47
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Measuring Distance Learning System Adoption in a Greek University during the Pandemic Using the UTAUT Model, Trust in Government, Perceived University Efficiency and Coronavirus Fear

      , ,
      Education Sciences
      MDPI AG

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The COVID-19 pandemic has led most universities around the world using e-learning services as an alternative to their curricula. These distance learning tools can help universities expand and enhance their curricula with flexible learning techniques. In order to measure distance learning systems adoption in the University of Macedonia, a Greek university in the city of Thessaloniki, an extended version of the UTAUT model is introduced by using the constructs of Trust in Government regarding the management of the pandemic, Perceived University Efficiency on issues regarding distance learning provision and Corona Fear. To analyze the proposed model, an online survey of 471 university students was conducted. Data were analyzed using Partial Least Squares. The findings revealed that students’ attitudes toward University Efficiency affect key variables of the proposed model, such as Performance Expectancy, Effort Expectancy, Social Influence, Facilitation Conditions and Use Behavior. Additionally, Trust in Government affects Perceived University Efficiency, and Use Behavior and Corona Fear affects University Efficiency and Trust in the Government in the management of pandemic issues. In contradiction with other research, Corona Fear has no moderating effects. University efficiency, Trust in Government and Corona Fear, because of the effects that they have on key variables, may have important managerial implications when considering the adoption of distance learning systems during the pandemic and in general.

          Related collections

          Most cited references85

          • Record: found
          • Abstract: found
          • Article: not found

          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              A new criterion for assessing discriminant validity in variance-based structural equation modeling

                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Education Sciences
                Education Sciences
                MDPI AG
                2227-7102
                September 2022
                September 15 2022
                : 12
                : 9
                : 625
                Article
                10.3390/educsci12090625
                def4211c-6d0f-4914-afc9-c90114d22c94
                © 2022

                https://creativecommons.org/licenses/by/4.0/

                History

                Comments

                Comment on this article