To adequately deal with the challenges faced within residential care for older people, such as the increasing complexity of care and a call for more person-centred practices, it is important that health care providers learn from their work. This study investigates both the nature of learning, among staff and students working within care for older people, and how workplace learning can be promoted and researched. During a longitudinal study within a nursing home, participatory and democratic research methods were used to collaborate with stakeholders to improve the quality of care and to promote learning in the workplace. The rich descriptions of these processes show that workplace learning is a complex phenomenon. It arises continuously in reciprocal relationship with all those present through which both individuals and environment change and co-evolve enabling enlargement of the space for possible action. This complexity perspective on learning refines and expands conventional beliefs about workplace learning and has implications for advancing and researching learning. It explains that research on workplace learning is itself a form of learning that is aimed at promoting and accelerating learning. Such research requires dialogic and creative methods. This study illustrates that workplace learning has the potential to develop new shared values and ways of working, but that such processes and outcomes are difficult to control. It offers inspiration for educators, supervisors, managers and researchers as to promoting conditions that embrace complexity and provides insight into the role and position of self in such processes.
Nationwide and across the globe, the quality, affordability, and accessibility of home-based healthcare are under pressure. This issue stems from two main factors: the rapidly growing ageing population and the concurrent scarcity of healthcare professionals. Older people aspire to live independently in their homes for as long as possible. Additionally, governments worldwide have embraced policies promoting “ageing in place,” reallocating resources from institutions to homes and prioritising home-based services to honour the desire of older people to continue living at home while simultaneously addressing the rising costs associated with traditional institutional care.Considering the vital role of district nursing care and the fact that the population of older people in need of assistance at home is growing, it becomes clear that district nursing care plays a crucial role in primary care. The aim of this thesis is twofold: 1) to strengthen the evidence base for district nursing care; and 2) to explore the use of outcomes for learning and improving in district nursing care. The first part of this thesis examines the current delivery of district nursing care and explores its challenges during the COVID-19 pandemic to strengthen the evidence base and get a better understanding of district nursing care. Alongside the goal of strengthening the evidence for district nursing care, the second part of this thesis explores the use of patient outcomes for learning and improving district nursing care. It focuses on nurse-sensitive patient outcomes relevant to district nursing care, their current measurement in practice, and what is needed to use outcomes for learning and improving district nursing practice.
To enhance the training of sport psychology consultants, it is important to know which learning experiences are useful for which components of professional development. We interviewed 15 novice consultants on their learning experiences related to 13 different topics. Traditional learning experiences (e.g., courses, teachers) were related to the development of practical know-how. Learning from others (e.g., peers, colleagues) was related to professional development (i.e., dealing with issues, challenges, and dilemmas that occur in sport psychology practice). Practical experience and reflective activities were related to both know-how and professional development. These results can be used to shape effective sport psychology education.
Horse riding falls under the “Sport for Life” disciplines, where a long-term equestrian development can provide a clear pathway of developmental stages to help individuals, inclusive of those with a disability, to pursue their goals in sport and physical activity, providing long-term health benefits. However, the biomechanical interaction between horse and (disabled) rider is not wholly understood, leaving challenges and opportunities for the horse riding sport. Therefore, the purpose of this KIEM project is to start an interdisciplinary collaboration between parties interested in integrating existing knowledge on horse and (disabled) rider interaction with any novel insights to be gained from analysing recently collected sensor data using the EquiMoves™ system. EquiMoves is based on the state-of-the-art inertial- and orientational-sensor system ProMove-mini from Inertia Technology B.V., a partner in this proposal. On the basis of analysing previously collected data, machine learning algorithms will be selected for implementation in existing or modified EquiMoves sensor hardware and software solutions. Target applications and follow-ups include: - Improving horse and (disabled) rider interaction for riders of all skill levels; - Objective evidence-based classification system for competitive grading of disabled riders in Para Dressage events; - Identifying biomechanical irregularities for detecting and/or preventing injuries of horses. Topic-wise, the project is connected to “Smart Technologies and Materials”, “High Tech Systems & Materials” and “Digital key technologies”. The core consortium of Saxion University of Applied Sciences, Rosmark Consultancy and Inertia Technology will receive feedback to project progress and outcomes from a panel of international experts (Utrecht University, Sport Horse Health Plan, University of Central Lancashire, Swedish University of Agricultural Sciences), combining a strong mix of expertise on horse and rider biomechanics, veterinary medicine, sensor hardware, data analysis and AI/machine learning algorithm development and implementation, all together presenting a solid collaborative base for derived RAAK-mkb, -publiek and/or -PRO follow-up projects.
Electronic Sports (esports) is a form of digital entertainment, referred to as "an organised and competitive approach to playing computer games". Its popularity is growing rapidly as a result of an increased prevalence of online gaming, accessibility to technology and access to elite competition.Esports teams are always looking to improve their performance, but with fast-paced interaction, it can be difficult to establish where and how performance can be improved. While qualitative methods are commonly employed and effective, their widespread use provides little differentiation among competitors and struggles with pinpointing specific issues during fast interactions. This is where recent developments in both wearable sensor technology and machine learning can offer a solution. They enable a deep dive into player reactions and strategies, offering insights that surpass traditional qualitative coaching techniquesBy combining insights from gameplay data, team communication data, physiological measurements, and visual tracking, this project aims to develop comprehensive tools that coaches and players can use to gain insight into the performance of individual players and teams, thereby aiming to improve competitive outcomes. Societal IssueAt a societal level, the project aims to revolutionize esports coaching and performance analysis, providing teams with a multi-faceted view of their gameplay. The success of this project could lead to widespread adoption of similar technologies in other competitive fields. At a scientific level, the project could be the starting point for establishing and maintaining further collaboration within the Dutch esports research domain. It will enhance the contribution from Dutch universities to esports research and foster discussions on optimizing coaching and performance analytics. In addition, the study into capturing and analysing gameplay and player data can help deepen our understanding into the intricacies and complexities of teamwork and team performance in high-paced situations/environments. Collaborating partnersTilburg University, Breda Guardians.
The textile industry is responsible for over 8% of global greenhouse gas emissions and 20% of the world’s wastewater, surpassing the emissions from international flights and shipping combined. In the European Union, textile purchases in 2020 led to around 270 kg of CO₂ emissions per person, yet only 1% of used clothing is recycled into new garments. The municipality of Groningen manages an estimated 950 kilotons of textile waste but is only able to collect, sort, and recycle 250 kilotons. To address these challenges, Textile Hub Groningen (THG) seeks to support small and medium-sized enterprises (SMEs) and stakeholders in creating circular textile value chains. However, designing circular value chains presents challenges, including conflicting interests, knowledge gaps on circular design principles, and inadequate tools for collaborative business model development. Potential stakeholders often find current tools too abstract and not conducive to collaboration, learning, or experimentation. As a result, circular value chains remain difficult to achieve from the perspective of individual stakeholders. Serious games have been employed to simulate and experiment with complex adaptive systems , . Research shows that well-designed playful learning enhances both learning and motivation, particularly when social elements are integrated . This project aims to answer the following research question: How can serious games be leveraged to design circular textile value chains in the region? The expected outcomes are: 1. Serious Game: Design, test, and deliver a serious game to facilitate the joint design of circular textile value chains. 2. Publications: Extract insights from the game’s design and evaluation, contributing to both academic and practical discussions. 3. Consortium for Follow-up: Mobilize partners and secure funding for future projects in related fields. Through game-based collaborative circular value chain and business model design experiences, this project overcomes barriers in designing viable circular value chains in the textile industry
