26 research outputs found

    WHAT ENDORSES TEACHERS TO USE GAMIFIED APPROACHES IN THEIR CLASSROOMS: SELF-EFFICACY TECHNOLOGY PROFICIENCY, AND PERCEIVED USEFULNESS

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    Gamified approaches in the classroom gained more consideration in the recent years. Although the benefits of evolving technologies integrated in the teaching process are better recognized for the student population, what enhances the adoption of such technologies from the teachers` perspective is less investigated. The present study investigated the associations between self-efficacy, teachers’ technology proficiency, perceived usefulness of gamification and behavioral intention to use gamification among 170 teachers, aged between 18 to 64 years old (M = 34.9; SD = 9.69), with a teaching experience ranging from almost one year to 44 years of experience (M = 8.71; SD = 9.62). Correlation analyses showed that there are associations between teachers’ self-efficacy, teachers’ technology proficiency, and perceived usefulness of gamification levels and behavioral intention to use gamification. Furthermore, the mediation analyses showed that technology proficiency level and perceived usefulness of gamification partially mediate the relationship between self-efficacy and the behavioral intention to use gamification among Romanian k-12 inservice teachers. These results advanced our knowledge about the relationship between self-efficacy and the behavioral intention to use gamification and its underlying mechanism

    EXPLORING ASSOCIATIONS BETWEEN SELF-EFFICACY, WORK ENGAGEMENT AND BEHAVIORAL INTENTION TO USE GAMIFICATION

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    Along with the growing interest and the continuous development in technology, gamification gained more recognition in the educational areas. While knowledge concerning gamified approaches and their advantages in the classroom are better understood for student populations, less is investigated in terms of factors that drive teachers to use such approaches in the classroom. The present study investigated the associations between self-efficacy, teachers’ work engagement, and behavioral intention to use gamification among 170 teachers, aged between 18 to 64 years old (M = 34.9; SD = 9.69), with a teaching experience ranging from almost one year to 44 years of experience (M = 8.71; SD = 9.62). Correlation analyses showed that there are associations between teachers’ self-efficacy, teachers’ work engagement, and behavioral intention to use gamification. This study showed that there are significant associations between self-efficacy, work engagement, and the behavioral intention to use gamification. These results stress out the need for more investigations on the personal characteristics of teachers that may be related to the use of gamified approaches in the classroom

    Subclinical right ventricular dysfunction in cystic fibrosis. a study using tissue Doppler echocardiography

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    Patients with severe cystic fibrosis can develop cor pulmonale, but little is known about the function of the right ventricle (RV) early in the disease. We hypothesized that such patients might have subclinical RV dysfunction, detectable by tissue Doppler echocardiography, and related to the severity of lung disease. We studied 21 clinically stable patients (Group 1), five patients with severe lung disease (Group 2), and 23 age-matched healthy subjects. Patients had impaired RV systolic function. The mean (SD) systolic velocities of the RV free wall were 8.9 (1.7) cm/s in Group 1, 7.7 (1.0) in Group 2, and 10.8 (1.9) in healthy subjects (p < 0.001). The velocities of the tricuspid annulus were less in patients (p < 0.0001). Patients had a greater isovolumic relaxation time (p < 0.001), indicating RV diastolic dysfunction. RV wall thickness was greater in patients (0.4 [0.1] versus 0.3 [0.1] cm/m(2), p < 0.01). RV systolic function was related to C-reactive protein (r = - 0.66, p < 0.001) and FEV(1) (r = 0.62, p = 0.003) and diastolic function to interleukin-6 (r = 0.64, p < 0.005). Patients with cystic fibrosis have subclinical RV dysfunction, which correlates with the severity of lung disease. Tissue Doppler echocardiography provides a quantifiable indicator useful for detection and monitoring of disease progression

    Social and Emotional Learning and Internalizing Problems among Adolescents: The Mediating Role of Resilience

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    (1) Background: The high rates of mental disorders in adolescence presented in the literature often exclude internalizing problems. Although there is extensive data on the effectiveness of SEL skills in improving resilience, few studies included evidence in their reports on the relationship between SEL skills and internalizing problems. The present study aims to deepen the understanding of the relationship between SEL, resilience, and internalizing problems, by investigating the mediating effect of resilience between SEL components and internalizing problems. (2) Methods: Adolescents (N = 968 adolescents, aged between 11 and 18 years old; M = 13.30; SD = 1.92) from 30 schools from the NE region of Romania were invited to fill out questionnaires on social and emotional learning, internalizing problems, and resilience. (3) Results: The results show that resilience mediates the link between self-awareness and internalizing problems, between self-management and internalizing problems, between relationship skills and internalizing problems, and between responsible decision-making and internalizing problems. (4) Conclusions: These findings revealed the need for social and emotional learning interventions that include resilience-oriented approaches in order to decrease internalizing problems in adolescents. Moreover, we suggest that more culturally appropriate interventions are required to better investigate the interaction between SEL components, resilience, and internalizing problems

    Imagistic Findings Using Artificial Intelligence in Vaccinated versus Unvaccinated SARS-CoV-2-Positive Patients Receiving In-Care Treatment at a Tertiary Lung Hospital

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    Background: In December 2019 the World Health Organization announced that the widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had become a global pandemic. The most affected organ by the novel virus is the lung, and imaging exploration of the thorax using computer tomography (CT) scanning and X-ray has had an important impact. Materials and Methods: We assessed the prevalence of lung lesions in vaccinated versus unvaccinated SARS-CoV-2 patients using an artificial intelligence (AI) platform provided by Medicai. The software analyzes the CT scans, performing the lung and lesion segmentation using a variant of the U-net convolutional network. Results: We conducted a cohort study at a tertiary lung hospital in which we included 186 patients: 107 (57.52%) male and 59 (42.47%) females, of which 157 (84.40%) were not vaccinated for SARS-CoV-2. Over five times more unvaccinated patients than vaccinated ones are admitted to the hospital and require imaging investigations. More than twice as many unvaccinated patients have more than 75% of the lungs affected. Patients in the age group 30–39 have had the most lung lesions at almost 69% of both lungs affected. Compared to vaccinated patients with comorbidities, unvaccinated patients with comorbidities had developed increased lung lesions by 5%. Conclusion: The study revealed a higher percentage of lung lesions among unvaccinated SARS-CoV-2-positive patients admitted to The National Institute of Pulmonology “Marius Nasta” in Bucharest, Romania, underlining the importance of vaccination and also the usefulness of artificial intelligence in CT interpretation

    Imagistic findings using artificial intelligence in vaccinated versus unvaccinated SARS-CoV-2-positive patients receiving in-care treatment at a tertiary lung hospital

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    Abstract: Background: In December 2019 the World Health Organization announced that the widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had become a global pandemic. The most affected organ by the novel virus is the lung, and imaging exploration of the thorax using computer tomography (CT) scanning and X-ray has had an important impact. Materials and Methods: We assessed the prevalence of lung lesions in vaccinated versus unvaccinated SARS-CoV-2 patients using an artificial intelligence (AI) platform provided by Medicai. The software analyzes the CT scans, performing the lung and lesion segmentation using a variant of the U-net convolutional network. Results: We conducted a cohort study at a tertiary lung hospital in which we included 186 patients: 107 (57.52%) male and 59 (42.47%) females, of which 157 (84.40%) were not vaccinated for SARS-CoV-2. Over five times more unvaccinated patients than vaccinated ones are admitted to the hospital and require imaging investigations. More than twice as many unvaccinated patients have more than 75% of the lungs affected. Patients in the age group 30-39 have had the most lung lesions at almost 69% of both lungs affected. Compared to vaccinated patients with comorbidities, unvaccinated patients with comorbidities had developed increased lung lesions by 5%. Conclusion: The study revealed a higher percentage of lung lesions among unvaccinated SARS-CoV-2-positive patients admitted to The National Institute of Pulmonology "Marius Nasta" in Bucharest, Romania, underlining the importance of vaccination and also the usefulness of artificial intelligence in CT interpretation

    Imagistic findings using artificial intelligence in vaccinated versus unvaccinated SARS-CoV-2-positive patients receiving in-care treatment at a tertiary lung hospital

    No full text
    Background: In December 2019 the World Health Organization announced that the widespread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had become a global pandemic. The most affected organ by the novel virus is the lung, and imaging exploration of the thorax using computer tomography (CT) scanning and X-ray has had an important impact. Materials and Methods: We assessed the prevalence of lung lesions in vaccinated versus unvaccinated SARS-CoV-2 patients using an artificial intelligence (AI) platform provided by Medicai. The software analyzes the CT scans, performing the lung and lesion segmentation using a variant of the U-net convolutional network. Results: We conducted a cohort study at a tertiary lung hospital in which we included 186 patients: 107 (57.52%) male and 59 (42.47%) females, of which 157 (84.40%) were not vaccinated for SARS-CoV-2. Over five times more unvaccinated patients than vaccinated ones are admitted to the hospital and require imaging investigations. More than twice as many unvaccinated patients have more than 75% of the lungs affected. Patients in the age group 30-39 have had the most lung lesions at almost 69% of both lungs affected. Compared to vaccinated patients with comorbidities, unvaccinated patients with comorbidities had developed increased lung lesions by 5%. Conclusion: The study revealed a higher percentage of lung lesions among unvaccinated SARS-CoV-2-positive patients admitted to The National Institute of Pulmonology "Marius Nasta" in Bucharest, Romania, underlining the importance of vaccination and also the usefulness of artificial intelligence in CT interpretation

    Pinning Potential of the Self-Assembled Artificial Pinning Centers in Nanostructured YBa2Cu3O7−x Superconducting Films

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    For high-field power applications of high-temperature superconductors, it became obvious in recent years that nano-engineered artificial pinning centers are needed for increasing the critical current and pinning potential. As opposed to the artificial pinning centers obtained by irradiation with various particles, which is a quite expensive approach, we have studied superconducting samples having self-assembled defects, created during the sample fabrication, that act as effective pinning centers. We introduced a simple, straight-forward method of estimating the frequency-dependent critical current density by using frequency-dependent AC susceptibility measurements, in fixed temperatures and DC magnetic fields, from the positions of the maxima in the dependence of the out-of-phase susceptibility on the amplitude of AC excitation magnetic field. The results are compatible with a model that stipulates a logarithmic dependence of the pinning potential on the probing current. A mathematical derivation allowed us to estimate from the experimental data the pinning potentials in various samples, and in various DC magnetic fields. The resulted values indicate large pinning potentials, leading to very small probability of magnetic flux escaping the pinning wells, hence, leading to very high critical currents in high magnetic fields

    Subclinical Right Ventricular Dysfunction in Cystic Fibrosis

    No full text
    Patients with severe cystic fibrosis can develop cor pulmonale, but little is known about the function of the right ventricle (RV) early in the disease. We hypothesized that such patients might have subclinical RV dysfunction, detectable by tissue Doppler echocardiography, and related to the severity of lung disease. We studied 21 clinically stable patients (Group 1), five patients with severe lung disease (Group 2), and 23 age-matched healthy subjects. Patients had impaired RV systolic function. The mean (SD) systolic velocities of the RV free wall were 8.9 (1.7) cm/s in Group 1, 7.7 (1.0) in Group 2, and 10.8 (1.9) in healthy subjects (p < 0.001). The velocities of the tricuspid annulus were less in patients (p < 0.0001). Patients had a greater isovolumic relaxation time (p < 0.001), indicating RV diastolic dysfunction. RV wall thickness was greater in patients (0.4 [0.1] versus 0.3 [0.1] cm/m(2), p < 0.01). RV systolic function was related to C-reactive protein (r = - 0.66, p < 0.001) and FEV(1) (r = 0.62, p = 0.003) and diastolic function to interleukin-6 (r = 0.64, p < 0.005). Patients with cystic fibrosis have subclinical RV dysfunction, which correlates with the severity of lung disease. Tissue Doppler echocardiography provides a quantifiable indicator useful for detection and monitoring of disease progression
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