“Critical Making in Collaboration with Nature”, discusses the outcomes of the Making Sustainability Work project from Fall 2020. With support of CoECI Zaaigelden scheme, the Critical Making learning community put together a group of makers from research, education and industry to explore the implications of designing with natural materials and biological processes, such as biopolymers, fungal composites and bacteria dye. By following a selection of modules from the Fabricademy global training program, participants explored hands-on techniques to create their own design materials and colours from renewable and biodegradable resources and documented their journeys. The shared experience was reflected upon in a series of interviews and essays touching on the following questions: • In what way do unruly natural materials challenge ways of doing and teaching design? • How do grown materials fit into or challenge makers’ goals of sustainability?• What is needed to bring biological processes into communities of practice in the field of design, art and making?• How and when does criticality emerge in the making process? • How do processes of thinking and doing intersect and what is the role of social interactions and collaboration?
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In case of a major cyber incident, organizations usually rely on external providers of Cyber Incident Response (CIR) services. CIR consultants operate in a dynamic and constantly changing environment in which they must actively engage in information management and problem solving while adapting to complex circumstances. In this challenging environment CIR consultants need to make critical decisions about what to advise clients that are impacted by a major cyber incident. Despite its relevance, CIR decision making is an understudied topic. The objective of this preliminary investigation is therefore to understand what decision-making strategies experienced CIR consultants use during challenging incidents and to offer suggestions for training and decision-aiding. A general understanding of operational decision making under pressure, uncertainty, and high stakes was established by reviewing the body of knowledge known as Naturalistic Decision Making (NDM). The general conclusion of NDM research is that experts usually make adequate decisions based on (fast) recognition of the situation and applying the most obvious (default) response pattern that has worked in similar situations in the past. In exceptional situations, however, this way of recognition-primed decision-making results in suboptimal decisions as experts are likely to miss conflicting cues once the situation is quickly recognized under pressure. Understanding the default response pattern and the rare occasions in which this response pattern could be ineffective is therefore key for improving and aiding cyber incident response decision making. Therefore, we interviewed six experienced CIR consultants and used the critical decision method (CDM) to learn how they made decisions under challenging conditions. The main conclusion is that the default response pattern for CIR consultants during cyber breaches is to reduce uncertainty as much as possible by gathering and investigating data and thus delay decision making about eradication until the investigation is completed. According to the respondents, this strategy usually works well and provides the most assurance that the threat actor can be completely removed from the network. However, the majority of respondents could recall at least one case in which this strategy (in hindsight) resulted in unnecessary theft of data or damage. Interestingly, this finding is strikingly different from other operational decision-making domains such as the military, police and fire service in which there is a general tendency to act rapidly instead of searching for more information. The main advice is that training and decision aiding of (novice) cyber incident responders should be aimed at the following: (a) make cyber incident responders aware of how recognition-primed decision making works; (b) discuss the default response strategy that typically works well in several scenarios; (c) explain the exception and how the exception can be recognized; (d) provide alternative response strategies that work better in exceptional situations.
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Current many changes are taking place in the elderly care: care is changing from supply-oriented to demand driven, problems have to be more serious than previously to get a placement in a nursing home, furthermore the demand for heavier care will increase due to ageing. The aim of this study is to acquire a clear insight in the decision-making process with regard to placement in a nursing home facility.
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Designing cities that are socially sustainable has been a significant challenge until today. Lately, European Commission’s research agenda of Industy 5.0 has prioritised a sustainable, human-centric and resilient development over merely pursuing efficiency and productivity in societal transitions. The focus has been on searching for sustainable solutions to societal challenges, engaging part of the design industry. In architecture and urban design, whose common goal is to create a condition for human life, much effort was put into elevating the engineering process of physical space, making it more efficient. However, the natural process of social evolution has not been given priority in urban and architectural research on sustainable design. STEPS stems from the common interest of the project partners in accessible, diverse, and progressive public spaces, which is vital to socially sustainable urban development. The primary challenge lies in how to synthesise the standardised sustainable design techniques with unique social values of public space, propelling a transition from technical sustainability to social sustainability. Although a large number of social-oriented studies in urban design have been published in the academic domain, principles and guidelines that can be applied to practice are large missing. How can we generate operative principles guiding public space analysis and design to explore and achieve the social condition of sustainability, developing transferable ways of utilising research knowledge in design? STEPS will develop a design catalogue with operative principles guiding public space analysis and design. This will help designers apply cross-domain knowledge of social sustainability in practice.
Om tegemoet te komen aan de eisen die gesteld worden aan werknemers in de huidig snel veranderende samenleving heeft de NHL Stenden Hogeschool gekozen voor een nieuw onderwijsconcept, namelijk Design Based Education (DBE). DBE is gebaseerd op het gedachtegoed van Design Thinking en stimuleert iteratieve en creatieve denkprocessen. DBE is een student-georiënteerde leeromgeving, gebaseerd op praktijk-, dialoog-, en vraaggestuurde onderwijsprincipes en op zelfsturend, constructief, contextueel en samenwerkend leren. Studenten construeren gezamenlijk kennis en ontwikkelen een prototype voor een praktijkvraagstuk. Student-georiënteerde leeromgevingen vragen andere begeleidingsstrategieën van docenten dan zij gewend zijn. Van docenten wordt verwacht dat zij studenten activeren gezamenlijk kennis te construeren en dat zij nauw samenwerken met werkveldprofessionals. Eerder onderzoek toont aan dat docenten, zelfs in een student-georiënteerde leeromgeving, geneigd zijn terug te vallen op conventionele strategieën. De overstap naar een ander onderwijsconcept gaat dus blijkbaar niet vanzelf. Collectief leren stimuleert docenten de dialoog aan te gaan met andere docenten en werkveldprofessionals met als doel gezamenlijk te experimenteren en collectief te handelen. De centrale vraag van het postdoc-onderzoek is het ontwerpen en ontwikkelen van (karakteristieken van) interventies die collectief leren van docenten en werkveldprofessionals stimuleren. Het doel van het postdoconderzoek is om de overstap naar DBE zo probleemloos mogelijk te laten verlopen door docenten te ondersteunen DBE leeromgevingen te ontwikkelen in samenwerking met werkveldprofessionals en DBE te integreren in hun docentactiviteiten. De onderzoeksmethode is Educational Design Research en bestaat uit vier fasen: preliminair onderzoek, ontwikkelen van prototypes, evaluatie en bijdrage aan de praktijk. Het onderzoek is verbonden aan het lectoraat Sustainable Educational Concepts in Higher Education en wordt hiërarchisch en inhoudelijk aangestuurd door de lector. Docenten, experts, werkveldprofessionals en studenten worden betrokken bij het onderzoek. Dit onderzoek kan zowel binnen als buiten de hogeschool een bijdrage leveren omdat steeds meer hogescholen kiezen voor een ander onderwijsconcept.
The increasing amount of electronic waste (e-waste) urgently requires the use of innovative solutions within the circular economy models in this industry. Sorting of e-waste in a proper manner are essential for the recovery of valuable materials and minimizing environmental problems. The conventional e-waste sorting models are time-consuming processes, which involve laborious manual classification of complex and diverse electronic components. Moreover, the sector is lacking in skilled labor, thus making automation in sorting procedures is an urgent necessity. The project “AdapSort: Adaptive AI for Sorting E-Waste” aims to develop an adaptable AI-based system for optimal and efficient e-waste sorting. The project combines deep learning object detection algorithms with open-world vision-language models to enable adaptive AI models that incorporate operator feedback as part of a continuous learning process. The project initiates with problem analysis, including use case definition, requirement specification, and collection of labeled image data. AI models will be trained and deployed on edge devices for real-time sorting and scalability. Then, the feasibility of developing adaptive AI models that capture the state-of-the-art open-world vision-language models will be investigated. The human-in-the-loop learning is an important feature of this phase, wherein the user is enabled to provide ongoing feedback about how to refine the model further. An interface will be constructed to enable human intervention to facilitate real-time improvement of classification accuracy and sorting of different items. Finally, the project will deliver a proof of concept for the AI-based sorter, validated through selected use cases in collaboration with industrial partners. By integrating AI with human feedback, this project aims to facilitate e-waste management and serve as a foundation for larger projects.
