Predicting international students' clinical and academic grades using two language tests (IELTS and C-test): a correlational research study

Academic English tests are used to ascertain if international English as a Second Language nursing students have sufficient language skills to commence their nursing degrees, and later, if they have sufficient English for nursing registration. However, an academic English test may not be appropriate for clinical contexts. This study examines the relationship between two types of English test and the performance of forty-nine undergraduate international nursing students in both their first year of theory-centred academic topics and practice-centred clinical topics. An academic English test, called the International English Language Testing System (IELTS), anda general English proficiency/processing speed test using a variation of the cloze-test (C-test) format were administered at the commencement of the students' course of study. At the end of one year, grade percentages were collected. It was found that both the IELTS test and the C-test were significantly correlated to both types of topic, albeit with different patterns. The two English tests were also tested for similarities in the constructs they measured, with a significant overlap found. The implications are to rethink the way English tests are applied to entry in university degrees involving a clinical component and, by extension, to direct universities to rethink how nursing students are supported during their degree. The question is also raised about the practice of using academic English tests for professional nursing registration purposes. The benefits of the two testing approaches are also considered, particularly the large differences in monetary outlay and time found between the two tests, given their performance in explaining the variance in grade outcomes

Entwicklung einer funktionalisierten Strukturkomponente mit adaptiver Steifigkeit für die Soft-Robotik

Current soft robots mostly lack the stiffness to apply sufficient loads. To ensure inherent safety and load capacity, an adjustable stiffness behavior seems promising. This thesis mainly focusses on the development of a structural component with adjustable stiffness for the realization of new gripper and motion concepts for soft robotics. Therefore, suitable effects and materials are researched and compared based on requirements and defined evaluation criteria. Providing high stiffness ratio, rapid stiffness control and low change in deformation and volume, the vacuum-based particle and layer jamming as well as the electrostatic layer jamming are found to be suitable for detailed investigations. Analytical, structural-mechanical and experimental investigations are made to compare and prioritize the effects regarding their structural and mechanical characteristics. Due to their best suited characteristics, a combination of the two vacuum-based jamming approaches is selected for the development of the structure. From there a structural component with adjustable stiffness, meeting the defined requirements, is developed and experimentally characterized. Mathematical calculations show that the development is not yet fully suitable to be applied in soft robotics. Therefore, appropriate measures for further developments are conceptually derived

Impact of scientific research beyond academia: an alternative classification schema

The actual or anticipated impact of research projects can be documented in scientific publications and project reports. While project reports are available at varying level of accessibility, they might be rarely used or shared outside of academia. Moreover, a connection between outcomes of actual research project and potential secondary use might not be explicated in a project report. This paper outlines two methods for classifying and extracting the impact of publicly funded research projects. The first method is concerned with identifying impact categories and assigning these categories to research projects and their reports by extension by using subject matter experts; not considering the content of research reports. This process resulted in a classification schema that we describe in this paper. With the second method which is still work in progress, impact categories are extracted from the actual text data