-regulation: A comparison of students with learning and behavior problems. Remedial and Special Education, 19, 300–309. doi: 10.1177/074193259801900506

Gasteiger-Klicpera, B., Klicpera, C., Gebhardt, M., & Schwab, S. (2012). Attitudes and experiences of parents regarding inclusive and special school education for children with learning and intellec- tual disabilities. International Journal of Inclusive Education. doi:10.1080/13603116.2012. 706321.

Gebhardt, M., Krammer, M., Schwab, S., Rossmann, P., & Gasteiger-Klicpera, B. (2013). What is behind the diagnosis of learning disabilities in Austrian schools? An empirical evaluation of the diagnostic process. International Journal of Special Education, 28, 1–7. http://www. internationaljournalofspecialeducation.com/articles.cfm?y=2013&v=28&n=1

Grolnick, W. S., & Ryan, R. (1990). Self-perceptions, motivation, and adjustment in learning disabled children: A multiple group comparison study. Journal of Learning Disabilities, 23, 177–184. doi: 10.1177/002221949002300308

Gustafsson, J.-E., & Undheim, J. O. (1996). Individual differences in cognitive functions. In D. C. Berliner & R. C. Calfee (Eds.), Handbook of educational psychology (pp. 186–242). New York: Prentice Hall International.

ACHIEVEMENT GOALS, ACHIEVEMENT AND CALIBRATION 473

Haeberlin, U. (2013). Inklusion als Vision und Exklusion als Realität – Reflexionen zur Inklusion und Exklusion von Benachteiligten in unserer Kultur und in unserem Bildungswesen [Inclusion as vision and exclusion as reality: Reflections on inclusion and exclusion of underpriviledged in our culture and educational system]. In S. Schwab, M. Gebhardt, E. M. Ederer-Fick & B. Gasteiger-Klicpera (Eds.), Theorien, Konzepte und Anwendungsfelder der inklusiven Pädagogik [Theories, concepts, and fields of application of inclusive pedagogy] (pp. 11–24). Vienna, Austria: Facultas-Verlag.

Haeberlin, U., Bless, G., Moser, U., & Klaghofer, R. (1999). Die Integration von Lernbehinderten: Versuche, Theorien, Forschungen, Enttäuschungen, Hoffnungen (Volume 3) [The integration of the learning disabled: Attempts, theories, research, disappointments, hopes (Vol. 3)]. Bern, Switzerland: Haupt.

Harackiewicz, J., Barron, K., Pintrich, P., Elliot, A., & Thrash, T. (2002). Revision of achievement goal theory: Necessary and illuminating. Journal of Educational Psychology, 94, 638–645. doi: 10.1037//0022-0663.94.3.638

Helmke, A., & Schrader, F. W. (2006). Determinanten der Schulleistung [Determinants of school achievement]. In D. H. Rost (Ed.), Handwörterbuch Pädagogischer Psychologie [Small dictio- nairy of pedagogical psychology] (pp. 685–692). Basel: Beltz.

Hessels, M. G. P., Hessels-Schlatter, C., Bosson, M. S., & Balli, Y. (2009). Metacognitive teaching in a special education class. Journal of Cognitive Education and Psychology, 8, 182–201. doi: 10. 1891/1945–8959.8.2.182

Huang, C. (2012). Discriminant and criterion-related validity of achievement goals in predicting aca- demic achievement: A meta-analysis. Journal of Educational Psychology, 104, 48–73. doi: 10. 1037/a0026223

Hulleman, C. S., Schrager, S. M., Bodmann, S. M., & Harackiewicz, J. M. (2010). A meta-analytic review of achievement goal measures: Different labels for the same constructs or different con- structs with similar labels? Psychological Bulletin, 136, 422–449. doi: 10.1037/a0018947

Kaplan, A., & Maehr, M. L. (2007). The contributions and prospects of goal orientation theory. Educational Psychological Review, 19, 141–184. doi: 10.1007/s10648-006-9012-5

Kistner, J., Haskett, M., White, K., & Robbins, R. (1987). Perceived competence and self-worth of learning disabled and normally achieving students. Learning Disability Quarterly, 10, 37–44. doi:10.2307/1510753

Labuhn, A. S., Zimmerman, B. J., & Hasselhorn, M. (2010). Enhancing students’ self-regulation and mathematics performance: The influence of feedback and self-evaluative standards. Metacognition Learning, 5, 173–194. doi: 10.1007/s11409-010-9056-2

Law, W., Elliot, A. E., & Murayama, K. (2012). Perceived competence moderates the relation between performance-approach and performance-avoidance goals. Journal of Educational Psychology, 104, 806–819. doi: 10.1037/a0027179

Licht, B. G., Kistner, J. A., Ozkaragoz, T., Shapiro, S., & Clausen, L. (1985). Causal attributions of learning disabled children: Individual differences and their implications for persistence. Journal of Educational Psychology, 77, 208–216. doi: 10.1037/0022-0663.77.2.208

Linnenbrink, E. A., & Pintrich, P. R. (2002). Motivation as an enabler for academic success. School Psychology Review, 31, 313–327. http://www.nasponline.org/publications/spr/abstract.aspx? ID=1615

Linnenbrink-Garcia, L., Middleton, M. J., Ciani, K. D., Easter, M. A., O’Keefe, P. A., & Zusho, A. (2012). The strength of the relation between performance-approach and performance-avoidance goal orientations: Theoretical, methodological, and instructional implications. Educational Psychologist, 47, 281–301. doi: 10.1080/00461520.2012.722515

Lucangeli, D., & Cornoldi, C. (1997). Mathematics and metacognition: What is the nature of the relationship? Mathematical Cognition, 3, 121–139. doi: 10.1080/135467997387443

Matthes, G. (2006). Individuelle Lernförderung bei Lernstörungen. [Individual teaching with learning disabilities]. Potsdam, Germany: Universitätsverlag Potsdam.

474 SCHWAB AND HESSELS

Middleton, M., & Midgley, C. (1997). Avoiding the demonstration of lack of ability: An unexplored aspect of goal theory. Journal of Educational Psychology, 89, 710–718. doi: 10.1037/0022- 0663.89.4.710

Miller, R. B., Greene, B. A., Montalvo, G. P., Ravindran, B., & Nichols, J. D. (1996). Engagement in academic work: The role of learning goals, future consequences, pleasing others, and perceived ability. Contemporary Educational Psychology, 21, 388–422. doi: 10.1006/ceps.1996.0028

Murayama, K., Elliot, A. J., & Yamagata, S. (2011). Separation of performance- approach and per- formance-avoidance goals: A broader analysis. Journal of Educational Psychology, 103, 238– 256. doi: 10.1037/a0021948

Nicholls, J. G. (1989). The competitive ethos and democratic education. Cambridge, MA: Harvard University Press.

Pekrun, R. (2009). Emotions at school. In K. R. Wentzel & A. Wigfield (Eds.), Handbook of motiv- ation at school (pp. 575–604). New York: Routledge.

Pels, T. (1991). Marokkaanse kleuters en hun cultureel kapitaal. Opvoeden en leren in het gezin en op school [Moroccan pre-schoolers and their cultural capital: Education and learning in the family and at school]. Amsterdam: Swets & Zeitlinger.

Pieschl, S. (2009). Metacognitive calibration: An extended conceptualization and potential appli- cations. Metacognition and Learning, 4, 3–31. doi: 10.1007/s11409-008-9030-4

Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 451–502). San Diego, CA: Academic Press.

Pressley, M., & Levin, J. R. (1987). Elaborative learning strategies for the inefficient learner. In S. J. Ceci (Ed.), Handbook of cognitive, social, and neuropsychological aspects of learning disabil- ities (Vol. 2, pp. 175–212). Hillsdale, NJ: Lawrence Erlbaum.

Resing, W. C. M., & Drenth, P. J. D. (2007). Intelligentie: Weten en meten [Intelligence: Knowing and measuring]. Amsterdam: Uitgeverij Nieuwezijds.

Rindermann, H. (2006). Was messen internationale Schulleistungsstudien? Schulleistungen, Schülerfähigkeiten, kognitive Fähigkeiten, Wissen oder allgemeine Intelligenz? [What du inter- national academic achievement studies measure? School achievement, student capacities, cogni- tive abilities, knowledge or general intelligence?] Psychologische Rundschau, 57(2), 69–86. doi: 10.1026/0033-3042.57.2.69

Ring, M. M., & Reetz, L. (2000). Modification effects on attributions of middle school students with learning disabilities. Learning Disabilities Research & Practice, 15, 34–42. doi: 10.1207/ SLDRP1501_4

Ruijs, N. M., & Peetsma, T. D. (2009). Effects of inclusion on students with and without special edu- cational needs reviewed. Educational Research Review, 4, 67–79. doi: 10.1016/j.edurev.2009. 02.002

Sander, A. (2005). Konzepte einer inklusiven Pädagogik [Concepts of an inclusive pedagogy]. Zeitschrift für Heilpädagogik, 55, 240–244.

Schraw, G. (2009). A conceptual analysis of five measures of metacognitive monitoring. Metacognition and Learning, 4, 33–45. doi: 10.1007/s11409-008-9031-3

Schraw, G., Potenza, M. T., & Nebelsick-Gullet, L. (1993). Constraints on the calibration of perform- ance. Contemporary Educational Psychology, 18, 455–463. doi: 10.1006/ceps.1993.1034

Schwab, S. (2014). Schulische Integration, soziale Partizipation und emotionales Wohlbefinden in der Schule. Ergebnisse einer empirischen Längsschnittstudie [Inclusive education, social partici- pation and emotional well-being in school. Results from an empirical longitudinal study]. Münster: Lit. Verlag.

Schwab, S., Gebhardt, M., & Gasteiger-Klicpera, B. (2013). Facing the challenges of inclusion – A Survey of social integration and social behavior of students with and without SEN in an integra- tive school system. International Journal of Disability, Communication and Rehabilitation, 12. www.ijdcr.ca/VOL12_01/articles/schwab.shtml

ACHIEVEMENT GOALS, ACHIEVEMENT AND CALIBRATION 475

Senko, C., Hulleman, C. S., & Harackiewicz, J. M. (2011). Achievement Goal Theory at the cross- roads: Old controversies, current challenges, and new directions. Educational Psychologist, 46, 26–47. doi: 10.1080/00461520.2011.538646

Sideridis, G. D., Morgan, P. L., Botsas, G., Padeliadu, S., & Fuchs, D. (2006). Predicting LD on the basis of motivation, metacognition, and psychopathology: A ROC analysis. Journal of Learning Disabilities, 39, 215–229. doi: 10.1177/00222194060390030301

Sideridis, G.D., & Scanlon, D. (2006). Motivational issues in learning disabilities: Editors’ introduc- tion to special issue. Learning Disability Quarterly, 29 (3), 131–135.

Sideridis, G. D. (2007). Why are students with learning disabilities depressed? A goal orientation model of depression vulnerability. Journal of Learning Disabilities, 40, 526–539. doi: 10. 1177/00222194070400060401

Snow, R. E., & Yalow, E. (1982). Education and intelligence. In R. J. Sternberg (Ed.), Handbook of human intelligence (pp. 493–585). Cambridge: Cambridge University Press.

Spinath, B. (2011). Lernmotivation [Motivation for learning]. In H. Reinders, H. Ditton, C. Gräsel & B. Griewosz (Eds.), Empirische Bildungsforschung [Empirical educational research] (pp. 45–56). Wiesbaden, Germany: VS Verlag für Sozialwissenschaften.

Spinath, B., Freudenthaler, H., & Neubauer, A. C. (2010). Domain-specific school achievement in boys and girls as predicted by intelligence, personality, and motivation. Personality and Individual Differences, 48, 481–486. doi: 10.1016/j.paid.2009.11.028

Spinath, B., & Schöne, C. (2003). Ziele als Bedingungen von Motivation am Beispiel der Skalen zur Erfassung der Lern- und Leistungsmotivation (SELLMO) [Goals as prerequisites of motivation from the example of the Assessment of Learning and Performance Motivation Scales (SELLMO)]. In J. Stiensmeier-Pelster & F. Rheinberg (Eds.), Diagnostik von Motivation und Selbstkonzept [Assessment of motivation and self-concept] (pp. 29–40). Göttingen, Germany: Hogrefe.

Spinath, B., Stiensmayr-Pelster, J., Schöne, C., & Dickhäuser, O. (2002). SELLMO. Skalen zur Erfassung der Lern- und Leistungsmotivation. Manual. [SELLMO: Assessment of Learning and Performance Motivation Scales. Manual]. Göttingen, Germany: Hogrefe.

Steinmayr, R., & Spinath, B. (2007). Predicting school performance from motivation and personality. Zeitschrift für Pädagogische Psychologie, 21, 207–216. doi: 10.1024/1010-0652.21.3.207

Swanson, H. L. (1993). Executive processing in learning disabled readers. Intelligence, 17, 117–149. doi: 10.1016/0160-2896(93)90024-Y

Tabachnick, B., & Fidell, L. (2006). Using multivariate statistics. New York: Allyn & Bacon. Tanzer, N. K. (1995). Validierung eines Selbstbeschreibungsinventars für Kinder und Jugendliche

nach Marsh (1988) [Validation of the self-description inventory for children and adolescents by Marsh (1988)]. Zeitschrift für Differentielle und Diagnostische Psychologie, 16, 281.

Tarnutzer, R. (2011, September). Goal orientation and affective experience in inclusive classes. Paper presented at the First Annual European Congress of Learning Disabilities, University of Applied Sciences of Special Needs Education, Zürich, Switzerland.

Veenman, M. V. J., Kok, R., & Blöte, A. W. (2005). The relationship between intellectual and meta- cognitive skills in early adolescence. Instructional Science, 33, 193–211. doi: 10.1007/s11251- 004-2274-8

Venetz, M., Tarnutzer, R., Zurbriggen, C., & Sempert, W. (2010). Die Qualität des Erlebens von Lernenden in integrativen und separativen Schulformen: Eine Untersuchung mit der Experience Sampling Method (ESM) [The quality of experience of learners in integrative and special schools: Research with the Experience Sampling Method (ESM)]. Zürich, Switzerland: University of Applied Sciences of Special Needs Education.

Vrugt, A., & Oort, F. J. (2008). Metacognition, achievement goals, study strategies, and academic achievement: Pathways to achievement. Metacognition Learning, 30, 123–146. doi: 10.1007/ s11409-008-9022-4

476 SCHWAB AND HESSELS

Waheeda, T., & Grainger, J. (2002). Self-concept, attributional style, and self-efficacy beliefs of stu- dents with learning disabilities with and without attention deficit hyperactivity disorder. Learning Disability Quarterly, 25, 141–151. doi: 10.2307/1511280

Weiß, R. H. (2008). CFT 20 R: Grundintelligenztest Skala 2-Revision [CFT20-R: Basic Intelligence Test Scales 2-Revised]. Göttingen, Germany: Hogrefe.

Weinert, F. E., & Kluwe R. H. (Eds.), (1987). Metacognition, motivation, and understanding. Hillsdale, NJ: Lawrence Erlbaum Associates.

Wilbert, J. (2011). Die Einsetzbarkeit der Skalen zur Erfassung der Lern- und Leistungsmotivation (SELLMO) bei Schülern des Förderschwerpunkts Lernen. [The applicability of the Assessment of Learning and Performance Motivation Scales (SELLMO) with students with special learning needs]. Zeitschrift für Heilpädagogik, 62, 11–17. http://www.reinhardt-verlag. de/de/einzelheft/50563/

World Health Organisation. (1993). The ICD-10 classification of mental and behavioural disorders: Diagnostic criteria for research. Geneva: WHO.

Zisimopoulos, D. A., & Galanki, E. P. (2009). Academic intrinsic motivation and perceived academic competence in Greek elementary students with and without learning disabilities. Learning Disabilities Research & Practice, 24, 33–43. doi: 10.1111/j.1540-5826.2008.01275.x

ACHIEVEMENT GOALS, ACHIEVEMENT AND CALIBRATION 477

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