204 research outputs found

    Student and teacher performance during COVID-19 lockdown:An investigation of associated features and complex interactions using multiple data sources

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    Due to the COVID-19 pandemic, testing what is required to support teachers and students while subject to forced online teaching and learning is relevant in terms of similar situations in the future. To understand the complex relationships of numerous factors with teaching during the lockdown, we used administrative data and survey data from a large Danish university. The analysis employed scores from student evaluations of teaching and the students’ final grades during the first wave of the COVID-19 lockdown in the spring of 2020 as dependent targets in a linear regression model and a random forest model. This led to the identification of linear and non-linear relationships, as well as feature importance and interactions for the two targets. In particular, we found that many factors, such as the age of teachers and their time use, were associated with the scores in student evaluations of teaching and student grades, and that other features, including peer interaction among teachers and student gender, also exerted influence, especially on grades. Finally, we found that for non-linear features, in terms of the age of teachers and students, the average values led to the highest response values for scores in student evaluations of teaching and grades

    The importance of expert knowledge in big data and machine learning

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    Many-Valued Hybrid Logic

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    In this paper we define a family of many-valued semantics for hybrid logic, where each semantics is based on a finite Heyting algebra of truth-values. We provide sound and complete tableau systems for these semantics. Moreover, we show how the tableau systems can be made terminating and thereby give rise to decision procedures for the logics in question. Our many-valued hybrid logics turn out to be "intermediate" logics between intuitionistic hybrid logic and classical hybrid logic in a specific sense explained in the paper. Our results show that many-valued hybrid logic is indeed a natural enterprise

    On the rationality of pluralistic ignorance

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    Pluralistic ignorance is a socio-psychological phenomenon that involves a systematic discrepancy between people’s private beliefs and public behavior in certain social contexts. Recently, pluralistic ignorance has gained increased attention in formal and social epistemology. But to get clear on what precisely a formal and social epistemological account of pluralistic ignorance should look like, we need answers to at least the following two questions: What exactly is the phenomenon of pluralistic ignorance? And can the phenomenon arise among perfectly rational agents? In this paper, we propose answers to both these questions. First, we characterize different versions of pluralistic ignorance and define the version that we claim most adequately captures the examples cited as paradigmatic cases of pluralistic ignorance in the literature. In doing so, we will stress certain key epistemic and social interactive aspects of the phenomenon. Second, given our characterization of pluralistic ignorance, we argue that the phenomenon can indeed arise in groups of perfectly rational agents. This, in turn, ensures that the tools of formal epistemology can be fully utilized to reason about pluralistic ignoranc

    Leber's Hereditary Optic Neuropathy and Hypertrophic Cardiomyopathy

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    Leber’s hereditary optic neuropathy (LHON) is a mitochondrial condition that gradually affects the central vision. In the current case report, we present 2 relatives with LHON due to a pathogenic variant within ND1 with a clinical phenotype resembling hypertrophic cardiomyopathy, including a short PQ-interval and hypertrophy on electrocardiogram as well as severe hypertrophy of the left ventricle on echocardiography. These findings highlight the importance of offering routine cardiac investigation to patients with LHON and their relatives carrying the ND1 variant to hopefully improve correct diagnosis and clinical management of LHON patients
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