Search Results (42)

This paper presents a hybrid knowledge-based expert system (KBES) designed to predict crack incubation and fatigue life in gear design, serving as both a research tool and an educational resource. While crack growth and initiation are well understood, crack incubation remains a challenging area. The presented expert system (KBES) integrates a novel mathematical model for crack incubation based on analogy and defect analysis principles with an optimization algorithm for gear design. The system uses genetic algorithms to optimize gear parameters, demonstrating a 5–10% deviation from experimental values in a specific gear design problem case study. Based on this KBES and a hybrid approach, we developed a learning environment based on an intelligent tutoring system (ITS) which serves older students (MSc and PhD) as a learning environment for the acquisition of knowledge and, above all, for the development of an in-depth understanding of the phenomena that occur both during incubation and initialization and during the further propagation of cracks in the root of the gear tooth, which is the basis for determining the lifespan of gear transmissions. Full article

Construction 4.0 refers to the integration of automation, artificial intelligence, and the Internet of Things (IoT) in the construction industry, which has changed traditional construction practices. MSc courses play a crucial role in developing the next generation of leaders within the construction industry by equipping graduates of these courses with advanced technical, managerial, and strategic skills, including the arrival of Construction 4.0. As future professionals and construction industry leaders, it is necessary to identify the current level of awareness and understanding of Construction 4.0 amongst master’s level students. As such, this paper studies these areas to help identify the gaps in education and training requirements—essential for matching academic programs with industry needs. Through the use of a survey-based approach with 112 MSc students on various Construction Management courses, a series of revealing results were obtained. The results presented herein indicate that there is a shared definition of what constitutes Construction 4.0 amongst engineering management students. However, while they are relatively aware of Construction 4.0 technologies, they do not differentiate strongly between Industry 4.0 and Construction 4.0. Therein, they are ambivalent as to the role of Education 4.0 in improving this situation. Key to this is the requirement to keep up with industry needs. The lack of application of Construction 4.0 means students lack the necessary ‘practical skills’ to implement innovations on real construction sites. Students advocated for more hands-on training, industry-linked projects, and guest lectures within the curriculum, alongside developing the essential skills of critical thinking and problem-solving. Changes in the curricula are suggested, achievable through readily existing 4.0 Frameworks. Full article

Introduction: Cancer is one of the evils of the current era and is considered a global public health problem. This disease has repercussions for the lives of patients in several dimensions, namely, physical, emotional, and psychosocial. Thus, it is believed that elements such as resilience, symptomatology, and self-care are related, as the disease and its treatments can have repercussions that extend beyond the clinic. Background/Objectives: We aimed to determine the relationship between symptom clusters and the mindful self-care of people with cancer in palliative care. Methods: This is a cross-sectional study conducted with 125 palliative care patients diagnosed with malignant neoplasms. The research was carried out at a reference hospital in Brazil, located in the western region of the state of Santa Catarina, specializing in antineoplastic treatment. The data were collected between May and August 2023 from hospitalized patients. Three instruments were employed to obtain data: a sociodemographic and clinical data questionnaire, the Edmonton Symptom Assessment Scale (ESAS-BR), and the Mindful Self-Care Scale (MSCS). For data analysis, descriptive statistics were used to characterize the participants, Student’s T-test was used for the other parametric tests, and variables with statistical evidence were selected for a linear regression model. Results: A statistically significant association was found between mindful self-care and symptoms of pain, tiredness, drowsiness, shortness of breath, depression, and malaise, with sleepiness being the only predictor of changes in this variable. Conclusions: Mindful self-care influences patients’ experience of symptoms, especially drowsiness, which predicts changes in self-care. Encouraging these practices reduces discomfort, enhances autonomy, and guides professionals in personalized care. Full article

Currently, citizens of the Western world are struggling with (1) the rapid growth and increasing densification of cities and (2) the excessive time spent of citizens indoors. This article aims to contribute to changing this paradigm through proposals for organizing outdoor spaces in schools that are easy to implement and that allow new generations to experience the multiple benefits of using the outdoors. To encourage such use, we propose using school outdoor spaces for teaching/learning activities, complementing spaces traditionally committed to play, sports, and peer socialization. The presented proposals were developed using a collaborative methodology involving the school community, supervised by final-year students and professors from the University of Lisbon’s MSc. in Architecture program. The results demonstrate a wide range of ideas capable of stimulating learning among children and young people, as well as encouraging teachers to increase outdoor teaching activities. The implementation of these proposals will certainly have a positive impact on the planning and construction/qualifying of cities, providing their citizens with greater and better use/enjoyment of outdoor space, as well as all the benefits associated with it. Full article

Effective resource planning in higher education requires anticipating student demand for courses, especially when dealing with elective programs. Monitoring student preference is a recurring topic in the literature; however, to the authors’ knowledge, no simple methods for estimating student preferences when choosing courses in higher education have been proposed. This study develops and explores the use of a simple questionnaire to capture patterns in student course preferences within a university context. The research is developed in the context of the nine Cross-Over modules offered as part of the curriculum of the master’s programs (MSc) of the Faculty of Civil Engineering and Geosciences of Delft University of Technology (The Netherlands). No prior registration is required far in advance for these courses, making an accurate estimation of student numbers critical for the planning and allocation of educational resources. The developed questionnaire is applied three times in two different academic years to the students’ choice of Cross-Over modules. The questionnaire was shared in 2021, with 225 responses out of 339 students, in 2022, with 159 responses out of 365 students, and in 2024, with 94 responses out of 272 students. Student enrollment in the academic year 2023/2024 is used to assess the performance of the questionnaire. The questionnaire is able to capture general preferences of the students, providing fair estimates of the number of students per course; larger differences are observed in courses with a lower number of students. In addition, some patterns were identified in student preferences: there is a relationship between the first and second choices, and students usually choose modules closer to their own disciplines. The developed questionnaire provides with a reasonable first estimation of the expected number of students in courses, allowing for better planning and allocation of educational resources beforehand. Full article

Pine nuts hold significant economic value due to their rich plant protein and healthy fats, yet precise variety classification has long been hindered by limitations of traditional techniques such as chemical analysis and machine vision. This study proposes a novel near-infrared (NIR) spectral feature selection algorithm, termed the improved binary equilibrium optimizer with selection probability (IBiEO-SP), which incorporates a dynamic probability adjustment mechanism to achieve efficient feature dimensionality reduction. Experimental validation on a dataset comprising seven pine nut varieties demonstrated that, compared to particle swarm optimization (PSO) and the genetic algorithm (GA), the IBiEO-SP algorithm improved average classification accuracy by 5.7% (p < 0.01, Student’s t-test) under four spectral preprocessing methods (MSC, SNV, SG1, and SG2). Remarkably, only 2–3 features were required to achieve optimal performance (MSC + random forest: 99.05% accuracy, 100% F1/precision; SNV + KNN: 97.14% accuracy, 100% F1/precision). Furthermore, a multimodal data synergy strategy integrating NIR spectroscopy with morphological features was proposed, and a classification model was constructed using a soft voting ensemble. The final classification accuracy reached 99.95%, representing a 2.9% improvement over single-spectral-mode analysis. The results indicate that the IBiEO-SP algorithm effectively balances feature discriminative power and model generalization needs, overcoming the contradiction between high-dimensional data redundancy and low-dimensional information loss. This work provides a high-precision, low-complexity solution for rapid quality detection of pine nuts, with broad implications for agricultural product inspection and food safety. Full article

A new graduate degree programme, Master of Science in Electric Vehicles (MScEV), for engineering students is presented, which is timely and vital for modern society. The purpose of this programme is to provide graduate students with up-to-date knowledge and skills that can enhance their career prospects in the fast-growing electric vehicle (EV) community. The programme not only provides technological knowledge in system design, operation, and management of EVs, but also involves research training in specific EV topics. This paper first outlines the rationale of the programme and reveals the shortcomings of existing EV education. Then, the curriculum structure of the newly developed MScEV programme as well as the corresponding core and elective courses are discussed. Finally, the findings of this programme are evaluated, indicating that the programme is attractive to an overwhelming number of students from diverse engineering backgrounds, as evidenced by the applicants’ and admittees’ degree qualifications and work experiences. Full article

This study proposes incorporating generative artificial intelligence large language models (LLMs) into the Master of Science (M.Sc.) curriculum on digitization in construction. The aim was to help students generate computer code to solve, automate, and streamline practical challenges in advanced construction engineering and management (CEM). To this end, a host of problem-based learning (PBL) individual assignments and collaborative team projects were developed, alongside a combination of flipped classroom models and blended learning lessons, in order to teach effective interactions with LLMs and mitigate concerns, such as bias and hallucination. The effective interaction with LLMs not only facilitated code generation, which would otherwise be complex without additional formal training, but also provided a platform for strengthening basic project management skills, such as departmentalization, work breakdown structuring, modularization, activity delegation, and defining key performance indicators. The effectiveness of this approach was quantitatively and qualitatively evaluated within two new modules, Digital Engineering and Construction and Digital Technologies in Field Information Modeling. These modules were offered over three semesters each as part of a new M.Sc. program in Technology and Management in Construction at the Karlsruhe Institute of Technology. It was observed that 86.4% of students fully completed the PBL projects, while the remaining 13.6% achieved over 50% completion across all six semesters. Furthermore, anonymous student surveys indicated a teaching quality index of 100% in five semesters and 96.4% in one semester. These preliminary results suggest that the proposed strategy can be used to effectively integrate LLMs to support students in code generation for open-ended projects in CEM. Further research was, however, found to be necessary to ensure the sustainable revision and redesign of the problems as LLM capabilities evolve. Full article

The presented work provides a comprehensive evaluation of the current availability of education programs and courses related to of AI the field of Information Technologies and Computer Science in higher education institutions (HIEs) in the Republic of Bulgaria. More specifically, this study examines 163 bachelor’s and 239 master’s degree programs from 28 HEIs available during the 2023/24 academic year in four professional fields: (1) Electrical Engineering, Electronics, and Automation; (2) Communication and Computer Technologies; (3) Informatics and Computer Science; and (4) Mathematics. The conducted evaluation shows that 41.1% of evaluated BSc programs and 26.4% of MSc programs include at least one AI-dedicated course. Results indicate a significant presence of AI-focused education, particularly in degrees related to Informatics and Computer Science, where 47.8% of AI courses are concentrated. However, a notable disparity exists in the inclusion of AI subjects across other technical fields, particularly in Electrical Engineering and related degrees, which contain only 8% of the identified AI courses for BSc degree programs. The findings highlight the need for a broader and more accelerated integration of AI education to meet the evolving demands of both students and the labor market. This work underscores the importance of strategic curriculum adaptation to enhance the readiness of Bulgarian HEIs to support the development and application of AI technologies, addressing the skills gap and fostering a workforce capable of navigating the AI-driven future. Full article

This study focused on vaccine hesitancy and decision regret about the COVID-19 vaccine among nursing students (BScN and MScN) and Registered Nurses (RNs) in Italy. The primary aim was to describe decision regret and vaccine hesitancy among these groups and to understand what influences vaccine hesitancy. Data were collected through an e-survey conducted from March to June 2024. The Decision Regret Scale and the Adult Vaccine Hesitancy Scale were employed to assess regret and hesitancy levels, assessing trust, concerns, and compliance regarding vaccination. Among the participants, 8.64% were not vaccinated. The results indicated moderate to high levels of decision regret and diverse levels of trust, concerns, and compliance with COVID-19 vaccination. Structural equation modeling revealed that decision regret significantly predicted Trust (R² = 31.3%) and Concerns (R² = 26.9%), with lower regret associated with higher trust and lower concerns about vaccine safety. The number of COVID-19 vaccine boosters was a significant predictor of Trust and Concerns, with more boosters associated with higher trust and lower concerns. MScN students exhibited higher Compliance compared to RNs (R² = 2.9%), highlighting the role of advanced education. These findings suggest that addressing decision regret and providing comprehensive vaccine information could enhance trust and compliance. Full article

Statistics modules are included in most university degrees, independent of the degree area, and this means that many students face these modules underprepared and struggle because of a lack of statistics knowledge. The Maths Support Centre (MSC) in the University College Dublin (UCD) provides support for various mathematics-related subjects, with statistics students being the second-largest cohort of visitors. The overall goal of this paper is to identify the common statistical issues students face during the transition from secondary education to tertiary education. The main data set for this study is the data from UCD students who have accessed the UCD MSC since 2015/16 for statistics support; the categorization of statistical concepts has been made with the statistics module description for each statistics subject at the Universidad Rey Juan Carlos (URJC). First, we conducted a categorization of statistical concepts taught in university (based on URJC’s catergorization); after that, UCD MSC tutor comments were categorized and validated, and subsequently descriptive analyses and text mining were used on the UCD MSC comments to achieve a deeper understanding of the statistical issues. The statistical issues presented were categorized as descriptive statistics (22.8%), probability (44%), statistical inference (29.2%), and statistical software (4%). Students struggled with material that was introduced at university level rather than material seen at secondary level. Our findings on students’ main statistical issues contribute to the development of a suite of evidence-based educational applications and games to support undergraduate students internationally in first- and second-year statistical modules. Full article

Our study investigated the effects of combining project-based learning (PBL) and flipped classroom (FC) methods in university education on the learning motivation and learning outcomes of students at the bachelor (BSc), master (MSc), and higher vocational education and training (HVET) levels. We aimed to explore how these modern teaching methods can influence students’ performance and motivation at different levels of education. The research used cross-sectional analysis and quantitative methods to evaluate the impact of FC and combined PBL and FC methods. This study followed groups of students for two academic years, comparing their results with control groups that did not benefit from the combined teaching method but were studied in a same FC environment. The results showed that students at the BSc and HVET levels significantly improved their learning motivation and achievement by combining PBL and FC methods (BSc: p = 0.0001248, HVET: p = 0.0485), while at the MSc level, this effect was not significant (p = 0.1000). These data support that an effective combination of PBL and FC methods can improve learning motivation and outcomes at certain levels of education, but further research is needed better to understand the effects for students at the MSc level. Full article

Background: Behaviorally informed interventions, such as nudging, encourage actions intended to promote longer and healthier lives. Holding significant potential for influencing health policies and healthcare practices, these interventions are partaking of a shift in governance and public health policymaking. However, a substantial knowledge gap remains regarding the feasibility and appropriateness of implementing policies that draw on nudge. Methods: Ae survey on nudge’s acceptability) was adapted to the Portuguese context to access attitudes towards 16 nudge measures. The research focused on evaluating attitudes among political science and public administration BSc and MSc students from nine Portuguese universities, and analyzing the relationship between these attitudes, sociodemographic characteristics, and sociopolitical attitudes. The data analysis involved the application of descriptive and inferential statistics. Results: The participants exhibited a moderate-to-high level of approval for various nudge measures, particularly those related to nutrition and public education/awareness raising. The study identified a nuanced relationship between the level of intrusiveness of nudges and their public approval, indicating that interventions preserving the architecture of choice gathered higher acceptance compared to more intrusive approaches. Notably, approval was associated with a high level of trust in social groups and a low propensity for risk-taking and alcohol consumption. Conclusions: This study not only sheds light on the types of nudge measures that are likely to be more acceptable for promoting healthy behaviors, but also establishes a crucial link between behavioral interventions and healthcare policies. Understanding the nuanced factors influencing the public acceptance of nudges contributes to the discourse on the implementation of behaviorally informed health policies and emphasizes the importance of tailoring interventions to align with public values and preferences. Full article

ChatGPT is an emerging tool that can be employed in many activities including in learning/teaching in universities. Like many other tools, it has its benefits and its drawbacks. If used properly, it can improve learning, and if used irresponsibly, it can have a negative impact on learning. The aim of this research is to study how ChatGPT can be used in academia to improve teaching/learning activities. In this paper, we study students’ opinions about how the tool can be used positively in learning activities. A survey is conducted among 430 students of an MSc degree in computer science at the University of Hertfordshire, UK, and their opinions about the tool are studied. The survey tries to capture different aspects in which the tool can be employed in academia and the ways in which it can harm or help students in learning activities. The findings suggest that many students are familiar with the tool but do not regularly use it for academic purposes. Moreover, students are skeptical of its positive impacts on learning and think that universities should provide more vivid guidelines and better education on how and where the tool can be used for learning activities. The students’ feedback responses are analyzed and discussed and the authors’ opinions regarding the subject are presented. This study shows that ChatGPT can be helpful in learning/teaching activities, but better guidelines should be provided for the students in using the tool. Full article

PBL is a widely used teaching approach that is increasingly incorporating digital components. Although, by its nature, a face-to-face approach is the preferred mode of delivery, its digital counterpart is gaining ground. The current paper discusses the digital redesign of PBL in an MSc in Biomedical Sciences. Face-to-face and online PBL followed the seven steps of the PBL process, and each case was completed in three sessions. For the delivery of online PBL, collaborative tools were utilized, including CiscoWebex, the online platform for synchronous meetings, and OneDrive, shareable PPT, and Moodle for synchronous and asynchronous self-directed learning. Three cohorts were followed, and students had both face-to-face and online PBL experiences. Student feedback was obtained using focus groups, and data analysis utilized a deductive and inductive approach. Our data indicate that CiscoWebex is a suitable and user-friendly platform for synchronous online PBL. The students enjoyed both formats and stated that online PBL is an effective teaching approach for promoting student learning. In regards to student interaction, the face-to-face mode was preferred, while online PBL was perceived as more organized. The redesign allowed for effective student learning and could pave the way forward for a fully online MSc program in Biomedical Sciences. Full article