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Im Zentrum dieses Beitrags stehen Ergebnisse der Messung pädagogischer Kompetenzen Studierender der Theologie, die das Praxissemester in Deutschland absolviert haben. Das bildungswissenschaftliche Wissen, Kompetenzselbsteinschätzungen und ihre Entwicklung sowie die Einschätzung der im Praxissemester erreichten Ziele Studierender werden dabei unter Berücksichtigung der Ausrichtung des Lehramtsstudiums auf eine Schulform betrachtet. Um die Ergebnisse der Messung bildungswissenschaftlichen Wissens und die der Messung von Kompetenzselbsteinschätzungen zu kontextualisieren (N = 304), wird zuerst die Relevanz des (bildungswissenschaftlichen) Wissens als Ausgangspunkt des Könnens herausgearbeitet. Daran anschließend werden Befunde zur schulformspezifischen Professionalisierung resümiert. Anschließend werden Hypothesen hergeleitet, die Anlage der Studie sowie die Testinstrumente vorgestellt, die Ergebnisse präsentiert und diskutiert. Die Ergebnisse zeigen wider Erwarten, dass sich weder das bildungswissenschaftliche Wissen, die Kompetenzselbsteinschätzungen und ihre Entwicklung noch die Einschätzung der im Praxissemester erreichten Ziele angehender Lehrkräfte in Abhängigkeit der Schulformen unterscheiden. Die Diskussion bezieht sich u.a. auf die Struktur der Lehramtsstudiengänge, die Denkfiguren zur Entwicklung von Können und die Konzeption der Messinstrumente.

This article focuses on the analytical competence of teachers, which can be defined as the ability to properly perceive and assess lessons in terms of the effectiveness of pupils' learning. However, learning opportunities for fostering this competence in teacher education can only be justified if the components of this construct are theoretically defined and empirically proven. This was the purpose of two studies on which we report here. The studies were combined to a mixed methods design in which the analytical competence of teachers has been investigated. The data were collected using a quantitative method (standardized test; N = 800) as well as a qualitative method (content analysis of interviews; N = 18). The construct of teachers' analytical competence was defined as having two dimensions: a content and a formal dimension. The content dimension is made up of two factors: pedagogical knowledge and content knowledge. The formal dimension of the construct is defined using different levels as factors of complexity with which teachers can process information relevant for teaching. Both studies provided empirical evidence for the validity of the underlying construct. Based on these results, recommendations for teacher education are given.

This study aimed to examine whether principles of effective teaching constitute essential criteria for a systematic and successful analysis of lessons. After watching a video of a complete lesson, the participants (each of nine experienced and pre-service teachers) were asked to analyse this lesson in terms of effectiveness for pupils' learning in the form of an open dialogue. Their comments were analysed by means of a qualitative content analysis and revealed that the experienced teachers independently used the wide range of principles of effective teaching and differed significantly from the pre-service teachers in this regard. Particularly striking were the large differences in the activation of knowledge about these five principles: goal orientation, relating cognitive activities to prior knowledge, classroom climate/learning atmosphere, clarity, and using appropriate examples. These differences point to specific development tasks, in order to improve the analytical skills of student teachers within teacher education.

We investigated informal workplace learning (IWL) within an under-researched target group: blue-collar workers. IWL is particularly important for these workers because of learning barriers to participation in formal training. Based on meta-analytical conceptualizations and findings, we developed a conceptual framework of antecedents, processes, and learning outcomes of IWL among blue-collar workers (APO framework), following an input-process-output perspective. The results of our structural equation model analysis with N = 702 blue-collar workers from small and medium-sized businesses provided support for seven of eight hypotheses: Personal antecedents, namely "curiosity," "learning goal orientation," and "self-directed learning orientation" were positively related to IWL; organizational antecedents, namely "social support"--containing "supervisor support," "coworker support," and "error-related learning climate"--and, surprisingly, "time pressure" were positively related to IWL; IWL was positively related to three learning outcomes, namely "job involvement," "newly acquired competency," and "organizational citizenship behavior." The findings establish a basis for future longitudinal studies and theory building in workplace learning research, and they provide managers in organizations with guidance to promote IWL.

Due to the high mortality rate, more effective non-invasive diagnostic methods are still needed for lung cancer, the most common cause of cancer-related death worldwide. In this study, the integration of Raman and Fourier-transform infrared spectroscopy with advanced data-fusion techniques is investigated to improve the detection of lung cancer from human blood plasma samples. A high statistical significance was found for important protein-related oscillations, which are crucial for differentiating between lung cancer patients and healthy controls. The use of low-level data fusion and feature selection significantly improved model accuracy and emphasizes the importance of structural protein changes in cancer detection. Although other biomolecules such as carbohydrates and nucleic acids also contributed, proteins proved to be the decisive markers found using this technique. This research highlights the power of these combined spectroscopic methods to develop a non-invasive diagnostic tool for discriminating lung cancer from healthy state, with the potential to extend such studies to a variety of other diseases. [ABSTRACT FROM AUTHOR]

Multivariate analysis applied in biosensing greatly improves analytical performance by extracting relevant information or bypassing confounding factors such as nonlinear responses or experimental errors and noise. Plasmonic sensors based on various light coupling mechanisms have shown impressive performance in biosensing by detecting dielectric changes with high sensitivity. In this study, gold nanodiscs are used as metasurface in a Kretschmann setup, and a variety of features from the reflectance curve are used by machine learning to improve sensing performance. The nanostructures of the metasurface generate new plasmonic features, apart from the typical resonance that occurs in the classical Kretschmann mode of a gold thin film, related to the evanescent field beyond total internal reflection. When the engineered metasurface is integrated into a microfluidic chamber, the device provides additional spectral features generated by Fresnel reflections at all dielectric interfaces. The increased number of features results in greatly improved detection. Here, multivariate analysis enhances analytical sensitivity and sensor resolution by 200% and more than 20%, respectively, and reduces prediction errors by almost 40% compared to a standard plasmonic sensor. The combination of plasmonic metasurfaces and Fresnel reflections thus offers the possibility of improving sensing capabilities even in commonly available setups. [ABSTRACT FROM AUTHOR]

This article reports on the development and testing of a questionnaire that can be used to measure the quasi-experimental attitude (QEA) of teachers. This attitude is reflected in the willingness of teachers to assess and organise their core activities (planning, implementing and analysing lessons) by analogy with experiments in the field of research, in order to gain meaningful experiences from this cyclical process, to evaluate critically these experiences and to draw from them conclusions on how to improve lessons in the future. The sample comprised 512 trainee teachers who had already been teaching independently for 15 months following the conclusion of their university studies. The analysis of the questionnaire showed that the reliability of the scale was satisfactory. Confirmatory factor analyses confirmed the assumption that the quasi-experimental attitude could be modelled in two ways: A first-order model with four intercorrelated factors (meticulous lesson planning, confidence in the predictability of how the lesson will turn out, evidence-based analysis of the lesson and scepticism about mere experience) and a second-order model in which these four factors are loading on the overarching factor QEA. Additionally, the instrument yielded plausible correlations to several validity criteria.

In the current debate on pedagogical content knowledge (PCK), the term is used to refer to the context-specific knowledge that teachers activate when reflecting on practice. Against the background of this debate, we conducted an empirical study and sought to answer the question of which knowledge experts and novices activated in assessing a videotaped lesson in relation to its effectiveness for learning. Our assumption was that the participants activate their PCK as a blending of content knowledge (CK) and pedagogical knowledge (PK) as suggested by Shulman's amalgam thesis. The participants (9 experts and 9 novices) were shown a lesson on optics, in which the law of refraction (Snell's law) was being studied. In a subsequent interview, the participants were asked to analyze the observed lesson. A qualitative and quantitative evaluation of the interviews showed that experts activated both CK and PK intensively and in this respect they differed significantly from novices. Further analysis of the expert statements also proved that they do not activate their CK and PK in isolation, but instead combine both kinds of knowledge together, in line with Shulman's amalgam thesis.

Alzheimer's disease is a progressive neurodegenerative disorder, the early detection of which is crucial for timely intervention and enrollment in clinical trials. However, the preclinical diagnosis of Alzheimer's encounters difficulties with gold-standard methods. The current definitive diagnosis of Alzheimer's still relies on expensive instrumentation and post-mortem histological examinations. Here, we explore label-free Raman spectroscopy with machine learning as an alternative to preclinical Alzheimer's diagnosis. A special feature of this study is the inclusion of patient samples from different cohorts, sampled and measured in different years. To develop reliable classification models, partial least squares discriminant analysis in combination with variable selection methods identified discriminative molecules, including nucleic acids, amino acids, proteins, and carbohydrates such as taurine/hypotaurine and guanine, when applied to Raman spectra taken from dried samples of cerebrospinal fluid. The robustness of the model is remarkable, as the discriminative molecules could be identified in different cohorts and years. A unified model notably classifies preclinical Alzheimer's, which is particularly surprising because of Raman spectroscopy's high sensitivity regarding different measurement conditions. The presented results demonstrate the capability of Raman spectroscopy to detect preclinical Alzheimer's disease for the first time and offer invaluable opportunities for future clinical applications and diagnostic methods. [ABSTRACT FROM AUTHOR]

This article reports the preparation of new mesoporous triazine‐based organic polymers and their characterization. The polymers were synthesized via a nucleophilic condensation reaction between cyanuric chloride and bisphenols or aromatic diamine linkers. As a result, two types of triazine‐based polymers were prepared: triazine‐ether and triazine‐amine polymers. The polymers reveal a mesoporous nature with surface area values ranging between 345 and 1275 m2 g−1 and mesopore volume between 0.273 and 1.03 cm3 g−1. These values were determined from argon gas isotherms at 87 K. The pore size distribution also confirmed the micro–mesoporosity, which reached up to 3.0 nm for all polymers. The triazine‐amine polymer shows good thermal oxidative stability up to 450 °C. Motivated by the mesopore size, the new polymers were also employed as palladium nanoparticle supports. The X‐ray diffraction technique indicated the successful incorporation of palladium nanoparticles, and Fourier transform infrared measurements proved that the framework of the polymers was retained after forming palladium supports. To ensure the catalytic reactivity of palladium nanoparticles, we employed one example as a catalyst in a Suzuki coupling reaction. The catalyst exhibited remarkable recyclability, maintaining catalytic efficiency through seven cycles, thereby enabling the use of palladium‐loaded triazine‐based polymeric catalysts in a variety of organic reactions in future. © 2023 Society of Industrial Chemistry. [ABSTRACT FROM AUTHOR]

Temperature‐modulated colloidal phase of plasmonic nanoparticles is a convenient playground for resettable soft‐actuators or colorimetric sensors. To render reversible clustering under temperature change, bulky ligands are required, especially if anisotropic morphologies are of interest. This study showcases thermoresponsive gold nanorods by employing small surface ligands, bis (p‐sulfonatophenyl) phenyl‐phosphine dihydrate dipotassium salt (BSPP) and native cationic surfactant. Temperature‐dependent analysis in real‐time allowed to describe the structural features (interparticle distance and cluster size) as well as thermal parameters, melting and freezing temperatures. These findings suggest that neither covalent Au−S bonds nor bulky ligands are required to obtain a robust thermoresponsive system based on anisotropic gold nanoparticles, paving the way to stimuli‐responsive nanoparticles with a wide range of sizes and geometries. [ABSTRACT FROM AUTHOR]