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Teachers' use of evaluation data to improve instruction and its relationship to student achievement
(2017)
In Deutschland stehen Lehrkräften mit Ergebnissen aus Vergleichsarbeiten, zentralen Abschlussprüfungen und internen Evaluationen verschiedene Informationen zur Verfügung. Diese Daten können von ihnen dazu verwendet werden, den eigenen Unterricht zu reflektieren und weiterzuentwickeln. Die Studie geht auf Basis des IQB-Ländervergleichs 2012 den Fragen nach, ob und welche Daten von Lehrkräften zur Unterrichtsentwicklung herangezogen werden und ob datenbasierte Unterrichtsentwicklung mit Schülerleistung zusammenhängt. Die Betrachtung mehrerer Evaluationsverfahren ermöglicht eine kontrastierende Analyse und die Untersuchung einer gemeinsamen Verwendung mehrerer Informationsquellen. Die überwiegende Mehrheit der befragten Lehrkräfte berichtet, Evaluationsergebnisse als Ausgangspunkt zur Unterrichtsentwicklung zu verwenden. Allerdings zeigt sich Heterogenität zwischen einzelnen Unterrichtsentwicklungsaktivitäten und Lehrkräften. Zur Initiierung einzelner Entwicklungsaktivitäten werden auch mehrere Datenquellen simultan herangezogen. Ein direkter signifikanter Zusammenhang zwischen datenbasierter Unterrichtsentwicklung und Schülerleistung kann nicht festgestellt werden. (DIPF/Orig.).
Reflecting in written form on one's teaching enactments has been considered a facilitator for teachers' professional growth in university-based preservice teacher education. Writing a structured reflection can be facilitated through external feedback. However, researchers noted that feedback in preservice teacher education often relies on holistic, rather than more content-based, analytic feedback because educators oftentimes lack resources (e.g., time) to provide more analytic feedback. To overcome this impediment to feedback for written reflection, advances in computer technology can be of use. Hence, this study sought to utilize techniques of natural language processing and machine learning to train a computer-based classifier that classifies preservice physics teachers' written reflections on their teaching enactments in a German university teacher education program. To do so, a reflection model was adapted to physics education. It was then tested to what extent the computer-based classifier could accurately classify the elements of the reflection model in segments of preservice physics teachers' written reflections. Multinomial logistic regression using word count as a predictor was found to yield acceptable average human-computer agreement (F1-score on held-out test dataset of 0.56) so that it might fuel further development towards an automated feedback tool that supplements existing holistic feedback for written reflections with data-based, analytic feedback.
Science education researchers typically face a trade-off between more quantitatively oriented confirmatory testing of hypotheses, or more qualitatively oriented exploration of novel hypotheses. More recently, open-ended, constructed response items were used to combine both approaches and advance assessment of complex science-related skills and competencies. For example, research in assessing science teachers' noticing and attention to classroom events benefitted from more open-ended response formats because teachers can present their own accounts. Then, open-ended responses are typically analyzed with some form of content analysis. However, language is noisy, ambiguous, and unsegmented and thus open-ended, constructed responses are complex to analyze. Uncovering patterns in these responses would benefit from more principled and systematic analysis tools. Consequently, computer-based methods with the help of machine learning and natural language processing were argued to be promising means to enhance assessment of noticing skills with constructed response formats. In particular, pretrained language models recently advanced the study of linguistic phenomena and thus could well advance assessment of complex constructs through constructed response items. This study examines potentials and challenges of a pretrained language model-based clustering approach to assess preservice physics teachers' attention to classroom events as elicited through open-ended written descriptions. It was examined to what extent the clustering approach could identify meaningful patterns in the constructed responses, and in what ways textual organization of the responses could be analyzed with the clusters. Preservice physics teachers (N = 75) were instructed to describe a standardized, video-recorded teaching situation in physics. The clustering approach was used to group related sentences. Results indicate that the pretrained language model-based clustering approach yields well-interpretable, specific, and robust clusters, which could be mapped to physics-specific and more general contents. Furthermore, the clusters facilitate advanced analysis of the textual organization of the constructed responses. Hence, we argue that machine learning and natural language processing provide science education researchers means to combine exploratory capabilities of qualitative research methods with the systematicity of quantitative methods.
This study investigated the role of medium (face-to-face, cyber) and publicity (public, private) in adolescents' perceptions of severity and coping strategies (i.e., avoidant, ignoring, helplessness, social support seeking, retaliation) for victimization, while accounting for gender and cultural values. There were 3432 adolescents (ages 11-15, 49% girls) in this study; they were from China, Cyprus, the Czech Republic, India, Japan, and the United States. Adolescents completed questionnaires on individualism and collectivism, and ratings of coping strategies and severity for public face-to-face victimization, private face-to-face victimization, public cyber victimization, and private cyber victimization. Findings revealed similarities in adolescents' coping strategies based on perceptions of severity, publicity, and medium for some coping strategies (i.e., social support seeking, retaliation) but differential associations for other coping strategies (i.e., avoidance, helplessness, ignoring). The results of this study are important for prevention and intervention efforts because they underscore the importance of teaching effective coping strategies to adolescents, and to consider how perceptions of severity, publicity, and medium might influence the implementation of these coping strategies.