Beyond Innovation: Centring Ethics and Social Responsibility in Educational Computing

This editorial considers the ethical, social, and global consequences of educational computing technologies, emphasizing the need to move beyond just a focus of innovation to critically engage with these issues. It highlights the Journal’ s expanded aims, which now include scholarship that examines the ethical foundations of educational computing technologies, their social impact, and their role in addressing global educational inequities. The editorial calls for research that explores justice, representation, and access, particularly for marginalized communities. Additionally, it introduces new article types, including Review Articles and Systems and Tools, encouraging a greater diversity of contributions that critically evaluate the implications of educational computing technologies in multiple educational contexts

Jumping and Landing Kinematics in Spanish Female Soccer Players: A Comparison Between Elite and Non-Elite Athletes

Landing from a jump has been identified as a common situation of increased risk in sport and the tuck jump assessment (TJA) has been proposed for a comprehensive examination of landing mechanics. However, group-specific data on female athletes are limited. The purpose of this study was to examine the movement mechanics during a TJA in Spanish female soccer players and to explore potential differences between players of different performance levels. A total of 96 (elite and non-elite) female soccer players performed a TJA, and a rater visually graded the technique using the modified 10-item scoring system (0, 1, or 2 for “none”, “small”, or “large” flaws). Descriptive statistics were calculated. The association between the flaws and performance groups was assessed using the chi-square test. Almost 90% of all players involved were categorized with small and large flaws for the item “Lower extremity valgus at landing”. The proportion of players categorized with technical flaws was also high for “Foot contact timing not equal” (85%) and “Does not land in same footprint” (82%). Differences between elite and non-elite players were only found for “Foot placement not parallel” and “Excessive landing contact noise” (p < 0.008). These results reveal the importance of implementing training programs to reduce jumping and landing deficits in female soccer players, independently of the players’ level of performance

Profiling hypermobile Ehlers-Danlos syndrome (hEDS): factors in health and wellbeing with chronic conditions and opportunities for improving self-management

Purpose Factors affecting physical and psychological outcomes for those with chronic conditions are complex, extending beyond medical symptomology to numerous demographic influences. Living with hypermobile Ehlers-Danlos Syndrome (hEDS) is characterised by diagnostic delay and numerous comorbidities, known to impact wellbeing. Materials and methods This high-powered study (n = 415 participants) investigates the mediating effect of diagnosis, comorbidity and age on wellbeing, and provides insights into the effects of the latest hEDS reclassification. Validated measures were used to assess quality of life, perceived social support, physical health, fatigue, anxiety, pain and loneliness. Results Results indicated worse outcomes for those diagnosed after the reclassification and for those with higher numbers of comorbidities. Conversely, improved outcomes were associated with older age. Findings were supported by insights captured in participants’ demographic profiles where a wider breadth of comorbidities were recorded than previously identified. Meanwhile, there was no evidence of a change in the route to diagnosis over time, and data showed ongoing limitations in terms of options for effective treatment. Conclusions These findings point to the potential effectiveness of self-management techniques for improving well-being with chronic conditions and highlight the need for improved awareness of hEDS and its management amongst primary care practitioners. IMPLICATIONS FOR REHABILITATION Hypermobile Ehlers-Danlos Syndrome (hEDS) is a complex, debilitating condition where rehabilitation is often hampered by protracted diagnoses, multiple comorbidities and limited treatment options. Findings support evidence that self-management is influential in improving outcomes. Greater awareness of hEDS at primary care level is urgently required both to improve diagnosis and enable opportunities for rehabilitation through self-management

Sustainability, the Circular Economy and Digitalisation in the European Textile and Clothing Industry

The scale of production of the textile and clothing (T&C) industry has been steadily increasing for many years, accompanied by significant resource consumption, waste generation, and environmental impact. The industry has hitherto made its products in linear fashion, with relatively little recycling of the finished goods. This book looks at the industry’s approach to the core sustainability concept, and the circular economy (CE) in particular, through the lens of researchers in nine European countries. It also examines the role of digital technology deployment in engendering sustainability and the CE in the industry. Digital technologies are increasingly recognised as key enablers and facilitators of this transition, promoting both efficiency and circularity in manufacturing processes. However, the extent to which these are implemented in the industry remains largely unexplored. This book aims to address this gap in the research literature by assessing different aspects of the industry across Europe, and puts forward some overall conclusions and an analytical framework for future research

Urban image change over two decades: Comparing the images of six British urban areas 20 years apart

This paper addresses a significant lacuna in the literature of urban image by examining urban image change for multiple towns and cities over a period of two decades. It revisits and repeats a survey of UK conference and events organisers from 2000 that explored the images they hold of six British towns and cities that had all positioned themselves as key venues for business and leisure tourism meetings, events and conferences. It found both continuities and changes in the images of the towns and cities examined across this time period. Whilst the images of some towns and cities had changed significantly, others had changed very little. Further, the ways in which this audience collectively talked about these urban areas had changed little over this time. The results show that, across an extended time period, significant change in the images of urban areas can occur but that it is not inevitable. The results point to the significance of individual circumstances rather than general processes of urban image change. Our results also reveal the significance of ongoing personal experiences of cities to the processes of urban image formation and change amongst this audience

FraudGNN-RL: A Graph Neural Network With Reinforcement Learning for Adaptive Financial Fraud Detection

As financial systems become increasingly complex and interconnected, traditional fraud detection methods struggle to keep pace with sophisticated fraudulent activities. This article introduces FraudGNN-RL, an innovative framework that combines Graph Neural Networks (GNNs) with Reinforcement Learning (RL) for adaptive and context-aware financial fraud detection. Our approach models financial transactions as a dynamic graph, where entities (e.g., users, merchants) are nodes and transactions form edges. We propose a novel GNN architecture, Temporal-Spatial-Semantic Graph Convolution (TSSGC), which simultaneously captures temporal patterns, spatial relationships, and semantic information in transaction data. The RL component, implemented as a Deep Q-Network (DQN), dynamically adjusts the fraud detection threshold and feature importance, allowing the model to adapt to evolving fraud patterns and minimize detection costs. We further introduce a Federated Learning scheme to enable collaborative model training across multiple financial institutions while preserving data privacy. Extensive experiments on a large-scale, real-world financial dataset demonstrate that FraudGNN-RL outperforms state-of-the-art baselines, achieving a 97.3% F1-score and reducing false positives by 31% compared to the best-performing baseline. Our framework also shows remarkable resilience to concept drift and adversarial attacks, maintaining high performance over extended periods. These results suggest that FraudGNN-RL offers a robust, adaptive, and privacy-preserving solution for financial fraud detection in the era of Big Data and interconnected financial ecosystems

The influence of COVID-19 on the adoption of disruptive technologies in SMEs practices: UAE context

Disruptive technologies (DTs) becoming pivotal issues towards successful business innovation strategies. DTs are the emerging technologies that result due to change in the cost of how we access products and services. DTs offer small-medium enterprises (SMEs) a wide range of advantages including improved productivity, value addition to the business, and improve the performance delivery to the end users. Organizations’ digital readiness and future research topics should also address the effect of technology on ethics like data privacy and identifying algorithmic bias, as well as sustainable digital business transformation initiatives outside the crisis phase. The chapter sheds lights on the socio-economic effects of the Covid-19 pandemic on the adoption of DTs in SMEs’ accounting practices in UAE. Adoption of AI, cloud solutions, mobile accounting, and robotic process automation of accounting are valuable and crucial instruments in relation to the absence of business continuity; their application contributes to remote work as well as increases efficiency. These technologies made it possible for SMEs to counter quick shocks in the market and supply changes, besides helping to cope with fluctuating cash flows. It was established that those companies that managed to adopt digitalization strategies in the organisation were in a better place to deal with the effects caused by the pandemic. The results also pointed to a strong influence of an external environment concerning the implementation of DTs by policy makers and market forces

Differences in Sprinting and Jumping Performance Between Maturity Status Groups in Youth: A Systematic Review and Meta-analysis

Background: Large interindividual differences can exist in the timing and tempo of growth and maturation of youth athletes. This can provide significant physical performance advantages to young athletes who mature in advance of their peers. Objective: The aim of this systematic review was to determine the magnitude of differences in sprinting and jumping performance in youth of different maturity status (classified as pre-, circa- or post-peak height velocity [PHV]) (aged < 18 years) to enhance the evaluation of performance. Methods: Eligibility criteria for inclusion were as follows: (1) the study had cross-sectional data available; (2) participants were male and/or female ≤ 18 years of age; (3) a somatic measure of maturity was used to identify maturity status (e.g. Mirwald or Khamis-Roche methods) with at least two maturity status classifications present; (4) the study included a measurement of sprinting speed (e.g. 10-100-m sprint data) and/or jump tests commonly used to assess power (e.g. countermovement jump [CMJ]). Searches were conducted up to November 2024 in PubMed, Embase, SPORTDiscus and preprint servers SportRxiv and medRxiv to identify any unpublished trials. Risk of bias and study quality was assessed using the Appraisal tool for Cross-Sectional Studies (AXIS). Meta-analysis was computed using a random-effects model. Results: The search identified 1578 studies. From those, 40 studies were identified for qualitative assessment and quantitative synthesis. In the primary analysis, 21 studies provided data for measures of speed, and 19 studies provided data for measures of power using jump tests. Sprinting and jumping performance increased with advancing maturity status and overall effect sizes were predominantly moderate to large between maturity groups. Pre-PHV versus post-PHV comparisons found moderate to large overall effect sizes (ES) for sprinting performance (10-m ES 1.34 [95% CI 0.87-1.80]; 20-m ES 1.40 [95% CI 0.85-1.96]; and 30-m ES 0.93 [95% CI 0.15-1.76] sprint times) and large to very large ES for the jump tests (CMJ ES 1.53 [95% CI 1.14-1.92]; squat jump ES 1.32 [95% CI 0.70-1.94]; and standing long jump ES 2.18 [95% CI 1.32-3.04]). When comparing consecutive maturity groups (i.e. pre- to circa-PHV and circa- to post-PHV), ES were predominantly moderate across the sprinting and jumping measures, with only a trivial difference found in 30-m sprint time (ES 0.45 [95% CI 0.21-0.69]) for the circa- to post-PHV comparisons. Conclusion: Large differences exist in sprinting and jumping performance between the least and most mature male athletes (pre- and post-PHV), with trivial to moderate ES indicated between consecutive groups (e.g. pre- and circa-PHV). Practitioners working with youth athletes should consider how these differences may impact performance in the athlete's sport, and regularly assess individual maturity to accurately evaluate performance against age and maturity group benchmarks to account for large differences in maturity that exist within chronological age groups. It should be noted we observed inconsistencies in maturity thresholds and test methods; thus, standardization is required for future research

Job role clarity: A missing component of supply chain visibility

Purpose - The paper aims to develop a methodology for designing job roles with a core set of knowledge requirements, skill sets, and activities adaptable to different contexts, contributing to job role clarity as a dimension of supply chain visibility. Design/methodology/approach - The study undertook a multi-method approach, including an archival study of over a thousand job adverts, published professional recruitment documents, and qualitative analysis of expert focus groups. Detailed data coding was followed by applying ”Bloom’s taxonomy to establish strategic, tactical, and operational knowledge and skills requirements for indicative job roles. Findings - The developed methodology created a framework relating specified job role characteristics, detailing knowledge and activity requirements and training needs. With a core set of evolving identifiers, the job role enabled local adaptation to be accessible at various levels of local, national, and international markets. Research limitations/implications - The methodology was focused on the work of expert teams and would benefit from the addition of a data-driven component based on machine learning technologies. Practical implications - The 5-step methodological approach leads to a framework for determining job role requirements, applicable in different contexts and situations across a supply chain, using a standard template to enhance visibility to all participants. The framework reduces job ambiguity while contributing to supply chain visibility by clarifying job roles, and identifying requirements and training needs for each defined job role. Originality/value - The value gained from using the developed methodology is that SCM managers and departments can work closely with HR departments to understand the primary skills, knowledge gaps, and training necessities. The benefit is gained by the individual, the organisation, and the specific sector with comparable job roles to provide consistency for recruitment requirements, pay scales and remuneration, and training and education requirements across and between supply chains

Cyber-Biosecurity Challenges in Next-Generation Sequencing: A Comprehensive Analysis of Emerging Threat Vectors

Next-generation sequencing (NGS) has transformed genomic research and healthcare by enabling the rapid and cost-effective sequencing of DNA and RNA, surpassing traditional techniques such as Sanger sequencing. This technological leap has had a profound impact on fields including biomedical research, personalised medicine, cancer genomics, agriculture, and forensic sciences. With its widespread adoption, NGS has made genomic information more accessible, facilitating the sequencing of millions of genomes. However, the growing reliance on NGS has also brought significant challenges related to cyber-biosecurity, particularly the protection of genomic data against cyber threats such as unauthorised access, data breaches, and exploitation. Genomic data is inherently sensitive, and vulnerabilities in NGS technologies, software, data-sharing practices, and open-access databases expose it to risks concerning data confidentiality, integrity, and privacy. While NGS data plays an indispensable role across numerous sectors, research addressing the cyber-biosecurity of these technologies remains fragmented. Most existing studies focus narrowly on specific areas, such as microbial sequencing or system architecture, and fail to provide a holistic perspective on the security challenges that span the entire NGS workflow. Additionally, the lack of interdisciplinary collaboration between the biotechnology and cybersecurity communities further exacerbates these gaps. This paper seeks to bridge these gaps by thoroughly examining cyber-biosecurity threats throughout the NGS workflow. It introduces a tailored taxonomy specifically designed for NGS, aimed at increasing stakeholder awareness of potential vulnerabilities and threats. Key insights include identifying vulnerabilities at various stages of the NGS process - from data generation to analysis and storage - and categorising these threats systematically. The study highlights critical gaps in current research, underscoring the need for interdisciplinary collaboration between experts in biotechnology and cybersecurity. It calls for focused efforts to mitigate risks associated with unauthorised access, data misuse, and exploitation. Failure to address these vulnerabilities could result in severe consequences, such as breaches of medical confidentiality, ethical concerns, and the potential for misuse in malicious applications like genetic warfare or bioterrorism. By providing a comprehensive analysis, this paper advocates for intensified research efforts and collaborative strategies to protect genomic data and ensure its ethical and secure use