In this study, we address the function of role models for entrepreneurship students. By using entrepreneurs as role models, students can get a better and realistic picture of the complexity of the entrepreneurial path. Choosing whom to interview as role model can be diverse, but it can be problematic if, as a result of that choice, the learning effect in the same group of students is different.
MULTIFILE
In higher education, students often misunderstand teachers’ written feedback. This is worrisome, since written feedback is the main form of feedback in higher education. Organising feedback conversations, in which feedback request forms and verbal feedback are used, is a promising intervention to prevent misunderstanding of written feedback. In this study a 2 × 2 factorial experiment (N = 128) was conducted to examine the effects of a feedback request form (with vs. without) and feedback mode (written vs. verbal feedback). Results showed that verbal feedback had a significantly higher impact on students’ feedback perception than written feedback; it did not improve students’ self-efficacy, or motivation. Feedback request forms did not improve students’ perceptions, self-efficacy, or motivation. Based on these results, we can conclude that students have positive feedback perceptions when teachers communicate their feedback verbally and more research is needed to investigate the use of feedback request forms.
MULTIFILE
Background: The dynamics of maternal and newborn care challenge midwifery education programs to keep up-to-date. To prepare for their professional role in a changing world, role models are important agents for student learning. Objective: To explore the ways in which Dutch and Icelandic midwifery students identify role models in contemporary midwifery education. Methods: We conducted a descriptive, qualitative study between August 2017 and October 2018. In the Netherlands, 27 students participated in four focus groups and a further eight in individual interviews. In Iceland, five students participated in one focus group and a further four in individual interviews. All students had clinical experience in primary care and hospital. Data were analyzed using inductive content analysis. Results: During their education, midwifery students identify people with attitudes and behaviors they appreciate. Students assimilate these attitudes and behaviors into a role model that represents their ‘ideal midwife’, who they can aspire to during their education. Positive role models portrayed woman-centered care, while students identified that negative role models displayed behaviors not fitting with good care. Students emphasized that they learnt not only by doing, they found storytelling and observing important aspects of role modelling. Students acknowledged the impact of positive midwifery role models on their trust in physiological childbirth and future style of practice. Conclusion: Role models contribute to the development of students’ skills, attitudes, behaviors, identity as midwife and trust in physiological childbirth. More explicit and critical attention to how and what students learn from role models can enrich the education program.
Hoewel drones worden gebruikt in steeds toenemende civiele toepassingen voor een goede daad, zijn kwaadwillende drones ook steeds meer en steeds vaker worden ingezet om schade aan te richten. Huis, tuin en keukendrones zijn in staat om door te dringen tot zwaarbeveiligde gebieden en daar verwoestende schade aan te brengen. Ze zijn goedkoop, precies en kunnen steeds grotere afstanden afleggen. Kwaadwillende drones vormen een groot gevaar voor de nationale veiligheid. In dit KIEM-project onderzoeken wij de vraag in hoeverre is het mogelijk om drones te ontwikkelen die volledig autonoom een ongecontroleerde omgeving (luchtruim) veilig kunnen houden? Counter drones moeten kamikaze-drones kunnen signaleren en uitschakelen. Bestaande systemen zijn nog onvoldoende in staat om kwaadwillende drones op tijd uit te schakelen. Bij Defensie, de Nationale Politie en het gevangeniswezen is dringend behoefte aan systemen die kwaadwillende drones kunnen detecteren en uitschakelen. Er zijn thans enkele (Europese) systemen waarmee drones kunnen worden gedetecteerd, onder andere met radiofrequentiesignalen (voelen), optische- en radartechnologie (zien) en akoestische systemen (horen). Geen van deze systemen vormen de ‘silver bullet’ voor het bestrijden van kwaadwillende drones, vooral kleine en laagvliegende drones. Met een feasibility study wordt nagegaan wat de state-of-the-art is van de huidige counter dronetechnologieën en op welke technologiedomeinen het consortium waarde kan toevoegen aan de ontwikkeling van effectieve counter drones. Saxion en haar partners zet zich de komende jaren in op Sleuteltechnologieën als: Human Robotic Interaction, Perception, Navigation, Systems Development, Mechatronics en Cognition. Technologieën die terugkomen in counter drones, maar ook worden doorontwikkeld voor andere toepassingsgebieden. Het project bestaat uit 4 fasen: een onderzoek naar de huidige counter dronetechnologieën (IST), onderzoek naar gewenste/toekomstige counter dronetechnologieën (SOLL), een gap-analyse (TOR) én een omgevingsanalyse om na te gaan wat er elders in Europa al aan onderzoek plaatsvindt. Tevens wordt een netwerk ontwikkeld om counter droneontwikkeling mogelijk te maken.
Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.
The Healthy Workplace monitor is being developed to monitor the health and well-being of knowledge workers in relation to the office space and their home workplace. Since the corona period, a lot has changed in the way knowledge workers work. Both offices and employees require more flexibility to carry out work in an efficient but also healthy and enjoyable way. It is important to identify office workers needs with regard to workspaces at the office and at home from a holistic view, in which mental , physical and social aspects play a role. A vital, happy employee is a productive employee.