What Works in School? Expert and Novice Teachers’ Beliefs about School Effectiveness

In 2009, John Hattie first published his extensive metasynthesis concerning determinants of student achievement. It provides an answer to the question: “What works in school?” The present study examines how this question is answered by pre- and in-service teachers, how their beliefs correspond to the current state of research and whether they differ according to the teachers' level of expertise. Thus, it takes on a novel approach as it draws on data from two sources in the field of education -- empirical research and teachers’ beliefs -- and examines their similarities and differences. The teachers’ beliefs were elicited by asking N = 729 participants to estimate the effect sizes of several determinants of student achievement. Those were compared to the empirical effect sizes found by Hattie (2009). Profile correlations showed that expert teachers’ beliefs are more congruent with current research findings than those of novice teachers. We further examined where expert and novice teachers’ beliefs differ substantially from each other by using confirmatory factor analysis (CFA) and comparing group means in latent variables. Our findings suggest that teachers’ beliefs about school effectiveness are related to professional experience: Expert teachers showed a stronger overall congruence with empirical evidence, scoring higher in achievement-related variables and lower in variables concerning surface- and infrastructural conditions of schooling as well as student-internal factors. Results are discussed with regard to teacher-education practices that emphasize research findings and challenge existing beliefs of (prospective) teachers

Investigation of ion-ion-recombination at atmospheric pressure with a pulsed electron gun

For future development of simple miniaturized sensors based on pulsed atmospheric pressure ionization as known from ion mobility spectrometry, we investigated the reaction kinetics of ion-ion-recombination to establish selective ion suppression as an easy to apply separation technique for otherwise non-selective ion detectors. Therefore, the recombination rates of different positive ion species, such as protonated water clusters H +(H 2O) n (positive reactant ions), acetone, ammonia and dimethyl-methylphosphonate ions, all recombining with negative oxygen clusters O 2 -(H 2O) n (negative reactant ions) in a field-free reaction region, are measured and compared. For all experiments, we use a drift tube ion mobility spectrometer equipped with a non-radioactive electron gun for pulsed atmospheric pressure ionization of the analytes. Both, ionization and recombination times are controlled by the duty cycle and repetition rate of the electron emission from the electron gun. Thus, it is possible to investigate the ion loss caused by ion-ion-recombination depending on the recombination time defined as the time delay between the end of the electron emission and the ion injection into the drift tube. Furthermore, the effect of the initial total ion density in the reaction region on the ion-ion-recombination rate is investigated by varying the density of the emitted electrons. © 2012 The Royal Society of Chemistry

Are students in teacher training interested in educational-scientific contents? A longitudinal study covering the first four semesters

Lehramtsstudierende interessieren sich zu Beginn ihres Studiums häufig stark für pädagogische Inhalte. Ob dieses hohe Interesse allerdings im Studienverlauf stabil ist, wurde bisher unzureichend empirisch untersucht. In der vorliegenden Studie wurde an N = 1169 Lehramtsstudierenden überprüft, wie sich das Interesse an bildungswissenschaftlichen Inhalten über vier Semester entwickelt. Zusätzlich wurden Eingangsmerkmale der Studierenden als Prädiktoren zur Erklärung interindividueller Unterschiede einbezogen. Ein zentrales Ergebnis latenter Wachstumskurvenmodelle ist, dass das Interesse an den Bildungswissenschaften zwar im Mittel über die Zeit stabil bleibt, sich aber bedeutsame Varianz im Veränderungswert zeigt. Diese kann durch die Sicherheit der Studienwahl und das angestrebte Lehramt erklärt werden, und zwar in die Richtung, dass Studierende mit hoher Entscheidungssicherheit sowie Studierende eines gymnasialen Lehramts tendenziell an Interesse dazugewinnen. (DIPF/Orig.)At the beginning of their studies, students in teacher training are often strongly interested in pedagogical contents. However, whether this strong interest remains stable throughout the course of studies has as yet hardly been examined empirically. On the basis of a sample of N = 1169 students enrolled in teacher training, the present study investigates how the interest in educational-scientific contents develops over a period of four semesters. In addition, enrollment characteristics of students are included as predictors for the explanation of inter-individual differences. A key result of latent growth curve models is that, on average, the interest in educational sciences remains stable over time, however, significant variance is revealed in the change value. This can be explained by the certainty of the choice of studies and the type of teaching post aimed at, namely, it can be shown that students who are to a high degree sure that they made the right choice and students choosing an academic track program tend to build up interest. (DIPF/Orig.

Das Kartenforum Sachsen: Innovativer Zugriff auf raumbezogene grafische Informationen

Historische Länderkarten, Stadtpläne und - ansichten gehören zu den wertvollsten Beständen großer europäischer Bibliotheken. Mit ihrer rund 167.000 Einzelblätter umfassenden, bis in das 16. Jh. zurückreichenden Kartensammlung besitzt die Sächsische Landesbibliothek -Staats- und Universitätsbibliothek Dresden (SLUB) eine der größten und wichtigsten Sammlungen dieser Art in Deutschland

A compact high resolution ion mobility spectrometer for fast trace gas analysis

Drift tube ion mobility spectrometers (IMS) are widely used for fast trace gas detection in air, but portable compact systems are typically very limited in their resolving power. Decreasing the initial ion packet width improves the resolution, but is generally associated with a reduced signal-to-noise-ratio (SNR) due to the lower number of ions injected into the drift region. In this paper, we present a refined theory of IMS operation which employs a combined approach for the analysis of the ion drift and the subsequent amplification to predict both the resolution and the SNR of the measured ion current peak. This theoretical analysis shows that the SNR is not a function of the initial ion packet width, meaning that compact drift tube IMS with both very high resolution and extremely low limits of detection can be designed. Based on these implications, an optimized combination of a compact drift tube with a length of just 10 cm and a transimpedance amplifier has been constructed with a resolution of 183 measured for the positive reactant ion peak (RIP+), which is sufficient to e.g. separate the RIP+ from the protonated acetone monomer, even though their drift times only differ by a factor of 1.007. Furthermore, the limits of detection (LODs) for acetone are 180 ppt(v) within 1 s of averaging time and 580 pptv within only 100 ms

Turnover of grassland roots in mountain ecosystems revealed by their radiocarbon signature: role of temperature and management

Root turnover is an important carbon flux component in grassland ecosystems because it replenishes substantial parts of carbon lost from soil via heterotrophic respiration and leaching. Among the various methods to estimate root turnover, the root’s radiocarbon signature has rarely been applied to grassland soils previously, although the value of this approach is known from studies in forest soils. In this paper, we utilize the root’s radiocarbon signatures, at 25 plots, in mountain grasslands of the montane to alpine zone of Europe.We place the results in context of a global data base on root turnover and discuss driving factors. Root turnover rates were similar to those of a subsample of the global data, comprising a similar temperature range, but measured with different approaches, indicating that the radiocarbon method gives reliable, plausible and comparable results. Root turnover rates (0.06–1.0 y-1) scaled significantly and exponentially with mean annual temperatures. Root turnover rates indicated no trend with soil depth. The temperature sensitivity was significantly higher in mountain grassland, compared to the global data set, suggesting additional factors influencing root turnover. Information on management intensity from the 25 plots reveals that root turnover may be accelerated under intensive and moderate management compared to low intensity or semi-natural conditions. Because management intensity, in the studied ecosystems, co-varied with temperature, estimates on root turnover, based on mean annual temperature alone, may be biased. A greater recognition of management as a driver for root dynamics is warranted when effects of climatic change on belowground carbon dynamics are studied in mountain grasslands.KB received support from the Swiss National Science Foundation, project 200021-115891 (www.snf.ch). SM received support from the Swiss State Secretariat for Education and Research, project C07.0031 (www.sbfi.admin.ch). MTS received support from the Spanish Ministry of Science and Innovation, (project CAPAS, CGL2010-22378-C03- 01) (www.idi.mineco.gob.es)

Implementation and Validation of non-semantic Out-of-Distribution Detection on Image Data in Manufacturing

Small changes in the production environment can have a negative impact on the performance of machine learning models. This study investigates the feasibility of various methods for detecting non-semantic Out-of-Distribution (OOD) cases in input images, which could be caused by hardware-side malfunctions, such as a defective camera flash. For this purpose, we design four experiments based on a real-world computer vision use case to simulate hardware problems that may occur in manufacturing and verify the performance of the various methods for detecting OOD cases. Furthermore, we explore the optimal sample size of input data to ensure that OOD cases can be found efficiently and successfully. The experimental results show that the tested methods can effectively and correctly detect the presence of non-semantic OOD data. The next step is to focus on securing ML models to identify malignant OOD cases, which negatively affects the performance of deep learning models