Before the start and during the first weeks of their first year, it has been observed by teachers that engineering students start with a high level of motivation, which often seems to decrease during the course of the first semesters. Such a decrease in motivation can be a main driver for students dropping out of University early. A qualitative research will be carried out to answer the main questions that have been raised within the engineering department of the Fontys University of Applied sciences: to what extent does a decrease in the motivation of first-year students exists, exactly when during the course of the first year does this decrease occur and what are the underlying reasons causing this decline in motivation? Gaining more insight in the motivation drop of students could result in modifications to the curriculum. The final objectives are reducing the dropout level of students in the first year and increasing the quality level of young propaedeutics. In [1] and [2] studies are carried out to measure student’s motivation constructs, which have been carried out for first year Engineering students. The authors describe a certain level of motivation drop for first year students at an Engineering University. In Geraedts 2010 [3] it is defined that Maslow rules for students can be seen as an element of a student’s perception onto his or hers education. Often it can be observed that in most cases undergraduates start their education as an unconscious insufficient competent student having a very limited view on the work arena and complexity of the engineering discipline. Quickly after the start of the education year this view develops into a more defined perception of what the content and complexity of the future work field is and what is expected of the student during his or hers education. It is hypothesised that this gain in insights of the student into the work field and the related expectations is a significant contributor to the decline of intrinsic motivation. In this paper the investigated hypothesis and possible other aspects that influence the motivation of students will be presented. Based on results, potential corrective and preventive measures will be defined and discussed. Corrective and predictive measures depend on the results of this study and could be aimed for instance at: 1) making adjustments to the content and/or structure of the first semester curriculum, 2) improving the support of students in making adaptations into a better learning strategy and 3) improve the information on-which students decide to start a mechanical engineering education. This paper will focus on the first year mechanical engineering students of the Fontys University of Applied Sciences. About 100 first year students will be questioned using predefined questionnaires and additionally 20 of them will be interviewed for validation. References [1] Brett D. Jones, Marie C. Paretti, Serge F. Hein, Tamarra W. Knott, An analysis of Motivation Constructs with first-Year Engineering students, Journal of Engineering Education; Oct 2010; 99, 4; Research Library pg. 319 [2] L. Benson, A Kirn, B. Morkos, CAREER: Student Motivation and Learning in Engineering, 120th ASEE annual conference & Exposition June 2013 [3] HGM Geraedts (2010) Innovative learning for innovation ISBN 978-90-5284-624-8 4751
Recent studies show that charging stations are operated in an inefficient way. Due to the fact that electric vehicle (EV) drivers charge while they park, they tend to keep the charging station occupied while not charging. This prevents others from having access. This study is the first to investigate the effect of a pricing strategy to increase the efficient use of electric vehicle charging stations. We used a stated preference survey among EV drivers to investigate the effect of a time-based fee to reduce idle time at a charging station. We tested the effect of such a fee under different scenarios and we modelled the heterogeneity among respondents using a latent class discrete choice model. We find that a fee can be very effective in increasing the efficiency at a charging station but the response to the fee varies among EV drivers depending on their current behaviour and the level of parking pressure they experience near their home. From these findings we draw implications for policy makers and charging point operators who aim to optimize the use of electric vehicle charging stations.
The project focuses on highlighting the importance of the work-life balance within the hospitality industry, in 5-star hotels. Moreover, it is tailored to deliver a concrete and efficient implementation plan of a 5-day work week system instead of the current 6-day work week model system within a 5 star hotel in Abu Dhabi, United Arab Emirates. Several aspects were taken in consideration when developing the project such as, financial implications, stakeholder management, resistance management and organizational change.
MULTIFILE
The postdoc candidate, Sondos Saad, will strengthen connections between research groups Asset Management(AM), Data Science(DS) and Civil Engineering bachelor programme(CE) of HZ. The proposed research aims at deepening the knowledge about the complex multidisciplinary performance deterioration prediction of turbomachinery to optimize cleaning costs, decrease failure risk and promote the efficient use of water &energy resources. It targets the key challenges faced by industries, oil &gas refineries, utility companies in the adoption of circular maintenance. The study of AM is already part of CE curriculum, but the ambition of this postdoc is that also AM principles are applied and visible. Therefore, from the first year of the programme, the postdoc will develop an AM material science line and will facilitate applied research experiences for students, in collaboration with engineering companies, operation &maintenance contractors and governmental bodies. Consequently, a new generation of efficient sustainability sensitive civil engineers could be trained, as the labour market requires. The subject is broad and relevant for the future of our built environment being more sustainable with less CO2 footprint, with possible connections with other fields of study, such as Engineering, Economics &Chemistry. The project is also strongly contributing to the goals of the National Science Agenda(NWA), in themes of “Circulaire economie en grondstoffenefficiëntie”,”Meten en detecteren: altijd, alles en overall” &”Smart Industry”. The final products will be a framework for data-driven AM to determine and quantify key parameters of degradation in performance for predictive AM strategies, for the application as a diagnostic decision-support toolbox for optimizing cleaning &maintenance; a portfolio of applications &examples; and a new continuous learning line about AM within CE curriculum. The postdoc will be mentored and supervised by the Lector of AM research group and by the study programme coordinator(SPC). The personnel policy and job function series of HZ facilitates the development opportunity.
Polycotton textiles are fabrics made from cotton and polyester. It is used in many textile applications such as sporting cloths, nursery uniforms and bed sheets. As cotton and polyester are quite different in their polymer nature, polycotton textiles are hard to recycle and therefore mostly incinerated. Incineration of discarded polycotton, and substitution by virgin polycotton, create a significant environmental impact. However, textile manufacturers and brand owners will become obliged to apply recycled content in clothing from 2023 onwards. Therefore, the development of more sustainable recycling alternatives for the separation and purification of polycotton into its monomers and cellulose is vital. In a recently approved GoChem project, it has been shown that cotton can be separated from polyester successfully, using a chemical recycling process. The generated solution is a mixture of suspended and partially decolorized cotton (cellulose) and a liquid fraction produced from the depolymerization of the polyester (monomers). A necessary further step of this work is the investigation of possible separation methods to recover the cotton and purify the obtained polyester monomers into polymer-grade pure products suitable for repolymerization. Repolymerize is a new consortium, composed of the first project members, plus a separation and purification process group, to investigate efficient and high yield purification steps to recover these products. The project will focus on possible steps to separate the suspended fraction (cotton) and further recover of high purity ethylene glycol from the rest fraction (polyester depolymerization solution). The main objective is to create essential knowledge so the private partners can evaluate whether such process is technologically and economically feasible.
The demand for mobile agents in industrial environments to perform various tasks is growing tremendously in recent years. However, changing environments, security considerations and robustness against failure are major persistent challenges autonomous agents have to face when operating alongside other mobile agents. Currently, such problems remain largely unsolved. Collaborative multi-platform Cyber- Physical-Systems (CPSs) in which different agents flexibly contribute with their relative equipment and capabilities forming a symbiotic network solving multiple objectives simultaneously are highly desirable. Our proposed SMART-AGENTS platform will enable flexibility and modularity providing multi-objective solutions, demonstrated in two industrial domains: logistics (cycle-counting in warehouses) and agriculture (pest and disease identification in greenhouses). Aerial vehicles are limited in their computational power due to weight limitations but offer large mobility to provide access to otherwise unreachable places and an “eagle eye” to inform about terrain, obstacles by taking pictures and videos. Specialized autonomous agents carrying optical sensors will enable disease classification and product recognition improving green- and warehouse productivity. Newly developed micro-electromechanical systems (MEMS) sensor arrays will create 3D flow-based images of surroundings even in dark and hazy conditions contributing to the multi-sensor system, including cameras, wireless signatures and magnetic field information shared among the symbiotic fleet. Integration of mobile systems, such as smart phones, which are not explicitly controlled, will provide valuable information about human as well as equipment movement in the environment by generating data from relative positioning sensors, such as wireless and magnetic signatures. Newly developed algorithms will enable robust autonomous navigation and control of the fleet in dynamic environments incorporating the multi-sensor data generated by the variety of mobile actors. The proposed SMART-AGENTS platform will use real-time 5G communication and edge computing providing new organizational structures to cope with scalability and integration of multiple devices/agents. It will enable a symbiosis of the complementary CPSs using a combination of equipment yielding efficiency and versatility of operation.
