Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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    Online learning adoption by Chinese university students during the Covid-19 pandemic
    (School of Psychology, Massey University, 2022-12-01) Huggins TJ; Tan ML; Kuo Y-L; Prasanna R; Rea DD
    The 2019 Novel Coronavirus Pandemic has severely challenged the continuity of post-secondary education around the world. Online learning platforms have been put to the test, in a context where student engagement will not occur as a simple matter of course. To identify the factors supporting online learning under pandemic conditions, a questionnaire based on the Unified Theory of Acceptance and Use of Technology was adapted and administered to a sample of 704 Chinese university students. Structural equation modelling was applied to the resulting data, to identify the most relevant theoretical components. Effort expectancy, social influence, and information quality all significantly predicted both students’ performance expectancies and the overall adoption of their university’s Moodle-based system. Performance expectancy mediated the effects of effort expectancy, social influence, and information quality on symbolic adoption. Internet speed and reliability had no clear impact on adoption, and neither did gender. The direct impact of information quality on symbolic adoption represents a particularly robust and relatively novel result; one that is not usually examined by comparable research. As outlined, this is one of three key factors that have predicted online learning engagement, and the viability of educational continuity, during the Coronavirus pandemic. The same factors can be leveraged through user-focused development and implementation, to help ensure tertiary education continuity during a range of crises
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    Earthquake early warning systems based on low-cost ground motion sensors: A systematic literature review
    (Frontiers Media S.A, 3/11/2022) Chandrakumar C; Prasanna R; Stephens M; Tan ML
    Earthquake early warning system (EEWS) plays an important role in detecting ground shaking during an earthquake and alerting the public and authorities to take appropriate safety measures, reducing possible damages to lives and property. However, the cost of high-end ground motion sensors makes most earthquake-prone countries unable to afford an EEWS. Low-cost Microelectromechanical systems (MEMS)-based ground motion sensors are becoming a promising solution for constructing an affordable yet reliable and robust EEWS. This paper contributes to advancing Earthquake early warning (EEW) research by conducting a literature review investigating different methods and approaches to building a low-cost EEWS using MEMS-based sensors in different territories. The review of 59 articles found that low-cost MEMS-based EEWSs can become a feasible solution for generating reliable and accurate EEW, especially for developing countries and can serve as a support system for high-end EEWS in terms of increasing the density of the sensors. Also, this paper proposes a classification for EEWSs based on the warning type and the EEW algorithm adopted. Further, with the support of the proposed EEWS classification, it summarises the different approaches researchers attempted in developing an EEWS. Following that, this paper discusses the challenges and complexities in implementing and maintaining a low-cost MEMS-based EEWS and proposes future research areas to improve the performance of EEWSs mainly in 1) exploring node-level processing, 2) introducing multi-sensor support capability, and 3) adopting ground motion-based EEW algorithms for generating EEW.