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Large class sizes are becoming the norm in higher education against concerns of dropping learning qualities. To maintain the standard of learning and add value, one of the common strategies is for the course convenor to proactively monitor student engagement with learning activities against their assessment outcomes and intervene timely. Learning analytics has been increasingly adopted to provide these insights into student engagement and their performance. This case study explores how learning analytics can be used to meet the convenor’s requirements and help reduce administrative workload in a large health science class at the University of New South Wales.

This case-based study adopts an “action learning research approach” in assessing ways of using learning analytics for reducing workload in the educator’s own context and critically reflecting on experiences for improvements. This approach emphasises reflexive methodology, where the educator constantly assesses the context, implements an intervention and reflects on the process for in-time adjustments, improvements and future development.

The results highlighted ease for the teacher towards the early “flagging” of students who may not be active within the learning management system or who have performed poorly on assessment tasks. Coupled with the ability to send emails to the “flagged” students, this has led to a more personal approach while reducing the number of steps normally required. An unanticipated outcome was the potential for additional time saving through improving the scaffolding mechanisms if the learning analytics were customisable for individual courses.

The results provide further benefits for learning analytics to assist the educator in a growing blended learning environment. They also reveal the potential for learning analytics to be an effective adjunct towards promoting personal learning design.

The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption of certain intelligent technologies and pedagogical designs applied in this domain.

A scoping review was conducted using six inclusive and exclusive criteria agreed upon by the author team. The collected studies, which focused on the adoption of AI in entrepreneurship education, were analysed by the team with regards to various aspects including the definition of intelligent technology, research question, educational purpose, research method, sample size, research quality and publication. The results of this analysis were presented in tables and figures.

Educators introduced big data and algorithms of machine learning in entrepreneurship education. Big data analytics use multimodal data to improve the effectiveness of entrepreneurship education and spot entrepreneurial opportunities. Entrepreneurial analytics analysis entrepreneurial projects with low costs and high effectiveness. Machine learning releases educators’ burdens and improves the accuracy of the assessment. However, AI in entrepreneurship education needs more sophisticated pedagogical designs in diagnosis, prediction, intervention, prevention and recommendation, combined with specific entrepreneurial learning content and entrepreneurial procedure, obeying entrepreneurial pedagogy.

This study holds significant implications as it can shift the focus of entrepreneurs and educators towards the educational potential of artificial intelligence, prompting them to consider the ways in which it can be used effectively. By providing valuable insights, the study can stimulate further research and exploration, potentially opening up new avenues for the application of artificial intelligence in entrepreneurship education.

Education 4.0 (E 4.0) represents a new paradigm in the field of education, which emphasizes a student-centric approach that allows learners to access education anytime, anywhere, tailored to their individual needs through modern-day technologies. The purpose of the study was to unearth the critical success factors (CSFs) essential for the successful implementation of E 4.0.

The CSFs were unearthed using a literature review and further the interrelationships were analysed using multi-criteria decision making (MCDM) approach.

The study unearthed 15 CSFs for the successful implementation of E 4.0. The most important factor for the successful implementation of E 4.0 was personalized learning which was found to be the casual factor. The other causal CSFs were clear vision and leadership for E 4.0, stakeholder involvement, data analytics in teaching and learning, inter-disciplinary learning and blended learning environments. The effect factors were digital citizenship-based education, teacher training and development for E 4.0, supportive environment, curriculum redesign for E 4.0, open educational resources, digital technologies, formative assessments, infrastructure for E 4.0 and sustainability in education.

This is the first study which unearthed the CSFs and found the interrelationships among them, thus contributing to the theory of technology organization environment.

This study represented a pioneering effort in understanding the CSFs underpinning the successful adoption of E 4.0, paving the way for a more personalized, tech-savvy and effective education system.

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.

Digital transformation continues to rapidly progress in higher education globally, spanning all aspects of higher education operations, values and culture. Despite expanding literature, guidance remains focussed on emergency application during pandemic lockdowns and/or on single organisational case studies. Digital transformation frameworks that move beyond these foci are heavily criticised for being commercially contextualised (outside of higher education) and are often too narrowly conceptualised. The purpose of this paper is to review the most common framework currently used in the UK, which takes a strategic and organisational perspective on digital transformation.

This is a technical review article that summarises key guidance for organisational digital capability and then reflects on its application in the UK (a developed economy and higher education system) and in Vietnam (one of the fastest-growing economies with a developing higher education committed to digital transformation) as an initial attempt to explore its applicability beyond the UK context. Vietnam has been chosen as a reference context, given its significant current digital transformation policy reform at the national level and as a collaboration partner with the UK in its digital transformation.

The guidance highlights six core areas to consider for digital capability: information and communication technology (ICT) infrastructure, content and information, research and innovation, communication, learning, teaching and assessment and organisational digital culture. Although the framework is normative, findings suggest it is sufficiently open-ended to enable its users to determine practical steps to drive digital transformation. However, complementary tools are suggested to deal with the rapidly developing digital transformation policy context of Vietnam.

This is the first time a review has been conducted from the perspective of different countries, with a view to supporting leaders, managers and policymakers in the UK, Vietnam and other Association of South Eastern Nations (ASEAN) networks in their own digital transformation transitions.

This study aims to explore and extend the consumer–brand relationship literature by integrating the relatively new construct of brand coolness with a growing body of work on gratitude. Specifically, gratitude is explored alongside emotional brand attachment as an additional mechanism affecting the relationship between cool brands and the loyalty outcome of repurchase intention. Consumption context is examined as a boundary condition to the effect of gratitude.

Data was collected from an online survey of a Qualtrics panel of 356 US consumers. A moderated mediation model is used to explain the effects of brand coolness on repurchase intention via emotional brand attachment and brand gratitude in the moderating presence of consumption context.

Brand coolness significantly increases repurchase intention. Furthermore, emotional brand attachment and brand gratitude are established as parallel mediators of the relationship between brand coolness and repurchase intention, with brand gratitude exhibiting a significantly stronger mediated effect. The impact of brand coolness on brand gratitude is moderated by social visibility, with publicly consumed cool brands stimulating greater brand gratitude than their privately consumed counterparts.

Brand gratitude is shown to influence repurchase intention independent of the impact exerted by consumers’ emotional brand attachment. Cognitive appraisal theory is used to distinguish brand gratitude from other mediators studied in consumer–brand relationships. Findings establish the moderating influence of the social visibility of the brand on the relationship between brand coolness and gratitude.

Given the pressing global challenges underpinning the United Nations’ Sustainable Development Goals, marketing managers can no longer focus only on purely economic outcomes but must simultaneously respond to social and environmental concerns. This requires the teaching of new competencies in marketing education, as also reflected in today’s accreditation requirements for business schools. Therefore, this paper aims to explore how current research into marketing education incorporates sustainable development.

Through a bibliometric literature review – examining 71 publications using the bibliographic coupling method – the current research front in marketing education is analysed.

This paper identifies seven trending topics in marketing education research that both highlight a currently prevalent sustainability gap in marketing education research and – when combined into a framework – help marketing education researchers and educators to address this gap.

This paper extends the already established concept of education for sustainable development to include the concept of marketing education for sustainable development (MESD) for the first time. The MESD framework combines its raison d’être with guidance on how sustainable development should be taught and what the learning objectives should be for future marketing managers.

Dados los apremiantes retos mundiales que sustentan los Objetivos de Desarrollo Sostenible (ODS) de las Naciones Unidas, los directores de marketing ya no pueden centrarse únicamente en los resultados puramente económicos, sino que deben responder simultáneamente a las preocupaciones sociales y medioambientales. Esto requiere la enseñanza de nuevas competencias en la educación de marketing, como también se refleja en los requisitos de acreditación actuales para las escuelas de negocios. Por lo tanto, este documento explorará cómo la investigación actual sobre la educación en marketing incorpora el desarrollo sostenible.

A través de una revisión bibliométrica de la literatura -examinando 71 publicaciones mediante el método de acoplamiento bibliográfico- se analiza el frente actual de la investigación en educación en marketing.

En este artículo se identifican siete temas de tendencia en la investigación sobre educación en marketing que ponen de manifiesto una laguna en materia de sostenibilidad que prevalece actualmente en la investigación sobre educación en marketing y que, combinados en un marco, ayudan a los investigadores y educadores en educación en marketing a abordar esta laguna.

Este artículo amplía el concepto ya establecido de Educación para el Desarrollo Sostenible (EDS) para incluir por primera vez el concepto de Educación en Marketing para el Desarrollo Sostenible (EMDS). El marco EMDS combina su razón de ser con orientaciones sobre cómo debe enseñarse el desarrollo sostenible y cuáles deben ser los objetivos de aprendizaje para los futuros directores de marketing.

鉴于联合国可持续发展目标（SDG）所依据的紧迫的全球挑战, 营销经理不能再只关注纯粹的经济成果, 而必须同时应对社会和环境问题。这就要求在营销教育中教授新的能力, 这也反映在当今商学院的认证要求中。因此, 本文将探讨目前对市场营销教育的研究是如何纳入可持续发展的。

通过文献计量学文献综述–使用文献耦合法对71份出版物进行研究–分析了当前市场营销教育的研究前沿。

本文确定了营销教育研究中的七个趋势性课题, 这些课题既突出了当前营销教育研究中普遍存在的可持续发展差距, 又–当结合成一个框架–帮助营销教育研究者和教育者解决这一差距。

本文扩展了已经建立的可持续发展教育（ESD）的概念, 首次将可持续发展的营销教育（MESD）的概念纳入其中。MESD框架将其存在的理由与指导如何教授可持续发展以及未来营销经理的学习目标相结合。

The purpose of this paper is to analyse data literacy in the new Digital Competence Framework for Citizens (DigComp 2.2). Mid-2022 the Joint Research Centre of the European Commission published a new version of the DigComp (EC, 2022). This new version focusses more on the datafication of society and emerging technologies, such as artificial intelligence. This paper analyses how DigComp 2.2 defines data literacy and how the framework looks at this from a societal lens.

This study critically examines DigComp 2.2, using the data literacy competence model developed by the Knowledge Centre for Digital and Media Literacy Flanders-Belgium. The examples of knowledge, skills and attitudes focussing on data literacy (n = 84) are coded and mapped onto the data literacy competence model, which differentiates between using data and understanding data.

Data literacy is well-covered in the framework, but there is a stronger emphasis on understanding data rather than using data, for example, collecting data is only coded once. Thematically, DigComp 2.2 primarily focusses on security and privacy (31 codes), with less attention given to the societal impact of data, such as environmental impact or data fairness.

Given the datafication of society, data literacy has become increasingly important. DigComp is widely used across different disciplines and now integrates data literacy as a required competence for citizens. It is, thus, relevant to analyse its views on data literacy and emerging technologies, as it will have a strong impact on education in Europe.

The purpose of this study is to address the generalised lack of guidance on ethical treatment of corporate (e.g. non-research) data in higher education institutions, by focusing on the case of the University of Queensland (Brisbane, Australia). No actionable framework is currently available in the country to govern the ethical usage of corporate data. As such, this research takes a stakeholder-centred approach to data ethics; the lived experience of the stakeholders involved coupled with a theory-based ethical framework allowed the authors build to build a framework to guide ethical data practice.

Adopting a revised canonical action research approach focused on intervention on the context, the authors conducted a review of the literature on ethical usage of data in higher education institutions; administered one survey to university students (n = 168); and facilitated three workshops with professional staff (two) and students (one).

Collected data highlighted how, among other themes, the role and ethical importance of transparency was the dominant claim among all stakeholder groups. Findings helped the authors develop an Enhanced Enterprise Data Ethics Framework (EEDEF) emphasising transparency and stakeholder-centricity.

Legislation is the driver to regulate the use of corporate data in higher education; however, this can be problematic because legislation is retrospective, lacks normativity and offers scarce directions for cases that do not exactly follow within the legislative mandate. In light of these regulatory limitations, the authors’ EEDEF offers operators guidance on how to ethically manage corporate data in the higher education environment.

This study fills gaps in praxis and theory; that is the lack of literature and guiding ethical frameworks to inform data practice in higher education. This research fosters a more ethical data management by virtue of genuine and authentic engagement with stakeholders and emphasises the importance of strategic decision-making and maturity of data culture in the higher education sector.

This study examines the relationship between servant leadership and its dimensions on firm performance, with big data playing the role of a mediator.

Survey responses used for analysis in this study have been taken from business managers associated reputed private sector organizations in India. A conceptual model is proposed grounded to the Conservation of Resource Theory (COR). Structural equation modeling has been used to test the proposed model.

Servant leadership significantly relates to firm performance, whereby Big Data is seen to play the role of a mediator. The results also indicate that none of the dimensions of servant leadership independently affect firm performance.

The study adds to extant research by examining the mediating mechanism of Big Data in servant leadership and firm performance. It also suggests that each dimension of servant leadership gets reflected in overall servant leadership. Here it is important to note that Big Data analytics partially mediate the effectiveness of servant leadership.