ABSTRACT
COVID-19 has wreaked havoc on communities, cities, countries, and continents globally, not solely in Africa. The affluent and most developed countries were not equipped for the COVID-19 pandemic. Organisations that were usually not recognised as critical services realised that in order to survive, they needed to substitute and find alternatives to continue doing business. Some countries went into level five lockdown. Higher education institutions were instantly pushed to switch from face-to-face teaching and learning to online learning. Teaching at the University of Zululand is done mainly through Moodle and WhatsApp. Lecturers use BigBlueButton to deliver Moodle lessons. These classes are recorded and readily accessible. M-Learning is becoming a common way of learning, however, lack of data, network connectivity, and load shedding has been a major challenge. The theoretical framework for this paper was the Shannon and Weaver Model of Communication. A mixed method research approach was used as part of their methodology. Due to students not being present on campus, Google Forms were used to disseminate the questionnaires. From the data, it is clear that students have a challenge with online assessment, however, the majority still prefer to study online. However, internet data connectivity and load shedding have become major obstacles in online teaching and learning.
ABSTRACT
PurposeOnline learning has become more popular than ever in higher education owing to the COVID-19 pandemic. However, this has also intensified students' propensity to engage in cyberslacking behaviour during online classes without the physical presence of instructors to monitor their behaviour. Hence, this research aims to investigate the association of the Big Five personality traits and situational factors with students' cyberslacking behaviour during online classes.Design/methodology/approachA self-administered survey questionnaire was distributed to current university students undertaking online modules this semester. In all, 194 completed surveys were obtained for further analysis.FindingsThe results reveal that extraversion, conscientiousness, neuroticism and apathy towards course material have a significant association with at least one of the cyberslacking dimensions (sharing, shopping, real-time updating, accessing online content and gaming/gambling). However, agreeableness, intellect/imagination and class engagement are found to have no significant association with all the dimensions of students' cyberslacking behaviour during online classes.Originality/valueThis study fills the research gaps by empirically testing the association of the Big Five personality traits and situational factors with students' cyberslacking behaviour in e-learning environments. Several limitations and future research are also discussed.
ABSTRACT
When a high-ranking British politician was falsely accused of child abuse by the BBC in November 2012, a wave of short messages followed on the online social network Twitter leading to considerable damage to his reputation. However, not only did the politician's image suffer considerable damage, moreover, he was also able to sue the BBC for 185,000 in damages. On the relatively new media of the internet and specifically in online social networks, digital wildfires, i.e., fast spreading, counterfactual or even intentionally misleading information occur on a regular basis and lead to severe repercussions. Although the example of the British politician is a simple digital wildfire that only damaged the reputation of a single person, there are more complex digital wildfires whose consequences are more far-reaching. This thesis deals with the capture, automatic processing, and investigation of a complex digital wildfire, namely, the Corona and 5G misinformations event - the idea that the COVID-19 outbreak is somehow connected to the introduction of the 5G wireless technology. In this context, we present a system whose application allows us to acquire large amounts of data from the online social network Twitter and thus create the database from which we extract the digital wildfire in its entirety. Furthermore, we present a framework that provides the playing field for investigating the spread of digital wildfires. The main findings that emerge from the study of the 5G and corona misinformation event can be summarised as follows. Although published work suggests that a purely structure-based analysis of the information spread allows for early detection, there is no way of predictively labelling spreading information as probably leading to a digital wildfire. Digital wildfires do not emerge out of nowhere but find their origin in a multitude of already existing ideas and narratives that are reinterpreted and recomposed in the light of a new situation. It does not matter if ideas and explanations contradict each other. On the contrary, it seems that it is the existence of contradictory explanations that unites supporters from different camps to support a new idea. Finally, it has been shown that the spread of a digital wildfire is not the result of an information cascade in the sense of single, particularly influential short messages within a single medium. Rather, a multitude of small cascades with partly contradictory statements are responsible for the rapid spread. The dissemination media are diverse, and even more so, it is precisely the mix of different media that makes a digital wildfire possible. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
Purpose: Our objective is to pilot an advertisement-driven sampling procedure among African American (AA) breast cancer survivors living in Maryland. These pilot study methods will inform a future population-based study of AA breast cancer survivors at high risk of poor outcomes due to biological differences and social inequities. Methods: This cross-sectional study utilizes an innovative, social media-based advertisement campaign with an associated social media study page to recruit 100 AA breast cancer survivors. Participants are biologically female, aged 18 and older, identify as AA/Black, have a diagnosis of breast cancer, and reside in Maryland. A preset "Audience" was created via Meta (formerly Facebook) to automatically target potential interest in the online study via geolocation and public social media interests (estimated range = 101,000 women). Eligible participants complete an online survey including demographic and clinical characteristics, cancer screening, healthcare access, and utilization, COVID-19 impact, quality of doctor-patient communication, and preferences for future study participation. Results: Recruitment began on 5 January 2022 and remains ongoing. As of 7 June 2002: 124 completed the screener, 110/124 (88.7%) consented passively, 24/110 (21.8%) started but did not complete survey, 86/110 (78.1%) completed the survey. Conclusions: Results from this study will inform a statewide multilevel prospective population-based study to improve health behaviors, disease management, and self-efficacy of chronic disease management among AA breast cancer survivors.