04 SES 08 C, Dealing With Personalisations, Individualisation And Inequalities From An Inclusive Perspective
With the ratification of the UN Convention of Rights of Persons with Disabilities (CRPD) on 26 March 2009, Germany has made the commitment – as have 181 other countries – to guarantee non-discriminatory access to inclusive and high-quality teaching at all levels of the (general) educational system. The much-noticed Article 24 of the UN CRPD demands that participating states ensure, among others, effective and personalized support measures in inclusive learning settings to maximize academic as well as social and emotional development of all learners. Access to the general educational system is a prerequisite, but not a sufficient condition for successful inclusion (Powell & Hadjar, 2016). Students´ wellbeing is regarded as an important indicator of the quality of inclusion and as one of the main aims of inclusive education (Kullmann et al., 2015). As such, responding to student diversity has brought about new challenges for teachers. In order to meet diversity challenges in classroom, it is critical that teachers adapt their instructional practices. In this regard, teacher’s ability to accurately assess a student’s subjective wellbeing is supposed to support each student’s personal and academic development. However, while teachers’ assessment accuracy for students’ academic achievement and cognitive abilities is in general relatively adequate, the agreement between self-reports and teacher reports of socio-emotional aspects is rather low (Machts et al., 2016). The low to moderate consistencies suggest the occurrence of an assessment bias. Recent findings indicate that especially student’s gender and the status special educational needs (SEN) influence teachers’ assessment accuracy of students’ inclusion at school (Schwab et al., 2020). Teacher characteristics such as their self-efficacy and their attitudes towards inclusion are regarded as fundamental for successfully implementing inclusive education (Gebhardt et al., 2015). Teachers’ responsibility is related to the teachers’ belief in their ability to influence students and with positive attitudes towards teaching in heterogenous classrooms (Halvorsen et al., 2009). Furthermore, teachers with more job experience are better able to judge students’ performance (Van Ophuysen, 2006). In this line of thought, teachers’ assessment bias represented as stigmatization effects could ultimately lead to increasing educational inequalities. Even though to date several studies investigated the accuracy of teacher judgments, teachers’ assessment accuracy with respect to students’ emotional inclusion has been largely neglected in previous research. In this regard, the present study investigates, first, the consistency of the self-reports and the teacher reports of students‘ emotional well-being, social inclusion and academic self-concept. Second, we address the question whether students’ gender, first language and SEN can explain teachers’ assessment accuracy of students’ inclusion in school. Third, the possible influence of teachers’ job experience, self-efficacy and attitudes towards inclusion as well as their responsibility for every student on teachers´ assessment accuracy is also part of our study.
Data are from the project “Inklusion in der Sekundarstufe I in Deutschland” (INSIDE). The sample consisted of 3772 grade 6 students (Mage = 12.6 years, SDage = 0.62) from 231 schools and 432 teachers. To assess students’ emotional well-being, social participation and academic self-concept, both students and teachers were asked to fill out the German Version of the Perceptions of Inclusion Questionnaire (PIQ; Venetz et al., 2015). In the project INSIDE, the PIQ items with negative wording were not included. Additionally, teachers filled out the Self-efficacy for Inclusive Teaching Questionnaire (Bosse & Spörer, 2014), the Attitudes towards an Inclusive Education System Questionnaire (Lüke & Grosche, 2017) and an adapted version of the Teacher Responsibility Scale (Lauermann & Karabenick, 2013). Analyses were performed in Mplus Version 8.0. Given the nested structure of the data, we used the complex sample option. First, we applied a correlated trait-correlated method minus one [CT-C(M-1)] model (Eid et al., 2003) to examine the consistency of student self-reports and teacher ratings. To address the second and third research questions, we fitted a CT-C(M-1) model with covariates and latent interaction effects (Koch et al., 2018).
Research question 1: How consistent are self-reports and teacher reports of students‘ emotional well-being, social inclusion and academic self-concept? Results showed low to moderate consistencies between self-reports and teacher reports (12–33%). The consistency between teachers’ reports and self-reports of students’ emotional well-being and social inclusion is rather low. The consistency for academic self-concept is somewhat higher. Research question 2: Do the students’ gender, first language and the status special educational needs (SEN) predict teachers’ assessment accuracy regarding students’ inclusion? The students’ gender and the status SEN were important predictors for the assessment bias. Teachers underestimate the academic self-concept of students with the status SEN (compared to students without SEN) – and to a smaller extent also their social inclusion and emotional well-being. Moreover, they tend to overestimate girls’ subjective well-being. Research question 3: Do the teachers’ job experience, self-efficacy and attitudes towards inclusion as well as their responsibility for every student predict teachers’ assessment accuracy of students’ inclusion? The bias could partly be explained by teachers’ self-efficacy and attitudes towards inclusion and their responsibility for every student. Teachers’ assessment (in-)accuracy regarding students’ subjective well-being could be predicted only to a small extent by the teachers’ self-efficacy and attitudes towards inclusion and their responsibility for every student. The findings will be discussed in terms of their significance for educational inequalities. Implications for practice and recommendations for future research will be given.
Bosse, S., & Spörer, N. (2014). Erfassung der Einstellung und der Selbstwirksamkeit von Lehramtsstudierenden zum inklusiven Unterricht. Empirische Sonderpädagogik, 4, 279–299. Eid, M., Lischetzke, T., Nussbeck, F. W., & Trierweiler, L. I. (2003). Separating trait from trait-specific method effects in multitrait-multimethod models: a multiple-indicator CT-C(M–1) model. Psychological Methods, 8, 38–60. Gebhardt, M., Schwab, S., Nusser, L., & Hessels, M. G. P. (2015). Einstellungen und Selbstwirksamkeit von Lehrerinnen und Lehrern zur schulischen Inklusion in Deutschland - eine Analyse mit Daten des Nationalen Bildungspanels Deutschlands (NEPS). Empirische Pädagogik, 2, 211–229. Halvorsen, A.-L., Lee, V. E., & Andrade, F. H. (2009). A mixed-method study of teachers’ attitudes about teaching in urban and low-income schools. Urban Education, 44(2), 181–224. Koch, T., Kelava, A., & Eid, M. (2018). Analyzing different types of moderated method effects in confirmatory factor models for structurally different methods. Structural Equation Modeling: A Multidisciplinary Journal, 25, 179–200. Kullmann, H., Geist, S., & Lütje-Klose, B. (2015). Erfassung schulischen Wohlbefindens in inklusiven Schulen. In P. Kuhl, P. Stanat, B. Lütje-Klose, C. Gresch, H. A. Pant, & M. Prenzel (Eds.), Inklusion von Schülerinnen und Schülern mit sonderpädagogischem Förderbedarf in Schulleistungserhebungen (pp. 301–333). Springer. Lauermann, F., & Karabenick, S. A. (2013). The meaning and measure of teachers’ sense of responsibility for educational outcomes. Teaching and Teacher Education, 30, 13–26. Lüke, T., & Grosche, M. (2017). Konstruktion und Validierung der Professionsunabhängigen Einstellungsskala zum Inklusiven Schulsystem (PREIS). Lizenziert unter CC-BY-SA. https://doi.org/10.6084/m9.figshare.2245630 Machts, N., Kaiser, J., Schmidt, F. T. C., & Möller, J. (2016). Accuracy of teachers’ judgments of students’ cognitive abilities: A meta-analysis. Educational Research Review, 19, 85–103. Powell, J. J. W., & Hadjar, A. (2016). Schulische Inklusion in Deutschland, in Luxemburg und in der Schweiz. Aktuelle Bedingungen und Herausforderungen. In K. Rathmann & K. Hurrelmann (Eds.), Leistung und Wohlbefinden in der Schule: Herausforderung Inklusion (pp. 46–64). Belz Juventa. Schwab, S., Zurbriggen, C. L. A., & Venetz, M. (2020). Agreement among student, parent and teacher ratings of school inclusion: A multitrait-multimethod analysis. Journal of School Psychology, 82, 1–16. Van Ophuysen, S. (2006). Vergleich diagnostischer Entscheidungen von Novizen und Experten am Beispiel der Schullaufbahnempfehlung. Zeitschrift Fur Entwicklungspsychologie Und Padagogische Psychologie, 38, 154–161. Venetz, M., Zurbriggen, C. L. A., Eckhart, M., Schwab, S., & Hessels, M. G. P. (2015). The Perceptions of Inclusion Questionnaire (PIQ). Retrieved from https://piqinfo.ch
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