This paper is dedicated to the higher education institutions shifting towards distance learning processes due to the global pandemic situation caused by COVID-19 in 2020. The paper covers the pandemic situation in Poland generally, analyzing governmental ordinances and tracking the gradual extension of restrictions for educational institutions. The purpose of this study is to investigate the influence of Experience, Enjoyment, Computer Anxiety, and Self-Efficacy on students’ acceptance of shifting education to distance learning. The study tested and used the adapted General Extended Technology Acceptance Model for E-Learning (GETAMEL) in the context of coronavirus pandemic. The partial least squares method of structural equation modeling was employed to test the proposed research model. The study utilizes an online survey to obtain data from 1692 Polish undergraduate and graduate students in both full- and part-time study. The dataset was analyzed using SmartPLS 3 software. Results showed that the best predictor of student’s acceptance of shifting education to distance learning is Enjoyment, followed by Self-Efficacy. Both Perceived Ease of Use and Perceived Usefulness predict student’s Attitude Towards Using and Intention to Use the distance learning. The findings improve understanding regarding the acceptance of distance learning and this work is therefore of particular interest to teachers and practitioners of education.

The article deals with distance education, which as a teaching method had to be suddenly introduced in schools and higher education institutions as a result of the global pandemic situation. The paper captures the second wave of Poland’s pandemic situation in relation to global circumstances and the methods of conducting distance learning used across the globe. The purpose of this study was to investigate first-year students’ expectations about the education shift to distance learning. GETAMEL, which is the adapted General Extended Technology Acceptance Model for E-Learning, was used in the study. The study analyzed the influence of Experience, Subjective Norms, Enjoyment, Computer Anxiety, and Self-Efficacy on students’ expectations in the context of distance learning during the COVID-19 pandemic. To test the research model presented during the research, The Partial Least Squares method of Structural Equation Modeling was used. An online survey was created to conduct the research, which collected data from 670 Polish first-year undergraduate students. The acquired data were analyzed using the SmartPLS 3 software. The results of the research indicated that the most important factors that influence the feelings of students and can convince them to change from teaching in the classroom to teaching in the distance learning model are the feeling of pleasure in this form of education and a sense of self-efficacy. The results of this study may be of particular interest to education practitioners, including teachers, and a starting point for further research on e-learning models, including, in particular, the understanding of students’ expectations regarding distance learning.

No abstract

The recent emergence of a new coronavirus (2019-nCoV) has gained a high cover in public media and worldwide news. This caused a viral pneumonia in thousands of people in Wuhan, a central city of China. This short communication gives a brief introduction on how the demand for information on this new epidemic is reported through Google Trends. Author draw conclusions on current infodemiological data on 2019-nCov using three main search queries: coronavirus, SARS and MERS. Two approaches are set. First is worldwide perspective, second is Chinese perspective. Chinese perspective reveals that in China, this disease in the beginning days was more often referred to SARS then to general coronaviruses, whereas worldwide, since the beginning is more often referred to coronaviruses.

The Google search engine answers many health and medical information queries every day. People have become used to searching for this type of information. This paper presents a study which examined the visibility of health and medical information websites. The purpose of this study was to find out why Google is decreasing the visibility of such websites and how to measure this decrease. Since August 2018, Google has been more rigorously rating these websites, since they can potentially impact people’s health. The method of the study was to collect data about the visibility of health and medical information websites in sequential time snapshots. Visibility consists of combined data of unique keywords, positions, and URL results. The sample under study was made up of 21 websites selected from 10 European countries. The findings reveal that in sequential time snapshots, search visibility decreased. The decrease was not dependent on the country or the language. The main reason why Google is decreasing the visibility of such websites is that they do not meet high ranking criteria.

No abstract

The pandemic of the coronavirus disease 2019 (COVID-19), has gained extensive coverage in public media and global news, generated international and national communication campaigns to educate the communities worldwide and raised the attention of everyone. The coronavirus has caused viral pneumonia in tens of thousands of people around the world, and the COVID-19 outbreak changed most countries’ routines and concerns and transformed social behaviour. This study explores the potential use of Google Trends (GT) in monitoring interest in the COVID-19 outbreak and, specifically, in personal protective equipment and hand hygiene, since these have been promoted by official health care bodies as two of the most protective measures. GT was chosen as a source of reverse engineering data, given the interest in the topic and the novelty of the research. Current data on COVID-19 are retrieved from GT using keywords in two languages—Portuguese and Polish. The geographical settings for GT are two countries: Poland and Portugal. The period under analysis is 20 January 2020, when the first cases outside China were known, to 15 June 2020. The results show that there is a correlation between the spread of COVID-19 and the search for personal protective equipment and hand hygiene and that GT can help, to a certain extent, understand people’s concerns, behaviour and reactions to sanitary problems and protection recommendations.

The paper is dedicated to factors influencing users’ adoption of sustainable cloud computing solutions. The article covers the important characteristics related to cloud computing. It also discusses how sustainable cloud computing is important for sustainability. The current state of their security and potential threats waiting for users is reviewed. The purpose of this study is to investigate the influence of perceived usefulness, security, availability, and satisfaction on users’ adoption of sustainable cloud computing solutions. The study tested and used the adapted Technology Acceptance Model (TAM) model in the context of cloud computing solutions. The partial least square method of structural equation modeling is employed to test the proposed research model. The study utilizes an online survey to obtain data from 252 cloud computing solutions users. The data set was analyzed using SmartPLS 3 software. Results showed that the best predictor of users’ perceived usefulness and system & service quality is perceived availability, followed by perceived security. Both perceived usefulness and system & service quality predict users’ attitude and intention to use of cloud computing solutions. The findings improve understanding regarding the adoption of cloud computing solutions, and this work is, therefore, of particular interest to the IT departments and cloud computing vendors.