ABSTRACT
With the rise of the COVID-19 pandemic, many undergraduates were forced to transition from in-person to remote learning. In order to hold live synchronous classes, institutions adopted online videoconferencing platforms such as Zoom. This study examined student experiences during Zoom classes with regard to perceptions of unproductive cognitive load stemming from factors such as personal software settings, instructor-determined class features, teaching methods, feelings toward the class, internal state, and external environment. For comparison, a parallel survey was administered to instructors regarding student perceptions. The top five factors students reported to increase unproductive load were life stress, tiredness, sickness, negative emotions, and auditory distractions;the factors linked most strongly to decrease unproductive load were enjoyment of the class, interest in the class topic, relevance to future goals, presentation of information in manageable and meaningful chunks, and ability to focus. Instructor ratings overall aligned with those of students. Participants also reported overall higher mental fatigue during Zoom, as framed in comparison to prior in-person classes;this was correlated with number and time spent in these classes, but not with demographic variables nor with several other independent measures of self-regulated learning and academic self-efficacy. Implications for improving the student experience in online learning are discussed, emphasizing that many of the factors reported as helpful to cognitive load management are applicable to all classrooms. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
With the emergence of the COVID-19 pandemic, the World Health Organization (WHO) has urged scientists and industrialists to explore modern information and communication technology (ICT) as a means to reduce or even eliminate it. The World Health Organization recently reported that the virus may infect the organism through any organ in the living body, such as the respiratory, the immunity, the nervous, the digestive, or the cardiovascular system. Targeting the abovementioned goal, we envision an implanted nanosystem embedded in the intra living-body network. The main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or to implement a targeted drug delivery system (i.e., delivery of the therapeutic drug to the diseased tissue or targeted cell). The communication among the nanomachines is accomplished via communication-based molecular diffusion. The control/interconnection of the nanosystem is accomplished through the utilization of Internet of bio-nano things (IoBNT). The proposed nanosystem is designed to employ a coded relay nanomachine disciplined by the decode and forward (DF) principle to ensure reliable drug delivery to the targeted cell. Notably, both the sensitivity of the drug dose and the phenomenon of drug molecules loss before delivery to the target cell site in long-distance due to the molecules diffusion process are taken into account. In this paper, a coded relay NM with conventional coding techniques such as RS and Turbo codes is selected to achieve minimum bit error rate (BER) performance and high signal-to-noise ratio (SNR), while the detection process is based on maximum likelihood (ML) probability and minimum error probability (MEP). The performance analysis of the proposed scheme is evaluated in terms of channel capacity and bit error rate by varying system parameters such as relay position, number of released molecules, relay and receiver size. Analysis results are validated through simulation and demonstrate that the proposed scheme can significantly improve delivery performance of the desirable drugs in the molecular communication system.
ABSTRACT
The pandemic of COVID 19 virus has caused a lot of damage around the world. In addition to human lives, the economies of entire countries are at risk. In order to avoid business, health and education systems breakdown, it was necessary to find a new models of their functioning. An increasing number of these systems depends on IT support, so online teaching, obtaining information on health status and video conferencing meetings in business corporations has become a daily life. Although from the point of view of the end users of these systems, the result is information or data that has been processed, special attention should be highlighted to the transfer of information of various types through existing modern communication systems. In case that information of a great importance is intercepted or unreliable, the consequences can be catastrophic. Given the current situation at the global level and the importance of the information transmitted, in this paper we will focus on the protection and reliability of information transmission using adaptive transmission algorithms. Modeling and implementation of adaptive transmission algorithms can allow us to adapt the data rate with higher bandwidth or fixed data rate with lower bandwidth depending on the needs of end users and their requirements. Whether optical cables, radio frequency systems or modern wireless optical communication systems are used for the transmission of information, adaptive transmission algorithms can be successfully implemented and thus greater security and reliability of the transmitted information can be achieved. In addition to the model of adaptive transmission algorithms, the pseudocode of their functioning will be given in this paper. Finally, a comparative analysis of these algorithms observed through a measure of channel capacity will be graphically presented.