ABSTRACT
The data is for empirical studies derived from a related research article about space tourism [1], which is a conceptual article with a different aim of economic measurement scale. Most space tourism research is conceptual because data from the nascent industry is limited [2]. Thus this data is constrictive for conducting empirical studies to contribute to quantitative analysis in space tourism [3]. Data from this study were collected by recruiting 361 respondents through snowball and convenient sampling targeted to samples interested in space tourism; 339 responses were adopted after the valid screening of missing data or data bias [4]. Targeted groups of potential space tourism customers were investigated to collect data through a designed questionnaire on the platform, Wenjuanxing, with a majority population database providing functions equivalent to Amazon Mechanical Turk [2]. The reliability and validity of all constructs showed that the questionnaire was proper for measurement [3]. Data analysis applied the structural equation model with Mplus to examine the CFA model and research hypothesis. Structural equation modeling was used to conduct the hypotheses test and model fitness through the statistical tool Mplus. Results imply that the data is suitable for conducting replication studies. To enlighten space tourism emergence studies, this data shows its importance for further research models [5].
ABSTRACT
The research article "Realtime Online Courses Mutated amid the COVID-19 Pandemic: Empirical Study in Hospitality Program" aims to explore the education evolution amid the pandemic [1]. Data were collected by recruiting 956 respondents; 926 responses were adopted after the valid screening through a cooperative survey company. A random sampling of targeted groups was required when outsourcing the data collection to the survey company Wenjuanxing, a platform with a majority population database providing functions equivalent to Amazon Mechanical Turk [2]. We asked the company to deliver the designed questionnaire to teachers and students in hospitality programs. The reliability and validity of all constructs showed that the questionnaire is proper for measurement [3]. Data analysis applied the structural equation model with Mplus to examine the CFA model and research hypothesis. Structural equation modeling was applied to conduct the hypotheses test and model fitness through the statistical tool Mplus. Results imply that the data is suitable for conducting replication studies.
ABSTRACT
Real-time online courses (RTOCs), a new online learning mode, have been developed because of a longitudinal suspension of classes amid the COVID-19 pandemic worldwide. We explore an information model to review the learning process and outcomes of RTOCs, which conducted educational activities via social media. Results show that social media can be a potent mediation factor with the moderation of structural differentiation to facilitate online learning outcomes. Conclusions imply that the life-changing impact of COVID-19 has caused an evolutionary online education mode that can be hybridized with face-to-face education and massive open online courses to flourish education approaches and pedagogies.
ABSTRACT
BACKGROUND/PURPOSE: Traditional dental care, which includes long-term oral hygiene maintenance and scheduled dental appointments, requires effective communication between dentists and patients. In this study, a new system was designed to provide a platform for direct communication between dentists and patients. METHODS: A new mobile app, Dental Calendar, combined with cloud services specific for dental care was created by a team constituted by dentists, computer scientists, and service scientists. This new system would remind patients about every scheduled appointment, and help them take pictures of their own oral cavity parts that require dental treatment and send them to dentists along with a symptom description. Dentists, by contrast, could confirm or change appointments easily and provide professional advice to their patients immediately. In this study, 26 dentists and 32 patients were evaluated by a questionnaire containing eight dental-service items before and after using this system. Paired sample t test was used for statistical analysis. RESULTS: After using the Dental Calendar combined with cloud services, dentists were able to improve appointment arrangements significantly, taking care of the patients with sudden worse prosthesis (p < 0.05). Patients also achieved significant improvement in appointment reminder systems, rearrangement of appointments in case of sudden worse prosthesis, and establishment of a direct relationship with dentists (p < 0.05). CONCLUSION: Our new mobile app, Dental Calendar, in combination with cloud services, provides efficient service to both dentists and patients, and helps establish a better relationship between them. It also helps dentists to arrange appointments for patients with sudden worsening of prosthesis function.
