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The purpose of the present study was to examine the moderation of parental mediation in the longitudinal association between being a bystander of cyberbullying and cyberbullying perpetration and cyberbullying victimization. Participants were 1067 7th and 8th graders between 12 and 15 years old (51% female) from six middle schools in predominantly middle-class neighborhoods in the Midwestern United States. Increases in being bystanders of cyberbullying was related positively to restrictive and instructive parental mediation. Restrictive parental mediation was related positively to Time 2 (T2) cyberbullying victimization, while instructive parental mediation was negatively related to T2 cyberbullying perpetration and victimization. Restrictive parental mediation was a moderator in the association between bystanders of cyberbullying and T2 cyberbullying victimization. Increases in restrictive parental mediation strengthened the positive relationship between these variables. In addition, instructive mediation moderated the association between bystanders of cyberbullying and T2 cyberbullying victimization such that increases in this form of parental mediation strategy weakened the association between bystanders of cyberbullying and T2 cyberbullying victimization. The current findings indicate a need for parents to be aware of how they can impact adolescents’ involvement in cyberbullying as bullies and victims. In addition, greater attention should be given to developing parental intervention programs that focus on the role of parents in helping to mitigate adolescents’ likelihood of cyberbullying involvement.
Der Einstieg in die berufliche Praxis ist für Lehramtsstudierende verbunden mit einer Vielzahl von Anforderungen. Selbstwirksamkeitserwartungen gelten als personenbezogene Ressource, um mit den vielfältigen Anforderungssituationen umzugehen. Die soziale Unterstützung durch Mentoring gilt demgegenüber als wichtige umgebungsbezogene Ressource. Ressourcen sind von hoher Bedeutung, um Belastungen beim Berufseinstieg zu bewältigen. Allerdings ist bislang wenig bekannt über das Zusammenwirken zwischen personen- und umgebungsbezogenen Ressourcen. Die vorliegende längsschnittliche Studie untersucht daher, welche Rolle Mentoring und Selbstwirksamkeitserwartungen für den Umgang mit Beanspruchungsfolgen im Praxissemester spielen. Des Weiteren wird untersucht, inwiefern Mentoring den Zusammenhang zwischen Selbstwirksamkeitserwartungen und negativen Beanspruchungsfolgen, in diesem Fall emotionaler Erschöpfung und reduzierter Leistungsfähigkeit, moderiert. Die empirische Grundlage der Untersuchung sind Fragebogendaten von 192 Lehramtsstudierenden, die zu Beginn und zum Ende ihres viermonatigen Praxissemesters befragt wurden. Multiple Regressionsanalysen zeigen, dass hohe Selbstwirksamkeitserwartungen zu Beginn des Praxissemesters mit geringerer emotionaler Erschöpfung sowie mit höherer Leistungsfähigkeit zum Ende des Praxissemesters einhergehen. Der Zusammenhang zwischen den Selbstwirksamkeitserwartungen und der Leistungsfähigkeit wird durch die von den Lehramtsstudierenden wahrgenommene soziale Unterstützung durch Mentoring moderiert. Die Implikationen der Ergebnisse für die Lehrkräftebildung werden diskutiert.
Value-added (VA) modeling can be used to quantify teacher and school effectiveness by estimating the effect of pedagogical actions on students’ achievement. It is gaining increasing importance in educational evaluation, teacher accountability, and high-stakes decisions. We analyzed 370 empirical studies on VA modeling, focusing on modeling and methodological issues to identify key factors for improvement. The studies stemmed from 26 countries (68% from the USA). Most studies applied linear regression or multilevel models. Most studies (i.e., 85%) included prior achievement as a covariate, but only 2% included noncognitive predictors of achievement (e.g., personality or affective student variables). Fifty-five percent of the studies did not apply statistical adjustments (e.g., shrinkage) to increase precision in effectiveness estimates, and 88% included no model diagnostics. We conclude that research on VA modeling can be significantly enhanced regarding the inclusion of covariates, model adjustment and diagnostics, and the clarity and transparency of reporting.
What is the added value from attending a certain school or being taught by a certain teacher? To answer this question, the value-added (VA) model was developed. In this model, the actual achievement attained by students attending a certain school or being taught by a certain teacher is juxtaposed with the achievement that is expected for students with the same background characteristics (e.g., pretest scores). To this end, the VA model can be used to compute a VA score for each school or teacher, respectively. If actual achievement is better than expected achievement, there is a positive effect (i.e., a positive VA score) of attending a certain school or being taught by a certain teacher. In other words, VA models have been developed to “make fair comparisons of the academic progress of pupils in different settings” (Tymms 1999, p. 27). Their aim is to operationalize teacher or school effectiveness objectively. Specifically, VA models are often used for accountability purposes and high-stakes decisions (e.g., to allocate financial or personal resources to schools or even to decide which teachers should be promoted or discharged). Consequently, VA modeling is a highly political topic, especially in the USA, where many states have implemented VA or VA-based models for teacher evaluation (Amrein-Beardsley and Holloway 2017; Kurtz 2018). However, this use for high-stakes decisions is highly controversial and researchers seem to disagree concerning the question if VA scores should be used for decision-making (Goldhaber 2015). For a more exhaustive discussion of the use of VA models for accountability reasons, see, for example, Scherrer (2011).
Given the far-reaching impact of VA scores, it is surprising that there is scarcity of systematic reviews of how VA scores are computed, evaluated, and how this research is reported. To this end, we review 370 empirical studies from 26 countries to rigorously examine several key issues in VA modeling, involving (a) the statistical model (e.g., linear regression, multilevel model) that is used, (b) model diagnostics and reported statistical parameters that are used to evaluate the quality of the VA model, (c) the statistical adjustments that are made to overcome methodological challenges (e.g., measurement error of the outcome variables), and (d) the covariates (e.g., pretest scores, students’ sociodemographic background) that are used when estimating expected achievement.
All this information is critical for meeting the transparency standards defined by the American Educational Research Association (AERA 2006). Transparency is vital for educational research in general and especially for highly consequential research, such as VA modeling. First, transparency is highly relevant for researchers. The clearer the description of the model, the easier it is to build upon the knowledge of previous research and to safeguard the potential for replicating previous results. Second, because decisions that are based on VA scores affect teachers’ lives and schools’ futures, not only educational agents but also the general public should be able to comprehend how these scores are calculated to allow for public scrutiny. Specifically, given that VA scores can have devastating consequences on teachers’ lives and on the students they teach, transparency is particularly important to evaluate the chosen methodology to compute VA models for a certain purpose. Such evaluations are essential to answer the question to what extent the quality of VA scores allows to base far-reaching decisions on these scores for accountability purposes.
Qualitative Forschung leistet mit einem differenzierten Methodenrepertoire einen zentralen Beitrag zur Empirie in der Erziehungswissenschaft. Das Handbuch führt umfassend in das breite Spektrum qualitativer Forschungszugänge ein.
Der erste Teil bietet eine grundlegende Einführung in qualitative Forschung, reflektiert ihre Bedeutung und Erkenntnispotentiale, zeichnet historische Entwicklungen nach und legt theoretische Grundlagen dar. Der zweite Teil stellt die wichtigsten methodischen Forschungskonzeptionen qualitativer erziehungswissenschaftlicher Forschung vor. Der dritte Teil führt in Strategien für Erhebungen und Auswertungen ein. Die Aufsätze des vierten Teils widmen sich dem forschenden Umgang mit visuellen Quellen und Medien. Der fünfte Teil stellt eine Auswahl gegenstandsbezogener qualitativer Forschungsansätze vor. Abschließend folgen Ansätze der Praxis-, Aktions- und Handlungsforschung und nützliche Informationen und Hinweise für die Planung und Durchführung von Forschungsvorhaben.
Das Handbuch richtet sich an Promovierende, Forschende, Lehrende und Studierende in den Erziehungs- und Sozialwissenschaften. Es bietet Pädagoginnen und Pädagogen Informationen über Methoden systematischer Praxisforschung und trägt damit zur Stärkung und Innovation qualitativer Forschungszugänge und zur Weiterentwicklung der methodischen Standards bei.
Forschende Lernwerkstatt
(2013)