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The paper at hand describes how a regional university of applied sciences tried to internationalize its learning and teaching environment. It describes the challenges encountered, the managerial approach taken, illustrates the implemented initiatives, and how effective they turned out. The results might be relevant to faculty staff in managerial positions at regional universities all over the world that face the challenge to internationalize their teaching and learning environment for the benefit of their domestic students.
The Exoplanet Imaging Data Challenge is a community-wide effort meant to offer a platform for a fair and common comparison of image processing methods designed for exoplanet direct detection. For this purpose, it gathers on a dedicated repository (Zenodo), data from several high-contrast ground-based instruments worldwide in which we injected synthetic planetary signals. The data challenge is hosted on the CodaLab competition platform, where participants can upload their results. The specifications of the data challenge are published on our website https://exoplanet-imaging-challenge.github.io/. The first phase, launched on the 1st of September 2019 and closed on the 1st of October 2020, consisted in detecting point sources in two types of common data-set in the field of high-contrast imaging: data taken in pupil-tracking mode at one wavelength (subchallenge 1, also referred to as ADI) and multispectral data taken in pupil-tracking mode (subchallenge 2, also referred to as ADI+mSDI). In this paper, we describe the approach, organisational lessons-learnt and current limitations of the data challenge, as well as preliminary results of the participants’ submissions for this first phase. In the future, we plan to provide permanent access to the standard library of data sets and metrics, in order to guide the validation and support the publications of innovative image processing algorithms dedicated to high-contrast imaging of planetary systems.
Due to the various demands for lecturers, there is only a limited time to prepare lectures and lab courses. Therefore, it is necessary to invest the time target-oriented for optimal student learning success. A theoretic model is developed to structure course preparation work regarding scientific content, didactic preparation, and course presentation. Model parameters have to be chosen for each course depending on topic complexity, the lecturer’s prior knowledge, and the already available preparation from the prior semesters. With these parameters, a course preparation model for a complete semester is developed. Analytic models for different optimization strategies are introduced according to the overall goal of the lecturer. Numerical optimization is done to find the appropriate course preparation times to reach an optimal course preparation for high student learning success. It is seen that due to the different optimization strategies, the preparation time results vary and no single truth is given. But this optimization system gives hints on how to invest preparation time target-oriented for high student learning success.
Ethical, intercultural and professional impulses integrated into a transmission systems lecture
(2017)
In the sixth semester of the bachelor study course “Electrical Engineering and Information Technology”, a lecture “Transmission Systems” is given. It explains basic principles, circuits and systems of electrical and optical transmission systems. Short intellectual impulses, which address professional, intercultural and ethical issues of engineers' working life are integrated into this regular lecture. In each lecture unit, an impulse with one specific topic is given approximately in the middle of the lecture hour. An evaluation was done at the end of the semester, which shows that most of the students remember the discussed topics and state high interest due to high importance for their professional life. Due to these encouraging results, this concept will be developed further.
This article describes a contactless fiber-optic position sensor. It comprises a Polymer Optical Fiber that is grinded to form a D-shaped cross-section with an exposed fiber core. This sensor has two photodiodes at both fiber ends to measure the emitted light intensity. Light is coupled using a red LED at the side face into the exposed core of the fiber at a defined position. The position of the LED at the length of the fiber is measured by calculating the optical power quotient measured by both photodiodes. To test this sensor, Polymer Optical Fibers with different side surface roughness are produced and qualified. Measurements show that the optical power quotient is reproducible and nearly linear over the length of the fiber. It is also seen that the fiber attenuation increases when grinding the fiber side-face with rougher sandpaper. Position measurements show an absolute position error of this sensor in the range of a few millimeters. Microscope images show surface defects along the polished side face of the fiber that are expected to lead to a nonuniform attenuation along the fiber and cause the position errors. Overall, it is proven that this sensor principle works as a contactless low-cost position sensor for short distances with an absolute position standard deviation error lower than 1 mm.
During recent years, there has been a trend to replace traditional lab courses by project-based learning activities. However, there is currently little scientific evidence for educational improvements through such changes. Some years ago, a lab course on electrical measurements in our bachelor Electrical Engineering and Information Technology was modified from single experiments to projects. This change led to a significant increase in the necessary manpower and lab costs. To justify these higher efforts, it is important to investigate if the learning success increased. We carried out the surveys and collected the statistical data from the students who attended this course. In order to see if the students appreciated this lab course and if there was an objective increase of the students' knowledge, these results were evaluated. Evaluation of the grades in the lecture and lab courses shows that the increase of the students' theoretical and practical knowledge is statistically significant.
During a student project a stratosphere balloon was developed and launched. This project included the definition of the balloon parameters and the scientific instruments for performing atmospheric measurements, the development of all mechanical and electronic parts, the administration of the project as well as the management tasks related to the balloon launch. The main challenge for the students was the high complexity of the project due to tasks involving many different knowledge domains and the long project duration from the initial definition to the launch.
Analysis and Improvement of Engineering Exams Toward Competence Orientation by Using an AI Chatbot
(2024)
ChatGPT is currently one of the most advanced general chatbots. This development leads to diverse challenges in higher education, like new forms of teaching and learning, additional exam methods, new possibilities for plagiarism, and many more topics. On the other side with the development of advanced AI tools, pure knowledge will be less and less important, and demands from industry will change toward graduates with higher competencies. Education has therefore to be changed from knowledge-centered toward competence centered. The goal of this article is to use ChatGPT for analyzing and improving the competence orientation of exams in engineering education. The authors use ChatGPT to analyze exams from different engineering subjects to evaluate the performance of this chatbot and draw conclusions about the competence orientation of the tested exams. The obtained information is used to develop ideas for increasing the competence orientation of exams. From this analysis, it is visible that ChatGPT gives good performance mainly where knowledge is tested. It has, however, much more problems with transfer questions or tasks where students need creativity or complex insights for finding new solutions. Based on this result, exams and also lectures can be optimized toward competence orientation.
Der Freistaat Bayern finanziert seit einigen Jahren ein Hochschulprogramm zur Förderung von internationalen Gastprofessorinnen und Gastprofessoren an seinen Hochschulen. Mit diesen Finanzmitteln fördert die OTH Regensburg unter anderem internationale Gastvorlesungen. In der Fakultät Informatik und Mathematik wurde seit 2015 eine Zusammenstellung internationaler Gastvorlesungen entwickelt, die als Wahlpflichtfächer systematisch in ein bestehendes Curriculum integriert sind. So werden den heimischen Studierenden internationale Erfahrungen ermöglicht ("internationalization at home"), die fachliche Breite des Curriculums wird erhöht und es können auf Basis persönlicher Kontakte internationale Hochschulpartnerschaften neu geknüpft und weiter entwickelt werden. Jede Vorlesung in diesem Programm besteht aus mehreren Teilen. Zum Vorlesungsbeginn werden die geplanten Inhalte und Anforderung den Studierenden in einer Videokonferenz erläutert. Die Studierenden erhalten Unterlagen, um sich in Selbstlerneinheiten auf die Präsenzvorlesungen des Gastes vorzubereiten. Im Präsenzteil verbringt die/der Gastdozierende ca. 2 bis 3 Wochen in Regensburg und hält an der Hochschule Blockvorlesungen. So ist es möglich, Veranstaltungen mit 5 ECTS Credits in einem "blended learning" Lehr-/Lernformat durchzuführen. Studierende schätzen das Programm sehr und äußern sich in Evaluationen äußerst positiv über die fachliche und didaktische Erweiterung des Fächerspektrums. Dieses Programm wird als "good practice" innerhalb der Hochschule angesehen und soll in anderen technischen Fakultäten verbreitet werden, u.a. wurde ein "Prozesshandbuch" mit konkreten Beispielen und Handreichungen erstellt. Der Vortrag geht auf diese und weitere Umsetzungsaspekte sowie zugehörige Herausforderungen ein.
It is generally known that project-based learning is a very important part of engineering education to connect theoretical knowledge with practical work. Students learn to apply their knowledge to real-world challenges as it is the case in their later professional life. If students are not used to project work or the scientific topic is new and relatively complex, they may be overwhelmed. The consequence is that students achieve poor results, are frustrated, and therefore learning success is low. Semi-structured projects are introduced that combine the advantages of structured experiments with projects. The project work is structured into several parts with detailed descriptions of the tasks. In the end, students get similar results to doing a free project, but the success rate is higher due to higher guidance. Therefore, these semi-structured projects are seen to be an appropriate method to guide students to learn how to do project work. The feedback from most students is very positive. Some students with no previous lab experience complained about the project work and wished for more guidance to become familiar with lab work. In sum, the student feedback is encouraging to develop semi-structured projects further.