More than 45,000 international students are now studying for bachelor programs in the Netherlands. The number of Asian students increased dramatically in the past decade. The current research aims at examining the differences between Western European and Asian students’ perceptual learning styles, and exploring the relationships between students’ learning styles and their academic achievements in international business (IB) study. One hundred and seventy-two students from a Dutch university participated in the survey research. Western European students significantly outperformed Asian studentsin academic performances. Significant differences in learning styles were also found between Western Europeans and Asian students in English, second language, business subjects, and group project learning. Besides, in comparison with Asian students, Western European students preferredto learn from hearing words, taking notes of lectures, and getting involved in some classroom experiences such as role-playing. They may benefit more from lecture-based subjects than Asian students.Based on the findings, practical recommendations are offered for instructors in international higher education
Although previous research programs have yielded valuable knowledge that can help sugar beet growers to innovate farming processes, actual transfer of this knowledge to the growers so far is lacking. Currents ways of knowledge transfer do not match learning styles, personal traits or the social environment of previously identified groups of growers. The current research was designed to asses to which level new means of knowledge transfer are suitable: using both digital means, e.g., decision support systems, and other means, e.g. study groups, knowledge transfer can be re-assessed to form specific inspiring learning environments.A survey study assessed learning styles, attitudes toward innovation, personality traits related to entrepreneurship and the social network growers use to obtain new knowledge. These data were linked to the crop yield data over the previous five years, to be able to compare the influence of learning styles, attitudes, network and individual differences on the occurrence and effectiveness of certain types of innovative behaviour. Results indicate that different learning styles correlate with different ways of using one's knowledge network: for instance, people who are more prone to seek help, have significantly more contacts and exchange more knowledge within their networks. Growers whom significantly participate more in meetings and interactions with colleagues, produce an above average crop yield, as compared to other groups. The innovation attitude appeared to predict the innovation intention of growers; people with more positive attitudes are more willing to try new ideas and implement not fully tested techniques than growers with less positive attitudes toward innovation. Knowledge networks are comprised of fellow growers, friends, family, but mostly the growers receive their knowledge from advisors, suppliers and study groups. Preferences for learning and innovating correlate with the size of the network, and how intensively it is used.
This study examines the relationships between students’ perceptions of heavy study load, time spent on learning, study strategies, and learning outcomes. Student’s study strategies were measured with a short version of Vermunt’s Inventory of Learning Styles. It was possible to replicate 5 processing and 5 regulation strategies. The higher order dimensions meaning directed learning style (relate and structure, concrete processing, critical processing) and reproduction directed learning style (memorize and repeat, analyze, self-regulation of contents, process and results, external regulation of the learning process) differed from Vermunt. The scales showed differences across groups, which is in line with previous research. Linear structural analysis showed that reproduction directed learning precedes meaning directed learning. Only meaning directed learning affected GPA, the influence of the two learning styles on ECs was not evidenced in this study. Contact hours influenced ECs, but this effect was tempered through its negative association with a heavy study load. The limitations, implications for practice, and directions for further research and development will be discussed in the round table.
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.
Despite the recognized benefits of running for promoting overall health, its widespread adoption faces a significant challenge due to high injury rates. In 2022, runners reported 660,000 injuries, constituting 13% of the total 5.1 million sports-related injuries in the Netherlands. This translates to a disturbing average of 5.5 injuries per 1,000 hours of running, significantly higher than other sports such as fitness (1.5 injuries per 1,000 hours). Moreover, running serves as the foundation of locomotion in various sports. This emphasizes the need for targeted injury prevention strategies and rehabilitation measures. Recognizing this social issue, wearable technologies have the potential to improve motor learning, reduce injury risks, and optimize overall running performance. However, unlocking their full potential requires a nuanced understanding of the information conveyed to runners. To address this, a collaborative project merges Movella’s motion capture technology with Saxion’s expertise in e-textiles and user-centered design. The result is the development of a smart garment with accurate motion capture technology and personalized haptic feedback. By integrating both sensor and actuator technology, feedback can be provided to communicate effective risks and intuitive directional information from a user-centered perspective, leaving visual and auditory cues available for other tasks. This exploratory project aims to prioritize wearability by focusing on robust sensor and actuator fixation, a suitable vibration intensity and responsiveness of the system. The developed prototype is used to identify appropriate body locations for vibrotactile stimulation, refine running styles and to design effective vibration patterns with the overarching objective to promote motor learning and reduce the risk of injuries. Ultimately, this collaboration aims to drive innovation in sports and health technology across different athletic disciplines and rehabilitation settings.
