Sprachförderkompetenz pädagogischer Fachkräfte

This paper introduces the basics of a (psycho)linguistically-oriented model of language-training competences of educators in pre-school and elementary education. It specifies competence criteria for language intervention based on psycholinguistic research. Ultimately, these criteria will be useful for grounding the additional training of educators and for certifying competences in early language intervention.     

Education in Europe and Muslim Demands for Competitive and Moral Education

International Review of Education - While European education systems fundamentally rest on a rather monolithic world-view, some of them are explicitly oriented towards Christianity and others are...     

Specific managerial human capital,firm age,and venture capital financing of biopharmaceutical ventures: A contingency approach

In this article we investigate how specific human capital in biopharmaceutical ventures' management teams impacts the financial commitment of venture capital investors. Further, we explore how this impact changes with the venture's age. We draw on data from 138 VC financing rounds in the US and Europe to show that biopharmaceutical ventures with greater portions of specific managerial human capital in the fields of management, law, medicine, and biosciences acquire more money in venture capital financing rounds, but this effect is contingent on the age of the venture. We discuss the implications of these findings for the literature on VC financing of high technology ventures.     

Konzeptueller und logischer Data-Warehouse-Entwurf

Zusammenfassung. Im Data-Warehouse-Bereich gibt es sowohl auf der konzeptuellen als auch auf der logischen Ebene unterschiedliche Modellierungsansätze, deren Entwicklung sich in der Regel an typischen Fragestellungen aus dem Bereich des Online Analytical Processing (OLAP) orientierte. Daneben spielen aber auch andere Ansätze zur Analyse der Daten in einem Data Warehouse eine bedeutende Rolle. Ein wichtiger Vertreter ist Data Mining, mit dessen Hilfe bislang unbekannte Muster und Zusammenhänge in Daten identifiziert werden können. Im vorliegenden Artikel wird untersucht, inwieweit sich die in der Literatur vorgeschlagenen konzeptuellen Datenmodelle für ein Data Warehouse eignen, das OLAP- und Data-Mining-Analysen gleichermaßen unterstützt. Hierzu wird das COCOM-Modell, das auf den Modellierungsmöglichkeiten verschiedener publizierter Modelle aufbaut, vorgestellt und bewertet. Für das logische Schema eines Data Warehouse wird häufig ein sogenanntes Star-Schema oder ein Snowflake-Schema erstellt. Für diese und weitere Schematypen wird analysiert, welchen Einfluss die Wahl des logischen Schemas auf Anwendungen aus den Bereichen OLAP und Data Mining hat. Wichtige Kriterien sind hier unter anderem der Informationsgehalt und die Performanz. Insgesamt zeigt dieser Beitrag, dass das COCOM-Modell und das Star-Schema eine gute Grundlage für den integrierten Einsatz von OLAP und Data-Mining bilden.Eingegangen am 30. April 2002, Angenommen am 25. Juni 2003 CR Subject Classification: H.2.1, H.2.7, H.2.8     

Microfluidic system for near-patient extraction and detection of miR-122 microRNA biomarker for drug-induced liver injury diagnostics

Drug-induced liver injury (DILI) results in over 100 000 hospital attendances per year in the UK alone and is a leading cause for the post-marketing withdrawal of new drugs, leading to significant financial losses. MicroRNA-122 (miR-122) has been proposed as a sensitive DILI marker although no commercial applications are available yet. Extracellular blood microRNAs (miRNAs) are promising clinical biomarkers but their measurement at point of care remains time-consuming, technically challenging, and expensive. For circulating miRNA to have an impact on healthcare, a key challenge to overcome is the development of rapid and reliable low-cost sample preparation. There is an acknowledged issue with miRNA stability in the presence of hemolysis and platelet activation, and no solution has been demonstrated for fast and robust extraction at the site of blood draw. Here, we report a novel microfluidic platform for the extraction of circulating miR-122 from blood enabled by a vertical approach and gravity-based bubble mixing. The performance of this disposable cartridge was verified by standard quantitative polymerase chain reaction analysis on extracted miR-122. The cartridge performed equivalently or better than standard bench extraction kits. The extraction cartridge was combined with electrochemical impedance spectroscopy to detect miR-122 as an initial proof-of-concept toward an application in point-of-care detection. This platform enables the standardization of sample preparation and the detection of miRNAs at the point of blood draw and in resource limited settings and could aid the introduction of miRNA-based assays into routine clinical practice.     

Significant vs meaningful differences in the effects of tangible reinforcement on intelligence test achievement and reliability of tmr subjects

The effects of tangible reinforcement on a set of four different intelligence test measures for 72 trainable mentally retarded children was investigated. Performance under a standard and reinforced (M & M) condition, differences in split-half reliability, power estimates, as well as the effect size resulting from treatments, were considered. The Lorge-Thorndike vocabulary, WISC Arithmetic, Picture Arrangement, and Comprehension subtests were administered. Reinforced administration resulted in significantly superior performance on all but the Comprehension test, although magnitude of treatment effects was low. Reliabilities under the reinforced condition were higher for all but the Lorge-Thorndike measures. Confidence bounded effect sizes even at their maximal value did not result in “meaningful” differences in performance, however.     

A Nonlinear Structural Equation Mixture Modeling Approach for Nonnormally Distributed Latent Predictor Variables

Structural equation models with interaction and quadratic effects have become a standard tool for testing nonlinear hypotheses in the social sciences. Most of the current approaches assume normally distributed latent predictor variables. In this article, we describe a nonlinear structural equation mixture approach that integrates the strength of parametric approaches (specification of the nonlinear functional relationship) and the flexibility of semiparametric structural equation mixture approaches for approximating the nonnormality of latent predictor variables. In a comparative simulation study, the advantages of the proposed mixture procedure over contemporary approaches [Latent Moderated Structural Equations approach (LMS) and the extended unconstrained approach] are shown for varying degrees of skewness of the latent predictor variables. Whereas the conventional approaches show either biased parameter estimates or standard errors of the nonlinear effects, the proposed mixture approach provides unbiased estimates and standard errors. We present an empirical example from educational research. Guidelines for applications of the approaches and limitations are discussed.