Sawik, Bartosz
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Sawik
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Bartosz
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Estadística, Informática y Matemáticas
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Publication Open Access Robots for elderly care: review, multi-criteria optimization model and qualitative case study(MDPI, 2023) Sawik, Bartosz; Tobis, Sławomir; Baum, Ewa; Suwalska, Aleksandra; Kropińska, Sylwia; Stachnik, Katarzyna; Pérez Bernabeu, Elena; Cildoz Esquíroz, Marta; Agustín Martín, Alba; Wieczorowska-Tobis, Katarzyna.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISCThis paper focuses on three areas: the first is a review of current knowledge about social and service robots for elderly care. The second is an optimization conceptual model aimed at maximizing the efficiency of assigning robots to serve the elderly. The proposed multi-criteria optimization model is the first one proposed in the area of optimization for robot assignment for the elderly with robot utilization level and caregiver stress level. The third is the findings of studies on the needs, requirements, and adoption of technology in elderly care. We consider the use of robots as a part of the ENRICHME project for long-term interaction and monitoring of older persons with mild cognitive impairment, to optimize their independence. Additionally, we performed focus group discussions (FGD) to collect opinions about robot-related requirements of the elderly and their caregivers. Four FDGs of six persons were organized: two comprising older adults, and two of the other formal and informal caregivers, based on a detailed script. The statements of older participants and their caregivers were consistent in several areas. The analysis revealed user characteristics, robot-related issues, functionality, and barriers to overcome before the deployment of the robot. An introduction of the robot must be thoroughly planned, include comprehensive pre-training, and take the ethical and practical issues into account. The involvement of future users in the customization of the robot is essential.Publication Open Access E-learning as a factor optimizing the amount of work time devoted to preparing an exam for medical program students during the COVID-19 epidemic situation(MDPI, 2021) Roszak, Magdalena; Sawik, Bartosz; Stando, Jacek; Baum, Ewa; Estadística, Informática y Matemáticas; Estatistika, Informatika eta MatematikaThe COVID-19 pandemic had a huge impact on the learning and teaching processes, particularly in healthcare education and training, because of the principal position of the cutting-edge student-patient interaction. Replacing the traditional form of organization and implementation of knowledge evaluation with its web-based equivalent on an e-learning platform optimizes the whole didactic process not only for the unit carrying it out but, above all, for students. This research is focused on the effectiveness of the application of e-learning for computer-based knowledge evaluation and optimizing exam administration for students of medical sciences. The proposed approach is considered in two categories: from the perspective of the providers of the evaluation process, that is, the teaching unit; and the recipients of the evaluation process, that is, the students.