Research-based teacher education can be understood in different ways: as a call to understand teacher education institutions as research institutions, as the ambition to educate student teachers to have an inquiring attitude, as the basing of teacher education curricula on the latest research, or as a combination of all three.In this chapter we reflect on a method of connecting research, curriculum development and practice in teacher education, presenting a case study of a conversational community of teacher educators and researchers. The aim of the conversational community was to understand the process of curriculum design in teacher education as an inspiring and practical combination of design research, self-study, collaborative action research and curriculum study by teacher educators. This process was supported by a conversational framework in which curriculum development was understood as an ongoing dialogue between vision, intentions, design and practice in the teacher education curriculum. Using the conversational framework in this single case study of a conversational community, we have tried to connect teacher education research, curriculum development and practice in a meaningful way.
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Within the Erasmus+ project Common European Numeracy Framework (CENF) (2018-2021) a framework was developed on numeracy in response to the challenges and needs of the 21st century.
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Motor learning is particularly challenging in neurological rehabilitation: patients who suffer from neurological diseases experience both physical limitations and difficulties of cognition and communication that affect and/or complicate the motor learning process. Therapists (e.g.,, physiotherapists and occupational therapists) who work in neurorehabilitation are therefore continuously searching for the best way to facilitate patients during these intensive learning processes. To support therapists in the application of motor learning, a framework was developed, integrating knowledge from the literature and the opinions and experiences of international experts. This article presents the framework, illustrated by cases from daily practice. The framework may assist therapists working in neurorehabilitation in making choices, implementing motor learning in routine practice, and supporting communication of knowledge and experiences about motor learning with colleagues and students. The article discusses the framework and offers suggestions and conditions given for its use in daily practice.
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The hospitality industry in the Netherlands has been slow to adopt artificial intelligence (AI), despite its potential to improve service efficiency and address workforce challenges. While some industries have embraced AI agents—automated systems interacting with users—for customer service, hospitality adoption remains limited. Many hotels struggle to integrate AI in ways that enhance guest experiences while ensuring workforce sustainability, a paradox. Workforce sustainability means keeping employees skilled and adaptable. This research addresses this paradox observed in professional practice, focusing on three key gaps in AI integration: • Hotel employees lack the skills and knowledge to adapt to AI-enhanced workplaces. • Hotel managers lack clear AI strategies that maintain service quality and employee well-being, ensuring AI complements rather than replaces human service. • AI developers often lack a clear understanding of the hospitality industry’s specific needs, hindering the development of effective solutions. This leads to the central question: How can AI agents be co-developed by hotel professionals and technical experts to enhance service efficiency while supporting a sustainable hospitality workforce? A one-year KIEM project provides the ideal framework for an agile, practice-based investigation in real hospitality environments. The project will unfold in four phases: (1) co-developing conversational AI chatbots with hotel businesses and technology providers, (2) testing the chatbot integration in hotels, (3) evaluating the impact on service efficiency and workforce sustainability, and (4) initiating a community of AI agent practice in service industry. Conducted in collaboration with industry partners, the research ensures findings are directly applicable to real-world hospitality challenges. By bridging academic research and industry needs, this project will generate insights into AI-driven service innovations that benefit hotel operations, employees, and AI developers. Beyond hospitality, its findings will offer scalable strategies for responsible AI adoption in sectors like healthcare, banking, and retail, fostering a more sustainable future of work.
