Stage fright among musicians and music students is a severe problem, and a problem moreover that is not easily talked about. This researchreport is a reflection of the project Peak Performance & Reducing Stage Fright, in which six students of the Prince Claus Conservatoire got the opportunity to take the HeartMath training. A training developed by de GGZ Heerenveen. The research, which is described in this report, was aimed at the usefulness of this training for professional music students.
We investigated the effects of reflex-based self-defence training on police performance in simulated high-pressure arrest situations. Police officers received this training as well as a regular police arrest and self-defence skills training (control training) in a crossover design. Officers' performance was tested on several variables in six reality-based scenarios before and after each training intervention. Results showed improved performance after the reflex-based training, while there was no such effect of the regular police training. Improved performance could be attributed to better communication, situational awareness (scanning area, alertness), assertiveness, resolution, proportionality, control and converting primary responses into tactical movements. As officers trained complete violent situations (and not just physical skills), they learned to use their actions before physical contact for de-escalation but also for anticipation on possible attacks. Furthermore, they learned to respond against attacks with skills based on their primary reflexes. The results of this study seem to suggest that reflex-based self-defence training better prepares officers for performing in high-pressure arrest situations than the current form of police arrest and self-defence skills training. Practitioner Summary: Police officers' performance in high-pressure arrest situations improved after a reflex-based self-defence training, while there was no such effect of a regular police training. As officers learned to anticipate on possible attacks and to respond with skills based on their primary reflexes, they were better able to perform effectively.
This article describes the relation between mental health and academic performance during the start of college and how AI-enhanced chatbot interventions could prevent both study problems and mental health problems.
Students in Higher Music Education (HME) are not facilitated to develop both their artistic and academic musical competences. Conservatoires (professional education, or ‘HBO’) traditionally foster the development of musical craftsmanship, while university musicology departments (academic education, or ‘WO’) promote broader perspectives on music’s place in society. All the while, music professionals are increasingly required to combine musical and scholarly knowledge. Indeed, musicianship is more than performance, and musicology more than reflection—a robust musical practice requires people who are versed in both domains. It’s time our education mirrors this blended profession. This proposal entails collaborative projects between a conservatory and a university in two cities where musical performance and musicology equally thrive: Amsterdam (Conservatory and University of Amsterdam) and Utrecht (HKU Utrechts Conservatorium and Utrecht University). Each project will pilot a joint program of study, combining existing modules with newly developed ones. The feasibility of joint degrees will be explored: a combined bachelor’s degree in Amsterdam; and a combined master’s degree in Utrecht. The full innovation process will be translated to a transferable infrastructural model. For 125 students it will fuse praxis-based musical knowledge and skills, practice-led research and academic training. Beyond this, the partners will also use the Comenius funds as a springboard for collaboration between the two cities to enrich their respective BA and MA programs. In the end, the programme will diversify the educational possibilities for students of music in the Netherlands, and thereby increase their professional opportunities in today’s job market.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
Big data spelen een steeds grotere rol in de (semi)professionele sport. De hoeveelheid gegevens die opgeslagen wordt, groeit exponentieel. Sportbegeleiders (coaches, inspanningsfysiologen, sportfysiotherapeuten en sportartsen) maken steeds vaker gebruik van sensoren om sporters te monitoren. Tijdens trainingen en wedstrijden worden de hartslagen, afgelegde afstanden, snelheden en versnellingen van sporters gemeten. Het analyseren van deze data vormt een grote uitdaging voor het begeleidingsteam van de sporters. Sportbegeleiders willen big data graag inzetten om meer grip te krijgen op sportblessures. Blessures kunnen namelijk desastreuze gevolgen hebben voor teamprestaties en de carrière van (semi)professionele sporters. In totaal stopt maar liefst 33% van de topsporters door blessures met hun sportloopbaan. Daarnaast is uitval door blessures een belangrijke oorzaak van stagnatie van talentontwikkeling. Het lectoraat Sportzorg van de Hogeschool van Amsterdam heeft veel expertise op het gebied van blessurepreventie in de sport. Sportbegeleiders hebben het lectoraat Sportzorg benaderd om antwoord te krijgen op de onderzoeksvraag: Wat zijn op data gebaseerde indicatoren om sportblessures te voorspellen? Deze onderzoeksvraagstelling is opgesplitst in de volgende deelvragen: 1. Hoe kan met sensoren relevante data van sporters verzameld worden om de sportbelasting in kaart te brengen? 2. Welke parameters kunnen blessures voorspellen? 3. Hoe kunnen deze parameters op betekenisvolle en eenvoudige wijze naar sportbegeleiders en sporters teruggekoppeld worden? Het project resulteert in de volgende projectresultaten: - Een overzicht van nauwkeurige en gebruiksvriendelijke sensoren om sportbelasting in kaart te brengen - Een overzicht van relevante parameters die blessures kunnen voorspellen - Een online tool dat per sporter aangeeft of de sporter wel of niet training- of wedstrijdfit is Bij dit project zijn de volgende organisaties betrokken: Hogeschool van Amsterdam, Universiteit Leiden, VUmc, Rijksuniversiteit Groningen (RuG), Amsterdam Institute of Sport Science (AISS), Johan Sports, Centrum voor Topsport en Onderwijs (CTO) Amsterdam, Koninklijke Nederlandse Voetbalbond (KNVB), de Nederlandse Vereniging voor Fysiotherapie in de Sport (NVFS), VV Noordwijk (voetbalclub) en Black Eagles (basketbalclub).
