Design and Development i-AVEN;GER as High-Tech Virtual Remote Teaching and Learning Platform with Experienced Based Learning and Self-regulated Learning Approaches in facilitating STEAM Education

With centuries-old lecture-based teaching methods, ingrained institutional biases, and obsolete classrooms, the slow pace of change in global education and academic institutions is lamentable. COVID-19, on the other hand, has acted as a catalyst for educational institutions worldwide to seek out novel solutions within a short or long timeframe. It is critical for countries to address the situation in such a way that the crisis fosters innovation and inclusion rather than exacerbating learning disparities. Schools are utilising distance learning programmes, educational apps, and platforms such as radio and the internet to reach students who live in remote areas. However, closing the so-called 'digital divide' - the divide between those with access to computers and the internet and those with limited or no access - is a difficult task. We propose in this paper the Interactive Accessible Virtual Education Network - Grand Educational Repository (i-AVEN$\vert$ GER), the world's first comprehensive futuristic hi-tech, comprehensive, and inclusive online structured learning platform with all types of interactivity, namely, educational app and portal. We've discussed the architecture and all of the associated functionalities thus far with recommended implementation. This proposed app and portal will be enhanced to ensure inclusivity for all people without regard for prejudice, as well as the incorporation of cutting-edge technology such as augmented reality, virtual reality, and artificial intelligence. © 2022 IEEE.

MFS usage intention during COVID-19 and beyond: an integration of health belief and expectation confirmation model

Purpose The usage rate of mobile financial services (MFS) has shown an uptick since the emergence of the COVID-19 pandemic in Bangladesh. This study aims to reveal the underpinning reasons for such MFS surge and its continuance by integrating health belief model (HBM) and expectation confirmation model (ECM). Design/methodology/approach The study analyzes 529 MFS users' responses during the second wave of the COVID-19 outbreak in Bangladesh using the partial least square method. Findings Satisfaction is more predictive than perceived usefulness in explaining continuance usage intention. Expectation confirmation also indirectly affects continuance intention. Among the HBM constructs, the indirect effect of perceived severity on continuance intention via perceived usefulness and satisfaction is significant. Besides, the impact of self-efficacy on continuance intention is also significant. Moreover, perceived credibility significantly affects satisfaction and indirectly affected continuance usage intention via satisfaction. Practical implications The study projects boosting customers' satisfaction is critical for the successful retention of existing MFS customers. MFS service providers should emphasize the factors that amplify satisfaction. They must evaluate preadoption factors so that customers can have positive confirmation. Especially, the service providers, the policymakers and the regulators should take an active role in improving the users' self-efficacy and the system's credibility. Undertaking the MFS literacy program, installing hotline service to provide emergency help will boost users' confidence in using the system. Originality/value The study is a unique contribution in the context of Bangladesh. To the best of the authors' knowledge, no previous MFS studies in Bangladesh explored MFS continuance usage intention during COVID-19 and beyond. Besides, the inclusion of "perceived credibility" in the framework will supplement the earlier studies conducted on this aspect.