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Institut
- Department Erziehungswissenschaft (28) (entfernen)
Teacher self-efficacy for classroom management is an important component of teachers' identity with implications for their teaching quality. Theoretically, it has been described that contextual variables play an important role for self-efficacy development and its consequences. However, little is known about the interrelationships of job resources and demands with teacher self-efficacy, and consequences for teachers' professional behaviors. We extend teacher self-efficacy research by drawing on the Job Demands-Resources model in examining contextual influences on developmental dynamics between classroom management self-efficacy and teacher-reported classroom management, from prior to qualifying as a teacher until mid-career. Participants were 395 primary and secondary Australian school teachers. Longitudinal structural equation models showed teachers' classroom management self-efficacy positively related to aspects of their perceived classroom management, particularly during early career. Between early and mid-career, the positive relationship between self-efficacy and classroom management was moderated by early career excessive demands. Implications are outlined for teacher education and school administration.
Some studies reveal that adolescents with intellectual disabilities and developmental disabilities are more likely to be victims of both face-to-face bullying and cyberbullying. Research also suggests that these adolescents are likely to witness bullying victimization. More research is needed to better understand the negative outcomes associated with their experiences. The purpose of this short-term longitudinal study was to investigate the buffering effect of parental social support on the associations of cyberbullying victimization and bystanding to subjective health complaints, suicidal ideation, and non-suicidal self-harm. Participants were 121 adolescents (63% male;Mage = 14.10 years) with intellectual disabilities and developmental disorders who completed questionnaires on their face-to-face and cyberbullying victimization and bystanding, parental social support, subjective health complaints, suicidal ideation, and non-suicidal self-harm during the 7th grade (Time 1). In 8th grade (Time 2), they completed questionnaires on subjective health complaints, suicidal ideation, and non-suicidal self-harm. The findings revealed that the positive associations between Time 1 cyberbullying victimization and Time 2 subjective health complaints, suicidal ideation, and non-suicidal self-harm were stronger at lower levels of Time 1 parental social support, while high levels of Time 1 parental social support diminished these relationships. Similar patterns were found for Time 1 cyberbullying bystanding and Time 2 subjective health complaints. Parental social support has a buffering effect on the relationships among cyberbullying victimization, bystanding, and health outcomes among adolescents with intellectual and developmental disorders.
Four topics were investigated in this longitudinal person-centered study: (a) profiles of subjective task values and ability self-concepts of adolescents in the domain of mathematics, (b) the stability of and changes to the profiles of motivational beliefs from Grade 7 to 12, (c) the relation of changes to student-perceived classroom characteristics, and (d) the extent to which profile membership in early adolescence predicted mathematics achievement and career plans in late adolescence and the choice of math-related college majors and occupations in adulthood. Data were drawn from the Michigan Study of Adolescent and Adult Life Transitions Study. We focused on students who participated in the following 4 waves of data collection (N = 867): at the beginning of Grade 7 (Wave 3), at the end of Grade 7, in Grade 10 (Wave 5), and in Grade 12 (Wave 6). Four profiles that were stable across Grades 7 to 12 were identified using Latent Profile Analysis. Student-reported fairness and friendliness and competition in class predicted changes in profile membership. Profile membership in Grade 7 predicted math-related career plans in Grade 12. Profile membership in Grade 12 predicted the choice of math-related college major after finishing school and of math-related occupations in adulthood.
Becoming Canadian
(2020)
We investigate how economic immigrants in Canada negotiate their identity in the process of "becoming Canadian" through an analysis of public texts. Drawing on the master narrative framework, we examine the interplay between individual and societal narratives as immigrants grapple with the tension between notions of "desirable" immigrants as those that are well integrated professionally and the reality of facing career related barriers. Among those whose success stories align with the master narrative of professional attainment there was little questioning of this expectation, thereby allowing it to remain invisible. Among those who had not (yet) achieved work related success in the receiving country, they tended to engage alternative narratives elaborating on the antecedents, outcomes, and barriers to labor market participation. Despite the countering nature of these alternative narratives, they strengthen the societal expectation of professional success as a key pathway to inclusion, thereby reinforcing the rigidity of this narrative. We contribute to literature on the social construction of national identity by examining the process of becoming national and the role of labor market participation in immigrants' perceptions of inclusion in their new society. Our study highlights the importance of including immigrants' voices in the construction of a more inclusive society, which may aid in breaking down exclusionary narratives of national identity.
The aim of educational policy should be to provide a good education to all students. Thus, a key question arises regarding the extent to which key characteristics of school composition (proportion of students with migration background, socioeconomic status [SES], prior school achievement, and achievement heterogeneity), instructional quality, school quality, and later school achievement are interrelated. The present study addressed this research question by examining school inspection data, official school statistics, and large-scale achievement data from all primary schools in Berlin, Germany (N = 343). The results of correlation and path analyses showed that school composition (average SES, average prior school achievement) predicted components of instructional quality (SES: classroom management, cognitive activation; achievement: cognitive activation, individual learning support). The relation between school composition characteristics and most components of school quality was close to zero. Contrary to our expectations, only the effect of school SES on later achievement was mediated by instructional quality.
Die Forschung zur Lehrerfortbildung weist darauf hin, dass zeitliche Einschränkungen eine Barriere für die Teilnahme an Fortbildungen darstellen. Insbesondere die Unvereinbarkeit der Arbeitszeit mit dem Zeitpunkt des Fortbildungsangebotes wird von Lehrkräften als hinderlich wahrgenommen. Welche zeitlichen Merkmale das Fortbildungsangebot für Lehrkräfte aufweist und ob diese im Zusammenhang mit der Fortbildungsteilnahme von Lehrkräften stehen, fand bisher wenig Berücksichtigung. Die vorliegende Studie verfolgt daher das Ziel, zeitliche Merkmale des Fortbildungsangebotes für Lehrkräfte zu beschreiben und ihre Vorhersagekraft für die Fortbildungsteilnahme zu untersuchen. Die Daten hierfür stammen aus der elektronischen Datenbank für Lehrerfortbildungen des Landes Brandenburg im akademischen Jahr 2016/2017. Der Datensatz umfasst 1330 schulexterne Lehrerfortbildungen staatlicher Anbieter. Die Ergebnisse zeigen, dass Dauer und Zeitpunkt einer Fortbildungsveranstaltung prädiktiv für die Teilnahme der Lehrkräfte sind. Die Befunde erweitern damit den Diskurs zu Bedingungen des beruflichen Lernens von Lehrkräften und liefern Implikationen für eine passgenaue Fortbildungsplanung.
Empirische Studien und schulische Rechtsvorschriften betonen die Relevanz von Schulleiter*innen für die Schulentwicklung. Auf diese Aufgabe müssen Schulleiter*innen in Aus- und Fortbildungen vorbereitet werden. Der vorliegende Beitrag untersucht in einem längsschnittlichen Design Effekte der Fortbildungsreihe Werkstatt „Schule leiten“. Die Teilnehmer*innen bewerten die Werkstatt zumeist positiv und es zeigen sich geringe bis moderate Veränderungen in ihrem selbstberichteten beruflichen Handeln. Schulleiter*innen mit wenigen Jahren Leitungserfahrung berichten dabei über die größten Zuwächse. Der Beitrag diskutiert Implikationen für die Forschung und Fortbildung von Schulleiter*innen.
Die Forschung zur Lehrerfortbildung weist darauf hin, dass zeitliche Einschränkungen eine Barriere für die Teilnahme an Fortbildungen darstellen. Insbesondere die Unvereinbarkeit der Arbeitszeit mit dem Zeitpunkt des Fortbildungsangebotes wird von Lehrkräften als hinderlich wahrgenommen. Welche zeitlichen Merkmale das Fortbildungsangebot für Lehrkräfte aufweist und ob diese
im Zusammenhang mit der Fortbildungsteilnahme von Lehrkräften stehen, fand bisher wenig Berücksichtigung. Die vorliegende Studie verfolgt daher das Ziel, zeitliche Merkmale des Fortbildungsangebotes für Lehrkräfte zu beschreiben und ihre Vorhersagekraft für die Fortbildungsteilnahme zu untersuchen. Die Daten hierfür stammen aus der elektronischen Datenbankfür Lehrerfortbildungen des Landes Brandenburg im akademischen Jahr 2016/2017. Der Datensatz umfasst 1330 schulexterne Lehrerfortbildungen staatlicher Anbieter. Die Ergebnisse zeigen, dass Dauer und Zeitpunkt einer Fortbildungsveranstaltung prädiktiv für die Teilnahme der Lehrkräfte sind. Die Befunde erweitern damit den Diskurs zu Bedingungen des beruflichen Lernens von
Lehrkräften und liefern Implikationen für eine passgenaue Fortbildungsplanung.
Background: Students' self-concept of ability is an important predictor of their achievement emotions. However, little is known about how learning environments affect these interrelations.
Aims: Referring to Pekrun's control-value theory, this study investigated whether teacher-reported teaching quality at the classroom level would moderate the relation between student-level mathematics self-concept at the beginning of the school year and students' achievement emotions at the middle of the school year.
Sample: Data of 807 ninth and tenth graders (53.4% girls) and their mathematics teachers (58.1% male) were analysed.
Method: Students and teachers completed questionnaires at the beginning of the school year and at the middle of the school year. Multi-level modelling and cross-level interaction analyses were used to examine the longitudinal relations between self-concept, teacher-perceived teaching quality, and achievement emotions as well as potential interaction effects.
Results: Mathematics self-concept significantly and positively related to enjoyment in mathematics and negatively related to anxiety. Teacher-reported structuredness decreased students' anxiety. Mathematics self-concept only had a significant and positive effect on students' enjoyment at high levels of teacher-reported cognitive activation and at high levels of structuredness.
Conclusions: High teaching quality can be seen as a resource that strengthens the positive relations between academic self-concept and positive achievement emotions.
There is no consensus on which statistical model estimates school value-added (VA) most accurately. To date, the two most common statistical models used for the calculation of VA scores are two classical methods: linear regression and multilevel models. These models have the advantage of being relatively transparent and thus understandable for most researchers and practitioners. However, these statistical models are bound to certain assumptions (e.g., linearity) that might limit their prediction accuracy. Machine learning methods, which have yielded spectacular results in numerous fields, may be a valuable alternative to these classical models. Although big data is not new in general, it is relatively new in the realm of social sciences and education. New types of data require new data analytical approaches. Such techniques have already evolved in fields with a long tradition in crunching big data (e.g., gene technology). The objective of the present paper is to competently apply these "imported" techniques to education data, more precisely VA scores, and assess when and how they can extend or replace the classical psychometrics toolbox. The different models include linear and non-linear methods and extend classical models with the most commonly used machine learning methods (i.e., random forest, neural networks, support vector machines, and boosting). We used representative data of 3,026 students in 153 schools who took part in the standardized achievement tests of the Luxembourg School Monitoring Program in grades 1 and 3. Multilevel models outperformed classical linear and polynomial regressions, as well as different machine learning models. However, it could be observed that across all schools, school VA scores from different model types correlated highly. Yet, the percentage of disagreements as compared to multilevel models was not trivial and real-life implications for individual schools may still be dramatic depending on the model type used. Implications of these results and possible ethical concerns regarding the use of machine learning methods for decision-making in education are discussed.