poster voor de EuSoMII Annual Meeting in Pisa, Italië in oktober 2023. PURPOSE & LEARNING OBJECTIVE Artificial Intelligence (AI) technologies are gaining popularity for their ability to autonomously perform tasks and mimic human reasoning [1, 2]. Especially within the medical industry, the implementation of AI solutions has seen an increasing pace [3]. However, the field of radiology is not yet transformed with the promised value of AI, as knowledge on the effective use and implementation of AI is falling behind due to a number of causes: 1) Reactive/passive modes of learning are dominant 2) Existing developments are fragmented 3) Lack of expertise and differing perspectives 4) Lack of effective learning space Learning communities can help overcome these problems and address the complexities that come with human-technology configurations [4]. As the impact of a technology is dependent on its social management and implementation processes [5], our research question then becomes: How do we design, configure, and manage a Learning Community to maximize the impact of AI solutions in medicine?
poster voor de EuSoMII Annual Meeting in Pisa, Italië in oktober 2023. PURPOSE & LEARNING OBJECTIVE Artificial Intelligence (AI) technologies are gaining popularity for their ability to autonomously perform tasks and mimic human reasoning [1, 2]. Especially within the medical industry, the implementation of AI solutions has seen an increasing pace [3]. However, the field of radiology is not yet transformed with the promised value of AI, as knowledge on the effective use and implementation of AI is falling behind due to a number of causes: 1) Reactive/passive modes of learning are dominant 2) Existing developments are fragmented 3) Lack of expertise and differing perspectives 4) Lack of effective learning space Learning communities can help overcome these problems and address the complexities that come with human-technology configurations [4]. As the impact of a technology is dependent on its social management and implementation processes [5], our research question then becomes: How do we design, configure, and manage a Learning Community to maximize the impact of AI solutions in medicine?
This report presents research on success factors of learning communities with a case study of the Innovation Lab Hanze International Business Office (further – Innovation Lab HIBO) at Hanze University of Applied Sciences Groningen, the Netherlands. The research project is a part of the broader research programme on innovation of education and the success factors of learning communities carried on by a number of researchers at Hanze University of Applied Sciences Groningen (further – Hanze University AS).In answering the main research question on success factors of learning communities and, specifically, the Innovation Lab HIBO, two sub-questions were formulated: the first deals with school level expectations about the Innovation Lab HIBO, whereas the second explores what are the institutional expectations and guidelines regarding living labs at Hanze University AS. The research focus is on formalised expectations about the goals and outcomes of living labs, as attaining the established goals and outcomes would testimony a successful activity of a living lab. The factors that facilitate or determine whether the goalsand outcomes of living labs are achieved are therefore the success factors.The analysis of both school level expectations about the Innovation Lab HIBO and the institutional expectations and guidelines regarding living labs reveals a number of success factors, conditions, and preconditions. As these do not coincide, it is argued that finding the right balance between local, school level, expectations and the institutional goals is crucial for the successful performance of living labs. Another important factor for successful performance of the living lab and, specifically the Innovation Lab HIBO, is development of a learning community. This process would require strengthening of an open organisationalculture and facilitation of exchange of ideas and learning process.The research project was carried on in the period from February 1, 2020, till August 30, 2020. From September 2020 the follow up research is planned into operationalization of success factors, definition of performance criteria, performance evaluation, development of suggestions for improvement of performance, and development of a blueprint for the establishment of innovation labs.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
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.
Het project ‘App4Support – doorontwikkeling en validering’ ondersteunt vrijwillige jeugdtrainers om sportuitval te voorkomen bij kinderen met milde psychosociale problemen. Hoewel sporten belangrijk is voor hun fysieke en mentale gezondheid, haken juist deze kwetsbare kinderen vaak vroeg¬tijdig af op de sportclub. Dit project wil daar verandering in brengen door de app ‘App4Support’ die we recentelijk vanuit Hogeschool Winderheim tezamen met het bedrijfsleven, sportclubs en professionals hebben ontworpen, verder te ontwikkelen en te valideren. De app ‘App4Support’ is ontworpen om vrijwillige jeugdtrainers te ondersteunen in het pedagogisch verantwoord omgaan met moeilijk-te-verstaan gedrag van kinderen op de sportclub. De app biedt inzicht in gedragingen van kinderen en de aanleidingen hiervoor en geeft praktische tips voor vrijwillige jeugdtrainers, gebaseerd op wetenschappelijk onderzoek en praktijkkennis. We werken in dit project aan een uitgebreidere en gevalideerde versie van de recentelijk ontworpen app. Een belangrijk aandachtspunt daarbij is het toevoegen van een digitaal samenwerkings¬platform waarop jeugdtrainers en sportprofessionals kennis en ervaringen kunnen uitwisselen. Om een beeld te krijgen van de bruikbaarheid – oftewel ter validering – van deze volgende versie van de app creëren we een living lab-setting tijdens één van de vele sportfestivals die jaarlijks in ons land plaatsvinden. Onder de bezoekers van het sportfestival zal zich ongetwijfeld een aanzienlijk aantal vrijwillige jeugdtrainers bevinden. We nodigen deze jeugd¬trainers op het sportfestival uit om de app, inclusief het digitale samenwerkingsplatform, ter plekke te verkennen in een interactieve setting, met een focus op de gebruiksvriendelijkheid, relevantie en compleetheid van de app. Het doel van deze testcase is om waardevolle input te verzamelen voor de doorontwikkeling en validering van de app ‘App4Support’. Hierdoor zal de app zo goed mogelijk aansluiten bij de behoeftes van vrijwillige jeugdtrainers in de dagelijkse praktijk op sportclubs. Dat voorkomt sport¬uitval bij kwetsbare kinderen en draagt in die zin bij aan een inclusieve sportparticipatie.
