Introduction: The social distancing restrictions due to the COVID-19 pandemic have changed students’ learning environment and limited their social interactions. Therefore, the objective of this study was to investigate the influence of the social distancing restrictions on students’ social networks, wellbeing, and academic performance. Methods: We performed a questionnaire study in which 102 students participated before and 167 students during the pandemic. They completed an online questionnaire about how they formed their five peer social networks (study-related support, collaboration, friendship, share information, and learn-from) out-of-class. We performed social network analysis to compare the sizes, structures, and compositions of students’ five social networks before and during the pandemic, between first- and second-year students, and between international and domestic students. Additionally, we performed Kruskal–Wallis H test to compare students’ academic performance before and during the pandemic. We performed thematic analysis to answers for two open-end questions in the online questionnaire to explore what difficulties students encountered during the COVID-19 pandemic and what support they needed. Results: The results showed that the size of students’ social networks during the pandemic was significantly smaller than before the pandemic. Besides, the formation of social networks differed between first- and second-year students, and between domestic and international students. However, academic performance did not decline during the COVID-19 pandemic. Furthermore, we identified three key areas in which students experienced difficulties and needed support by thematic analysis: social connections and interactions, learning and studying, and physical and mental wellbeing. Conclusion: When institutions implement learning with social distancing, such as online learning, they need to consider changes in students’ social networks and provide appropriate support.
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An investigation in the learning effects of integrated development projects. In two subsequent semesters the students were asked how they rated their competencies at the start of the project as well as at the end of it. The students voluntarily filled out a questionnaire. After the last questionnaire a number of students were also interviewed in order to learn more about their perceptions. It was a remarkable outcome of these interviews that a lot of students tended to give themselves lower ratings in the end if they met any difficulties in for instance communication or co-operation during the project. Then the questionnaire showed a decrease in the student's ratings, while anyone else would say the student did learn something after recognizing these difficulties. It required a different interpretation of the outcomes of the questionnaires. The investigation showed that co-operating in general and in multidisciplinary teams in particular, co-operating with companies and also working according to plans are the four objectives that are recognized mostly by the students. The factors that actually contribute to, or block, the learning effects remained unknown yet.
Motor learning is particularly challenging in neurological rehabilitation: patients who suffer from neurological diseases experience both physical limitations and difficulties of cognition and communication that affect and/or complicate the motor learning process. Therapists (e.g.,, physiotherapists and occupational therapists) who work in neurorehabilitation are therefore continuously searching for the best way to facilitate patients during these intensive learning processes. To support therapists in the application of motor learning, a framework was developed, integrating knowledge from the literature and the opinions and experiences of international experts. This article presents the framework, illustrated by cases from daily practice. The framework may assist therapists working in neurorehabilitation in making choices, implementing motor learning in routine practice, and supporting communication of knowledge and experiences about motor learning with colleagues and students. The article discusses the framework and offers suggestions and conditions given for its use in daily practice.
Traffic accidents are a severe public health problem worldwide, accounting for approximately 1.35 million deaths annually. Besides the loss of life, the social costs (accidents, congestion, and environmental damage) are significant. In the Netherlands, in 2018, these social costs were approximately € 28 billion, in which traffic accidents alone accounted for € 17 billion. Experts believe that Automated Driving Systems (ADS) can significantly reduce these traffic fatalities and injuries. For this reason, the European Union mandates several ADS in new vehicles from 2022 onwards. However, the utility of ADS still proves to present difficulties, and their acceptance among drivers is generally low. As of now, ADS only supports drivers within their pre-defined safety and comfort margins without considering individual drivers’ preferences, limiting ADS in behaving and interacting naturally with drivers and other road users. Thereby, drivers are susceptible to distraction (when out-of-the-loop), cannot monitor the traffic environment nor supervise the ADS adequately. These aspects induce the gap between drivers and ADS, raising doubts about ADS’ usefulness among drivers and, subsequently, affecting ADS acceptance and usage by drivers. To resolve this issue, the HUBRIS Phase-2 consortium of expert academic and industry partners aims at developing a self-learning high-level control system, namely, Human Counterpart, to bridge the gap between drivers and ADS. The central research question of this research is: How to develop and demonstrate a human counterpart system that can enable socially responsible human-like behaviour for automated driving systems? HUBRIS Phase-2 will result in the development of the human counterpart system to improve the trust and acceptance of drivers regarding ADS. In this RAAK-PRO project, the development of this system is validated in two use-cases: I. Highway: non-professional drivers; II. Distribution Centre: professional drivers.
Traffic accidents are a severe public health problem worldwide, accounting for approximately 1.35 million deaths annually. Besides the loss of life, the social costs (accidents, congestion, and environmental damage) are significant. In the Netherlands, in 2018, these social costs were approximately € 28 billion, in which traffic accidents alone accounted for € 17 billion. Experts believe that Automated Driving Systems (ADS) can significantly reduce these traffic fatalities and injuries. For this reason, the European Union mandates several ADS in new vehicles from 2022 onwards. However, the utility of ADS still proves to present difficulties, and their acceptance among drivers is generally low.As of now, ADS only supports drivers within their pre-defined safety and comfort margins without considering individual drivers’ preferences, limiting ADS in behaving and interacting naturally with drivers and other road users. Thereby, drivers are susceptible to distraction (when out-of-the-loop), cannot monitor the traffic environment nor supervise the ADS adequately. These aspects induce the gap between drivers and ADS, raising doubts about ADS’ usefulness among drivers and, subsequently, affecting ADS acceptance and usage by drivers.To resolve this issue, the HUBRIS Phase-2 consortium of expert academic and industry partners aims at developing a self-learning high-level control system, namely, Human Counterpart, to bridge the gap between drivers and ADS. The central research question of this research is:How to develop and demonstrate a human counterpart system that can enable socially responsible human-like behaviour for automated driving systems?HUBRIS Phase-2 will result in the development of the human counterpart system to improve the trust and acceptance of drivers regarding ADS. In this RAAK-PRO project, the development of this system is validated in two use-cases:I. Highway: non-professional drivers;II. Distribution Centre: professional drivers.Collaborative partners:Bielefeld University of Applied Sciences, Bricklog B.V., Goudappel B.V., HaskoningDHV Nederland B.V., Rhine-Waal University of Applied Sciences, Rijkswaterstaat, Saxion, Sencure B.V., Siemens Industry Software Netherlands B.V., Smits Opleidingen B.V., Stichting Innovatiecentrum Verkeer en Logistiek, TNO Den Haag, TU Delft, University of Twente, V-Tron B.V., XL Businesspark Twente.
It is VHL’s mission to train high-quality, committed and innovative professionals who con-tribute to a more sustainable world , and who are able to organize and manage multi-stakeholder processes for sustainable change: graduates with transdisciplinary competences. Secondly, VHL aims to contribute to the SDG-agenda by linking its education and applied research to eight particular SDGs of which Resilient Communities is one. However, to operationalize SDGs in practice, and aligning targets and strategies of different stakeholders is difficult: ‘resilience’ and ‘sustainability’ refer to ‘wicked problems’ for which no definitive problem formulation, nor clear-cut solutions exist. Addressing wicked problems like ‘resilience’ and ‘sustainability’ requires transdisciplinary collaboration to manage and transform divergent values and conflicting interests, and to co-create sustainable innovations. This HBO postdoc views the 17 SDGs as a compass to align targets and strategies of citizens, government, civil society organizations, private sector and knowledge institutes who collaborate in Living Labs of VHL focusing on resilient communities/regions. Through spiraling action-reflection cycles, stakeholders will use the SDG compass to make success mechanisms, obstacles and trade-offs visible, assuming they stay engaged to overcome difficulties to improve interventions and innovations; this is expected to result in adapted sustainability practices and lessons learned on reaching community resilience. The postdoc’s aim is two-fold highlighting the link between research and education: (1) Design a methodology to integrate SDGs effectively in VHL’s applied research: using the SDGs as compass to improve performance and outcomes of transdisciplinary collaborations. (2) Develop a Roadmap for transdisciplinary education at course, curriculum, and institutional level with SDGs as compass. Future graduates require the competence to work together with others outside one own’s discipline, institute, culture or context. Living Labs offer a suitable learning environment to develop this competence