The objectives of this editorial are to provide a brief overview of the themes of EJEL papers published in 2023, compare these themes with the areas of work suggested in the previous Editorial (Charbonneau-Gowdy, et al., 2023), and propose new areas of focus for future research. The present Editorial will primarily concentrate on the main challenges arising from the release and use of GPT-3 and GPT-4 in 2023.

Building on the literature on the concept-product gap in new product development, we examine how FinTech SMEs are developing Artificial Intelligence (AI)-based innovations and which organisational or project factors best contribute to the acceleration of AI innovation. The empirical evidence collected from interviews with key stakeholders, practitioners’ forums, and public company documents yields two distinct approaches that differ in their potential for accelerating innovation and reducing the concept-product gap. From a contingency perspective, these two approaches are expanded into four distinct development process configurations, contingent on the business development stage, reliance on 3rd party platforms, availability of high volumes of data, investment level, organisational agility, and level of novelty. The resulting process typology could be used as a diagnostic tool for FinTech SMEs interested in effectively leveraging AI innovation. Using contingency theory, we further develop these insights into a new theoretical framework to explain how AI innovation development unfolds in FinTech SMEs and the rationale for different implementations. Our new process typology and theoretical model can help researchers investigate the mechanisms underlying technological innovation processes. We further identify the specific reasons why the potential of AI for creating new services and disrupting incumbents via digital startups has not been fully realised even in contexts with significant investment and support from public and private business development programmes. This field is still rapidly evolving, and thus, new areas for future research are also highlighted.

PBL's motivation, outcomes, and its significance for students’ experience and fo r graduate marketing programs. They describe the collaboration between faculty members and graduate students from business and education fields to develop a web-based simulation, immersing students in a factory environment and addressing a challenging learning topic. The simulation proved to be more useful and productive than the original design team anticipated and has since been scaled for use by other university and industry students. The paper presents a compelling argument for hybrid online PBL learning design, a popular topic in e-Learning.

A rapidly aging population, combined with restrictions on public spending, is creating strong latent demands for eHealth. For many older people, institutionalised inpatient care is not only expensive, but also less attractive than their being cared for in their own homes. eHealth innovations offer promising new avenues that will allow health and social care systems to cope with these challenges and improve the quality of life for older people. However, the user uptake of eHealth is surprisingly low, and successful deployment is not guaranteed unless the interests of key stakeholders are better addressed. While many previous studies have addressed technological aspects of eHealth innovations, the business models underpinning these innovations are often overlooked. This study thus examines the key characteristics of eHealth market from the dual perspectives of business model and information systems success model to contribute to more sustainable and scalable market development of eHealth innovations. A multiple-case study design based on 20 UK and 13 international cases in combination with expert workshops was used to formulate the main barriers and challenges for the commercialisation of eHealth innovations in UK and propose frameworks for more sustainable eHealth innovations. The implications for both management practice and policy are also discussed.

Introduction Artificial intelligence (AI) offers great potential for transforming healthcare delivery leading to better patient-outcomes and more efficient care delivery. However, despite these advantages, integration of AI in healthcare has not kept pace with technological advancements. Previous research indicates the importance of understanding various organisational factors that shape integration of new technologies in healthcare. Therefore, the aim of this study is to provide an overview of the existing organisational factors influencing adoption of AI in healthcare from the perspectives of different relevant stakeholders. By conducting this review, the various organisational factors that facilitate or hinder AI implementation in healthcare could be identified. Methods and analysis This study will follow the Joanna Briggs Institute framework, which includes the following stages: (1) defining and aligning objectives and questions, (2) developing and aligning the inclusions criteria with objectives and questions, (3) describing the planned approach to evidence searching and selection, (4) searching for the evidence, (5) selecting the evidence, (6) extracting the evidence, (7) charting the evidence, and summarising the evidence with regard to the objectives and questions. The databases searched will be MEDLINE (Ovid), CINAHL (Plus), PubMed, Cohrane Library, Scopus, MathSciNet, NICE Evidence, OpenGrey, O’REILLY and Social Care Online from January 2000 to June 2021. Search results will be reported based on The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews guidelines. The review will adopt diffusion of innovations theory, technology acceptance model and stakeholder theory as guiding conceptual models. Narrative synthesis will be used to integrate the findings. Ethics and dissemination Ethics approval will not be sought for this scoping review as it only includes information from previously published studies. The results will be disseminated through publication in a peer-reviewed journal. In addition, to ensure its findings reach relevant stakeholders, they will be presented at relevant conferences.

Purpose The recent rise in online knowledge repositories and use of formalism for structuring knowledge, such as ontologies, has provided necessary conditions for the emergence of tools for generating knowledge assessment. These tools can be used in a context of interactive computer-assisted assessment (CAA) to provide a cost-effective solution for prompt feedback and increased learner’s engagement. The purpose of this paper is to describe and evaluate a tool developed by the authors, which generates test questions from an arbitrary domain ontology, based on sound pedagogical principles encapsulated in Bloom’s taxonomy. Design/methodology/approach This paper uses design science as a framework for presenting the research. A total of 5,230 questions were generated from 90 different ontologies and 81 randomly selected questions were evaluated by 8 CAA experts. Data were analysed using descriptive statistics and Kruskal–Wallis test for non-parametric analysis of variance. Findings In total, 69 per cent of generated questions were found to be useable for tests and 33 per cent to be of medium to high difficulty. Significant differences in quality of generated questions were found across different ontologies, strategies for generating distractors and Bloom’s question levels: the questions testing application of knowledge and the questions using semantic strategies were perceived to be of the highest quality. Originality/value The paper extends the current work in the area of automated test generation in three important directions: it introduces an open-source, web-based tool available to other researchers for experimentation purposes; it recommends practical guidelines for development of similar tools; and it proposes a set of criteria and standard format for future evaluation of similar systems.

The number of academic papers in the area of Artificial Intelligence (AI) and its applications across business and management domains has risen significantly in the last decade, and that rise has been followed by an increase in the number of systematic literature reviews. The aim of this study is to provide an overview of existing systematic reviews in this growing area of research and to synthesise the findings related to drivers, barriers and social implications of the AI adoption in business and management. The methodology used for this tertiary study is based on Kitchenham and Charter's guidelines [14], resulting in a selection of 30 reviews published between 2005 and 2019 which are reporting results of 2021 primary studies. These reviews cover the AI adoption across various business sectors (healthcare, information technology, energy, agriculture, apparel industry, engineering, smart cities, tourism and transport), management and business functions (HR, customer services, supply chain, health and safety, project management, decision-support, systems management and technology adoption). While the drivers for the AI adoption in these areas are mainly economic, the barriers are related to the technical aspects (e.g. availability of data, reusability of models) as well as the social considerations such as, increased dependence on non-humans, job security, lack of knowledge, safety, trust and lack of multiple stakeholders'perspectives. Very few reviews outside of the healthcare management domain consider human, organisational and wider societal factors of the AI adoption. In addition to increased focus on social implications of AI, the reviews are recommending more rigorous evaluation, increased use of hybrid solutions (AI and non-AI) and multidisciplinary approach to AI design and evaluation. Furthermore, this study found that there is a lack of systematic reviews in some of the early AI adoption sectors such as financial industry and retail.

These Proceedings represent the work of contributors to the 14th European Conference on e-Learning, ECEL 2015, hosted this year by the University of Hertfordshire, Hatfield, UK on 29-30 October 2015. The Conference and Programme Co-Chairs are Pro-fessor Amanda Jefferies and Dr Marija Cubric, both from the University of Hertfordshire. The conference will be opened with a keynote address by Professor Patrick McAndrew, Director, Institute of Educational Tech-nology, Open University, UK with a talk on Innovating for learning: designing for the future of education. On the second day the keynote will be delivered by Professor John Traxler, University of Wolverhampton, UK on the subject of Mobile Learning - No Longer Just e-Learning with Mobiles. ECEL provides a valuable platform for individuals to present their research findings, display their work in progress and discuss conceptual advances in many different branches of e-Learning. At the same time, it provides an important opportunity for members of the EL community to come together with peers, share knowledge and exchange ideas. With an initial submission of 169 abstracts, after the double blind, peer review process there are 86 academic papers,16 Phd Papers, 5 Work in Progress papers and 1 non academic papers in these Conference Proceedings. These papers reflect the truly global nature of research in the area with contributions from Algeria, Australia, Austria, Belgium, Botswana, Canada, Chile, Cov-entry, Czech Republic, Denmark, Egypt, England, Estonia, France, Germany, Ireland, Japan, Kazakhstan, New Zealand, Nigeria, Norway, Oman,Portugal, Republic of Kazakhstan, Romania, Saudi Arabia, Scotland, Singapore, South Africa, Sweden, the Czech Republic, Turkey, Uganda, UK, United Arab Emirates, UK and USA, Zimbabwe. A selection of papers - those agreed by a panel of reviewers and the editor will be published in a special conference edition of the EJEL (Electronic Journal of e-Learning www.ejel.org ).

Electronic Voting System (EVS) is a classroom technology that provides a means to increase students' engagement, attention and attendance. The purpose of this paper is to provide a deeper insight into students' views on the benefits and challenges of EVS in the context of a large-scale institutional deployment and across different subject areas in higher education.The data were collected from an online survey of 590 students across eleven academic schools at a UK university. The non-linear principal component analysis of 32 question items from the survey showed that learning benefits, classroom-related benefits, usability and student-centered challenges are four distinctive dimensions in student's perceptions of the use of EVS. The non-parametric group comparison tests suggested that there are significant differences in learning benefits and challenges across different subject groups. However, the disparity appears to be related more to the way the EVS was used and the experience of students with it, rather than resulting from disciplinary differences. Content analysis of open questions revealed that summative use and staff competencies are the main issues related to EVS use by students. Finally, despite the overwhelming perception of the ease of use, it was found that usability could be an issue for students when EVS was used for summative assessment.The implications of the study are: for practitioners, it underlines the importance of the focus on formative benefits of EVS as only then and regardless of disciplinary differences, can the promised rewards of the technology be gained; for institutions, it outlines some of the new challenges specific to the large-scale institutional implementation, judged through the lens of students' experience; for researchers, it provides an overview of the literature on large-scale deployment of EVS and it suggests some new areas for research on the use of EVS in higher education. (C) 2015 Elsevier Ltd. All rights reserved.

In recent years there has been much encouragement to investigate the use of classroom technologies to enhance the student learning experience especially in the STEM subjects but now extending across other subject areas as well. A typical classroom technology is electronic voting system (EVS) handsets which allow a lecturer to invite students to vote for their choice from a selection of given answers. Recently, a medium-size UK University has purchased over 9000 EVS handsets for use across the academic Schools as an innovative means for supporting formative and summative testing. Numerous training and support sessions have been provided to staff with the intention of supporting new and experienced users and increasing the take up by academics. As noted in earlier research reported at ECEL 2013, the student feedback was very positive for the use of EVS for formative activities, and less so, for its use in summative assessment. A recent review of the trends of EVS adoption at the University has been undertaken to inform decision-making and future use and support for the technology. One aspect of this review has considered the effectiveness of the strategies adopted by different academic Schools. EVS adoption and use across the University has been compared and placed within Rogers' theory of the diffusion of innovation. This paper further considers a set of six different strategies adopted for EVS use by academic Schools. They have been categorised according to several variables, including their choice of speed of uptake and the number of handsets in use. The inherent strengths and possible weaknesses of the approaches adopted are considered. Among the questions raised were, does a strategy of large-scale technology adoption over a short time period indicate a greater likelihood of long term engagement and ultimate adoption of the technology? Or, does a longer elapsed time taken for a gradual purchase and adoption of EVS technology suggest a greater inclination for the embedding of technology for enhancing learning? What other success factors should be considered alongside the training and support provided for technology adoption to enhance the likelihood of long term adoption of classroom technologies? The discussion provides a comparison of six different strategies identified across the university and the rationale behind them and then proposes a set of strategy choices which can lead to a greater likelihood of successful adoption of classroom technology.

The aim of this paper is to describe, evaluate and discuss a new method for teaching agile project management and similar subjects in higher education.Agile is not only a subject domain in this work, the teaching method itself is based on Scrum, a popular agile methodology mostly used in software development projects. The method is supported by wikis, a natural platform for simulation of software development environments.The findings from the evaluation indicate that the method enables the creation of "significant learning", which prepares students for life-long learning and increases their employability. However, the knowledge gains, resulting from wiki interactions are found to be more quantitative than qualitative.The results also imply that despite the active promotion of agile values of communication and feedback, issues regarding the teamwork are still emerging. The engagement of the teacher in the learning and teaching process was discovered to be a motivational factor for the team cohesion.This paper could be of interest to anyone planning to teach agile in the higher education settings, but also to a wider academic community interested in applying agile methods in their own teaching practice. (C) 2013 Elsevier Ltd. All rights reserved.