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This scoping review article aimed to systematically search the literature on the use, purpose and barriers of information and communication technology (ICT) for culturally and linguistically diverse (CALD) older adults in the host country. The review also conducted a search for literature on programs that aim to develop digital literacy skills for CALD older adults.

A scoping review approach was utilized to identify and search the available literature, and to map the key concepts. A total of 23 relevant articles were included following a systematic search across seven databases.

The review suggests that CALD older adults use ICT for various purposes, including social interaction, health management, information gathering, immigration, everyday routines and leisure. The barriers faced by these older adults in using ICT encompass fear and limited knowledge, language issues, lack of interest, limited access to technology and health concerns. The existing training programs focus on enhancing self-efficacy and confidence and promoting attitudinal changes toward ICT.

Despite the presence of empirical studies, few scoping or systematic reviews have focused on CALD older adults and technology. Research developments related to the technology use of CALD older adults and associated training programs have been fragmented and sporadic, resulting in gaps in the evidence base. This review fills such a gap to better understand the research status connected to CALD older people’s technology adoption and use.

Absence of Health and Safety (H&S) induction training can expose workers to construction hazards and risks. To protect workers, construction organisations provide site H&S induction training. This training is used in the construction industry to train workers on organisation, project and client H&S practices and rules. While researchers have recognised its role in creating worker awareness, developing H&S culture and influencing accident rate, but there has been little research. Furthermore, there lacks a review that identifies the research trends, research focus and future research directions on H&S induction training in the construction industry. This study aims to review literature on H&S induction training in the construction industry.

Scopus, Web of Science, Science Direct and Google Scholar databases were used to identify articles. Initial search produced a total of 278 papers and final analysis resulted in ten articles. Content analysis was applied.

The identified three contributions to knowledge: (a) identifies specific trajectory or development trends of H&S induction training in the construction industry (three research areas were identified, namely, impact of H&S induction training on H&S culture, impact of H&S induction training on accident rate and barriers affecting supervisor’s skills and ability to conducting H&S induction training), (b) suggestions have been given on the contribution of H&S induction training to H&S culture and (c) future research directions have been proposed. The review provides knowledge that the contribution of H&S induction training to H&S culture is influenced by skills, knowledge and experience of presenter, language used, content covered, mode of delivery, technological tools used, type of assessment and duration.

The review is limited to studies related to H&S induction training in the construction industry. Other safety training studies and industries could have provided different findings. The review is limited to 2012 and 2022 and to ten articles.

Understanding the role of H&S induction training to worker behaviour, H&S culture and outcomes will improve H&S practices and standards within the construction industry. Construction organisations can consider the factors identified in this study to improve the effectiveness of H&S induction training.

Understanding the contribution of H&S induction training to H&S culture may help to improve H&S culture.

The study has identified three main research areas and future research directions. It further revealed the factors that researchers, practitioners and policy makers can consider to improve the effectiveness of H&S induction training in the construction industry.

Artificial intelligence (AI) is a significant game changer in human resource development (HRD). The launch of ChatGPT has accelerated its progress and amplified its impact on organizations and employees. This study aims to review and examine literature on AI in HRD, using a bibliometric approach.

This study is a bibliometric review. Scopus was used to identify studies in the field. In total, 236 papers published in the past 10 years were examined using the VOSviewer program.

The obtained results showed that most cited documents and authors are mainly from computer sciences, emphasizing machine learning over human learning. While it was expected that HRD authors and studies would have a more substantial presence, the lesser prominence suggests several interesting avenues for explorations.

This study provides insights and recommendations for researchers, managers, HRD practitioners and policymakers. Prioritizing the development of both humans and machines becomes crucial, as an exclusive focus on machines may pose a risk to the sustainability of employees' skills and long-term career prospects.

There is a dearth of bibliometric studies examining AI in HRD. Hence, this study proposes a relatively unexplored approach to examine this topic. It provides a visual and structured overview of this topic. Also, it highlights areas of research concentration and areas that are overlooked. Shedding light on the presence of more research originating from computer sciences and focusing on machine learning over human learning represent an important contribution of this study, which may foster interdisciplinary collaboration with experts from diverse fields, broadening the scope of research on technologies and learning in workplaces.

Studies on technology and interpreting have increasingly explored how technology influences the role and performance of interpreters in their practice; however, there is a lack of comprehensive reviews and analyses. This paper aims to synthetically review the state-of-the-art application and integration of various interpreting technologies, identify the key trends of recent studies, and evaluate the associated opportunities and challenges.

Adopting a systematic review approach, 40 articles on technology and interpreting practice from 2013 to 2024 were selected and analysed.

A growing number of empirical studies on technology-mediated remote interpreting and technology-supported interpreting is observed in public service settings, suggesting that mobile and emerging technologies have gained more attention alongside phone and video. In addition, mixed results are revealed with respect to the impact of technology on interpreting performance.

This review not only provides a bird’s-eye view of how interpreting practice has reconciled with different technologies but also offers insights into the changing role of interpreters, the need for training, and the direction for future research.

The health crisis has highlighted the shortcomings of the industry sector which has revealed its vulnerability. To date, there is no guarantee of a return to the “world before”. The ability of companies to cope with these changes is a key competitive advantage requiring the adoption/mastery of industry 4.0 technologies. Therefore, companies must adapt their business processes to fit into similar situations.

The proposed methodology comprises three steps. First, a comparative analysis of the existing CPSs is elaborated. Second, following this analysis, a deep learning driven CPS framework is proposed highlighting its components and tiers. Third, a real industrial case is presented to demonstrate the application of the envisioned framework. Deep learning network-based methods of object detection are used to train the model and evaluation is assessed accordingly.

The analysis revealed that most of the existing CPS frameworks address manufacturing related subjects. This illustrates the need for a resilient industrial CPS targeting other areas and considering CPSs as loopback systems preserving human–machine interaction, endowed with data tiering approach for easy and fast data access and embedded with deep learning-based computer vision processing methods.

This study provides insights about what needs to be addressed in terms of challenges faced due to unforeseen situations or adapting to new ones. In this paper, the CPS framework was used as a monitoring system in compliance with the precautionary measures (social distancing) and for self-protection with wearing the necessary equipments. Nevertheless, the proposed framework can be used and adapted to any industrial or non-industrial environments by adjusting object detection purpose.

The growth of the internet, access to technology and rapid digital transformations have paved the way for developing attack surfaces for individuals and organizations. There is a dire need to provide cybersecurity awareness most effectively. Gamification-based platforms have evolved to make cybersecurity education more engaging and effective. This study explores the gamification platforms available for cybersecurity training and awareness, the extent to which they are used and their benefits and challenges.

PRISMA 2020 was used to conduct the systematic literature review.

The study comprehends the game design elements and their role in the effectiveness of cybersecurity training and awareness. The study unveils that traditional education methodologies are insignificant in cybersecurity awareness, and gamification-based platforms are more beneficial. The paper summarizes the implications of the findings and further postulates future research directions.

This work comprehends the various forms of gamification platforms and frameworks available for cybersecurity training and will motivate further development of gamification platforms. This paper will help academia, private and public organizations and game designers enhance their gamification-based cybersecurity education interventions.

Cybersecurity competitions can effectively develop skills, but engaging a wide learner spectrum is challenging. This study aims to investigate the perceptions of cybersecurity competitions among Reddit users. These users constitute a substantial demographic of young individuals, often participating in communities oriented towards college students or cybersecurity enthusiasts. The authors specifically focus on novice learners who showed an interest in cybersecurity but have not participated in competitions. By understanding their views and concerns, the authors aim to devise strategies to encourage their continuous involvement in cybersecurity learning. The Reddit platform provides unique access to this significant demographic, contributing to enhancing and diversifying the cybersecurity workforce.

The authors propose to mine Reddit posts for information about learners’ attitudes, interests and experiences with cybersecurity competitions. To mine Reddit posts, the authors developed a text mining approach that integrates computational text mining and qualitative content analysis techniques, and the authors discussed the advantages of the integrated approach.

The authors' text mining approach was successful in extracting the major themes from the collected posts. The authors found that motivated learners would want to form a strategic way to facilitate their learning. In addition, hope and fear collide, which exposes the learners’ interests and challenges.

The authors discussed the findings to provide education and training experts with a thorough understanding of novice learners, allowing them to engage them in the cybersecurity industry.

This paper aims to consolidate empirical studies between 2013 and 2022 to investigate the impact of artificial intelligence (AI) in higher education. It aims to examine published research characteristics and provide insights into the promises and challenges of AI integration in academia.

A systematic literature review was conducted, encompassing 44 empirical studies published as peer-reviewed journal papers. The review focused on identifying trends, categorizing research types and analysing the evidence-based applications of AI in higher education.

The review indicates a recent surge in publications concerning AI in higher education. However, a significant proportion of these publications primarily propose theoretical and conceptual AI interventions. Areas with empirical evidence supporting AI applications in academia are delineated.

The prevalence of theoretical proposals may limit generalizability. Further research is encouraged to validate and expand upon the identified empirical applications of AI in higher education.

This review outlines imperative implications for future research and the implementation of evidence-based AI interventions in higher education, facilitating informed decision-making for academia and stakeholders.

This paper contributes a comprehensive synthesis of empirical studies, highlighting the evolving landscape of AI integration in higher education and emphasizing the need for evidence-based approaches.

Information security awareness (ISA) mainly refers to those aspects that need to be addressed to effectively respond to information security challenges. This research used focus groups to empirically investigate the main ISA dimensions that emerge from the Italian public health-care sector. This study aims to identify the most critical dimension of ISA and to evaluate the diffusion and maturity of information security policies (ISPs) of health-care infrastructure and training programs.

This research adopted a qualitative research design and focus groups as a research methodology. Data analysis was conducted using the NVIVO 14 software package and followed the principles of thematic analysis.

The focus group results highlighted that health-care personnel find it difficult to comply with the main ISA dimensions, a situation that leads to risky behaviors. Password management, data storage and transfer and instant messaging applications emerged as the most critical of the main ISA dimensions in the context of this research. It also transpired that ISPs are not all-encompassing as they mainly focus on privacy problems but neglect security concerns. Finally, training programs are not fully implemented in the investigated context, thus undermining their positive enhancing role for ISA.

The public health-care sector emerged as a critical yet still under-investigated context. The need for an in-depth investigation of organizational sciences approaches to overcoming information security challenges is also recommended in several prior research studies.

Computer vision (CV) offers a promising approach to transforming the conventional in-person inspection practices prevalent within the construction industry. However, the reliance on centralized systems in current CV-based inspections introduces a vulnerability to potential data manipulation. Unreliable inspection records make it challenging for safety managers to make timely decisions to ensure safety compliance. To address this issue, this paper proposes a blockchain (BC) and CV-based framework to enhance safety inspections at construction sites.

This study adopted a BC-enhanced CV approach. By leveraging CV and BC, safety conditions are automatically identified from site images and can be reliably recorded as safety inspection data through the BC network. Additionally, by using this data, smart contracts coordinate inspection tasks, assign responsibilities and verify safety performance, managing the entire safety inspection process remotely.

A case study confirms the framework’s applicability and efficacy in facilitating remote and reliable safety inspections. The proposed framework is envisaged to greatly improve current safety inspection practices and, in doing so, contribute to reduced accidents and injuries in the construction industry.

This study provides novel and practical guidance for integrating CV and BC in construction safety inspection. It fulfills an identified need to study how to leverage CV-based inspection results for remotely managing the safety inspection process using BC. This work not only takes a significant step towards data-driven decision-making in the safety inspection process, but also paves the way for future studies aiming to develop tamper-proof data management systems for industrial inspections and audits.