The Impact of Formal Education on Computer Literacy

Milić, Melita; Škorić, Igor

doi:10.3991/ijet.v5s2.1253

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…For example, a US Department of Education report posits that Black people were twice as likely to be digitally illiterate than their White counterparts [ 43 ]. An individual’s level of formal education also affects their knowledge of computer literacy [ 44 ]. Such factors may contribute heavily to the ability of individuals to identify misinformation on the internet and the desire to get a COVID-19 vaccination—otherwise known as the degree that they are vaccine hesitant.…”

Section: Discussionmentioning

confidence: 99%

Predictive Modeling of Vaccination Uptake in US Counties: A Machine Learning–Based Approach

Cheong¹,

Au-Yeung²,

Quon³

et al. 2021

J Med Internet Res

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Background Although the COVID-19 pandemic has left an unprecedented impact worldwide, countries such as the United States have reported the most substantial incidence of COVID-19 cases worldwide. Within the United States, various sociodemographic factors have played a role in the creation of regional disparities. Regional disparities have resulted in the unequal spread of disease between US counties, underscoring the need for efficient and accurate predictive modeling strategies to inform public health officials and reduce the burden on health care systems. Furthermore, despite the widespread accessibility of COVID-19 vaccines across the United States, vaccination rates have become stagnant, necessitating predictive modeling to identify important factors impacting vaccination uptake. Objective This study aims to determine the association between sociodemographic factors and vaccine uptake across counties in the United States. Methods Sociodemographic data on fully vaccinated and unvaccinated individuals were sourced from several online databases such as the US Centers for Disease Control and Prevention and the US Census Bureau COVID-19 Site. Machine learning analysis was performed using XGBoost and sociodemographic data. Results Our model predicted COVID-19 vaccination uptake across US counties with 62% accuracy. In addition, it identified location, education, ethnicity, income, and household access to the internet as the most critical sociodemographic features in predicting vaccination uptake in US counties. Lastly, the model produced a choropleth demonstrating areas of low and high vaccination rates, which can be used by health care authorities in future pandemics to visualize and prioritize areas of low vaccination and design targeted vaccination campaigns. Conclusions Our study reveals that sociodemographic characteristics are predictors of vaccine uptake rates across counties in the United States and, if leveraged appropriately, can assist policy makers and public health officials to understand vaccine uptake rates and craft policies to improve them.

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Section: Discussionmentioning

confidence: 99%

Predictive Modeling of Vaccination Uptake in US Counties: A Machine Learning–Based Approach

Cheong¹,

Au-Yeung²,

Quon³

et al. 2021

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…Furthermore, since computer anxiety is associated with a negative relationship to ICT and low computer literacy (cf. Milic & Škoric, 2010), and since it is expected to weaken intrinsic motivation to cope with ICT-specific situations and/or problems, we predicted negative correlations of ICT engagement dimensions with computer anxiety.…”

Section: Research Goals and Hypothesesmentioning

confidence: 96%

Moving beyond cognitive elements of ICT literacy: First evidence on the structure of ICT engagement

Zylka

Christoph

Kroehne

et al. 2015

Computers in Human Behavior

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a b s t r a c tThe use of Information and Communication Technology (ICT) is of immense importance in today's digital knowledge society. As a basis for private and vocational participation in society, ICT literacy has been widely discussed in recent decades. Although motivational and metacognitive facets play an important role in developing ICT literacy and competence, studies assessing media, computer or ICT literacy often fail to present a comprehensive concept on these motivational and metacognitive facets. This article addresses this issue by integrating them into the concept of ICT engagement. Its theoretically deduced dimensions of ICT-related interest, self-concept related to the use of ICT, and social exposure to ICT were analyzed in an explorative study assessing N = 445 students aged between 14 and 17 years in the German federal state of Baden-Wuerttemberg. The obtained dimensional structure included the assumed factors, and suggested to distinguish a positive and a negative self-concept on using ICT as well as to separate interest in computers and interest in mobile devices factor. The ICT engagement dimensions were related to individual differences in behavioral, cognitive and emotional ICT constructs as expected.

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“…Graphics is an important tool for students doing art and design, therefore should be well catered for during studies [5]. The use of computer exists almost at every stage in modern life which makes it hard for people without computer skills to advance in professional and personal life [6].…”

Section: Computer Skills Amongst Students Is Necessarymentioning

confidence: 99%

Investigation on the Poor Computer Graphic Design Skills among Art and Design Students at University

2019

International Journal of Humanities, Social Sciences and Educat

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The Impact of Formal Education on Computer Literacy

Cited by 3 publications

References 8 publications

Predictive Modeling of Vaccination Uptake in US Counties: A Machine Learning–Based Approach

Predictive Modeling of Vaccination Uptake in US Counties: A Machine Learning–Based Approach

Moving beyond cognitive elements of ICT literacy: First evidence on the structure of ICT engagement

Investigation on the Poor Computer Graphic Design Skills among Art and Design Students at University

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