Ubiquitous learning (u-learning) refers to anytime and anywhere learning. U-learning has progressed to be considered a conventional teaching and learning approach in schools and is adopted to continue with the school curriculum when learners cannot attend schools for face-to-face lessons. Computer Science, namely the field of Artificial Intelligence (AI) presents tools and techniques to support the growth of u-learning and provide recommendations and insights to academic practitioners and AI researchers. Aim: The aim of this study was to conduct a meta-analysis of Artificial Intelligence works in ubiquitous learning environments and technologies to present state from the plethora of research. Method: The mining of related articles was devised according to the technique of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The complement of included research articles was sourced from the broadly used databases, namely, Science Direct, Springer Link, Semantic Scholar, Academia, and IEEE. Results: A total of 16 scientific research publications were shortlisted for this study from 330 articles identified through database searching. Using random-effects model, the estimated pooled estimate of artificial intelligence works in ubiquitous learning environments and technologies reported was 10% (95% CI: 3%, 22%; I 2 = 99.46%, P = 0.00) which indicates the presence of considerable heterogeneity. Conclusion: It can be concluded based on the experimental results from the sub group analysis that machine learning studies [18% (95% CI: 11%, 25%), I 2 = 99.83%] was considerably more heterogeneous (I 2 = 99.83%) than intelligent decision support systems, intelligent systems and educational data mining. However, this does not mean that intelligent decision support systems, intelligent systems and educational data mining is not efficient.

Purpose The purpose of this paper is to identify and present a global perspective of digital pedagogies in relation to technology and academic librarians. Design/methodology/approach The preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology was used in this study. Findings Based on the data, academic librarians must develop a foundational understanding of 21st century pedagogies and digital skills to teach in an online environment. Originality/value This review paper considers the emergent teaching role of the academic librarian within the digital environment. The themes in the findings highlight the importance of digital pedagogical knowledge and digital fluency of academic librarians as a teacher within the digital environment in higher education.

No abstract

Globally, the role of academic librarians as online teachers at higher education institutions is experiencing a tsunami of change. This is due to the Fourth Industrial Revolution and the influence of technology on pedagogy. The 21st-century academic librarian is challenged to adopt innovative teaching methods using technology in a digital environment. The purpose of this study was to explore the pedagogical and technological preparedness of academic librarians at University of Technologies in South Africa for online teaching. The technology pedagogy content knowledge framework guided the methodology in exploring the pedagogical and technological preparedness of academic librarians. A pragmatic approach using quantitative techniques was used in the data collection process. The data collected from the findings were analyzed and validated resulting in emerging themes. The results show a lack of pedagogical and technological skills among academic librarians at UOT in South Africa.

The economic impact of carbon emissions in Africa is gaining traction in the extant literature. This study adopted Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to concomitantly track data on carbon emissions versus economic growth in Africa from 2018 to 2022 providing evidence from a meta-analysis. Through database searches, 591 publications were identified. A machine learning algorithm called Latent Dirichlet Allocation (LDA) was used as a visualization technique for reporting trends in the eleven papers selected for the analysis. Identifying, evaluating, and summarizing the findings of all relevant individual studies conducted in Africa on the impact of economic growth on carbon emissions contributes to the existing body of knowledge. This study fills a critical gap by surveying the studies conducted in Africa in the last five years, implying that economic growth negatively and significantly triggers CO2 emissions in Africa. The debate on the economic impact of CO2 emissions in Africa, the most vulnerable continent to climate change, is elucidated. The findings tracked sources of data for carbon emissions in Africa. The results showed that although some studies reported a positive correlation (and some a negative correlation) between economic growth and carbon emissions, most studies concur that the economic impact of carbon emissions over a timeline can be explained by the Environmental Kuznets Curve (EKC) hypothesis. Therefore, there is a dire need for African countries to strengthen economic growth without deteriorating their environment or having ecological footprint. Future research must assess whether this trend on the economic impact of carbon emissions in Africa continues. AcknowledgmentThe authors express their appreciation to the Durban University of Technology for providing the resources to conduct this study.