L. Darling-Hammond, Deborah J. Holtzman, Su Jin Gatlin
et al.
Recent debates about the utility of teacher education have raised questions about whether certified teachers are, in general, more effective than those who have not met the testing and training requirements for certification, and whether some candidates with strong liberal arts backgrounds might be at least as effective as teacher education graduates. This study examines these questions with a large student-level data set from Houston, Texas that links student characteristics and achievement with data about their teachers' certification status, experience, and degree levels from 1995-2002. The data set also allows an examination of whether Teach for America (TFA) candidates-recruits from selective universities who receive a few weeks of training before they begin teaching-are as effective as similarly experienced certified teachers. In a series of regression analyses looking at 4th and 5th grade student achievement gains on six different reading and mathematics tests over a six-year period, we find that certified teachers consistently produce stronger student achievement gains than do uncertified teachers. These findings hold for TFA recruits as well as others. Controlling for teacher experience, degrees, and student characteristics, uncertified TFA recruits are less effective than certified teachers, and perform about as well as other uncertified teachers. TFA recruits who become certified after 2 or 3 years do about as well as other certified teachers in supporting student achievement gains; however, nearly all of them leave within three years. Teachers' effectiveness appears strongly related to the preparation they have received for teaching.
Abstract This integrative review examines 44 published articles (empirical, descriptive, and pedagogical frameworks) on the topic of STEAM (Science, Technology, Engineering, Arts, Mathematics) education from 2007 to 2018. Despite the emergence of STEAM as a popular pedagogical approach for enhancing students’ creativity, problem-solving skills, and interest in STEM fields, the definitions and purposes of STEAM education remain ubiquitous. Therefore, the review examined descriptions of the overall purpose of STEAM education, definitions of the STEAM acronym and the ‘A’ in STEAM, creativity as a learning outcome, elements of arts education, and arts education learning outcomes. The review found a myriad of definitions of the STEAM concept in general, a variety of interpretations for the “A” in STEAM, and an overall lack of reported learning outcomes in the areas of creativity, problem-solving, and arts education. The articles also differentiate in methods for merging STEAM disciplines, described in one of five ways: transdisciplinary, interdisciplinary, multi-disciplinary, cross-disciplinary, and arts-integration. Recommendations are provided to advance both research and practice in STEAM education.
Leonard Nürnberg, Dennis Bontempi, Suraj Pai
et al.
Artificial intelligence (AI) has the potential to transform medical imaging by automating image analysis and accelerating clinical research. However, research and clinical use are limited by the wide variety of AI implementations and architectures, inconsistent documentation, and reproducibility issues. Here, we introduce MHub$.$ai, an open-source, container-based platform that standardizes access to AI models with minimal configuration, promoting accessibility and reproducibility in medical imaging. MHub$.$ai packages models from peer-reviewed publications into standardized containers that support direct processing of DICOM and other formats, provide a unified application interface, and embed structured metadata. Each model is accompanied by publicly available reference data that can be used to confirm model operation. MHub$.$ai includes an initial set of state-of-the-art segmentation, prediction, and feature extraction models for different modalities. The modular framework enables adaptation of any model and supports community contributions. We demonstrate the utility of the platform in a clinical use case through comparative evaluation of lung segmentation models. To further strengthen transparency and reproducibility, we publicly release the generated segmentations and evaluation metrics and provide interactive dashboards that allow readers to inspect individual cases and reproduce or extend our analysis. By simplifying model use, MHub$.$ai enables side-by-side benchmarking with identical execution commands and standardized outputs, and lowers the barrier to clinical translation.
María Guadalupe Valladares González, Giselda Emérita Hernández
El trabajo aborda una visión crítica de las autoras sobre el viaje cognitivo realizado por la maestranda Libety Martínez en la Universidad de las Artes de Cuba. Desde una perspectiva de distanciamiento se analiza el camino identitario recorrido por ésta, (Martínez/2024) para corregir limitaciones y normalizaciones impuestas por la comunidad científica en la antedicha universidad basadas en epistemocentrismos y etnocentrismos disciplinares. Este trabajo va a los estratos más remotos de estas construcciones investigativas que responden en alguna medida a relaciones de poder.
This Special Issue of <i>ARTS</i> allocates considerable scholarly and analytical attention to the intricate exploration of performative traditions of experimentation within the Russian and Soviet milieus [...]
Diffusion models are currently the leading generative AI approach used for image generation in e.g. DALL-E and Stable Diffusion. In this talk we relate diffusion models to stochastic quantisation in field theory and employ it to generate configurations for scalar fields on a two-dimensional lattice. We end with some speculations on possible applications.
Résumé : Analyser les travaux scientifiques est une tache aussi ardue que difficile qui demande beaucoup de munitie. Cet article fait une analyse bibliométrique des mémoires de licence (Bac+5) défendus au sein du Département des Sciences et techniques Documentaires de l'Université de Kinshasa de 2014 à 2018. Les travaux produits par des universités sont de plus en plus oubliés par les autorités. Jeune qu’il soit le Département des Sciences et techniques Documentaires est parmi les rares départements que l’on retrouve dans des universités et facultés congolaises et il organise des études sur les archives, la bibliothèque et l’Edition.
Mots-clés : Analyse, bibliologie, bibliometrie, memoire, Sciences et Techniques documentaires.
Arts in general, Computational linguistics. Natural language processing
Keno K. Bressem, Jens-Michalis Papaioannou, Paul Grundmann
et al.
This paper presents medBERTde, a pre-trained German BERT model specifically designed for the German medical domain. The model has been trained on a large corpus of 4.7 Million German medical documents and has been shown to achieve new state-of-the-art performance on eight different medical benchmarks covering a wide range of disciplines and medical document types. In addition to evaluating the overall performance of the model, this paper also conducts a more in-depth analysis of its capabilities. We investigate the impact of data deduplication on the model's performance, as well as the potential benefits of using more efficient tokenization methods. Our results indicate that domain-specific models such as medBERTde are particularly useful for longer texts, and that deduplication of training data does not necessarily lead to improved performance. Furthermore, we found that efficient tokenization plays only a minor role in improving model performance, and attribute most of the improved performance to the large amount of training data. To encourage further research, the pre-trained model weights and new benchmarks based on radiological data are made publicly available for use by the scientific community.
The hitting set problem is a well-known NP-hard optimization problem in which, given a set of elements and a collection of subsets, the goal is to find the smallest selection of elements, such that each subset contains at least one element in the selection. Many geometric set systems enjoy improved approximation ratios, which have recently been shown to be tight with respect to the shallow cell complexity of the set system. The algorithms that exploit the cell complexity, however, tend to be involved and computationally intensive. This paper shows that a slightly improved asymptotic approximation ratio for the hitting set problem can be attained using a much simpler algorithm: solve the linear programming relaxation, take one initial random sample from the set of elements with probabilities proportional to the LP-solution, and, while there is an unhit set, take an additional sample from it proportional to the LP-solution. Our algorithm is a simple generalization of the elegant net-finder algorithm by Nabil Mustafa. To analyze this algorithm for the hitting set problem, we generalize the classic Packing Lemma, and the more recent Shallow Packing Lemma, to the setting of weighted epsilon-nets.
We consider the problem of fairly allocating the cost of providing a service among a set of users, where the service cost is formulated by an NP-hard {\it covering integer program (CIP)}. The central issue is to determine a cost allocation to each user that, in total, recovers as much as possible of the actual cost while satisfying a stabilizing condition known as the {\it core property}. The ratio between the total service cost and the cost recovered from users has been studied previously, with seminal papers of Deng, Ibaraki, \& Nagomochi and Goemans \& Skutella linking this {\it price-of-fair-sharing} to the integrality gap of an associated LP relaxation. Motivated by an application of cost allocation for network design for LPWANs, an emerging IoT technology, we investigate a general class of CIPs and give the first non-trivial price-of-fair-sharing bounds by using the natural LP relaxation strengthened with knapsack-cover inequalities. Furthermore, we demonstrate that these LP-based methods outperform previously known methods on an LPWAN-derived CIP data set. We also obtain analogous results for a more general setting in which the service provider also gets to select the subset of users, and the mechanism to elicit users' private utilities should be group-strategyproof. The key to obtaining this result is a simplified and improved analysis for a cross-monotone cost-allocation mechanism.
تتبنى هذه الدراسة مفهوم الانتقائية في نظرية هاليداي لاظهار طريقة عرض المعلومات المطروحة في العناوين الصحفية في الصحف الاجنبية وخصوصا ما يتعلق بموضوع الهجمات الاخيرة على غزة من قبل القوات الاسرائيلية في فلسطين. تسعى هذه الدراسة لاظهار طرق تمثيل الخبر في الصحف الاجنبية بما يتعلق بالصراع الفلسطيني-الاسرائيلي. المعلومات التي تم تحليلها بهذه الدراسة تم جمعها من عناوين صحيفة نيويورك تايمز المنشورة في الفترة من 13الى 17 ايار لعام 2021 وهي فترة الهجمات على غزة.
History of scholarship and learning. The humanities, Arts in general
This paper looks at the polyphonic analysis of Moroccan caricature in the context of the Covid-19 pandemic. It highlights the importance of the image as an information tool within an area of multiple communication. As a form of visual expression, caricature aims to convey information concisely and persuasively, while reflecting the perspective of its creator. The present study sets out to understand caricature by adopting a linguistic approach and focusing specifically on the analysis of linguistic polyphony in Moroccan caricatures related to the global health crisis. This approach adopts Ducrot's enunciative theory as an analytical framework. Based on Imad Sanouni's caricatures addressing this theme, the present analysis highlights the diversity of voices and perspectives within a caricatural image image, faithfully illustrating the crisis experienced by Moroccan society during the pandemic. Results show that these drawings faithfully reflect this epidemiological period through the means of iconographic and linguistic codes to create layers of meaning and discourse. By combining visual and linguistic elements, this study demonstrates that caricature could constitute a polyphonic means of visual communication, contributing
Résumé : Cet article présente une étude scientifique sur la linguistique et la didactique. Les deux domaines sont considérés comme un pilier essentiel en classe du français langue étrangère. La présente étude concerne précisément la compréhension orale, étant une compétence primordiale de la communication orale, car l'apprenant est naturellement exposé à l'écoute de la langue avant de la produire. Sur la base de cette logique, mener une enquête auprès d'un groupe d'élèves du secondaire qualifiant marocain en vue d’identifier les erreurs liées à une telle compétence et leur origine, reste la première étape didactique pour concevoir des dispositifs pédagogiques dans les futurs projets de recherche sur le même sujet. Cette recherche porte également sur l'analyse de certaines erreurs de compréhension orale recueillies à partir de l'enquête déjà citée ; cette analyse est basée sur des cadres contextuel, épistémologique et théorique qui régissent la compréhension orale et l'analyse de l'erreur.
Mots-clés : didactique, FLE, erreur, compétence grammaticale, compréhension orale.
Arts in general, Computational linguistics. Natural language processing
This study used the Q-methodology to categorize and examine the characteristics of pre-service teachers' perceptions of the writing course called ‘Creative Writing,’ a liberal arts writing course at K University, in order to identify the types of class perceptions of students in the Korean Language Education Department and the English Language Education Department.Based on the results of previous studies, a Q-sample was constructed and reviewed by 33 experts. The sample involved in-depth interviews with students, as well as questionnaires related to university liberal arts writing courses. 28 students of ‘Creative Writing’ were selected as a P-sample and analyzed using PQ method 2.35, and the results of the study were interpreted based on strong positive, strong negative, and identification questions in order to derive five types of perceptions related to creative writing. The fourth type of writer is the “discovery writer,” who has discovered the joy of writing itself. The fifth category is “collaborative writing strategy discovery,” where students are intrigued by the collaborative process and discover different strategies for good writing.It is hoped that these findings will serve as a foundation for the development and improvement of college liberal arts writing courses and as a way to increase the awareness of pre-service teachers when it comes to writing instruction.