Students’ Satisfaction and e-Learning Courses in Covid-19 Pandemic Era: A Case Study

Erfannia, Leila; Sharifian, Roxana; Yazdani, Azita; Sarsarshahi, Aida; Rahati, Rezvaneh; Jahangiri, Saeedeh

doi:10.3233/shti210889

Cited by 6 publications

(14 citation statements)

References 8 publications

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“…Our study also showed that the standard of study materials, student-teacher communication, digital competences of the teacher and the student are positively correlated. This finding is in line with research [34], [35], which revealed a positive correlation between student-centred teaching design and the quality of distance education based on interactive communication methods and developed online communication. It can be concluded that the development of online learning applying user-friendly tools is an effective component of blended learning [35].…”

Section: Level Of Study Psupporting

confidence: 92%

“…This finding is in line with research [34], [35], which revealed a positive correlation between student-centred teaching design and the quality of distance education based on interactive communication methods and developed online communication. It can be concluded that the development of online learning applying user-friendly tools is an effective component of blended learning [35]. This is facilitated by digital infrastructure, support for student work and optimized, appropriately structured educational content in the form of study materials.…”

Section: Level Of Study Psupporting

confidence: 92%

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Perception of Selected Aspects of Online Learning by Czech Higher Education Students

Krelová¹,

Berková²,

Krpálek³

et al. 2022

Int. J. Eng. Ped.

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The study is based on an analysis of real educational processes in the period 2020-2021, when the most significant pandemic waves of Covid-19 were recorded in the Czech Republic. In relation to this, the study aims to identify the views of 968 students on the changed conditions of education and the perception of selected aspects of the transition to online learning by respondents from two higher education institutions in the Czech Republic, the first of which is focused on humanities and the second specializes in economics studies. The research is aimed at discovering students’ attitudes towards the form of distance education forced on them by the relevant circumstances, the use of individual components of distance education to support teaching originally designed for the in-person form, the level and effectiveness of the use of information technologies in online learning and the potential of hybrid learning. For a greater degree of analyticity, a combined research model based on both quantitative and qualitative research has been chosen. Aspects of online learning that could be employed as complementary tools in the full-time conventional study mode have been identified. Students of economics can better visualize the inclusion of online learning in the full-time conventional study mode. Master level students are critical of online learning. The results have been used to design and empirically validate appropriate learning strategies with reflection on current student needs.

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Section: Level Of Study Psupporting

confidence: 92%

Section: Level Of Study Psupporting

confidence: 92%

Perception of Selected Aspects of Online Learning by Czech Higher Education Students

Krelová¹,

Berková²,

Krpálek³

et al. 2022

Int. J. Eng. Ped.

View full text Add to dashboard Cite

show abstract

“…Consumer satisfaction is important, and businesses must maintain it to survive and succeed in competition (Tj and Tanuraharjo, 2020 ). In recent years, satisfaction has been widely considered in e-learning (Erfannia et al, 2022 ; Ung et al, 2022 ). Satisfaction with an online course is a variable that involves a self-perceived range of fulfillment linked to the individual's wish to learn and is an indicator of a positive evaluation of a learning experience (Dal Santo et al, 2022 ).…”

Section: Theoretical Development and Hypothesesmentioning

confidence: 99%

“…Research has proved that course quality significantly contributes to consumer satisfaction (Li et al, 2012 ; Cheng, 2020 ). For example, Erfannia et al ( 2022 ) explained that better support of e-learning course quality resulted in more fabulous students' satisfaction at Zahedan University of Medical Sciences. Cheng ( 2020 ) indicated that course quality (content quality and design quality) positively contributed to students' satisfaction with the cloud-based e-learning system.…”

Section: Theoretical Development and Hypothesesmentioning

confidence: 99%

Chinese Consumers' E-Learning Satisfaction and Continuance Purchase Intention on Paid Online Python Course

et al. 2022

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With the development of internet technology, e-learning has become an essential part of the modern education system. However, the e-learning market faces enormous competition. Consumers' continuance purchase intention has become a vital factor in the success of e-learning courses. Thus, factors that influence consumers' continuance purchase intention should be examined in the e-learning market. However, little research has focused on identifying the continuance purchase intention of an e-learning course. Based on the information system continuity model ISC), this paper develops a research model to investigate the factors influencing satisfaction and continuance purchase intention in e-learning. A cross-sectional, questionnaire-based research design was used in this study. We collected data from consumers who had enrolled in paid online Python courses. In total, 508 paid online Python course users completed the online survey. SmartPLS software was used for data analysis. The results demonstrated that perceived course quality, service quality, convenience, and usefulness significantly affect consumers' satisfaction with the experience course. Moreover, the findings show that satisfaction, self-efficacy, and e-word of mouth (e-WOM) determine the consumers' continuance purchase intention of the reminder course. This study also found that satisfaction mediates the effects of experience courses on consumers' continuance purchase intention of the online Python course. The implications for theory and practice and future research directions are discussed.

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“…n December 2019, a new coronavirus disease (COVID-19) outbreak appeared in Wuhan, China [1,2]. Due to fast transmission, COV-ID-19 was known as a pandemic in a few months worldwide, affecting public health, economic, and social conditions [3,4] with a wide range of clinical presentation and prognosis, such as the common cold, respiratory infections, multiple organ failure, and death [5,6].…”

mentioning

confidence: 99%

Predicting Risk of Mortality in COVID-19 Hospitalized Patients using Hybrid Machine Learning Algorithms

2022

J Biomed Phys Eng

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Background: Since hospitalized patients with COVID-19 are considered at high risk of death, the patients with the sever clinical condition should be identified. Despite the potential of machine learning (ML) techniques to predict the mortality of COVID-19 patients, high-dimensional data is considered a challenge, which can be addressed by metaheuristic and nature-inspired algorithms, such as genetic algorithm (GA).Objective: This paper aimed to compare the efficiency of the GA with several ML techniques to predict COVID-19 in-hospital mortality. Material and Methods:In this retrospective study, 1353 COVID-19 in-hospital patients were examined from February 9 to December 20, 2020. The GA technique was applied to select the important features, then using selected features several ML algorithms such as K-nearest-neighbor (K-NN), Decision Tree (DT), Support Vector Machines (SVM), and Artificial Neural Network (ANN) were trained to design predictive models. Finally, some evaluation metrics were used for the comparison of developed models.Results: A total of 10 features out of 56 were selected, including length of stay (LOS), age, cough, respiratory intubation, dyspnea, cardiovascular diseases, leukocytosis, blood urea nitrogen (BUN), C-reactive protein, and pleural effusion by 10-independent execution of GA. The GA-SVM had the best performance with the accuracy and specificity of 9.5147e+01 and 9.5112e+01, respectively. Conclusion:The hybrid ML models, especially the GA-SVM, can improve the treatment of COVID-19 patients, predict severe disease and mortality, and optimize the utilization of health resources based on the improvement of input features and the adaption of the structure of the models.

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Students’ Satisfaction and e-Learning Courses in Covid-19 Pandemic Era: A Case Study

Cited by 6 publications

References 8 publications

Perception of Selected Aspects of Online Learning by Czech Higher Education Students

Perception of Selected Aspects of Online Learning by Czech Higher Education Students

Chinese Consumers' E-Learning Satisfaction and Continuance Purchase Intention on Paid Online Python Course

Predicting Risk of Mortality in COVID-19 Hospitalized Patients using Hybrid Machine Learning Algorithms

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