Introduction Student success is positively linked to engagement, but negatively linked to emotional exhaustion. Though both constructs have been conceptualized as opposites previously, we hypothesize that students can demonstrate high or low engagement and emotional exhaustion simultaneously. We used quantitative and qualitative data to identify the existence of four student profiles based on engagement and exhaustion scores. Furthermore, we studied how profiles associate to study behaviour, wellbeing and academic achievement, and what risks, protective factors and support requirements students and teachers identify for these profiles. Methods The Student Wellbeing Monitor 2021, developed by Inholland University of Applied Sciences, was used to identify profiles using quadrant analyses based on high and low levels of engagement and emotional exhaustion (n= 1460). Correlation analyses assessed profile specific differences on study behaviours, academic delay, and wellbeing. Semi-structured interviews with students and teachers are currently in progress to further explore the profiles, to identify early signals, and to inspect support requirements. Results The quadrant analysis revealed four profiles: low engagement and low exhaustion (energised-disengaged; 9%), high engagement and low exhaustion (energised-engaged; 15%), low engagement and high exhaustion (exhausted-disengaged; 48%), and high engagement and high exhaustion (exhausted-engaged; 29%). Overall, engaged students demonstrated more active study behaviours and more social connections and interactions with fellow students and teachers. The exhausted students scored higher on depressive symptoms and stress. The exhausted-engaged students reported the highest levels of performance pressure, while the energised-disengaged students had the lowest levels of performance pressure. So far, students and teachers recognise the profiles and have suggested several support recommendations for each profile. Discussion The results show that students can be engaged but at the same time are exhausting themselves. A person-oriented mixed-methods approach helps students and teachers gain awareness of the diversity and needs of students, and improve wellbeing and student success.
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In a rapidly developing labor market, in which some parts of jobs disappear and new parts appear due to technological developments, companies are struggling with defining future-proof job qualifications and describing job profiles that fit the organization’s needs. This is even more applicable to smaller companies with new types of work because they often grow rapidly and cannot hire graduates from existing study programs. In this research project, we undertook in-depth, qualitative research into the five roles of a new profession: social media architect. It has become clear which 21st century skills and motivations are important per role and, above all, how they differ in subcategory and are interpreted by a full-service team in their working methods, in a labor market context, and in the talents of the professional themselves. In a workshop, these “skills” were supplemented through a design-based approach and visualized per team role in flexibly applicable recruitment cards. This research project serves as an example of how to co-create innovative job profiles for the changing labor market. Ellen Sjoer, Petra Biemans. “A design-based (pre)recruitment approach for new professions: defining futureproof job profiles.” Információs Társadalom XX, no. 2 (2020): 84–100. https://dx.doi.org/10.22503/inftars.XX.2020.2.6
A decline in both student well-being and engagement were reported during the COVID-pandemic. Stressors and internal energy sources can co-exist or be both absent, which might cohere with different student needs. This study aimed to develop student profiles on emotional exhaustion and engagement, as well as examine how profiles relate to student participation, academic performance, and overall well-being. Survey-data from 1,460 Dutch higher education students were analyzed and resulted in a quadrant model containing four student profiles on engagement and emotional exhaustion scores. Semi-structured interviews with 13 students and 10 teaching staff members were conducted to validate and further describe the student profiles. The majority of the survey participants were disengaged-exhausted (48%) followed by engaged-exhausted students (29%). Overall, the engagedenergized students performed best academically and had the highest levels of well-being and participation, although engaged-exhausted students were more active in extracurricular activities. The engaged exhausted students also experienced the most pressure to succeed. The qualitative validation of the student profiles demonstrates that students and teachers recognize and associate the profiles with themselves or other students. Changes in the profiles are attributed to internal and external factors, suggesting that they are not fixed but can be influenced by various factors. The practical relevance of the quadrant model is acknowledged by students and teachers and they shared experiences and tips, with potential applications in recognizing students’ well-being and providing appropriate support. This study enriches our grasp of student engagement and well-being in higher education, providing valuable insights for educational practices.
Human kind has a major impact on the state of life on Earth, mainly caused by habitat destruction, fragmentation and pollution related to agricultural land use and industrialization. Biodiversity is dominated by insects (~50%). Insects are vital for ecosystems through ecosystem engineering and controlling properties, such as soil formation and nutrient cycling, pollination, and in food webs as prey or controlling predator or parasite. Reducing insect diversity reduces resilience of ecosystems and increases risks of non-performance in soil fertility, pollination and pest suppression. Insects are under threat. Worldwide 41 % of insect species are in decline, 33% species threatened with extinction, and a co-occurring insect biomass loss of 2.5% per year. In Germany, insect biomass in natural areas surrounded by agriculture was reduced by 76% in 27 years. Nature inclusive agriculture and agri-environmental schemes aim to mitigate these kinds of effects. Protection measures need success indicators. Insects are excellent for biodiversity assessments, even with small landscape adaptations. Measuring insect biodiversity however is not easy. We aim to use new automated recognition techniques by machine learning with neural networks, to produce algorithms for fast and insightful insect diversity indexes. Biodiversity can be measured by indicative species (groups). We use three groups: 1) Carabid beetles (are top predators); 2) Moths (relation with host plants); 3) Flying insects (multiple functions in ecosystems, e.g. parasitism). The project wants to design user-friendly farmer/citizen science biodiversity measurements with machine learning, and use these in comparative research in 3 real life cases as proof of concept: 1) effects of agriculture on insects in hedgerows, 2) effects of different commercial crop production systems on insects, 3) effects of flower richness in crops and grassland on insects, all measured with natural reference situations
Over the past decade, the trend in both the public sector and industry has been to outsource ICT to the cloud. While cost savings are often used as a rationale for outsourcing, another argument that is frequently used is that the cloud improves security. The reasoning behind this is twofold. First, cloud service providers are typically thought to have skilled staff trained in good security practices. Second, cloud providers often have a vastly distributed, highly connected network infrastructure, making them more resilient in the face of outages and denial-of-service attacks. Yet many examples of cloud outages, often due to attacks, call into question whether outsourcing to the cloud does improve security. In this project our goal therefore is to answer two questions: 1) did the cloud make use more secure?and 2) can we provide specific security guidance to support cloud outsourcing strategies? We will approach these questions in a multi-disciplinary fashion from a technical angle and from a business and management perspective. On the technical side, the project will focus on providing comprehensive insight into the attack surface at the network level of cloud providers and their users. We will use a measurement-based approach, leveraging large scale datasets about the Internet, both our own data (e.g. OpenINTEL, a large- scale dataset of active DNS measurements) and datasets from our long-term collaborators, such as CAIDA in the US (BGPStream, Network Telescope) and Saarland University in Germany (AmpPot). We will use this data to study the network infrastructure outside and within cloud environments to structurally map vulnerabilities to attacks as well as to identify security anti-patterns, where the way cloud services are managed or used introduce a weak point that attackers can target. From a business point of view, we will investigate outsourcing strategies for both the cloud providers and their customers. For guaranteeing 100% availability, cloud service providers have to maintain additional capacity at all times. They also need to forecast capacity requirements continuously for financially profitable decisions. If the forecast is lower than the capacity needed, then the cloud is not able to deliver 100% availability in case of an attack. Conversely, if the forecast is substantially higher, the cloud service provider might not be able to make desired profits. We therefore propose to assess the risk profiles of cloud providers (how likely it is a cloud provider is under attack at a given time given the nature of its customers) using available attack data to improve the provider resilience to future attacks. From the costumer perspective, we will investigate how we can support cloud outsourcing by taking into consideration business and technical constraints. Decision to choose a cloud service provider is typically based on multiple criteria depending upon the company’s needs (security and operational). We will develop decision support systems that will help in mapping companies’ needs to cloud service providers’ offers.
The application of sensors in water technology is a crucial step to provide broader, more effi-cient and more circular systems. Among the different technologies used in this filed, ultra-sound based systems are widely used in water technology, basically to generate energy peaks for cell lyse and particle separation. In this work we propose the adaptation of a (cur-rently used for medical applications) ultra sound ecosystem to monitor the vertical profile of solid particles in UASB reactors. Such information is nowadays obtained via long duration (solids) analysis and can compromises the efficiency of such reactors, especially regarding the sludge stabilization and phase separation. The project is a small part of a big effort done by different countries, e.g. Brazil, UK and The Netherlands, to bring international technology and expertise to improve the quality of waste water systems in Brazil, by supporting tech-nology and knowledge sharing. If proven feasible, the concept can generate a big business market to the involved Dutch (SME) partners as well as favor the automation of WWTP in Brazil and around the world.
