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Higher education plays an essential role in achieving the United Nations sustainable development goals (SDGs). However, there are only scattered studies on monitoring how universities promote SDGs through their curriculum. The purpose of this study is to investigate the connection of existing common core courses in a university to SDG education. In particular, this study wanted to know how common core courses can be classified by machine-learning approach according to SDGs.

In this report, the authors used machine learning techniques to tag the 166 common core courses in a university with SDGs and then analyzed the results based on visualizations. The training data set comes from the OSDG public community data set which the community had verified. Meanwhile, key descriptions of common core courses had been used for the classification. The study used the multinomial logistic regression algorithm for the classification. Descriptive analysis at course-level, theme-level and curriculum-level had been included to illustrate the proposed approach’s functions.

The results indicate that the machine-learning classification approach can significantly accelerate the SDG classification of courses. However, currently, it cannot replace human classification due to the complexity of the problem and the lack of relevant training data.

The study can achieve a more accurate model training through adopting advanced machine learning algorithms (e.g. deep learning, multioutput multiclass machine learning algorithms); developing a more effective test data set by extracting more relevant information from syllabus and learning materials; expanding the training data set of SDGs that currently have insufficient records (e.g. SDG 12); and replacing the existing training data set from OSDG by authentic education-related documents (such as course syllabus) with SDG classifications. The performance of the algorithm should also be compared to other computer-based and human-based SDG classification approaches for cross-checking the results, with a systematic evaluation framework. Furthermore, the study can be analyzed by circulating results to students and understanding how they would interpret and use the results for choosing courses for studying. Furthermore, the study mainly focused on the classification of topics that are taught in courses but cannot measure the effectiveness of adopted pedagogies, assessment strategies and competency development strategies in courses. The study can also conduct analysis based on assessment tasks and rubrics of courses to see whether the assessment tasks can help students understand and take action on SDGs.

The proposed approach explores the possibility of using machine learning for SDG classifications in scale.

Prior research suggests that collaboration is key to sustainable community development and environmental management, and peer-to-peer learning (P2PL) may facilitate community building and collaborative learning skills. This study aims to examine the effect of P2PL on the enhancement of environmental management and sustainable development skills, community building and social capital (i.e. connectedness) and understanding of course learning objectives.

Quantitative and qualitative longitudinal survey data was collected in a sustainable development focused course offered at a large American public university that uses P2PL to explicitly facilitate community building and collaborative skills. Safety precautions and changing locational course offerings due to the COVID-19 pandemic in years 2020, 2021 and 2022 provided an opportunity to evaluate the impact of P2PL on these skills during both virtual and in-person formats. Additionally, this study compared in-course student evaluations with students taking other sustainable development-related courses with collaborative learning aspects to understand the wider effectiveness of this course structure.

This study finds that course format (virtual vs in-person) overall made no difference in either connectedness or conceptual understandings, and that students in both formats felt more connected to others than students taking other courses with P2PL. Scaffolding P2PL and supplemental peer support can yield improved connectedness and learning among students taking environmental coursework.

Sustainable development requires group collaboration and partnership building skills. Issues are consistently raised about the challenges to teaching these skills in higher education. The students and instructors in this research study identify P2PL strategies to address these challenges for in-person and virtual classroom settings.

E-learning has become a polarizing issue. Some say that it enhances accessibility to education and some say that it hinders it. While the literature on the subject underscores the effectiveness of the pedagogical frameworks, strategies and distance learning technologies, the firsthand accounts of students, parents and practitioners challenge the validity of experts’ assessments. There is a gap between theory and practice and between the perceptions of providers and consumers of online learning. Following a period of lockdowns and a transition to online learning during the recent pandemic, the prevailing sentiment toward a distance mode of instruction became one of strong skepticism and negative bias. The aim of the study was to examine why e-learning has struggled to meet stakeholder expectations. Specifically, the study posed two research questions: 1. What are the reasons for dissatisfaction with online learning? 2. What are the implications for future research and practice?

The study used a mixed methods approach to examine the reasons behind negative perceptions of online learning by comparing the firsthand accounts posted on social media with the literature. To this end, n = 62,874 social media comments of secondary and postsecondary students, as well as parents, teachings staff and working professionals, covering the span of over 14 years (2008–2022), were collected and analyzed.

The study identified 28 themes that explain the stakeholder’s discontent with the online learning process and highlighted the importance of user-centric design. The analysis revealed that the perceived ineffectiveness of distance education stems from the failure to identify and address stakeholders’ needs and, more particularly, from the incongruence of instructional strategies, blindness to the cost of decisions related to instructional design, technology selection and insufficient levels of support. The findings also highlight the importance of user-centric design.

To address dissatisfaction with e-learning, it is imperative to remove barriers to learning and ensure alignment between technology and learners’ needs. In other words, the learning experience should be personalized to account for individual differences. Despite its cost-effectiveness, the one-size-fits-all approach hinders the learning process and experience and is likely to be met with resistance.

Drawing from the extensive literature, the study offers an explanation for stakeholders’ discontent with e-learning. Unlike survey research that is prone to social desirability bias, the sample provides a rare opportunity to observe and measure the visceral reactions that provide a more authentic sense of stakeholders’ perceptions toward online learning. The authors offer recommendations and identify areas for future research.

This paper aims to shed light on how the composition of future blended learning (BL) courses can be changed to provide students with quality academic learning experiences. The model suggested in this study will guide instructors on how to design their course learning outcomes to ensure effective delivery.

The new model has been developed by combining Bloom's taxonomy and Carman's model. Later, a new framework entitled “PATHCO” based on an extensive literature review is applied to enhance the quality of all five components of Carman's model.

The PATHCO conceptual framework has been developed to ensure quality in the five main teaching and learning factors. This framework covers criteria like pedagogical, assessments, technical, health care and organizational. Further research is required to broaden the main elements of the suggested framework and to validate this research through a case study.

The COVID-19 pandemic has transformed the landscape of the education sector by encouraging an extensive acceptance of technology-enhanced learning and teaching. Blended learning (BL) has become the most appropriate medium to deliver online learning (OL). However, educators and students have reported dissatisfaction with the BL mode of delivery. To address this dissatisfaction, this study outlines, using the PATHCO model, all the essential building blocks which are required to find the right blend of both face-to-face and online components.

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.

In today’s world, empowering individuals, promoting social cohesion and advancing economic development all hinge on access to high-quality education, prioritizing diversity, inclusion and equality. Rethinking current educational strategies using cyber-physical learning assets is necessary to accommodate the learning inclusivity and equity and escalating demands of a globalized world. There is a pressing demand for evidence to support the efficacy of collaborative learning in transforming curriculum and fostering learner inclusion. However, it is recognized as a pedagogical technique within the quality education domain. This study aims to address this knowledge gap by investigating how hybridized cybergogy paradigms facilitate collaborative learning, focusing on diversity, equity and inclusion, to improve educational quality in higher education.

This study used a qualitative approach with an exploratory design guided by an interpretive philosophical perspective. The data was gathered from 60 prospective teachers from the public sector university of Sindh, Pakistan. Semi-structured interviews were conducted with participants. They were then analyzed using theme analysis to understand their views on the potential of hybridized cybergogy paradigms for collaborative learning to improve the quality of education provided at institutions.

The study results confirm that learners benefit from increased access to learning resources, improved critical thinking and problem-solving skills and a more diverse and inclusive classroom working together in a collaborative hybridized cybergogy setting. By fostering SDG 4 (Quality Education) and the 21st-century skills necessary for global marketplace engagement and competing in progressive environments, this creative method equips learners with the capabilities to face modern global challenges.

The study offers valuable practical suggestions to stakeholders in higher education, including faculty, policymakers and teacher education programs, for integrating hybridized cybergogy and collaborative learning to align curricula with sustainable development goals. Additionally, it bridges a significant gap in the existing literature, which will aid future researchers interested in exploring this area.

This study stands out as it explores an underexamined area while providing novel educational insights.

Although doctoral education has experienced substantial development in recent decades, it remains an elite, hence fragile, dimension of university policy and practice. This study aims to articulate perspectives to guide the next phase of strengthening and growth.

Working from theoretical and empirical research conducted in China, including scholarship on workforce ecosystems, education design and the student experience, this study contributes a framework with qualitative insights which clarify the goals and experiences of doctoral education in ways that will render it more relevant, effective and contributing.

The paper identifies areas for doctoral reform to ensure career readiness, including three distinctive outcomes and four indispensable experiences.

This study advances a doctoral design framework which can render transparent the substance of programs and prompt program coordinators to develop and ensure career relevance.

The use of augmented reality (AR) and experiential learning go hand in hand. Although AR learning opportunities have been well discussed, there is limited empirical research on the use of AR within higher education settings. Drawing from the uses and gratifications theory (U&GT), this study aims to explore the use of AR for learning satisfaction and student engagement, while also examining differences in learning styles.

This study used experiments with higher education students in the UK to explore the use of AR as part of the learning experience. Data from 173 students who experienced AR as part of their learning experience were analysed using partial least square analysis.

The authors found that hedonic, utilitarian, sensual and modality gratifications influence AR learning satisfaction and student engagement. Furthermore, the authors found differences between active and passive learners with regards to utilitarian (information seeking, personalisation) and sensual gratifications (immersion, presence) and effects on learning satisfaction.

This study developed and validated a U&GT framework incorporating different learning styles rooted in Kolb’s learning cycle. Findings provide important implications for the use of commercial AR applications as part of the learning experience within higher education settings.

Purpose: The business world has become more turbulent than ever. Organisations must be proactive to meet the challenges of the increasingly disruptive, dynamic, and unpredictable world. One technique that has supported leaders and organisations under challenging circumstances is ‘backcasting’, which works by envisioning a desirable future state and then working backwards to attain it. The current study aims to extend an understanding of the backcasting practices and strategic approaches that can be used by leadership teams in different industries in order to survive in turbulent times and can be adapted within and beyond any pandemic.

Methodology: The research employs a desktop research method to review and compare the most commonly used strategies that leaders from different sectors can use for their respective organisations to thrive in the VUCA world.

Findings: There needs to be more research on the applicability and relevance of backcasting that the leaders of different sectors can employ. The study would provide insights that would bridge the existing research gap and come up with suitable strategies that can be employed for dealing with VUCA challenges in the Indian context.

Significance: The outcome of the study will be helpful to the leaders in designing and aligning ‘out of the box’ backcasting strategies to survive in the highly disruptive world.

Introduction: Skill development is crucial in developing economies by enhancing productivity and creating employment opportunities. At the macro level, it also leads to industrial development and economic growth.

Purpose: The research is to identify the types of skills required for increasing the probability of employability of labour. It also aims to define the challenges and opportunities in skill development to drive change.

Need of the Study: Studying opportunities and challenges for skill development in developing economies is essential for achieving sustainable economic growth, reducing poverty, increasing employment opportunities, and promoting global competitiveness.

Research Methodology: Some skills are recognised through research that has been published to determine the skill set needed to increase labour productivity. To draw lessons, some skill development initiatives by various companies are also identified and presented in case studies. Additionally, several government programs are available to assess the possibilities and prospects for skill development in the Indian market.

Practical Implications: The research will be valuable in micro and macro decision making. At the micro level, research is advantageous for a business person to initiate the skill development of its employees by using government schemes. Nations other than India can understand the policy framework for skill development.

Findings: The term ‘skilling’ has become fashionable. Due to the need for skill-based earnings data, only some studies examine the return on skill (ROS) of the labour market. Skill development plays a significant role in bringing change at the micro and macro levels. Hence it is necessary to exploit all opportunities for skill development.