While feedback is frequently emphasized as a crucial principle of presentation courses in higher education, previous studies revealed that teachers outperform peers in terms of impact on students’ development of oral presentation competence. Further, presentation research showed that the lack of quality of peer feedback can be considered as an essential argumentation for the identified differences in effect. Follow-up field experiments demonstrated that Virtual Reality (VR) can be considered as a valuable alternative feedback source for developing public speaking skills, since this technology is able to simulate real-life presentation situations as well as to deliver feedback from the VR system to the individual learner. Recent technological developments allowed to convert quantitative information from VR systems into qualitative feedback messages that directly relate to the standards for high-quality feedback. If students are able to individually interpret the feedback messages without the intervention of a human feedback source, it could enrich the quality of feedback in peer and self-learning and further increase students’ oral presentation competence development. This chapter provides a synthesis of the literature in presentation research with the aim to construct a research agenda on computer-mediated feedback in VR for peer learning in this field. Further, two recent VR experiments in presentation research are discussed with the aim to effectively construct feedback messages in VR for improving peer learning.
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In flexible education, recommender systems that support course selection, are considered a viable means to help students in making informed course selections, especially where curricula offer greater flexibility. However, these recommender systems present both potential benefits and looming risks, such as overdependence on technology, biased recommendations, and privacy issues. User control mechanisms in recommender interfaces (or algorithmic affordances) might offer options to address those risks, but they have not been systematically studied yet. This paper presents the outcomes of a design session conducted during the INTERACT23 workshop on Algorithmic Affordances in Recommender Interfaces. This design session yielded insights in how the design of an interface, and specifically the algorithmic affordances in these interfaces, may address the ethical risks and dilemmas of using a recommender in such an impactful context by potentially vulnerable users. Through design and reflection, we discovered a host of design ideas for the interface of a flexible education interface, that can serve as conversation starters for practitioners implementing flexible education. More research is needed to explore these design directions and to gain insights on how they can help to approximate more ethically operating recommender systems.
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Computer security incident response teams (CSIRTs) respond to a computer security incident when the need arises. Failure of these teams can have far-reaching effects for the economy and national security. CSIRTs often have to work on an ad hoc basis, in close cooperation with other teams, and in time constrained environments. It could be argued that under these working conditions CSIRTs would be likely to encounter problems. A needs assessment was done to see to which extent this argument holds true. We constructed an incident response needs model to assist in identifying areas that require improvement. We envisioned a model consisting of four assessment categories: Organization, Team, Individual and Instrumental. Central to this is the idea that both problems and needs can have an organizational, team, individual, or technical origin or a combination of these levels. To gather data we conducted a literature review. This resulted in a comprehensive list of challenges and needs that could hinder or improve, respectively, the performance of CSIRTs. Then, semi-structured in depth interviews were held with team coordinators and team members of five public and private sector Dutch CSIRTs to ground these findings in practice and to identify gaps between current and desired incident handling practices. This paper presents the findings of our needs assessment and ends with a discussion of potential solutions to problems with performance in incident response. https://doi.org/10.3389/fpsyg.2017.02179 LinkedIn: https://www.linkedin.com/in/rickvanderkleij1/
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Smart city technologies, including artificial intelligence and computer vision, promise to bring a higher quality of life and more efficiently managed cities. However, developers, designers, and professionals working in urban management have started to realize that implementing these technologies poses numerous ethical challenges. Policy papers now call for human and public values in tech development, ethics guidelines for trustworthy A.I., and cities for digital rights. In a democratic society, these technologies should be understandable for citizens (transparency) and open for scrutiny and critique (accountability). When implementing such public values in smart city technologies, professionals face numerous knowledge gaps. Public administrators find it difficult to translate abstract values like transparency into concrete specifications to design new services. In the private sector, developers and designers still lack a ‘design vocabulary’ and exemplary projects that can inspire them to respond to transparency and accountability demands. Finally, both the public and private sectors see a need to include the public in the development of smart city technologies but haven’t found the right methods. This proposal aims to help these professionals to develop an integrated, value-based and multi-stakeholder design approach for the ethical implementation of smart city technologies. It does so by setting up a research-through-design trajectory to develop a prototype for an ethical ‘scan car’, as a concrete and urgent example for the deployment of computer vision and algorithmic governance in public space. Three (practical) knowledge gaps will be addressed. With civil servants at municipalities, we will create methods enabling them to translate public values such as transparency into concrete specifications and evaluation criteria. With designers, we will explore methods and patterns to answer these value-based requirements. Finally, we will further develop methods to engage civil society in this processes.
Induced seismicity problems in the Groningen area caused by gas extraction have been one of the major challenges for the engineering and construction companies in the region and the Netherlands, not only because earthquake phenomena are new to the Dutch engineering community but also because the problem is very much complicated due to its social extents. The companies working in the structural engineering field in the region in different disciplines were forced to adapt very quickly to the earthquake related problems. It was a real size and investment problem for the SMEs, several of which benefited from this rush, however, only under certain conditions can this new skill set be sustainable. The SafeGo project aims mostly to help to facilitate sustainable development and build confidence for the SMEs in the field of earthquake engineering, rather than producing new scientific knowledge for them. SMEs are positioned in the seismic strengthening process either for collection of data or for providing and applying strengthening solutions. The proposed project aims to answer the question on how the “data-collection SMEs” can translate their data into more valuable assets to be used in the earthquake problem because the collection and the use of field data are vital. Furthermore, the question is also how the “strengthening SMEs” can verify and demonstrate their systems on a seismic shake table, because strengthening requires proven methodologies. The project goal is to combine these two central questions into findings on how the experimental and field data can efficiently be translated into suitable procedures, products and computer simulations for seismic assessment and strengthening of buildings, allowing SMEs to provide novel, integrated and accurate solutions not only in the region but also in international markets.
Prompt and timely response to incoming cyber-attacks and incidents is a core requirement for business continuity and safe operations for organizations operating at all levels (commercial, governmental, military). The effectiveness of these measures is significantly limited (and oftentimes defeated altogether) by the inefficiency of the attack identification and response process which is, effectively, a show-stopper for all attack prevention and reaction activities. The cognitive-intensive, human-driven alarm analysis procedures currently employed by Security Operation Centres are made ineffective (as opposed to only inefficient) by the sheer amount of alarm data produced, and the lack of mechanisms to automatically and soundly evaluate the arriving evidence to build operable risk-based metrics for incident response. This project will build foundational technologies to achieve Security Response Centres (SRC) based on three key components: (1) risk-based systems for alarm prioritization, (2) real-time, human-centric procedures for alarm operationalization, and (3) technology integration in response operations. In doing so, SeReNity will develop new techniques, methods, and systems at the intersection of the Design and Defence domains to deliver operable and accurate procedures for efficient incident response. To achieve this, this project will develop semantically and contextually rich alarm data to inform risk-based metrics on the mounting evidence of incoming cyber-attacks (as opposed to firing an alarm for each match of an IDS signature). SeReNity will achieve this by means of advanced techniques from machine learning and information mining and extraction, to identify attack patterns in the network traffic, and automatically identify threat types. Importantly, SeReNity will develop new mechanisms and interfaces to present the gathered evidence to SRC operators dynamically, and based on the specific threat (type) identified by the underlying technology. To achieve this, this project unifies Dutch excellence in intrusion detection, threat intelligence, and human-computer interaction with an industry-leading partner operating in the market of tailored solutions for Security Monitoring.
