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The Swedish International Development Cooperation Agency (SIDA) (2019) explicated there are four dimensions of poverty, and they include (1) resources, (2) opportunities and choice, (3) power and voice and (4) human security (e.g. violence issues and concerns). Contrastingly, Ellis (1984) postulated dimensions of poverty are social, economic, legal and political poverty. The Organisation for Economic Co-operation and Development (OECD) (2015) stated poverty is not always about income, indicating ‘income poverty’. Deprivation factors can be broad, but reported poor health, inadequate living standards and lack of education are dimensions of poverty (OECD, 2015). Also, according to the World Bank, the world's extremely poor are people who live on less than $1.90 USD per day (Beck et al., 2020). The $1.90 amount is at 2011 purchasing power parity levels. Additionally, the $1.90USD amount has decreased significantly over the last decades (Beck et al., 2020). Nevertheless, entrepreneurship, UN SDGs and technology can be strategies for sustainable alleviation of poverty and pandemic global economic recovery, in the 21st century.

I am concerned with insights heterodox economics, and particularly the new institution economics, can offer regarding interactions between health emergencies and the airline industry. Air services not only facilitates the transmissions of diseases among humans, and between animals, but on the positive side, can expedite the movement of medicines and the transfer of those afflicted during pandemics and epidemics. They can serve to limit the outbreak of disease by providing “mercy flights” to regions poorly served by other modes. Significant challenge confronting carriers during a major event, however, often included immediate financial shocks as well as ensuring their operations do not contribute to the spread of disease. These economic challenges for both commercial carriers and public policymakers involve sources of finance for what is, in this context, a semi-public service as well as the extent to which airlines should retain standby capacity extending resilience to the air-service supply chain. Conventional neoclassical economics, while still at the center of analyzing many of these sorts of issues, has increasingly, because of its rigid assumption and poor forecasting record, been supplemented by heterodox economic thinking. This trend has been reinforced by progress in fields such as psychology. What I demonstrate is that heterodox economics, and especially the role of institutions, offers a more complete picture of the interactions between air transportation and the spread of disease.

This paper aims to present commentary on adult safeguarding designated officers’ (nominated senior staff members in the Health Service Executive and its funded services) in Ireland readiness for online learning and their perception of the blended approach used in their training and considers the implications of this for practice.

In total, 233 designated officers were surveyed. A self-administered online survey comprising of two instruments was used. The questionnaire combines two previously validated tools measuring readiness for online learning and perceptions of blended learning. Minor modifications were made to account for local circumstance and language. Demographic questions relevant to the survey population were added. The response rate was 49%.

Designated officers regarded specified competencies for online learning as important to very important with highest importance placed in time management. Designated officers expressed they were confident to very confident in their ability to accomplish all competencies in online learning. The highest confidence was in the technical competencies. Designated officers are demonstrating high readiness for online learning. Designated officers reported positively on online contributions and on blended learning workload. The scores indicate positive perceptions of the blended learning experience. Responses to an open-ended question were largely positive with some suggestions for improvement made.

Findings have helped inform planning and development of the Health Service Executive’s adult safeguarding training for designated officers with changes made since this survey was undertaken.

To the best of the author’s knowledge, this is the first time a survey was undertaken of designated officers in Ireland with a view to improving safeguarding training. Recommendations for adaptions to the blended designated officer programme were proposed and subsequently accepted and implemented.

The primary purpose of this paper is to articulate the pivotal function of phenomenographic analysis in advancing the depth and breadth of insights into doctoral research in educational studies. By examining the distinctive contributions and advantages afforded by phenomenographic analysis, the paper aims to highlight its profound capability to reveal the intricacies and variegated dimensions of human experiences and perceptions. It advocates for the integration of phenomenographic analysis into social science research methodologies to foster a deeper, more nuanced appreciation of its utility and impact.

This article leverages empirical evidence from a specific educational research project to provide an in-depth examination of phenomenographic analysis. It meticulously outlines the procedural application of this methodological approach, showcasing how it enriches research outcomes by offering a profound exploration of the complex layers and subtle variations present within social phenomena. The study employs phenomenographic analysis to amplify the nuanced understanding and inherent value of research findings in educational studies.

The findings demonstrate that phenomenographic analysis significantly enriches research outcomes by offering a comprehensive exploration of complex social phenomena. The method’s capability to uncover the intricacies and variegated dimensions of human experiences and perceptions enhances the quality and relevance of research conducted within the domain. By providing empirical evidence and detailed procedural application, the paper illustrates how phenomenographic analysis contributes to the enrichment of academic discourse and elevates the caliber of research in the social sciences.

This article offers invaluable perspectives to both researchers and practitioners by providing a comprehensive analysis of phenomenographic methodology. It underscores the indispensable contribution of phenomenographic analysis in fostering a deeper understanding of educational research findings. The work advocates for its integration into social science research methodologies, highlighting its unique value in enhancing the quality and relevance of research. By illuminating the method’s profound capability to reveal complex human experiences, the paper significantly contributes to the enrichment of academic discourse in the social sciences.

This research intends to analyse the trend in educational technology (EdTech) over the last 20 years using systematic scientific mapping and bibliometric analysis and how it relates to the Indian context. Considering the anticipated growth in this field over the previous three years post-pandemic, an existing literature analysis is required. This study aims to map the existing intellectual structure in EdTech applications to extend the knowledge base further in this field. This study also intends to research how the Indian education sector compares in terms of the research output for the EdTech sector, considering the increased government focus on online learning as per the education policy in 2020. The study's findings will pave the way for sustainable research that will be extended in the future.

Bibliometric analysis is conducted on the manuscripts extracted from Web of Science databases for the last 20 years (from 2003 to 2023). This study uses a descriptive research approach for bibliometric analysis as, by nature, this is an exploratory investigation, and no physical or existing experiment can be performed on the quantification, characteristic or productivity of EdTech applications. VoS Viewer and R software are extensively considered for a detailed bibliometric analysis.

E-learning, blended learning and distance education emerged as the most frequently used keywords. The results reveal that technology adoption, higher education, technology and modelling are the most researched topics in this field.

This research is limited to the last 20 years' database obtained from the Web of Science database and limited to educational, management and operation databases only.

The paper intends to analyse the global scenario of EdTech research and ensures that the paper will effectively connect with researchers, educators, policymakers and practitioners from different parts of the world. The results derived from the bibliometric analysis, cluster analysis and identification of key authors, journals and countries can contribute towards the improved contribution in this area.

The paper discusses the research in EdTech over the last two decades and effectively tries to bridge the gap in global research. Integrating systematic scientific mapping and bibliometric analysis is an innovative way to assess the growth and impact of EdTech. Considering the post-pandemic scenario and the government's emphasis on online learning, these are consistent with current developments.

In recent years, studies have shown that machine learning significantly improves student performance and retention and reduces the risk of student dropout and withdrawal. However, there is a lack of empirical research reviews focusing on the application of machine learning to predict student performance in terms of learning engagement and self-efficacy and exploring their relationships. Hence, this paper conducts a systematic research review on the application of machine learning in higher education from an empirical research perspective.

This systematic review examines the application of machine learning (ML) in higher education, focusing on predicting student performance, engagement and self-efficacy. The review covers empirical studies from 2016 to 2024, utilizing a PRISMA framework to select 67 relevant articles from major databases.

The findings show that ML applications are widely researched and published in high-impact journals. The primary functions of ML in these studies include performance prediction, engagement analysis and self-efficacy assessment, employing various ML algorithms such as decision trees, random forests, support vector machines and neural networks. Ensemble learning algorithms generally outperform single algorithms regarding accuracy and other evaluation metrics. Common model evaluation metrics include accuracy, F1 score, recall and precision, with newer methods also being explored.

First, empirical research literature was selected from only four renowned electronic journal databases, and the literature was limited to journal articles, with the latest review literature and conference papers published in the form of conference papers also excluded, which led to empirical research not obtaining the latest views of researchers in interdisciplinary fields. Second, this review focused mainly on the analysis of student grade prediction, learning engagement and self-efficacy and did not study students’ risk, dropout rates, retention rates or learning behaviors, which limited the scope of the literature review and the application field of machine learning algorithms. Finally, this article only conducted a systematic review of the application of machine learning algorithms in higher education and did not establish a metadata list or carry out metadata analysis.

The review highlights ML’s potential to enhance personalized education, early intervention and identifying at-risk students. Future research should improve prediction accuracy, explore new algorithms and address current study limitations, particularly the narrow focus on specific outcomes and lack of interdisciplinary perspectives.

The purpose of this study is to identify the main perspectives and trends in educational data mining (EDM) in the e-learning environment from a managerial perspective.

This paper proposes a systematic literature review to identify the main perspectives and trends in EDM in the e-learning environment from a managerial perspective. The study domain of this review is restricted by the educational concepts of e-learning and management. The search for bibliographic material considered articles published in journals and papers published in conferences from 1994 to 2023, totaling 30 years of research in EDM.

From this review, it was observed that managers have been concerned about the effectiveness of the platform used by students as it contains the entire learning process and all the interactions performed, which enable the generation of information. From the data collected on these platforms, there are improvements and inferences that can be made about the actions of educators and human tutors (or automatic tutoring systems), curricular optimization or changes related to course content, proposal of evaluation criteria and also increase the understanding of different learning styles.

This review was conducted from the perspective of the manager, who is responsible for the direction of an institution of higher education, to assist the administration in creating strategies for the use of data mining to improve the learning process. To the best of the authors’ knowledge, this review is original because other contributions do not focus on the manager.

This study aims to develop a low-cost additive-subtractive hybrid machine equipped with reverse scanning to fabricate high-precision dental surgical guides. The major focus of developing the hybrid additive manufacturing technology is to achieve clinical precision of dental tools at an affordable price.

The designed machine consists of a self-developed vat-photopolymerization-based 3D printer that can fabricate dental surgical guides. The 3D printer is integrated with a self-developed 3D scanner that will analyze the fabricated part and evaluate the dimensional discrepancies. Based on the data provided by the scanner, the integrated secondary milling process will successfully machine the part to meet the clinical precision and standard.

The efficacy of the newly developed hybrid machine is demonstrated with the fabrication of complex part, lower and upper dental surgical guides with the mean dimensional deviations of 198.1, 136.6 and 117.9 µm, respectively. The integration of the secondary scanning and machining system successfully enhanced the mean dimensional deviation of upper and lower guides by 11.88% and 28.75%, respectively. Furthermore, this study also benchmarked the dimensional accuracies achieved by this low-cost technology with the high-end commercial 3D printers. The overall cost of the machine is evaluated to be $2,399.

This paper proposes a novel hybrid additive manufacturing process with integrated reverse scanning and machining modules to fabricate high-precision dental guides. The developed machine is a low-cost alternative to the existing high-end commercial counterparts. The developed machine has the potential to make endodontic treatments more affordable.