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摘要： This article deals with the problem of the functioning of existing training programs for students mastering natural science programs for applied training areas, which take into account the dominant part of the load on the problem-experimental essence of the knowledge acquisition process. It consists in solving specific problems with a different nature of phenomena, which are easier to consider in the context of simulation tools in a virtual environment. The nature of cognition is determined, affecting both the form of imparting properties to the studied phenomenon or process, and the specific characteristics of the assimilation of knowledge, mediated with work in special-purpose software environments. The authors also indicate the aspectology of the process of cognitive activity in a virtual environment exclusively - they emphasize the role of learning to work with a specific type of software, which often have a complicated and single-tasking graphical interface. The result of software development is demonstrated. It provides an adaptive design of teaching in accordance with the type of problem to be solved on the part of the student, the optimization role of the complex of topics under consideration is indicated.

摘要： Inequality prevails in science. Individual inequality means that most perish quickly and only a few are successful, while gender inequality implies that there are differences in achievements for women and men. Using large-scale bibliographic data and following a computational approach, we study the evolution of individual and gender inequality for cohorts from 1970 to 2000 in the whole field of computer science as it grows and becomes a team-based science. We find that individual inequality in productivity (publications) increases over a scholar’s career but is historically invariant, while individual inequality in impact (citations), albeit larger, is stable across cohorts and careers. Gender inequality prevails regarding productivity, but there is no evidence for differences in impact. The Matthew Effect is shown to accumulate advantages to early achievements and to become stronger over the decades, indicating the rise of a "publish or perish" imperative. Only some authors manage to reap the benefits that publishing in teams promises. The Matthew Effect then amplifies initial differences and propagates the gender gap. Women continue to fall behind because they continue to be at a higher risk of dropping out for reasons that have nothing to do with early-career achievements or social support. Our findings suggest that mentoring programs for women to improve their social-networking skills can help to reduce gender inequality. © 2023, CC BY.

关键词： heart rate   machine learning   mental stress   knowledge worker   photoplethysmography   pulse rate variability  

摘要： The aim of this study is to analyze the performance of classifying stress and non-stress by measuring biosignal data using a wearable watch without interfering with work activities at work. An experiment is designed where participants wear a Galaxy Watch3 to measure HR and photoplethysmography data while performing stress-inducing and relaxation tasks. The classification model was constructed using k-NN, SVM, DT, LR, RF, and MLP classifiers. The performance of each classifier was evaluated using LOSO-CV as a verification method. When the top 9 features, including the average and minimum value of HR, average of NNI, SDNN, vLF, HF, LF, LF/HF ratio, and total power, were used in the classification model, it showed the best performance with an accuracy of 0.817 and an F1 score of 0.801. This study also finds that it is necessary to measure physiological data for more than 2 or 3 min to accurately distinguish stress states.

关键词： Prediction models  

摘要： After completing their undergraduate studies, many computer science (CS) students apply for competitive graduate programs in North America. Their long-term goal is often to be hired by one of the big five tech companies or to become a faculty member. Therefore, being aware of the role of admission criteria may help them choose the best path towards their goals. In this paper, we analyze the influence of students’ previous universities on their chances of being accepted to prestigious North American universities and returning to academia as professors in the future. Our findings demonstrate that the ranking of their prior universities is a significant factor in achieving their goals. We then illustrate that there is a bias in the undergraduate institutions of students admitted to the top 25 computer science programs. Finally, we employ machine learning models to forecast the success of professors at these universities. We achieved an RMSE of 7.85 for this prediction task. © 2023, CC BY.

关键词： Computer science   Machine learning   Technology  

摘要： Naturestaff take on the big topics that matter in science.

关键词： Computer science   Technology   Policy  

摘要： Artificial-intelligence tools are transforming data-driven science - better ethical standards and more robust data curation are needed to fuel the boom and prevent a bust. Artificial-intelligence tools are transforming data-driven science - better ethical standards and more robust data curation are needed to fuel the boom and prevent a bust.

关键词： Computer science   Ethics   Machine learning   Society  

摘要： Robust regulation of AI technologies will be crucial to protecting against harms. Researchers’ voices must be heard. [Figure not available: see fulltext.] © 2023, Springer Nature Limited.

关键词： Computer science identities   relational space   celebrated identities   sense of belonging   narrative interviews  

摘要： There is a call for more students to continue into computer science (CS), but as many leave their studies before completing, there is a potential in retaining students rather than focusing on recruitment alone. The retention literature proposes 'sense of belonging' as a key concept. This paper contributes with nuancing how sense of belonging is shaped differently within different spaces at the same CS study-programme, by drawing on narrative interviews and ethnographic fieldwork with BA-students, analysed through a spatial analytic lens. By applying the metaphors of a solar system and force fields, we investigate how sense of belonging was constructed within relational spaces and students' identity-negotiations within them. Three spaces are found: The studylounge (the epicenter of the solar system), the pulsating planet, and the distant isolated planet. Conclusions show how the epicenter are enforced by teaching and learning activities, and how broadening what counts hold potential to retain students.

关键词： Computer science   Ethics   Machine learning   Society  

摘要： Robust regulation of AI technologies will be crucial to protecting against harms. Researchers' voices must be heard. Robust regulation of AI technologies will be crucial to protecting against harms. Researchers' voices must be heard.