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This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field.

The research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI.

This emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection.

The proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies.

The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

This paper argues for the need to use multiple sources and methods that respond to research challenges presented by new forms of war. There are methodological constraints and contention on the superiority given to positivist and interpretivist research designs when doing fieldwork in war situations, hence there is a need to use integrated data generation techniques. The combined effect of severe limitations of movement for both the researcher and researched fragmented data because of polarized views about the causes of the war and unpredictable events that make information hard to come by militate against systematic, organised and robust data generation. The purpose of this paper, therefore, is to make fieldwork researchers understand significant research problems unique to war zones.

This research was guided by the postmodernist mode of thought which challenges standardised research traditions. Fieldwork experiences in Cabo suggest the need to use the composite strategies that rely on the theoretical foundation of integrative and creative collection of data when doing research in violent settings.

The fieldwork experiences showed that the standardised, conventional and valorised positivist and ethnographic research strategies may not sufficiently facilitate understanding of the dynamics of war. There should not be firm rules, guidelines or regulations governing the actions of the researcher in conflict. As such, doing research in violent settings require reflexivity, flexibility and creativity in research strategies that respond to rapid changes. Research experiences in Mozambique show the need to use blended methods that include even less structured methodologies.

Fieldwork experiences in Cabo challenges researchers who cling to standardised research traditions which often hamper awareness of new postmodernist mode of thought applicable to war settings. It is essential to study the nature of African armed conflicts by combining creativity and flexibility in the selection of research strategies.

The purpose of this study is to investigate the integration of entrepreneurial spirit and multicultural values in Islamic education, particularly within the context of pesantren, and to understand its implications for educational practices and outcomes.

This study adopts a qualitative research approach, using literature review and analysis of empirical data to explore the intersection of entrepreneurial spirit and multicultural values in Islamic education. It incorporates findings from multiple sources, including scholarly articles, books and empirical studies, to provide a comprehensive understanding of the topic.

The findings reveal that the integration of entrepreneurial spirit and multicultural values in Islamic education empowers students economically, fosters innovation in teaching methods and promotes character development and business ethics. Moreover, it emphasizes appreciation for diversity, cross-cultural collaboration and social responsibility within the educational context. This integration creates an inclusive learning environment conducive to the development of entrepreneurial skills, innovation and ethical leadership.

Generalizability: the findings of this study may be limited in their generalizability due to the focus on specific multicultural Islamic educational institutions, potentially limiting the applicability of the results to broader educational contexts. Sample size and diversity: the study’s sample size and diversity may impact the representativeness of the findings. Future research could aim for larger and more diverse samples to enhance the robustness of the results. Methodological constraints: the reliance on certain research methods, such as surveys and interviews, may introduce biases or limitations in data collection. Researchers should consider using a variety of methodologies to triangulate findings and ensure comprehensive understanding. Time constraints: the study’s timeframe may have constrained the depth of analysis and limited the exploration of the long-term effects of entrepreneurship education on student development. Future research could adopt longitudinal approaches to address this limitation. Cultural context: the findings are contextualized within the cultural and educational landscape of multicultural Islamic institutions, which may limit their transferability to other cultural or religious contexts. Researchers should consider examining similar phenomena in diverse cultural settings. Resource constraints: resource limitations may have impacted the scope and depth of the research. Future studies could seek additional resources to conduct more extensive investigations and analyses. Bias and subjectivity: despite efforts to minimize bias, researchers’ subjectivity and potential biases in data interpretation and analysis cannot be entirely eliminated. Researchers should acknowledge and address their own biases transparently. Ethical considerations: the study may have encountered ethical challenges related to participant consent, confidentiality and cultural sensitivity. Future research should prioritize ethical guidelines and considerations to ensure the protection and well-being of participants. Addressing these limitations in future research endeavors can contribute to a more comprehensive understanding of the role and impact of entrepreneurship education in multicultural Islamic educational settings.

Practically, the study informs educational institutions, especially pesantren, about the benefits of integrating entrepreneurial spirit and multicultural values into their curriculum and pedagogical approaches. It offers insights into effective strategies for fostering entrepreneurship, innovation and intercultural competence among students.

The integration of entrepreneurial spirit and multicultural values in Islamic education has broader societal implications. It cultivates a generation of socially responsible and inclusive leaders capable of addressing global challenges with creativity and empathy. By promoting cultural understanding and collaboration, it contributes to building more harmonious and resilient communities.

This study is original in its comprehensive exploration of the intersection between entrepreneurial spirit and multicultural values in Islamic education, particularly within the context of pesantren. It offers fresh insights into how these dimensions can be integrated synergistically to enhance educational practices and outcomes.

Addressing Environmental, Social and Governance (ESG) issues has become a critical aspect of business strategy. Since ESG has primarily focused on ratings and measures for reporting, there is a scarcity of methods to assist stakeholders in better comprehending corporate risk and addressing ESG-related issues and problems. The purpose of this paper is to propose a new model to narrow the critical gap.

This study is based on several well-known structural frameworks for managing risks and projects in various industries. Two case studies on topics related to environment (E) and social (S) responsibility are used to demonstrate the practical implementation of the CEPAR® model.

The CEPAR® model, a trademarked five-step methodology (the Challenge-Evaluation-Planning-Action-Review model) was developed by the International Chamber of Sustainable Development (ICSD). The method and guidelines are outlined for easier appreciation by stakeholders of corporations to analyze ESG-related challenges and dilemmas, then able to make principled decisions, take actions, and review the outcomes. Each phase of the new model adheres to the theoretical and practical frameworks for problem-solving and decision-making, emphasizing the iterate process of addressing challenges, evaluating materiality, planning actions, taking actions, and reviewing the outcomes.

The new model is applicable for business corporations and organizations seeking to gain insight and tackle crucial ESG issues, ultimately improving their short- and long-term decision-making and business opportunities.

Upon graduating from university, many engineers will work in new product development and/or technology adoption for continuous improvement and production optimization. These jobs require employees to be cognizant of ethical practices and implications for design. However, little engineering coursework, outside the traditional ABET (Accreditation Board for Engineering and Technology) required Engineering Ethics course, accounts for the role of ethics within this process. Because of this, engineering students have few learning opportunities to practice and reflect on ethical decision-making.

This paper highlights one approach to integrating ethics into an engineering course (outside of engineering ethics). Specifically, the study is implemented within a five-week module with a focus on big data ethics, as part of a Supply Chain Management Technology course (required for Industrial Engineering Technology majors), using metacognition as the core assessment.

Four main themes were identified through the qualitative data analysis of the metacognitive reflections: (1) overreliance on content knowledge, (2) time management skills, (3) career connections and (4) knowledge extensions.

Three notable points emerged which contribute to the literature. First, this study showcased one example of how an ethics module can be integrated into an engineering course (other than Engineering Ethics). Second, this study demonstrated how metacognitive reflections can be used to reinforce student self-awareness of the learning process and connections to big data ethics in the workplace. Finally, this study exhibited how metacognitive reflection assignments can be deployed as a teaching and learning assessment tool, providing an opportunity for the instructor to make immediate changes as needed.

The purpose of this paper is to illuminate the ethical concerns associated with the use of artificial intelligence (AI) in the medical sector and to provide solutions that allow deriving maximum benefits from this technology without compromising ethical principles.

This paper provides a comprehensive overview of AI in medicine, exploring its technical capabilities, practical applications, and ethical implications. Based on our expertise, we offer insights from both technical and practical perspectives.

The study identifies several advantages of AI in medicine, including its ability to improve diagnostic accuracy, enhance surgical outcomes, and optimize healthcare delivery. However, there are pending ethical issues such as algorithmic bias, lack of transparency, data privacy issues, and the potential for AI to deskill healthcare professionals and erode humanistic values in patient care. Therefore, it is important to address these issues as promptly as possible to make sure that we benefit from the AI’s implementation without causing any serious drawbacks.

This paper gains its value from the combined practical experience of Professor Elhassan gained through his practice at top hospitals worldwide, and the theoretical expertise of Dr. Arabi acquired from international institutes. The shared experiences of the authors provide valuable insights that are beneficial for raising awareness and guiding action in addressing the ethical concerns associated with the integration of artificial intelligence in medicine.

Self-regulated learning (SRL) is crucial for successful learning and lifelong learning in today’s rapidly changing world, yet research has shown that many learners need support for SRL. Recently, learning analytics has offered exciting opportunities for better understanding and supporting SRL. However, substantial endeavors are still needed not only to detect learners’ SRL processes but also to incorporate human values, individual needs and goals into the design and development of self-regulated learning analytics (SRLA). This paper aims to examine the challenges that lifelong learners faced in SRL, their needs and desirable features for SRLA.

This study triangulated data collected from three groups of educational stakeholders: focus group discussions with lifelong learners (n = 27); five teacher interviews and four expert evaluations. The groups of two or three learners discussed perceived challenges, support needs and willing-to-share data contextualized in each phase of SRL.

Lifelong learners in professional development programs face challenges in managing their learning time and motivation, and support for time management and motivation can improve their SRL. This paper proposed and evaluated a set of design principles for SRLA.

This paper presents a novel approach for theory-driven participatory design with multistakeholders that involves integrating learners, teachers and experts’ perspectives for designing SRLA. The results of the study will answer the questions of how learners’ voices can be integrated into the design process of SRLA and offer a set the design principles for the future development of SRLA.