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This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.

The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.

The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.

This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.

The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.

This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.

This study aims to analyze the effectiveness and efficiency of research-based community service programs in Indonesia that used government funds in 2017–2021.

The design of this research is a quantitative research method using a data envelopment analysis to evaluate 370 leading universities in Indonesia. Furthermore, six analytical models were considered to compare effectiveness and efficiency between universities. It involved two resource (budget and staff academic involved), three output (intellectual property, prototype and publication) and three outcome variables (economic impact, social impact and capacity building).

The findings showed that several universities are considered necessary, with great potential to increase output and outcome efficiency in community involvement. The study mapped and divided the position of 370 universities for additional information. The effectiveness aspect provides another perspective in assessing the performance of tertiary institutions in Indonesia and can be an option for evaluating research performance to improve the quality of output.

The authors use data from research and community service management information systems used, both the resources used and the results. Efficiency and effectiveness of 370 universities were compared in this study, including comparing their position on the previous assessment with the assessment of the results of this study. Approach to the concept of Mandl et al. (2008) regarding the relationship between input, output and outcome as the main component of the indicators, the authors apply to analyze efficiency and effectiveness.

The main purpose of this paper is twofold: to present a proposal for a model of educational quality management system within a process approach context for technical universities, and a conceptual model of a performance measurement system (PMS) towards the assessment of the quality level of management, core and support processes.

The paper encompasses two main parts: a theoretical portion and a case study. Within the theoretical background, the authors discuss the issue of educational quality management supported on a process approach perspective as well as performance measurement system in high education (HE). The case study reports the development of the concept of performance measurement system for technical universities.

The proposed system of educational quality management supported on a process approach, together with a conceptual model of the performance measurement system, can be implemented in every technical university. The identification of processes in the education quality management system permitted the development of the PMS. The model covers 32 key performance indicators (KPIs) for management processes, 39 for core processes and 19 for supporting ones.

The proposed performance measurement system is limited in its focus on educational processes and support of these processes. The evaluation of scientific and research activity and aspects related to financial resources is not pursued.

Elaboration of a conceptual model of a performance measurement system towards the assessment of the quality level of management, core and support processes is dedicated to technical universities.

This article aims to explore the advantages of integrating a new generative artificial intelligence (AI) technology in education. It investigates the use of ChatGPT in personalized learning, assessment and content creation and examines ways to manage its limitations and some ethical considerations. The purpose is to stimulate discussion on the effective application of ChatGPT as a tool for learning and skill development while remaining mindful of the ethical issues involved.

The methodology in this article includes four steps: a literature search, screening and selection, analysis and synthesis. The literature was thoroughly screened and selected on the basis of its relevance to the research question, before selected material were carefully read and analyzed. The insights gained from this analysis were then synthesized to identify key considerations in integrating ChatGPT in education.

The study concludes that ChatGPT can be effectively integrated into education to automate routine tasks and enhance the learning experience for students, ultimately increasing productivity and efficiency and fostering adaptive learning. However, the limitations of ChatGPT, even when updated, must be borne in mind, including factual inconsistencies, potential bias promotion, lack of in-depth understanding and safety concerns. The study nevertheless highlights the benefits of responsibly integrating ChatGPT within the field of education.

This study has practical implications for educators and policymakers who are interested in the integration of AI technology in education. The study provides insights of using ChatGPT in education.

This article contributes to the existing literature by specifically examining the advantages of integrating ChatGPT in higher education and offering recommendations for its responsible use. Moreover, the article emphasizes ethical considerations in the context of ChatGPT integration.

In this chapter, the authors aimed to analyze the existing sustainability curriculum being followed by higher education institutions (HEIs) in the emerging world, and call out the underlying inadequacies within it and provide solutions for the same, by drawing insights through interviews with key stakeholders in this area. The authors planned to talk to higher education policymakers, Educational Institutional heads, researchers and faculty members and corporates (who deal in sustainable products and who will benefit from this subject). The respondents’ sample consisted of both Indian and international interviewees to help us better understand and analyze the perspective and scenario globally in terms of north-south as well as understand multiple point of views. The interview analyses were carried out using the N Vivo software tool. The expected outcome includes a curriculum contour on sustainability for the HEIs.

Artificial intelligence (AI) is a growing paradigm and has made considerable changes in many fields of study, including medical education. However, more investigations are needed to successfully adopt AI in medical education. The purpose of this study was identify the determinant factors in adopting AI-driven technology in medical education.

This was a descriptive-analytical study in which 163 faculty members from Tabriz University of Medical Sciences were randomly selected by nonprobability sampling technique method. The faculty members’ intention concerning the adoption of AI was assessed by the conceptual path model of task-technology fit (TTF).

According to the findings, “technology characteristics,” “task characteristics” and “TTF” showed direct and significant effects on AI adoption in medical education. Moreover, the results showed that the TTF was an appropriate model to explain faculty members’ intentions for adopting AI. The valid proposed model explained 37% of the variance in faulty members’ intentions to adopt AI.

By presenting a conceptual model, the authors were able to examine faculty members’ intentions and identify the key determining factors in adopting AI in education. The model can help the authorities and policymakers facilitate the adoption of AI in medical education. The findings contribute to the design and implementation of AI-driven technology in education.

The finding of this study should be considered when successful implementation of AI in education is in progress.

Faced with the existential threat of COVID-19, the College of Business Administration (CBA) at Princess Nourah Bint Abdulrahman University (PNU) decided to work toward the dual goals to achieve accreditation and an effective social and educational response to the pandemic. CBA’s quality improvement process was implemented synergistically with Seligman’s (2011) PERMA well-being model, namely positive emotions, engagement, relationship, meaning, and accomplishment/achievement. The case study methodology, which was based on direct observations, faculty and students’ interviews, surveys, feedback, documents, and archival data records, allowed to capture the context and lived reality of all the participants in QAA processes. Results showed that quality improvement was facilitated through three domains: (1) governance and academic leadership, (2) teaching and learning, and (3) digitalization and technology. Within each domain, specific programs, activities, human resources, and networks were enabled through a framework based on the PERMA well-being model. As a result of this hybrid QAA well-being implementation process, CBA achieved NCAAA accreditation for its offered programs, while experiencing high levels of well-being and commitment to teaching and learning by the staff members and students. The description of CBA’s accreditation journey might be insightful for other higher education institutions (HEIs).

Health profession education has evolved to incorporate didactic instruction and experiential learning opportunities over time. Constructivism and interprofessional education are essential theoretical concepts that have shaped modern health profession education. However, transformative active learning is an approach that is particularly well suited to the needs of healthcare professionals. By integrating theoretical knowledge with practical skills, transformative active learning helps prepare students for the complex challenges they will face in their future careers and encourages them to become agents of change committed to improving healthcare practice. Saudi National Institute of Health (Saudi NIH) is one of the Ministry of Health's initiatives in the National Transformation Program 2020 to achieve the Kingdom's Vision 2030, as it supports biomedical research in the health sector in Saudi Arabia. One of the mandates of Saudi NIH is to build the research capacity through well-designed educational and training programs through the directory of education and research skills adopting active learning strategies. This chapter aims to communicate the methodological framework of the Education and Research Skills Directory of the SNIH for integrating active learning in the various training programs and initiatives aiming to promote the core learning capabilities with excellence, diversity, diversity, uniqueness, competency, and efficiency values.