Knowledge Extraction
Fatemeh Baratloo
Abstract
The purpose of this study is to identify the thematic trends of scientific publications in the fields of humanities and social sciences, considering the impact of Covid-19. The study utilizes a descriptive approach with a scientometric and content analysis method, incorporating co-word analysis and social ...
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The purpose of this study is to identify the thematic trends of scientific publications in the fields of humanities and social sciences, considering the impact of Covid-19. The study utilizes a descriptive approach with a scientometric and content analysis method, incorporating co-word analysis and social network analysis techniques. The research population comprises Covid-19 studies in the fields of humanities and social sciences in the Web of Science, conducted between 2019 and 2021, involving the top countries in three prominent continents. CiteSpace, Bibexcel, and Gephi software were used to analyze the data, while VOSviewer software was utilized to visualize the intellectual structure. The analysis reveals that religion, spirituality, public health, religiosity, mental health, epidemics, depression, crisis, social media, anxiety, and ethics are significant keywords in research within the humanities and social sciences. Additionally, thematic overlap is observed in the clusters of "China and Spain" and "India, Turkey, Britain, Italy, United States, Canada, and Brazil," with a greater accumulation of clusters in the studies of Turkey, Canada, and Brazil. In addition, it can be said that the focus of studies in the Americas is more on social sciences than on studies in the other two continents.
Ebrahim Rajabpour; Ahmad Ghorbanpur; Mohammad Reza Fathi; Seyed Mohammad Sobhani
Abstract
This study aims to provide a Gamification Driver Soft modelling of Learning Management Systems in Covid-19 Pandemic. By studying the theoretical foundations and experimental background and content analysis approach, eleven drivers were identified in the first phase. This study's statistical population ...
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This study aims to provide a Gamification Driver Soft modelling of Learning Management Systems in Covid-19 Pandemic. By studying the theoretical foundations and experimental background and content analysis approach, eleven drivers were identified in the first phase. This study's statistical population consisted of Persian Gulf University (Bushehr) faculty members with appropriate empirical and theoretical knowledge in information systems scope. Fourteen of them were selected as sample members by purposeful judgmental sampling method. The data collection tool was a researcher-made questionnaire whose validity was confirmed by face content analysis method, and also the reliability was confirmed by inconsistency rate method. The collected data were analyzed by fuzzy interpretive structural modelling to design a Gamification Driver Soft modelling. The results showed that the driver of "learning opportunity", "appropriate design", "ease of use", "motivation" and "cooperation" which were placed in the lower levels of the model, as effective and root driver. Therefore, it is requisite to have more emphasis on these drivers when designing systems to motivate users resulting in the improvement of learning outcomes. It should be noted that the proposed research is innovative in terms of modelling Gamification driver in learning/teaching systems in the Covid- 19 pandemic. In today's digital age; ideas formation will not be possible without considering other facts in terms of emerging paradigms of technology. Gamification is a new concept of information systems in the motivational learning scope that if used in virtual learning guarantees its success as the critical element of training in the pandemic of Covid-19.