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Focusing on the quality of teaching and learning, this study aims to explore the perceptions of accountancy students in two emerging UK Higher Education Institutions (HEIs) of the quality of their learning experiences and the impact of these experiences on generic skills development.

A questionnaire survey was used to collect the data. OLS regression was used to test the hypothesis regarding the impact of student learning experiences (lecturer ability, assessment and curriculum) on generic skills development.

Students value the lecturer as the most important determinant of the quality of their experience. They rated their assessment programme very positively, and the curriculum suggests that students tend to experience a deep blended approach to learning. They also felt that they acquired a wide range of soft competency skills such as those associated with research, critical thinking and time management. Multivariate findings indicate that lecturer ability and curriculum contribute significantly and positively to generic skills development.

The study provides a benchmark for international accounting and business educators in any efforts to assess the efficacy of HE delivery since the pandemic. By implication, it enables the identification of enhancements to the previous character of delivery and hence offers the means to direct improvements to the student experience. Such improvements can then be seen in the National Student Survey (NSS) scores, thereby positively contributing to the next Teaching Excellence Framework. Additionally, such tangible enhancements in NSS scores may be advantageous to HEIs, in the UK and other Western countries, in their efforts to recruit international students on whom they place great reliance for increased revenue, to their international business education programmes.

This study addresses the research gap surrounding the link between teaching and learning approaches in accounting and the development of generic skills. Furthermore, acknowledging that the COVID-19 pandemic with its imposed structural change in the HE teaching and learning environment ushered in a new model of curriculum delivery, this study reflects on the pre-COVID-19 scenario and gathers student perceptions of their teaching and learning experiences before the changes necessitated by lockdowns. It therefore brings the opportunity to anchor future research exploring the post-COVID-19 environment and secure comparative analyses.

This article investigates the application of generative artificial intelligence (GenAI) in experiential learning for authentic assessment in higher education. Recognized for its human-like content generation, GenAI has garnered widespread interest, raising concerns regarding its reliability, ethical considerations and overall impact. The purpose of this study is to explore the transformative capabilities and limitations of GenAI for experiential learning.

The study uses “thing ethnography” and “incremental prompting” to delve into the perspectives of ChatGPT 3.5, a prominent GenAI model. Through semi-structured interviews, the research prompts ChatGPT 3.5 on critical aspects such as conceptual clarity, integration of GenAI in educational settings and practical applications within the context of authentic assessment. The design examines GenAI’s potential contributions to reflective thinking, hands-on learning and genuine assessments, emphasizing the importance of responsible use.

The findings underscore GenAI’s potential to enhance experiential learning in higher education. Specifically, the research highlights GenAI’s capacity to contribute to reflective thinking, hands-on learning experiences and the facilitation of genuine assessments. Notably, the study emphasizes the significance of responsible use in harnessing the capabilities of GenAI for educational purposes.

This research showcases the application of GenAI in operations management education, specifically within lean health care. The study offers insights into its capabilities by exploring the practical implications of GenAI in a specific educational domain through thing ethnography and incremental prompting. Additionally, the article proposes future research directions, contributing to the originality of the work and opening avenues for further exploration in the integration of GenAI in education.

A mixed-method study was performed to determine the impact of integrating systems thinking (ST) into an electronic learning module for junior high school teachers in the Philippines. The study aims to assess how an ST approach to pedagogy compared against a conventional approach in terms of contribution to the participants’ global climate change content knowledge, holistic thinking and depth and accuracy of knowledge and reasoning.

The study implemented e-learning modules using an ST approach versus a conventional approach in teaching climate science to junior high school teachers. The paper presents quantitative data obtained from pre and posttests results of the 20 teacher-participants and qualitative data obtained during the focus-group discussion (FGD) after the implementation of the study.

The results from the statistical analysis indicated that the ST group obtained a significant increase in their assessment scores compared to the non-ST group, according to predetermined criteria. Content knowledge, depth and accuracy of knowledge and reasoning increased the most. The participants mentioned during the FGD that the module helped deepen their understanding of climate change.

The study was limited to 20 teacher-participants, but it has relevance for public school teachers in the country given that participants had raised concerns regarding the lack of training in their schools for teaching climate science. They admitted that they lacked critical information to include in climate change topics in their classes.

This paper shows how the ST approach can be used to teach climate change to junior high students. The e-learning module can provide teachers with better understanding, knowledge and reasoning to teach climate change to high school students more effectively.

This study aims at understanding how higher education institutions (HEIs) can contribute to sustainable development, by designing their programmes for bringing about a transformative impact on communities and students, and also to examine what alternative pedagogical approaches could be used for that. In the past decades, HEIs have increasingly created social innovation (SI) programmes, as a way to achieve United Nations Sustainable Development Goals. These community-oriented and field-based programmes are difficult to ally with conventional classroom education. This study explores how these programmes could integrate the participatory approach and what would be the benefits. It also investigates the effectiveness of the experiential learning approach for teaching sustainability.

A case study method is used to document SI projects initiated by an HEI programme in rural India.

It was found that the participatory approach contributes to empowering communities and also benefits the students in terms of academic, professional and personal growth. Empirical findings show that experiential learning is an efficient method to teach sustainability. Ultimately, both pedagogical approaches are found to be mutually beneficial.

This study fills a gap in the literature, by providing empirical evidence on how HEI can implement innovative educational strategies such as participatory approach and experiential learning in their programmes towards teaching sustainability. A conceptual model for HEI interested in developing similar programmes is also proposed. To the best of the authors’ knowledge, this study is one of the first studies focusing on the context of Indian HEI.

This paper aims to systematically review and synthesize existing research on learning-driven strategic renewal and examines the findings to elucidate the dimensions, antecedents, mechanisms and consequences associated with learning-driven strategic renewal, thereby addressing gaps in the existing literature.

This research covers learning-driven strategic renewal from 1992 to 2022, using hybrid snowball sampling techniques and Boolean searches on the Scopus and Web of Science databases to extract 49 papers.

This review proposes an organizing framework for learning-driven strategic renewal, building upon existing literature. The framework identifies various dimensions of the process, including antecedents, mechanisms and consequences. The antecedents are categorized into individual, organizational and external factors. The mechanisms for learning-driven strategic renewal were explored within the context of Crossan’s established 4I framework, which serves as a lens for emphasizing the balance between exploratory and exploitative learning. Within this framework, intuiting, interpreting, integrating and institutionalizing are the four “Is” that guide the renewal process. These mechanisms require a robust system to enforce the prescribed processes effectively, thereby contributing to long-term firm performance and sustainability.

Despite using search terms similar to those in existing literature on strategic renewal, the scope and depth of this study may be limited. Further research may benefit from bibliometric screening or more refined inclusion criteria.

While there has been extensive research into both organizational learning and strategic renewal, no coherent framework links them. This study fills this gap by building a framework that identifies connections between these two concepts, providing valuable insights that may be used to foster successful strategic renewal efforts. The review offers valuable knowledge and understanding of the subject matter, serving as useful guidance for effectively driving renewal initiatives within organizations.

This study explores virtual platforms’ capabilities, particularly emphasising the influence of educational movies embedded with lifelike narratives to serve as a potent medium for immersive learning within the auditing discipline. Through this exploration, we aim to discern how cinematic depictions can educate and encapsulate the intricate dynamics of real-world auditing scenarios, thereby enriching the educational experience for budding auditors.

By employing an action research methodology, this study engaged 134 auditing students from China in an experiment, using a questionnaire to assess their grasp of auditing concepts like internal control, corporate governance, and professional ethics.

Preliminary findings underscore the efficacy of movies as pedagogical tools. These movie experiences bridge the gap between theoretical knowledge and its real-world application, particularly highlighting the nuances of professional ethics and corporate governance. Results show that such a method amplifies students’ comprehension of auditor skillsets, practical complications, and ethical insight and nurtures professional scepticism about tangible audit issues.

This study illuminates a novel virtual learning approach using movies that primes students to exercise critical thinking and augments cognitive skillsets, especially when navigating ethical conundrums. The broader implication is the potential enhancement of auditing education quality in China, presenting educators with an innovative teaching modality that bolsters students’ critical analysis and cognitive development.

This study has multiple implications for auditing education policy. It underscores the imperative need for curriculum revision in contemporary auditing education. Our study can significantly change contemporary auditing education by incorporating movie-based experiential learning. Educators and institutions in China and other parts of the world explore this avenue, customising it to fit the unique requirements of their respective courses and the country’s contexts. Our study also highlights the challenges and recommendations for real-world audit simulation for auditing education. While our research highlights the promise of educational movies, it also sheds light on the potential difficulties in their integration. Audit educators need adequate support and training for effective assimilation, ensuring they leverage educational movies to maximise learning outcomes. Careful curation and selection of movies, combined with strategic planning, are paramount to this teaching method’s success. With the continual evolution of video tools, there is an opportunity for a more immersive and holistic education model, shaping the next generation of auditors.

This study offers insights into innovative strategies to imbue real-world experience into traditional curricula, ensuring relevance and applicability across diverse educational landscapes.

(Digital) servitization, referring to service-driven strategies and their increasing implementation in manufacturing, is one of the most rapidly growing areas in industrial service research. However, the cultural change involved in successful servitization is a phenomenon that is widely observed but poorly understood. This research aims to clarify the processes of social construction as manufacturers change their organizational culture to transform into industrial service providers.

This research takes a systematic approach to integrate disparate literature on servitization into a cohesive framework for cultural change, which is purposefully augmented by rationale culled from organizational learning and sensemaking literature.

The organizational learning framework for cultural change in servitization introduces a dynamic perspective on servitizing organizations by explaining social processes between organizational and member-level cultural properties. It identifies three major cultural orientations toward service, digital and learning that govern successful servitization.

This research contributes to the servitization literature by presenting a new approach to reframe and explore cultural change processes across multiple levels, thus providing a concrete starting point for further research in this area.

This study aims to analyze the evolution and current state of talent management in learning organizations and the design of managerial curricula, highlighting the challenges and opportunities in the context of a rapidly changing global business environment.

A narrative literature review was conducted, tracing the conceptual evolution of learning organizations. Seminal works emphasizing continuous learning and transformation were highlighted, and the progression of managerial education was analyzed, from its early focus on ethics and soft skills to its current emphasis on sustainability, digital literacy and experiential learning.

The research reveals challenges in balancing foundational knowledge with emerging competencies in curriculum design. Tensions are evident in maintaining relevance in rapidly changing, globally interconnected environments. Notable limitations include the trade-offs in innovation and the need to cater to diverse student demographics.

This review uniquely synthesizes developments at the intersection of curriculum innovation, organizational learning and curriculum design, offering valuable insights for institutions aiming to nurture talent for modern learning organizations.

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

The present research aimed to examine the role of FDP in enhancing the teachers' competencies through modern technological tools and innovative teaching methods. And also, to evaluate the impact of FDPs on teachers' attitudes and motivation to integrate modern teaching innovations into their classroom practices.

Using a pre-post study design, the study was conducted in two phases, Phase I was conducted one week before conducting FDP (14th to 20th August 2023) and Phase II was conducted after one week of FDP (15th to 21st September 2023). The data were gathered through structured questionnaires from the participants in FDP and collected data were processed and analyzed through a statistical package for social sciences.

The study found that undergoing FDP by teachers significantly influences the adoption of advanced pedagogical approaches and technology integration during their teaching practice. This indirectly helps in promoting quality education at large and contributes to the UNSDG-4. The study also revealed that the effective FDP not only helps in advancing teaching methods but also influences instructors' philosophies and attitudes towards students' overall learning and development.

These findings have several key implications for higher education institutions, policymakers and teachers at large. Firstly, HEIs should prioritize undertaking FDPs that promote in adopting advanced pedagogical approaches. This indirectly equips the instructors with the knowledge and skills necessary to integrate modern teaching methods into their real classroom practices. Further, by adopting FDP as a strategic initiative to improve the quality of education and work by aligning these programs with broader SDG goals.

Advancing education for enhancing the overall quality of learning depends on the competencies of instructors. The competencies of instructors rely upon the involvement of instructors in life-long learning, level of adoption of technology, innovative approaches used, etc. This study may help higher education institutions adopt FDP as a strategic initiative to improve the quality of education and work by aligning these programs with broader SDG goals.