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Portal Wissen = Learning
(2023)
Changing through learning is one of the most important characteristics we humans have. We are born and can – it seems – do nothing. We have to comprehend, copy, and acquire everything: grasping and walking, eating and speaking. Of course, we also have to read and do number work. In the meantime, we know: We will never be able to finish this. At best, we learn for a lifetime. If we stop, it harms us. The Greek philosopher Plato said more than 2,400 years ago, “There is no shame in not knowing something. The shame is in not being willing to learn.”
As humans we are also capable of learning; thanks to more and more knowledge about the world around us, we have moved from the Stone Age into the digital age. That this development is not a finish line either, but that we still have a long way to go, is shown by man-made climate change – and above all by our inability as a global community to translate what research teaches us into appropriate actions. Let us dare to hope that we also comprehend this.
What we tend to ignore in the intensive discussion about the multi-layered levels of learning: We are by no means the only learners. Many, if not all, living beings on our planet learn, some more in a more purposeful and complex and more cognitive way than others. And for some time now, machines have also been able to learn more or less independently. Artificial intelligence sends its regards.
The significance of learning for human beings can hardly be overestimated. Science has also understood this and has discovered the learning processes and conditions in almost all contexts for itself, no matter whether it is about our own learning processes and conditions or those around us. We have investigated some of these for the current issue of “Portal Wissen”.
Psycholinguist Natalie Boll-Avetisyan has developed a box that can be used to detect language learning disorders already in young children. The behavioral biologists Jana Eccard and Valeria Mazza investigated the behavior of small rodents and found out that they do not only develop different personality traits but they also described how they learn to adapt them different environmental conditions. Computer linguist David Schlangen examines the question what machines have to learn so that our communication with them works even better.
Since research is ultimately always a learning process that strives to understand something yet unknown, this time all texts are somehow along the motto of the title theme: It is about what the history of past centuries reveals about “military cultures of violence” and the question of what lessons we should learn from natural hazards for the future.
We talked with a legal scholar who looks beyond the university’s backyard and wants to make law comprehensible to everyone. We also talked with a philosopher who analyzes why “having an opinion” means something different today than 100 years ago. We report about an AI-based genome analysis that can change healthcare sustainably. Furthermore, it is about the job profile “YouTuber”, minor cosmopolitanisms, and wildlife management in Africa. When you have finished reading, you will have learnt something. Promised! Enjoy your read!
Angesichts der dramatischen Lage in der Ukraine untersucht der folgende Beitrag, auf welchem Wege, vor welchen völkerrechtlichen Gerichten, in welchem Umfang und mit welcher Aussicht auf Erfolg die Ukraine oder einzelne ukrainische Staatsangehörige Sicherheitsschutz vor der russischen Invasion und/oder den im Zusammenhang damit bereits begangenen oder noch bevorstehenden Völkerrechtsverstößen Rechtsschutz erlangen können. Im Einzelnen handelt es sich hierbei um zwei anhängige Verfahren vor dem Internationalen Gerichtshof, mehrere Staaten- sowie eine große Vielzahl von Individualbeschwerden vor dem Europäischen Gerichtshof für Menschenrechte; ein Verfahren vor dem Internationalen Seegerichtshof; zahlreiche Investitionsverfahren vor internationalen Schiedsgerichten sowie schließlich zwei "Situationen" vor dem Internationalen Strafgerichtshof. Abschließend wird die Option der Schaffung eines ad-hoc-Tribunals für das Verbrechen der Aggression behandelt.
Finnland und Schweden
(2023)
Records from ocean bottom seismometers (OBSs) are highly contaminated by noise, which is much stronger compared to data from most land stations, especially on the horizontal components. As a consequence, the high energy of the oceanic noise at frequencies below 1 Hz considerably complicates the analysis of the teleseismic earthquake signals recorded by OBSs.
Previous studies suggested different approaches to remove low-frequency noises from OBS recordings but mainly focused on the vertical component. The records of horizontal components, which are crucial for the application of many methods in passive seismological analysis of body and surface waves, could not be much improved in the teleseismic frequency band. Here we introduce a noise reduction method, which is derived from the harmonic–percussive separation algorithms used in Zali et al. (2021), in order to separate long-lasting narrowband signals from broadband transients in the OBS signal. This leads to significant noise reduction of OBS records on both the vertical and horizontal components and increases the earthquake signal-to-noise ratio (SNR) without distortion of the broadband earthquake waveforms. This is demonstrated through tests with synthetic data. Both SNR and cross-correlation coefficients showed significant improvements for different realistic noise realizations. The application of denoised signals in surface wave analysis and receiver functions is discussed through tests with synthetic and real data.
The persistence of food preferences, which are crucial for diet-related decisions, is a significant obstacle to changing unhealthy eating behavior. To overcome this obstacle, the current study investigates whether posthypnotic suggestions (PHSs) can enhance food-related decisions by measuring food choices and subjective ratings. After assessing hypnotic susceptibility in Session 1, at the beginning of Session 2, a PHS was delivered aiming to increase the desirability of healthy food items (e.g., vegetables and fruit). After the termination of hypnosis, a set of two tasks was administrated twice, once when the PHS was activated and once deactivated in counterbalanced order. The task set consisted of rating 170 pictures of food items, followed by an online supermarket where participants were instructed to select enough food from the same item pool for a fictitious week of quarantine. After 1 week, Session 3 mimicked Session 2 without renewed hypnosis induction to assess the persistence of the PHS effects. The Bayesian hierarchical modeling results indicate that the PHS increased preferences and choices of healthy food items without altering the influence of preferences in choices. In contrast, for unhealthy food items, not only both preferences and choices were decreased due to the PHS, but also their relationship was modified. That is, although choices became negatively biased against unhealthy items, preferences played a more dominant role in unhealthy choices when the PHS was activated. Importantly, all effects persisted over 1 week, qualitatively and quantitatively. Our results indicate that although the PHS affected healthy choices through resolve, i.e., preferred more and chosen more, unhealthy items were probably chosen less impulsively through effortful suppression. Together, besides the translational importance of the current results for helping the obesity epidemic in modern societies, our results contribute theoretically to the understanding of hypnosis and food choices.
Für die Entwicklung professioneller Handlungskompetenzen angehender Lehrkräfte stellt die Unterrichtsreflexion ein wichtiges Instrument dar, um Theoriewissen und Praxiserfahrungen in Beziehung zu setzen. Die Auswertung von Unterrichtsreflexionen und eine entsprechende Rückmeldung stellt Forschende und Dozierende allerdings vor praktische wie theoretische Herausforderungen. Im Kontext der Forschung zu Künstlicher Intelligenz (KI) entwickelte Methoden bieten hier neue Potenziale. Der Beitrag stellt überblicksartig zwei Teilstudien vor, die mit Hilfe von KI-Methoden wie dem maschinellen Lernen untersuchen, inwieweit eine Auswertung von Unterrichtsreflexionen angehender Physiklehrkräfte auf Basis eines theoretisch abgeleiteten Reflexionsmodells und die automatisierte Rückmeldung hierzu möglich sind. Dabei wurden unterschiedliche Ansätze des maschinellen Lernens verwendet, um modellbasierte Klassifikation und Exploration von Themen in Unterrichtsreflexionen umzusetzen. Die Genauigkeit der Ergebnisse wurde vor allem durch sog. Große Sprachmodelle gesteigert, die auch den Transfer auf andere Standorte und Fächer ermöglichen. Für die fachdidaktische Forschung bedeuten sie jedoch wiederum neue Herausforderungen, wie etwa systematische Verzerrungen und Intransparenz von Entscheidungen. Dennoch empfehlen wir, die Potenziale der KI-basierten Methoden gründlicher zu erforschen und konsequent in der Praxis (etwa in Form von Webanwendungen) zu implementieren.
Reformen bei Elterngeld und Ehegattensplitting könnten gleichstellungspolitische Impulse setzen
(2023)
Germany is characterised by large gender gaps in the labour market. Both the gender pay gap as well as the gender gap in working hours are among the highest in Europe. Family policy reforms such as increasing the parental leave period that is ear-marked for fathers as well as reducing the high marginal tax rates for secondary earners resulting from the joint taxation of married couples with full income splitting (“Ehegattensplitting”) could help to mitigate the existing gender gaps in the labour market. These reforms are also paramount due to the increasing labour scarcity stemming from the demographic change.
Elterngeld
(2023)