Wat is de beroepsidentiteit van sociaal werk, wat behoort zij te zijn? Sociaal werk wordt wel omschreven als een professie maar ook als een ambacht, vaak zonder duidelijk onderscheid tussen en wellicht zelfs door impliciete gelijkstelling van deze kwalificaties. Met behulp van de ideaaltypische benadering kan echter worden aangetoond dat deze twee typen beroepen niet alleen veel overeenkomsten delen maar ook op enkele punten fundamenteel van elkaar verschillen. Op basis van het werk van Freidson (2001) en Sennett (2008) kan worden aangetoond dat het ideaaltypische doel van professies het realiseren van een abstracte waarde (zoals rechtvaardigheid) is, terwijl ambachten gericht zijn op het manipuleren van concrete materialen (bijvoorbeeld steen). Bijgevolg zijn (enkel) professies beroepen met een morele identiteit. In alle zelfdefinities van sociaal werk is deze morele identiteit, deze humanitaire kern aanwezig (zie bv. IFSW, NVMW). Daarom moet sociaal werk worden beschouwd als een professie en niet als een ambacht. Dit is niet louter een academische discussie maar beïnvloedt bijvoorbeeld de positie van dit beroep in de samenleving, zoals aan de hand van de ministeriële richtlijnen betreffende Welzijn Nieuwe Stijl kan worden geïllustreerd.
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Students’ health profession education includes learning at the workplace through placements. For students, participating in daily work activities in interaction with supervisors, co-workers and peers is a valuable practice to learn the expertise that is needed to become a health care professional. To contribute to the understanding of HPE-students’ workplace learning, the focus of this study is to identify affordances and characterise student’s participation during placements. We applied a research design based on observations. Three student-physiotherapists and four student-nurses were shadowed during two of their placement days. A categorisation of affordances is provided, in terms of students’ participation in activities, direct interactions and indirect interactions. Students’ daily participation in placements is discussed through unique combinations and sequences of the identified affordances reflecting changing patterns over time, and differences in the degree of presence or absence of supervisors, co-workers and peers.
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A social media architect is an appealing new profession that entails crossovers between communication and IT & Design. There are no study programmes for this job. Important questions are how to interest secondary school pupils for such a new job, and how to prepare them for these jobs or jobs that do not even exist today? This research aims to set an example by presenting a realistic job profile of a social media architect by linking the ‘21st century skills’ to the context in which he/she operates.
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Although basic features of journalism have remained the same over the last decades, the tasks journalists perform, the skills they need and the position they have within news organizations have changed dramatically. Usually the focus in the discourse on changes in journalism is on skills, especially on technical multi-media skills or research skills. In this paper we focus on changes in professional roles of journalists, arguing that these roles have changed fundamentally, leading to a new generation of journalists. We distinguish between different trends in journalism. Journalism has become more technical, ranging from editing video to programming. At the same time, many journalists are now more ‘harvesters’ and ‘managers’ of information and news instead of producers of news. Thirdly, journalists are expected to gather information from citizens and social media, and edit and moderate user-contributions as well. Lastly, many journalists are no longer employed by media but work as freelancers or independent entrepreneurs. We track these trends and provide a detailed description of developments with examples from job descriptions in the Netherlands.
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In my previous post on AI engineering I defined the concepts involved in this new discipline and explained that with the current state of the practice, AI engineers could also be named machine learning (ML) engineers. In this post I would like to 1) define our view on the profession of applied AI engineer and 2) present the toolbox of an AI engineer with tools, methods and techniques to defy the challenges AI engineers typically face. I end this post with a short overview of related work and future directions. Attached to it is an extensive list of references and additional reading material.
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Abstract Study Objective To provide an overview of patients' needs concerning goal‐setting, and indications of how those needs can be met by nurses. Methods A narrative review. Pubmed and Cinahl were searched through March 1, 2020 for: patients' experiences concerning goal‐setting and the role of nursing in rehabilitation. Additional articles were found through snowballing. A total of 22 articles were reviewed on patients' experiences, and 12 on the nursing role. Results Patients need to be prepared for collaborating in goal‐setting and to receive an explanation about their part in that process. The multiplicity of disciplines may cloud patients' understanding of the process. The nurse's planning of the rehabilitation process should be aimed at resolving this issue. Goals need to be meaningful, and patients need support in attaining them. The interpretive, integrative, and consoling functions of Kirkevold's nursing role are suitable to meet these needs. Conclusions Both the literature about patients' needs regarding goal‐setting and the nursing role make clear that the way nurses work in rehabilitation can gain in clarity. Strengthening the role of nurses will improve the goal‐setting process for patients. Interprofessional collaboration, clear work procedures, continuity of care, time and trust, and the physical environment all are important to reinforce this role.
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Computational thinking (CT) skills are crucial for every modern profession in which large amounts of data are processed. In K-12 curricula, CT skills are often taught in separate programming courses. However, without specific instructions, CT skills are not automatically transferred to other domains in the curriculum when they are developed while learning to program in a separate programming course. In modern professions, CT is often applied in the context of a specific domain. Therefore, learning CT skills in other domains, as opposed to computer science, could be of great value. CT and domain-specific subjects can be combined in different ways. In the CT literature, a distinction can be made among CT applications that substitute, augment, modify or redefine the original subject. On the substitute level, CT replaces exercises but CT is not necessary for reaching the learning outcomes. On the redefining level, CT changes the questions that can be posed within the subject, and learning objectives and assessment are integrated. In this short paper, we present examples of how CT and history, mathematics, biology and language subjects can be combined at all four levels. These examples and the framework on which they are based provide a guideline for design-based research on CT and subject integration.
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Recently, the job market for Artificial Intelligence (AI) engineers has exploded. Since the role of AI engineer is relatively new, limited research has been done on the requirements as set by the industry. Moreover, the definition of an AI engineer is less established than for a data scientist or a software engineer. In this study we explore, based on job ads, the requirements from the job market for the position of AI engineer in The Netherlands. We retrieved job ad data between April 2018 and April 2021 from a large job ad database, Jobfeed from TextKernel. The job ads were selected with a process similar to the selection of primary studies in a literature review. We characterize the 367 resulting job ads based on meta-data such as publication date, industry/sector, educational background and job titles. To answer our research questions we have further coded 125 job ads manually. The job tasks of AI engineers are concentrated in five categories: business understanding, data engineering, modeling, software development and operations engineering. Companies ask for AI engineers with different profiles: 1) data science engineer with focus on modeling, 2) AI software engineer with focus on software development , 3) generalist AI engineer with focus on both models and software. Furthermore, we present the tools and technologies mentioned in the selected job ads, and the soft skills. Our research helps to understand the expectations companies have for professionals building AI-enabled systems. Understanding these expectations is crucial both for prospective AI engineers and educational institutions in charge of training those prospective engineers. Our research also helps to better define the profession of AI engineering. We do this by proposing an extended AI engineering life-cycle that includes a business understanding phase.
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Because social workers respond to local contexts, it is often said that social work is not a global profession. Indeed, social workers adapt their practices to local conditions. However, these local practices are recognised globally. The exchange of these practices and methods enriches social workers, inspires them and strengthens the further development of the profession. To facilitate this exchange, social work has had several international associations and networks for almost a century, which have enabled the sharing of local practices and educational programs. Today, social work works within a basic international framework that guides both professional practice and education. This descriptive article will take the reader through the history of international social work, by mentioning some global social work associations and networks and their achievements. Furthermore, the article will address internationalisation of the social work curriculum and will mention the added values and disadvantages of an international experience abroad. (Includes an abstract in the Slovakian language)
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