Albeit the widespread application of recommender systems (RecSys) in our daily lives, rather limited research has been done on quantifying unfairness and biases present in such systems. Prior work largely focuses on determining whether a RecSys is discriminating or not but does not compute the amount of bias present in these systems. Biased recommendations may lead to decisions that can potentially have adverse effects on individuals, sensitive user groups, and society. Hence, it is important to quantify these biases for fair and safe commercial applications of these systems. This paper focuses on quantifying popularity bias that stems directly from the output of RecSys models, leading to over recommendation of popular items that are likely to be misaligned with user preferences. Four metrics to quantify popularity bias in RescSys over time in dynamic setting across different sensitive user groups have been proposed. These metrics have been demonstrated for four collaborative filteri ng based RecSys algorithms trained on two commonly used benchmark datasets in the literature. Results obtained show that the metrics proposed provide a comprehensive understanding of growing disparities in treatment between sensitive groups over time when used conjointly.
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Long-term care facilities are currently installing dynamic lighting systems with the aim to improve the well-being and behaviour of residents with dementia. The aim of this study was to investigate the implementation of dynamic lighting systems from the perspective of stakeholders and the performance of the technology. Therefore, a questionnaire survey was conducted with the management and care professionals of six care facilities. Moreover, light measurements were conducted in order to describe the exposure of residents to lighting. The results showed that the main reason for purchasing dynamic lighting systems lied in the assumption that the well-being and day/night rhythmicity of residents could be improved. The majority of care professionals were not aware of the reasons why dynamic lighting systems were installed. Despite positive subjective ratings of the dynamic lighting systems, no data were collected by the organizations to evaluate the effectiveness of the lighting. Although the care professionals stated that they did not see any large positive effects of the dynamic lighting systems on the residents and their own work situation, the majority appreciated the dynamic lighting systems more than the old situation. The light values measured in the care facilities did not exceed the minimum threshold values reported in the literature. Therefore, it seems illogical that the dynamic lighting systems installed in the researched care facilities will have any positive health effects.
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The inefficiency of maintaining static and long-lasting safety zones in environments where actual risks are limited is likely to increase in the coming decades, as autonomous systems become more common and human workers fewer in numbers. Nevertheless, an uncompromising approach to safety remains paramount, requiring the introduction of novel methods that are simultaneously more flexible and capable of delivering the same level of protection against potentially hazardous situations. We present such a method to create dynamic safety zones, the boundaries of which can be redrawn in real-time, taking into account explicit positioning data when available and using conservative extrapolation from last known location when information is missing or unreliable. Simulation and statistical methods were used to investigate performance gains compared to static safety zones. The use of a more advanced probabilistic framework to further improve flexibility is also discussed, although its implementation would not offer the same level of protection and is currently not recommended.
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This chapter focuses on how pupil’s scientific understanding can be studied. The principles of a complex dynamic systems approach are highlighted.
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Usually the whole is the sum of its parts (added linearly): someone is happy and travelling, so happy travelling. Someone walks across a motionless and stable bridge and thus moves forward. But when hundreds of people walk together, the bridge may start to wobble quite suddenly. Both systems - the pedestrian and the bridge - are coupled into one new pattern, in which the whole is more than the sum of its parts. Such discontinuous shifts can be observed everywhere: in horses, the shift from walk to trot to canter (3 patterns); from ice to water to steam. Psychological measures - IQ, emotional stability, planning skills are marginal at best. It is argued that our behaviour is often determined by such dynamic systems.
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The final of a four-part series that explores Dynamic Systems Theory (DST). DST has taught us that phase transitions are based on self-organization and that they are not predictable a priori. They can be described, but not explained. This is well established in physics, but not at all in the social sciences and everyday life. It also takes a lot of practice to learn to see dynamic systems in everyday life. A few examples are given.
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We developed an application which allows learners to construct qualitative representations of dynamic systems to aid them in learning subject content knowledge and system thinking skills simultaneously. Within this application, we implemented a lightweight support function which automatically generates help from a norm-representation to aid learners as they construct these qualitative representations. This support can be expected to improve learning. Using this function it is not necessary to define in advance possible errors that learners may make and the subsequent feedback. Also, no data from (previous) learners is required. Such a lightweight support function is ideal for situations where lessons are designed for a wide variety of topics for small groups of learners. Here, we report on the use and impact of this support function in two lessons: Star Formation and Neolithic Age. A total of 63 ninth-grade learners from secondary school participated. The study used a pretest/intervention/post-test design with two conditions (no support vs. support) for both lessons. Learners with access to the support create better representations, learn more subject content knowledge, and improve their system thinking skills. Learners use the support throughout the lessons, more often than they would use support from the teacher. We also found no evidence for misuse, i.e., 'gaming the system', of the support function.
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In this paper, we focus on how the qualitative vocabulary of Dynalearn, which is used for describing dynamic systems, corresponds to the mathematical equations used in quantitative modeling. Then, we demonstrate the translation of a qualitative model into a quantitative model, using the example of an object falling with air resistance.
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In today’s intellectual capital literature, we see a shift from identifying intangibles towards understanding the dynamics of value creation. As it is not clear what “dynamic” stands for, the aim of this explorative and conceptual paper is to contribute to a better understanding of the dynamic dimension of IC. Based on a review of the early IC literature, the dynamic dimension (or dynamics) of intellectual capital seems to refer to the logic that value creation is the product of interaction between different types of (intangible) resources. As the idea of value creation through combination of knowledge resources is closely related to the New Growth Theory (Romer, 1990, 1994), this paper explores the New Growth Theory and its implications for the dynamic dimension of intellectual capital. Based on the exploration of the New Growth Theory, a conceptual model is presented in which the elements that constitute the dynamic dimension of intellectual capital are integrated. These elements are ideas, things, the process of knowledge creation, the process of continuous innovation, and institutions. The main conclusion of this paper is that the concept of knowledge is more closely related to the dynamic dimension of IC, than the concept of intellectual capital. Therefore, further research would probably benefit from approaching this topic from a knowledge management point of view. It is suggested that further research should focus on exploring the metaphors that contribute to a better understanding of the dynamics of IC, on the contribution that ideas can make to increase the effectiveness of knowledge management, and finally on the institutional arrangements that support the process of knowledge creation and innovation.
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Studying real-time teacher-student interaction provides insight into student's learning processes. In this study, upper grade elementary teachers were supported to optimize their instructional skills required for co-constructing scientific understanding. First, we examined the effect of the Video Feedback Coaching intervention by focusing on changes in teacher-student interaction patterns. Second, we examined the underlying dynamics of those changes by illustrating an in-depth micro-level analysis of teacher-student interactions. The intervention condition showed significant changes in the way scientific understanding was co-constructed. Results provided insight into how classroom interaction can elicit optimal co-construction and how this process changes during an intervention.
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