In summarizing the research on collaborative learning, the quest for the holy grail of effective collaborative learning has not yet ended. The use of the GLAID framework tool for the design of collaborative learning in higher education may contribute to better aligned designs and hereby contribute to more effective collaborative learning. The GLAID framework may help monitor, evaluate and redesign projects and group assignments. We know that the perception of the quality of the task, and the extent to which students feel engaged, influences the perception of students of how much they learn from a GLA. However, perceptions alone are only an indication of what is learned. A next step is to study exactly what those learning outcomes are. This leads to a more difficult question: how can we measure the learning outcomes? Although a variety of research underlines the large potential of collaboration for learning outcomes, the exact learning outcomes of team learning can only be partly foretold. During collaborative learning students could partly achieve the same or similar learning outcomes, but as each individual learning internalizes what is learned from the collaborative learning by his/her given prior experiences and knowledge, the learning outcomes of collaborative learning are probabilistic (Strijbos, 2011), and therefore attaining specific learning outcomes is likely but not guaranteed. If learning outcomes are different per individual and are probabilistic, how can we measure those learning outcomes? Wenger, Trayner, & De Laat (2011) regard the outcomes of learning communities as value creations that have an individual outcome and a group outcome. This value creation induced by collaborative learning consists, for example, of changed behaviour in the working environment as well as the production of useful products or artefacts. Tillema (2006) also describes that communities of inquiry can lead to the design of conceptual artefacts: products that are useful for a professional working environment.
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Study of new networks that are currently emerging in the local energy initiatives.
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This is the second edition of the Startup Workbook. This workbook is different from the first version. The first version, which was made with a so called touch-grant from Saxion, was primarily a digital version. In addition, the book was printed as a deluxe edition in a limited number of copies. The eBook has quickly been downloaded thousands of times through the website (www.startupwerkboek.nl). By using the Startup Work-book by Startups in the Startup Center Saxion (part of the Center for Entrepreneurship) it was revealed that one has a need to really use it as a workbook. That is, the questions that are in the book, must be filled in. Some Startups printed out the downloaded version, to be able to use it for writing answers. The printed version has therefore become a real book. That means that the questions can be answered directly in the book. It is in a writable form. If you have access to the Toolbox, you can also fill in the online questionnaire after each step, which you then will get mailed back. If required we can then remotely assist you with your cus-tomer development based on your reply. Another change in this version is that the business devel-opment trajectory isn’t spread over 12 weeks, but spread over 12 steps. A startup probably needs a week for a certain step, whereas another startup may sometimes need more time. This second edition is still primarily an eBook, which is free to download. The advantage of the eBook is that adjustments can be made quickly (the knowledge and methodologies for startups go so fast), and direct links to other website can be used easier when presented in an electronic way.
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The transition towards an economy of wellbeing is complex, systemic, dynamic and uncertain. Individuals and organizations struggle to connect with and embrace their changing context. They need to create a mindset for the emergence of a culture of economic well-being. This requires a paradigm shift in the way reality is constructed. This emergence begins with the mindset of each individual, starting bottom-up. A mindset of economic well-being is built using agency, freedom, and responsibility to understand personal values, the multi-identity self, the mental models, and the individual context. A culture is created by waving individual mindsets together and allowing shared values, and new stories for their joint context to emerge. It is from this place of connection with the self and the other, that individuals' intrinsic motivation to act is found to engage in the transitions towards an economy of well-being. This project explores this theoretical framework further. Businesses play a key role in the transition toward an economy of well-being; they are instrumental in generating multiple types of value and redefining growth. They are key in the creation of the resilient world needed to respond to the complex and uncertain of our era. Varta-Valorisatielab, De-Kleine-Aarde, and Het Groene Brein are frontrunner organizations that understand their impact and influence. They are making bold strategic choices to lead their organizations towards an economy of well-being. Unfortunately, they often experience resistance from stakeholders. To address this resistance, the consortium in the proposal seeks to answer the research question: How can individuals who connect with their multi-identity-self, (via personal values, mental models, and personal context) develop a mindset of well-being that enables them to better connect with their stakeholders (the other) and together address the transitional needs of their collective context for the emergence of a culture of the economy of wellbeing?
Drones have been verified as the camera of 2024 due to the enormous exponential growth in terms of the relevant technologies and applications such as smart agriculture, transportation, inspection, logistics, surveillance and interaction. Therefore, the commercial solutions to deploy drones in different working places have become a crucial demand for companies. Warehouses are one of the most promising industrial domains to utilize drones to automate different operations such as inventory scanning, goods transportation to the delivery lines, area monitoring on demand and so on. On the other hands, deploying drones (or even mobile robots) in such challenging environment needs to enable accurate state estimation in terms of position and orientation to allow autonomous navigation. This is because GPS signals are not available in warehouses due to the obstruction by the closed-sky areas and the signal deflection by structures. Vision-based positioning systems are the most promising techniques to achieve reliable position estimation in indoor environments. This is because of using low-cost sensors (cameras), the utilization of dense environmental features and the possibilities to operate in indoor/outdoor areas. Therefore, this proposal aims to address a crucial question for industrial applications with our industrial partners to explore limitations and develop solutions towards robust state estimation of drones in challenging environments such as warehouses and greenhouses. The results of this project will be used as the baseline to develop other navigation technologies towards full autonomous deployment of drones such as mapping, localization, docking and maneuvering to safely deploy drones in GPS-denied areas.
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.
Lectoraat, onderdeel van NHL Stenden Hogeschool
