Across the globe, linguistically heterogeneous populations increasingly define school systems at the same time that developing the ability to communicate cross-culturally is becoming essential for internationalized economies. While these trends seem complimentary, they often appear in paradoxical opposition as represented in the content and execution of nationwide education policies. Given the differing geopolitical contexts within which school systems function, wide variation exists with regard to how policymakers address the challenges of providing language education, including how they frame goals and design programs to align with those goals. Here we present a cross-continental examination of this variation, which reveals parallel tensions among aims for integrating immigrant populations, closing historic achievement gaps, fostering intercultural understanding, and developing multilingual competencies. To consider implications of such paradoxes and parallels in policy foundations, we compare language education in the US and in the EU, focusing on the Netherlands as an illustrative case study.
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While Communicative Language Teaching (CLT) is recognised as an effective approach worldwide, its implementation in foreign language (FL) classrooms remains difficult. Earlier studies have identified factors impeding CLT implementation, such as a lack of communicative lesson materials or teachers' more traditional views on language learning. In the Netherlands, CLT goals have been formulated at the national level, but are not always reflected in daily FL teaching and assessment practice. As constructive alignment between learning goals, classroom activities and assessments is a precondition for effective teaching, it is important to gain a deeper understanding of the degree of alignment in Dutch FL curricula and the factors influencing it. The current study therefore aims to take a systematic inventory of classroom practices regarding the translation of national CLT goals into learning activities and assessments. Findings revealed that teaching activities and classroom assessments predominantly focused on grammar knowledge and vocabulary out of context and, to a lesser extent, on reading skills. External factors, such as teaching and testing materials available, and conceptual factors, such as teachers' conceptions of language learning, were identified to contribute to the observed lack of alignment. Assessments in particular seem to exert a negative washback effect on CLT implementation.
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.
De bereikbaarheid en beschikbaarheid van de ambulancezorg staat onder druk. Een belangrijke ingangsklacht van de mensen die 112 bellen is een kortdurende bewusteloosheid. Als deze bewusteloosheid het gevolg is van een verminderde bloedtoevoer in de hersenen noemen we het syncope. Syncope kan onschuldig of ernstig van aard zijn. De risico-inschatting en besluitvorming bij patiënten met syncope in de ambulancezorg is complex. Ambulanceprofessionals moeten in een kort tijdsbestek en onder hoge druk, met veel onderliggende informatie en onzekerheden risico’s inschatten en besluiten of een patiënt ingestuurd moet worden naar de spoedeisende hulp. Bij twee-derde van de ingestuurde syncope patiënten blijkt het niet ernstig te zijn. Twee HAN lectoraten ontwikkelden praktische en onderbouwde handvatten voor de praktijk (RAAK.PUB05.017 en RAAK.IMP.01.036). Deze zijn sinds juli 2022 onderdeel van de landelijke werkwijze. In vervolg hierop heeft de praktijk de lectoraten gevraagd om te kijken of de inzet van digitale- en informatietechnologie, specifiek generatieve kunstmatige intelligentie (AI) op basis van Large Language Models (LLM), hen nog verder kan ondersteunen bij het inschatten van risico’s en besluiten maken bij patiënten met syncope in de ambulancezorg. Deze KIEM-aanvraag is een proof of concept studie. We onderzoeken in hoeverre generatieve AI op basis van LMM technisch goed tekstbestanden kan analyseren op belangrijke medische- en omgevingsfactoren bij patiënten met een syncope. We kiezen voor een pilot concurrente validatiestudie door kwalitatieve tekstanalyse, in combinatie met aanvullende focusgroepinterviews voor de interpretatie van de uitkomsten. Voor de pilot concurrente validatiestudie gebruiken we tekstbestanden uit de Safe End studie. De eerdere analyse van deze tekstbestanden uit de Safe End studie fungeert als de gouden standaard. Zo wordt de validiteit van de generatieve AI-analyse op basis van LMM vastgesteld. In focusgroepinterviews bespreken we de impact en ethische aspecten van de bevindingen voor de praktijk, wetenschap, onderwijs en de (door)ontwikkeling van beslissingsondersteuningsinstrumenten voor de toekomst.
