The perceived usability of the learning management system during the COVID-19 pandemic: Integrating system usability scale, technology acceptance model, and task-technology fit.

BACKGROUND: The education system has shifted from traditional to online during the COVID-19 pandemic. Thus, the Learning Management System (LMS) is one of the most important and comprehensive learning platforms that support and facilitate online learning during this pandemic. OBJECTIVE: This study explored the perceived system usability of LMS during the COVID-19 pandemic by utilizing Technology Acceptance Model (TAM), Task-Technology Fit (TTF), and System Usability Scale (SUS). METHODS: An online survey was utilized to collect data from 502 Filipino students from different academic institutions and different areas of study. RESULTS: Structural Equation Modeling (SEM) indicated that students' perceived ease of use of LMS had a significant effect on perceived usefulness which subsequently and positively led to students' perceived satisfaction of LMS. In addition, LMS technology characteristics was found to have a significant effect on LMS task-technology fit which subsequently led to perceived usefulness and perceived satisfaction. Interestingly, perceived satisfaction was found to have a significant effect on students' perceived system usability of LMS which was calculated using a System Usability Scale (SUS). CONCLUSION: The findings have implications within the education system globally, particularly in recognizing the relevance of LMS moving forward. Furthermore, since this is the first study that integrated SUS, TAM, and TTF, the conceptual framework can be utilized to evaluate the perceived usability of LMS worldwide.

Factors Influencing the Perceived Effectiveness of COVID-19 Risk Assessment Mobile Application "MorChana" in Thailand: UTAUT2 Approach.

COVID-19 contact-tracing mobile applications have been some of the most important tools during the COVID-19 pandemic. One preventive measure that has been incorporated to help reduce the virus spread is the strict implementation of utilizing a COVID-19 tracing application, such as the MorChana mobile application of Thailand. This study aimed to evaluate the factors affecting the actual usage of the MorChana mobile application. Through the integration of Protection Motivation Theory (PMT) and Unified Theory of Acceptance and Use of Technology (UTAUT2), latent variables such as performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), habit (HB), perceived risk (PCR), self-efficacy (SEF), privacy (PR), trust (TR), and understanding COVID-19 (U) were considered to measure the intention to use MorChana (IU) and the actual usage (AU) of the mobile application. This study considered 907 anonymous participants who voluntarily answered an online self-administered survey collected via convenience sampling. The results show that IU presented the highest significant effect on AU, followed by HB, HM, PR, FC, U, SEF, PE, EE, TR, and SI. This is evident due to the strict implementation of using mobile applications upon entering any area of the vicinity. Moreover, PCR was not seen to be a significant latent factor affecting AU. This study is the first to have evaluated mobile contact tracing in Thailand. The integrated framework can be applied and extended to determine factors affecting COVID-19 tracing applications in other countries. Moreover, the findings of this study could be applied to other health-related mobile applications worldwide.

Utilization of Random Forest and Deep Learning Neural Network for Predicting Factors Affecting Perceived Usability of a COVID-19 Contact Tracing Mobile Application in Thailand "ThaiChana".

The continuous rise of the COVID-19 Omicron cases despite the vaccination program available has been progressing worldwide. To mitigate the COVID-19 contraction, different contact tracing applications have been utilized such as Thai Chana from Thailand. This study aimed to predict factors affecting the perceived usability of Thai Chana by integrating the Protection Motivation Theory and Technology Acceptance Theory considering the System Usability Scale, utilizing deep learning neural network and random forest classifier. A total of 800 respondents were collected through convenience sampling to measure different factors such as understanding COVID-19, perceived severity, perceived vulnerability, perceived ease of use, perceived usefulness, attitude towards using, intention to use, actual system use, and perceived usability. In total, 97.32% of the deep learning neural network showed that understanding COVID-19 presented the most significant factor affecting perceived usability. In addition, random forest classifier produced a 92% accuracy with a 0.00 standard deviation indicating that understanding COVID-19 and perceived vulnerability led to a very high perceived usability while perceived severity and perceived ease of use also led to a high perceived usability. The findings of this study could be considered by the government to promote the usage of contact tracing applications even in other countries. Finally, deep learning neural network and random forest classifier as machine learning algorithms may be utilized for predicting factors affecting human behavior in technology or system acceptance worldwide.

Factors Affecting the Perceived Usability of the COVID-19 Contact-Tracing Application "Thai Chana" during the Early COVID-19 Omicron Period.

Thai Chana is one of the mobile applications for COVID-19 disease-control tracking, especially among the Thais. The purpose of this study was to determine factors affecting the perceived usability of Thai Chana by integrating protection motivation theory, the extended technology acceptance model, and the system usability scale. In all, 800 Thais participated and filled an online questionnaire with 56 questions during the early COVID-19 omicron period (15 December 2021 to 14 January 2022). Structural equation modeling (SEM) showed that the understanding of COVID-19 has significant effects on perceived severity and perceived vulnerability, which subsequently leads to perceived usefulness. In addition, perceived usefulness and perceived ease of use have significant direct effects on attitude, which subsequently leads to the intention to use, actual use, and perceived usability. This study is one of the first studies that have analyzed the mobile application for COVID-19 disease-control tracking. The significant and substantial findings can be used for a theoretical foundation, particularly in designing a new mobile application for disease-control tracking worldwide. Finally, protection motivation theory, the extended technology acceptance model, and the system usability scale can be used for evaluating other disease-control tracking mobile applications worldwide.

Public utility vehicle service quality and customer satisfaction in the Philippines during the COVID-19 pandemic.

The implementation of lockdown due to the COVID-19 pandemic has affected most businesses worldwide. The transportation business, specifically in the Philippines, has been heavily affected since only the healthcare and essential workers were allowed to leave their homes during the early stage of the pandemic. This paper aimed to explore the service quality of Public Utility Vehicles (PUV) in the Philippines during the COVID-19 pandemic utilizing the SERVQUAL dimensions. A total of 564 participants answered an online questionnaire using the convenience sampling approach, consisting of 58 questions. Structural equation modelling (SEM) was applied to derive the causal relationships between SERVQUAL dimensions, COVID-19 safety protocol, and customer satisfaction simultaneously. Out of the six dimensions, the SEM indicated that COVID-19 protocols, tangibility, and assurance variables were found to significantly affect PUV service quality and thus, customer satisfaction. This study is one of the first complete studies that analyzed the PUV service quality during the COVID-19 pandemic. The findings could provide the government with an evaluation of the compliance of PUVs to the imposed COVID-19 protocols. Furthermore, the framework of this study could also be applied and extended in evaluating PUV worldwide.