Een bekend probleem: je hebt je net op een nieuwe dienst geabonneerd of een nieuw apparaat gekocht en je krijgt bepaalde functies niet aan de praat. Of, je hebt een nieuw softwarepakket aangeschaft, dit op je PC geïnstalleerd en er duikt allerlei narigheid op. Bijvoorbeeld, die handige integratie van het net gekochte elektronische woordenboek met Microsoft Office op je Windows XP-machine komt niet tot stand. Erger nog: Office gedraagt zich plotseling instabiel. Hoe los je als gebruiker dit soort problemen op? De dienstinstructies, de handleiding van het apparaat of de helpfuncties van de softwarepakketten bieden geen uitkomst. In FAQ’s zoeken op de websites van leveranciers en producenten levert ook geen antwoord op. Bellen met helpdesks en de winkel geeft na vele minuten van irritante wachtkamermuziek ook geen uitkomst. E-mailen leidt uitsluitend tot nietszeggende, door een mailrobot vervaardigde antwoorden. Of tot helemaal geen antwoord. Kortom: dit moet beter kunnen. En anders bedenk je je een volgende keer minstens tien keer of je die nieuwe dienst, dat nieuwe apparaat of dat nieuwe softwarepakket eigenlijk wel wilt hebben.
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Design education has a nuanced relationship with examples. Although they are considered useful teaching tools, their use is often restricted to illustrating the design theories and principles around which the curriculum is structured. In contrast, professional designers view examples as autonomous entities and use them to initiate a critical dialogue with their current problem space. Therefore, students should be facilitated in cultivating their own repertoire of solutions and learn to initiate conversations between existing solutions and design challenges to gain a better understanding of the problem space and generate new designs. This paper outlines a small-scale experiment conducted with master's students in Applied Data Science at Utrecht University who took a course on designing recommender system interfaces. The students were provided with a set of examples of recommender interface designs as their main instructional tool. They could use this set to curate their own solution repertoire. As a result, the majority of the participants' work displayed more diverse designs, and they used design patterns distilled from those examples generatively, developing innovative designs. Based on this case study, we tentatively conclude that a design curriculum built around examples, complemented by theories, could be advantageous, as long as special attention is given to helping students initiate fruitful iterations between their challenges and a set of solutions.
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In the course of our supervisory work over the years we have noticed that qualitative research tends to evoke a lot of questions and worries, so-called frequently asked questions (FAQs). This series of four articles intends to provide novice researchers with practical guidance for conducting high-quality qualitative research in primary care. By ‘novice’ we mean Master’s students and junior researchers, as well as experienced quantitative researchers who are engaging in qualitative research for the first time. This series addresses their questions and provides researchers, readers, reviewers and editors with references to criteria and tools for judging the quality of qualitative research papers. The first article provides an introduction to this series. The second article focused on context, research questions and designs. The third article focused on sampling, data collection and analysis. This fourth article addresses FAQs about trustworthiness and publishing. Quality criteria for all qualitative research are credibility, transferability, dependability, and confirmability. Reflexivity is an integral part of ensuring the transparency and quality of qualitative research. Writing a qualitative research article reflects the iterative nature of the qualitative research process: data analysis continues while writing. A qualitative research article is mostly narrative and tends to be longer than a quantitative paper, and sometimes requires a different structure. Editors essentially use the criteria: is it new, is it true, is it relevant? An effective cover letter enhances confidence in the newness, trueness and relevance, and explains why your study required a qualitative design. It provides information about the way you applied quality criteria or a checklist, and you can attach the checklist to the manuscript.
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