Following the COVID-19 outbreak, teaching and learning have been forced to move fully to the Internet rather than the conventional offline medium. As a result, the use of M-learning has risen dramatically, which was neither expected or anticipated. The challenges and benefits of such widespread usage are beginning to emerge in front of us. Thus, in this paper, we systematically review the benefits and challenges of leveraging M-learning for Science and Technology courses during the COVID-19 pandemic by educators and learners. Related articles were obtained from various databases, namely, IEEE, ACM Digital Library, ScienceDirect, and Springer. In total, 4210 related articles were initially found. Upon executing careful selection criteria, 22 articles were selected for review. After that, the advantages and threats were identified and discussed. As per our findings, it was determined that M-learning has excellent potential to be an effective platform for education provided that the identified shortcomings are resolved. This review will be helpful for education stakeholders and institutions to gauge the impact of leveraging M-learning as the only means for education to proceed. Moreover, it reveals the strengths and shortcomings that would aid in adjusting the relevant policies administered by the institutions. Furthermore, application developers will be able to comprehend the expected features that should be included in novel M-learning platforms.

The global COVID-19 mass vaccination program has created a polemic amongst pro- and anti-vaccination groups on social media. However, the working mechanism on how the shared information might influence an individual decision to be vaccinated is still limited. This study embarks on adopting the elaboration likelihood model (ELM) framework. We examined the function of central route factors (information completeness and information accuracy) as well as peripheral route factors (experience sharing and social pressure) in influencing attitudes towards vaccination and the intention to obtain the vaccine. We use a factorial design to create eight different scenarios in the form of Twitter posts to test the interaction and emulate the situation on social media. In total, 528 respondents were involved in this study. Findings from this study indicated that both the central route and peripheral route significantly influence individually perceived informativeness and perceived persuasiveness. Consequently, these two factors significantly influence attitude towards vaccination and intention to obtain the vaccine. According to the findings, it is suggested that, apart from evidence-based communication, the government or any interested parties can utilize both experience sharing and social pressure elements to increase engagement related to COVID-19 vaccines on social media, such as Twitter.

Education is an avenue of gaining knowledge and skills that will, in turn, support economic growth. Therefore, as online learning platforms are abundantly available in Malaysia, the urban poor in the Klang Valley have a means of improving their knowledge and skills to generate more income. However, online learning requires technical readiness. As such, this study examined the factors affecting the acceptance of online learning among the urban poor in Malaysia. An acceptance model was developed by integrating the constructs of the unified theory of acceptance and use of technology (UTAUT) with factors that influence the perceived value of online learning among the urban poor. To assess the reliability of these factors, 293 respondents participated in an online survey. SmartPLS 3.0 was then used to analyse the collected data. We found that performance expectancy (PE), facilitating conditions (FC), and perceived value (PV) positively influenced the behavioural intention to use (BI) online learning. Therefore, the findings of this study provide an understanding of the value and vital factors that impact the acceptance of online learning among the urban poor in the Klang Valley.

This paper identifies the factors that determine users' behavioral intention to use Clinic Information System and its causal relationships using theoretical model based on the Technology Acceptance Model and Theory of Planned Behavior. Using questionnaire survey, data related to the study were collected from 252 users work in private healthcare in Malaysia and subjected to structural equation modeling analysis. The proposed model fits the data well. Results indicate that the determinants of users' behavioral intention to use the system are computer anxiety, computer self efficacy, perceived ease of use, perceived usefulness, subjective norm, perceived behavioral control, and attitude. Finally, implications of these findings are discussed.

Type 2 diabetes (T2D) is a chronic condition that can lead to many life-threatening diseases. Prediabetes is defined as a state in which blood glucose levels are elevated but not high enough to be diagnosed as diabetes. This stage can be reversible with appropriate lifestyle and dietary modifications. Existing solutions are mostly developed to deal with T2D instead of preventing it in the first place. In this study, we propose a framework to aid in the development of self-care systems to prevent T2D, which integrates behavioral change theories and techniques and offers features, such as goal setting, activity planning, and health monitoring. We then assessed the feasibility of a prediabetes self-care system designed based on the proposed framework. Quantitative and qualitative methods were adopted in evaluating i-PreventDiabetes, a prototype. Numerous aspects of the prototype were evaluated, including (1) its effectiveness in assisting individuals with prediabetes in improving their health management behaviors, (2) its effect on users’ attitudes toward diabetes prevention, (3) users’ motivation levels, (4) user acceptability of the system, and (5) user experience. Users viewed i-PreventDiabetes positively and experienced a positive change in their attitude toward their health. Diabetes prevention systems, such as i-PreventDiabetes, have the potential to increase self-care behaviors among individuals with prediabetes, enabling them to manage their lifestyle and nutrition more effectively to avert a variety of potentially fatal conditions.