Students often struggle with constructing models of system behaviour, particularly in open modelling tasks where there is no single correct answer. The challenge lies in providing effective support that helps students develop high quality models while maintaining their autonomy in the modelling process. This study presents a procedure for assessing the quality of student-generated qualitative models in open modelling tasks, based on three characteristics: correctness, parsimony, and completeness. The procedure was developed and refined using student-generated models from two secondary school tasks on thermoregulation and sound properties. The findings contribute to the development of automated support systems that guide students through open modelling tasks by focusing on quality characteristics rather than adherence to a predefined norm model.
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Background: The dynamics of maternal and newborn care challenge midwifery education programs to keep up-to-date. To prepare for their professional role in a changing world, role models are important agents for student learning. Objective: To explore the ways in which Dutch and Icelandic midwifery students identify role models in contemporary midwifery education. Methods: We conducted a descriptive, qualitative study between August 2017 and October 2018. In the Netherlands, 27 students participated in four focus groups and a further eight in individual interviews. In Iceland, five students participated in one focus group and a further four in individual interviews. All students had clinical experience in primary care and hospital. Data were analyzed using inductive content analysis. Results: During their education, midwifery students identify people with attitudes and behaviors they appreciate. Students assimilate these attitudes and behaviors into a role model that represents their ‘ideal midwife’, who they can aspire to during their education. Positive role models portrayed woman-centered care, while students identified that negative role models displayed behaviors not fitting with good care. Students emphasized that they learnt not only by doing, they found storytelling and observing important aspects of role modelling. Students acknowledged the impact of positive midwifery role models on their trust in physiological childbirth and future style of practice. Conclusion: Role models contribute to the development of students’ skills, attitudes, behaviors, identity as midwife and trust in physiological childbirth. More explicit and critical attention to how and what students learn from role models can enrich the education program.
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This paper presents three qualitative models that were developed for the Stargazing Live! program. This program consists of a mobile planetarium that aims to inspire and motivate learners using real telescope data during the experience. To further consolidate the learning experience three lessons are available that teachers can use as follow up activities with their learners. The lessons implement a pedagogical approach that focuses on learning by creating qualitative models with the aim to have learners learn subject specific concepts as well as generic systems thinking skills. The three lessons form an ordered set with increasing complexity and were developed in close collaboration with domain experts.
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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.
In line with European sustainability goals, small and medium sized enterprises (SMEs) in the Dutch automotive aftermarket face the challenge of maintaining competitiveness while transitioning to circular business models. These models, supported by EU policies such as the Circular Economy Action Plan and the European Green Deal, drive innovation in product lifecycle management, recycling, and sustainability. However, as SMEs adapt to these changes, they must also navigate the growing competition from imported Chinese electric vehicles (EVs), which bring both opportunities and risks. Logistics plays a critical role in this transition, as optimizing supply chains, enhancing resource efficiency, and minimizing waste are essential for achieving circularity. Will the Chinese car manufacturers move their value chain to Europe? Or will they further localize in aftersales businesses? Either scenario would affect a chain of SMEs in automotive aftermarket. Focusing on the auto parts SMEs in the Brainport region, this research examines how SMEs can stay competitive by leveraging logistics strategies to support circular practices, and navigate the challenges posed by the influx of Chinese EVs while remaining resilient and adaptable in the automotive aftermarket value chain. Together with our consortium partners, we help the regional SMEs in the automotive aftermarket with: 1. Mapping out logistical challenges and objectives, 2. Risk mitigation and demand planning, 3. Strategic supply chain development. Involving Fontys International Business graduation projects on data analysis, this project combines quantitative and qualitative insights to examine the transition of automotive aftermarket to an EV-dominated future. The SMEs in our consortium network are drive to adapt to the evolving landscape by investing in new measures. Through scenario assessment, we help them with scenario strategies in circular transition. For a broader impact, this project brings SMEs, branch and public organizations together and presents shared responsibilities in creating a resilient supply chain.
While several governmental and research efforts are set upon mobility-as-a-service (MaaS), most of them are driven by individual travel behavior and potential usage. Scholars argue that this is a too narrow perspective when evaluating government projects because choices individuals make in a private setting might not accurately reflect their preferences towards public policy. Participatory Value Evaluation (PVE) is a novel evaluation framework specifically designed to alleviate this issue by analyzing preferences on the allocation of public budgets. Thus, based on PVE, this project aims at assessing different features of MaaS-services (e.g. enhancing mobility of the elderly and the poor, complementing public transport, etc.) from a social desirability perspective and compare them with investments in alternative social projects. Specifically, it aims at establishing the citizen value of MaaS as compared to social investments in green/recreational areas or transport infrastructure (e.g. bike or bus lanes), and eliciting trade-offs between different features of them. The project includes the selection of different investment projects (and their features) that are politically relevant in Rotterdam. It also includes a qualitative assessment on the way individuals evaluate different social projects and their features and a quantitative assessment based on choice models that allow eliciting trade-offs between different attributes and projects. Finally, policy recommendations are provided based on these results. They allow conceiving investments projects to maximize the societal benefits as well as to construct optimal investment portfolios. This information is to be used as a complement of the evaluation of projects on the basis of individual preferences.
