Presented at Conference: IPMA World Conference 2014, At Rotterdam, The Netherlands, Volume: 28 A taxonomy is used for classifying things in general. For the purpose of this paper it is a systematic classification of competences into hierarchical groups where each sublevel constitutes a breakdown of the higher level. Although a vast amount of research has been done in project management competences, there is no standard set of project management competences used (Nijhuis, 2012). Important reasons for constructing a taxonomy for project management competences are found in comparing previous research and in identifying key fields for project management education in higher education. First a definition of competence is given, secondly the rationale of this research is given by discussing recent research. Several different published taxonomies of competences are reviewed. Finally a proposed taxonomy for project management competences is presented.
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From the article: "The vast amount of previous research on project management competence does not provide a basis for educational needs. Analyzing previous research poses two challenges: the lack of a uniform list of competences, necessitating a taxonomy, and the use of importance as a criterion, favoring general important competences. Criticality is introduced as the competence a project manager adds to the team. Validation research using criticality and the taxonomy among experienced Dutch project managers is more comprehensive and provides a less focus on general important competences than previous research. Criticality focuses more on the essence of the profession."
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The Dutch government and leading academics in the field of circular economy propose that “repurposing”, i.e., finding new usages for discarded material, is important to reduce resource usage. Waste collectors, municipalities and start-ups increasingly find ways to develop circular business models, aiming for minimum loss of material integrity. Repurpose is a circular business model strategy which entails using a discarded product or its parts in a new product with a different function.The aim of this research is to gain a better understanding of this promising but academically underexposed circular strategy by empirically exploring its key characteristics and developing a taxonomy that reflects the scope and potential of the concept. The taxonomy development was based on clustering and comparing 96 case examples using key characteristics and critical factors empirically collected by means of 11 semi-structured expert interviews. The taxonomy was iteratively refined and validated by means of workshops with experts.This paper proposes a taxonomy and a comprehensive definition for repurposing. The Repurpose taxonomy distinguishes three main categories with increasing levels of material integrity: “Reprocess”, “Reshape” and “Recontextualize”. The taxonomy provides a refinement of existing circular business model patterns and frameworks for closing material loops strategies. It shows how repurposing may exploit the creative potential of design to fill the gap between reuse and recycling by retaining previously added value with three levels of physical adjustment.
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Peer discussions play a major role in students’ collaborative problem-solving activity. These discussions provide researchers and teachers with a wealth of information about the students' reasoning. To analyse such discussions, different theoretical lenses are available, such as Schoenfeld’s problem solving model, the Florida Taxonomy of Cognitive Behaviour, and the Scheme for Educational Dialogue Analysis. The question is, however, how these three perspectives can complement each other. To investigate this, the discussion between four students was analysed through the three lenses. Results indicate that these frameworks are both complementary and connected. This connection allows an in-depth analysis of the discussion and reveals possibilities and limitations for an integration of the three models, which will guide future discussions’ analyses in our study.
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Integrated curricula seem promising for the increase of attention on science and technology in primary education. A clear picture of the advantages and disadvantages of integration efforts could help curriculum innovation. This review has focussed on integrated curricula in primary education from 1994 to 2011. The integrated curricula were categorized according to a taxonomy of integration types synthesized from the literature. The characteristics that we deemed important were related to learning outcomes and success/fail factors. A focus group was formed to facilitate the process of analysis and to test tentative conclusions. We concluded that the levels in our taxonomy were linked to (a) student knowledge and skills, the enthusiasm generated among students and teachers, and the teacher commitment that was generated; and (b) the teacher commitment needed, the duration of the innovation effort, the volume and comprehensiveness of required teacher professional development, the necessary teacher support, and the effort needed to overcome tensions with standard curricula. Almost all projects were effective in increasing the time spent on science at school. Our model resolves Czerniac’s definition problem of integrating curricula in a productive manner, and it forms a practical basis for decision-making by making clear what is needed and what output can be expected when plans are being formulated to implement integrated education.
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Given the growing number of older people, society as a whole should ideally provide a higher quality of life (QoL) for its ageing citizens through the concept of personalised ageing. Information and communication technologies (ICT) are subject to constant and rapid development, and can contribute to the goal of an improved QoL for older adults. In order to utilise future ICT solutions as a part of an age-friendly smart environment that helps achieve personalised ageing with an increased QoL, one must first determine whether the existing ICT solutions are satisfying the needs of older people. In order to accomplish that, this study contributes in three ways. First, it proposes a framework for the QoL of older adults, in order to provide a systematic review of the state-of-the-art literature and patents in this field. The second contribution is the finding that selected ICT solutions covered by articles and patents are intended for older adults and are validated by them. The third contribution of the study are the six recommendations that are derived from the review of the literature and the patents which would help move the agenda concerning the QoL of older people and personalised ageing with the use of ICT solutions forward. Original article at MDPI; DOI: http://dx.doi.org/10.3390/ijerph17082940 (This article belongs to the Special Issue Feature Papers "Age-Friendly Cities & Communities: State of the Art and Future Perspectives")
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From the article: Abstract: An overview of neural network architectures is presented. Some of these architectures have been created in recent years, whereas others originate from many decades ago. Apart from providing a practical tool for comparing deep learning models, the Neural Network Zoo also uncovers a taxonomy of network architectures, their chronology, and traces back lineages and inspirations for these neural information processing systems.
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Explainable Artificial Intelligence (XAI) aims to provide insights into the inner workings and the outputs of AI systems. Recently, there’s been growing recognition that explainability is inherently human-centric, tied to how people perceive explanations. Despite this, there is no consensus in the research community on whether user evaluation is crucial in XAI, and if so, what exactly needs to be evaluated and how. This systematic literature review addresses this gap by providing a detailed overview of the current state of affairs in human-centered XAI evaluation. We reviewed 73 papers across various domains where XAI was evaluated with users. These studies assessed what makes an explanation “good” from a user’s perspective, i.e., what makes an explanation meaningful to a user of an AI system. We identified 30 components of meaningful explanations that were evaluated in the reviewed papers and categorized them into a taxonomy of human-centered XAI evaluation, based on: (a) the contextualized quality of the explanation, (b) the contribution of the explanation to human-AI interaction, and (c) the contribution of the explanation to human- AI performance. Our analysis also revealed a lack of standardization in the methodologies applied in XAI user studies, with only 19 of the 73 papers applying an evaluation framework used by at least one other study in the sample. These inconsistencies hinder cross-study comparisons and broader insights. Our findings contribute to understanding what makes explanations meaningful to users and how to measure this, guiding the XAI community toward a more unified approach in human-centered explainability.
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