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Indigenous students that live in poverty experience contextual socio-economic factors with residual effects of lower educational outcomes than their non-Indigenous counterparts. Indigenous children that live in poverty often have fewer resources, are segregated, and continue to be marginalized in the classroom. The vicious cycle of low education levels for Indigenous peoples confines them to low paying employment or unemployment that results in ongoing poverty or being a statistic categorized as the working poor. The purpose of this research was to gain a better understanding of the strategies that teachers have animated in their classrooms, which they perceived to be successful in encouraging Indigenous students to attend school, remain in school, complete course credits, and persevere to graduate from high school. The intent was to discover the how-to strategies and advance working knowledge of pedagogical practices leading to improved educational experiences and achievement levels for Indigenous students. This chapter will present the observations and qualitative findings of the case studies conducted in New Zealand and Canada, wherein 14 teachers described what they did and what it looked like in their classrooms. A constructivist approach was utilized to make meaning and gain the interpretations from the participants. This was achieved by first viewing the interactions in the classrooms and, through the interview process, being able to garner a better understanding of what was witnessed from the point of view of the participants.

A gripping keyword emerged in the dynamic world of 2022: GPT or the advent of Generative Artificial Intelligence (GAI), at its forefront, embodied by the mysterious ChatGPT. This technological marvel had been silently lurking in the background for just over five years. However, all of a sudden, it emerged onto the scene, capturing the public’s attention and quickly becoming one of the most widely adopted inventions in history. Therefore, this narrative review is conducted in order to explore the impact of generative AI and ChatGPT on lifelong learning and upskilling of students in higher education and address opportunities and challenges proposed by Artificial Intelligence from a global perspective.

This review has been conducted using a narrative literature review approach. For in-depth identification of research gaps, 105 relevant articles were included from scholarly databases such as Scopus, Web of Science, ERIC and Google Scholar. Seven major themes emerged from the literature to answer the targeted research questions that describe the use of AI, the impact of generative AI and ChatGPT on students, the challenges and opportunities of using AI in education and mitigating strategies to cope with the challenges associated with the integration of ChatGPT and generative AI in education.

The review of the literature presents that generative AI and ChatGPT have gained a lot of recognition among students and have revolutionized educational settings. The findings suggest that there are some contexts in which adult education research and teaching can benefit from the use of chatbots and generative AI technologies like ChatGPT. The literature does, however, also highlight the necessity of carefully considering the benefits and drawbacks of these technologies in order to prevent restricting or distorting the educational process or endangering academic integrity. In addition, the literature raises ethical questions about data security, privacy and cheating by students or researchers. To these, we add our own ethical concerns about intellectual property, such as the fact that, once we enter ideas or research results into a generative chatbot, we no longer have control over how it is used.

This review is helpful for educators and policymakers to design the curriculum and policies that encourage students to use generative AI ethically while taking academic integrity into account. Also, this review article identifies the major gaps that are associated with the impact of AI and ChatGPT on the lifelong learning skills of students.

This review of the literature is unique because it explains the challenges and opportunities of using generative AI and ChatGPT, also defining its impact on lifelong learning and upskilling of students.

The current and modern electrical distribution networks, named smart grids (SGs), use advanced technologies to accomplish all the technical and nontechnical challenges naturally demanded by energy applications. Energy metering collecting is one of these challenges ranging from the most basic (i.e., visual assessment) to the expensive advanced metering infrastructure (AMI) using intelligent meters networks. The AMIs’ data acquisition and system monitoring environment require enhancing some routine tasks. This paper aims to propose a methodology that uses a distributed and sustainable approach to manage wide-range metering networks, focused on using current public or private telecommunication infrastructure, optimizing the implementation and operation, increasing reliability and decreasing costs.

Inspired by blockchain technology, a collaborative metering system architecture is conceived, managing massive data sets collected from the grid. The use of cryptography handles data integrity and security issues.

A robust proof-of-concept simulation results are presented concerning the resilience and performance of the proposed distributed remote metering system.

The methodology proposed in this work is an innovative AMI solution related to SGs. Regardless of the implementation, operation and maintenance of AMIs, the proposed solution is unique, using legacy and new technologies together in a reliable way.

The purpose of this study is to identify seminal research works on distance and online learning that have had significant impact on the domain.

The authors used the SCOPUS database for this study as the data source, and a well-defined search strategy retrieved the items for analysis. First, the authors identified the h-index (n = 207) of the discipline to determine the threshold for listing the top works. The authors critically analysed these classic publications using several bibliometric parameters to present the analysis. To understand the primary focus of the classic research works, the authors also carried out a keyword cluster analysis using VOSviewer.

While the USA produced maximum classic research, authors from Canada have maximum research visibility in terms of citations (n = 474.06). Canada also received the highest value of RCI (1.30), followed by Taiwan and Australia. The majority of the classics are published in 67 scientific journals. Of these, Computers and Education published the highest number with a quarter of the total citations (n = 19,403). Although e-learning was the nucleus of the research theme, the authors observed that students, learning systems, online learning, blended learning, learning management systems and computer-aided instructions dominated their influence in the research cluster.

To the best of the authors’ knowledge, this is the first of its kind work in the field of distance and online learning. Findings of this study would be useful to faculty, researchers and students in the discipline to focus on the seminal works and understand their implications better in the context of the growing significance of the discipline.

The outbreak of COVID-19 has caused a slowdown of economic activity across the globe, which has resulted in high levels of disruption to labour markets. This study seeks to examine how the outbreak of COVID-19 has impacted the search strategies of students seeking for an internship, and whether these have changed since the start of the pandemic. The study utilises the strength of weak ties hypothesis, social capital theory and status attainment theory to explore the changes in securing a position since the outbreak of COVID-19.

This study draws on data from two cohorts of MBA students seeking to secure internships: one before the outbreak and one during. A multinomial regression is employed to examine how students have used network ties to secure internships and how this has changed since the outbreak of COVID-19.

The multinomial regression results indicate that there was little difference in the strategies employed by students before the crisis compared to those that secured them during, potentially indicating that students are unwilling to deviate from typical job search strategies, especially in times of uncertainty.

This study provides insights into how network ties are used by job seekers during a period of economic and environmental uncertainty.

This study aims to determine the factors influencing employee retention working in construction-related small-medium enterprises (SMEs) in Krung Thep Maha Nakhon. The study contributes to the construction site manager getting insight into employees' desired goals in the workplace. Furthermore, the study provided information about the diversity of generations (age groups), income levels and educational levels of employees working in the construction industry in the Krung Thep area.

The researcher decided to investigate a sample size of 386 respondents based on the target population. A purposive sampling method was selected by giving out questionnaires to the respondents employed in construction-related SMEs in Krung Thep. The questions comprised two major parts, which are demographic questions and measuring variables relevant to the independent variables.

The study's aim of findings is to investigate the factors that retain the employees who are pursuing their careers in construction-related SMEs. The findings of this research are to unveil that task interdependence significantly contributes to agile working. Lastly, employee retention is significantly affected by agile working among employees in an organisation.

This research only studies factors influencing employee retention among those of all ranges of ages, incomes and educational levels working in construction-related SMEs. The researcher collected data on the income level, age group and educational level of employees to use for further study.

The study is about determining the factor that affects agile working and employee retention among those working in construction-related SMEs.

This paper aimed to determine the self- and co-regulation influences on the community of inquiry (CoI) for collaborative online learning.

A quantitative survey was used on a sample of (N = 626) enrolled postgraduate students in a South African Open Distance and e-Learning (ODeL) university. The measuring instruments were the CoI and the shared metacognitive surveys. Correlation and multiple regression analyses were used to determine the association and influence of self- and co-regulation on the CoI.

The results indicated that self- and co-regulation related to the CoI (teaching, cognitive and social) presences. In addition, the results revealed that self- and co-regulation influence the CoI presences. Self-regulation had the highest influence on teaching and cognitive presence, while co-regulation influenced social presence.

The study’s convenience sampling method from a single university limited the applicability of the findings to other online learning environments.

Higher educational teachers who encourage student self- and co-regulation may enhance their online teaching, cognitive and social presence when studying online. The research’s findings may be valuable to teachers to enable them to provide a more collaborative and interactive online learning environment and promote productive online communities.

This study contributes to the body of knowledge about the relationship between teaching, social and cognitive presence and self- and co-regulation within the CoI framework. Furthermore, there has also been limited research focussing on the dynamics of shared metacognition within the CoI framework in an ODeL context.