Student communications: a review of current practices and scoping a new vision

Student communications has developed as a professional field in universities in recent decades, as universities seek to more strategically engage diverse student populations with ever-changing expectations and needs. Whilst most universities now have some form of function or resourcing dedicated to considering how to best communicate with current students, there is minimal research exploring the priorities of these functions. This article takes a narrative review of practice approach, critiquing and highlighting the student communications practices of 17 universities around the world. The review thematically grouped the efforts of these institutions, finding that the main activities of student communications functions are: (1) implementing structures, strategic frameworks and policies (2) creation of campaigns to build campus pride and belonging (3) development of channels to better inform students about support and opportunities (4) evaluate students’ engagement, satisfaction and trust with their institution. Following the review of current practice, this article identifies gaps that should be addressed to enhance student communications functions, as well as principles that student communicators should adopt to gain legitimacy in their work

'Understanding domestic violence and abuse: victim, suspect and crime predictors of police outcomes'

Purpose: Domestic violence and abuse (DVA) cases remain under-reported and under-prosecuted in the criminal justice system (CJS), with researchers frequently having limited access to raw police data. Here, a range of factors relating to DVA offences occurring between 2018 and 2020 in one large English police force were described and measured. As part of the research, it was investigated if victim and suspect characteristics predicted outcome decisions, specifically charge rate, case attrition, and evidential difficulties despite victims’ support in pursuing the allegations. The number of offences meeting the DVA legal definition, and those falling outside that definition, were also explored. Methods: Univariate and multivariate logistic regressions were performed to predict the relationship between demographic information and criminal history on three coded crime outcome categories (namely, ‘charge’, ‘victim does not proceed’, and ‘law does not pursue’). Results: The dataset included 198,617 crimes, and for 94.1% of them, the suspect was not charged. Relationship type, age, crime type, and the number of victim allegations predicted all three outcomes. For instance, being partners of the victim significantly decreased the chances of a charge compared to suspects who were not partners. Conclusions: The findings are in line with evidence from the literature which highlights all-time low charge rates for DVA and high levels of victim attrition. We argue that the influence of victim/suspect characteristics and DVA-related dynamics should be considered by police personnel and members of the CJS when assessing crime reports

Signature-based security analysis and detection of IoT threats in advanced message queuing protocol

The Advanced Message Queuing Protocol (AMQP) is a widely used communication standard in IoT systems due to its robust and reliable message delivery capabilities. However, its increasing adoption has made it a target for various cyber threats, including Distributed Denial of Service (DDoS), Man-in-the-Middle (MitM), and brute force attacks. This study presents a comprehensive analysis of AMQP-specific vulnerabilities and introduces a statistical model for the detection and classification of malicious activities in IoT networks. Leveraging a custom-designed IoT testbed, realistic attack scenarios were simulated, and a dataset encompassing normal, malicious, and mixed traffic was generated. Unique attack signatures were identified and validated through repeated experiments, forming the foundation of a signature-based detection mechanism tailored for AMQP networks. The proposed model demonstrated high accuracy in detecting and classifying attack-specific traffic while maintaining a low false positive rate for benign traffic. Notable results include effective detection of RST packets in DDoS scenarios, precise classification of MitM attack patterns, and identification of brute force attempts on AMQP systems. This research highlights the efficacy of signature-based approaches in enhancing IoT security and offers a benchmark for future machine learning-driven detection systems. By addressing AMQP-specific challenges, the study contributes to the development of resilient and secure IoT ecosystems

The solar shading performance of the multi-angled façade system and its impact on the sustainable improvement of the buildings

This research paper explores the visual potential of the multi-angled façade system, allowing office employees to achieve optimal exposure to the external environment through the room façade. This contributes to sustainability objectives by enhancing indoor climate quality, promoting health and well-being, and aligning with the UN Sustainable Development Goals 3, 9, and 11. This façade concept provides a solution to the issue of shading devices being fully closed for long periods due to intense solar radiation on the room’s window. The concept of a multi-angled window involves incorporating two differently oriented window sections within each façade along a vertical axis (right and left), rather than tilting them upward or downward. The larger section is oriented more toward the north to maximize daylight access and external views, while the smaller section faces south to enhance passive solar heating. The visual potential is assessed based on the periods when the solar shading devices are not fully closed—meaning one section of the multi-angled façade may remain open while the other is shaded. To evaluate this, along with the resulting energy consumption and indoor climate, the software program IDA ICE version 4.8 is utilized. Simulation results indicate that the duration of complete shading closure is significantly lower for a multi-angled façade compared to a flat façade, in some instances nearly half, thereby improving visual comfort, daylight availability, and heat gain while simultaneously reducing spatial energy consumption

Understanding the factors and consequences of student belonging in higher education: a critical literature review

Student belonging is becoming an increasingly prominent concept in how universities pursue policies and practices to ensure student success. Through this increased prevalence, there has been a substantial increase in research output on this topic in recent years. This critical literature review aims to provide a comprehensive and accessible synthesis of research around the factors that affect student belonging and how it links to student success. Utilising a systematised search and appraisal method, 118 studies were included and reviewed. The existing literature has robustly shown the connections between belonging and many different aspects of student success – including student engagement levels, wellbeing, and retention. Critical analysis of the studies shows that the factors affecting student belonging are also multiple, although only some – such as experiential pedagogies and personalised support from staff – have been replicated in studies across multiple contexts and with experimental research methods. Importantly, there are also factors which negatively impact students’ sense of belonging – such as experiences of being stereotyped by staff. Utilising these findings around factors that influence student belonging, this article provides a set of recommendations for practitioners and identified gaps for future research on student belonging. Overall, this article contributes to understandings of how to impact students’ sense of belonging and how this links to student success

The phenomenology of intelligences – connecting personal flexibility with corporate agility in complexity

This thesis is the unfolding of an inner dance that explores the evolution of physical intelligence as a vital component in understanding and developing leadership agility within complex organisational environments. Through an autoethnographic examination of three public works spanning two decades — a model for embodied leadership, a book on physical intelligence, and a digital cluster of educational works — the research investigates how embodied understanding of movement (patterns, rhythms, behavioural intentions and neurochemistry) can transform approaches to personal and cultural change. The investigation centres on the premise that contemporary leadership development requires a fundamental re-integration of physical intelligence with cognitive and emotional intelligences to meet the challenges of accelerating change and growing complexity. Drawing upon transdisciplinary perspectives including dance, neuroscience, phenomenology, and organisational development, the study reveals how conscious attention to embodiment and the lived experience of science can create new possibilities for organisational transformation. The methodological approach combines reflective practice with participatory observation, incorporating movement analysis techniques adapted from contemporary dance and somatic practices. Through analysis of case studies and personal experiences in both artistic and business contexts, the research documents the transformation of abstract movement concepts into practical applications for leadership development. This translation process demonstrates how movement-based understanding can enhance leadership practices and team and organisational dynamics. The findings establish several key insights about the nature of leadership agility. First, the research demonstrates that organisational cultures embody specific movement patterns that can either facilitate or inhibit change. Second, it reveals how conscious attention to these patterns and their neurophysiology through physical intelligence can create new possibilities for organisational transformation and a different behavioural neuroscience. Third, it illustrates how principles of movement can be effectively translated into business language and practice, creating a bridge between embodied knowledge and organisational strategy. The thesis introduces new theoretical frameworks including Neurophysiological Phenomenology and Expanded Leadership Intelligence (ELI) which integrate scientific understanding with lived experience. These frameworks provide practical tools for leaders to work with organisational dynamics using movement-based principles. The research also establishes new vocabulary for discussing organisational change that integrates embodied knowledge with traditional business concepts. The outcomes of this research have significant implications for leadership development, organisational change management, and cultural transformation initiatives. The study demonstrates how movement-aware approaches can enhance organisational adaptability, improve team coordination, and facilitate more effective cultural change processes. Future research directions include further investigating the role of neurochemical sequencing in leadership development, exploring the relationship between physical intelligence and artificial intelligence in organisational settings, and examining how embodied practices might accelerate the evolution of human consciousness in response to increasing global complexity. The findings also suggest practical applications for leadership education, including the further development of movement-based assessment tools, the integration of somatic practices into executive training programmes, and the wider application of standardised physical intelligence methodologies for coaching and organisational development. Through this exploration of the inner dance of organisational life, the thesis ultimately presents a new paradigm for understanding and working with cultural change in business contexts. It challenges traditional mechanistic approaches to organisational development and offers instead an organic, movement-based framework that acknowledges the dynamic, embodied nature of organisational culture and change. The research concludes by proposing that intentional resequencing of neurochemistry through embodied practice may contribute to a more positive direction for accelerated human evolution, particularly in terms of developing the flexibility and agility needed to navigate increasing complexity. Rather than treating science and culture as equal and opposite, ranged on either side of an arbitrary division between space and place, and between reason and tradition, a better way forward – I suggest – would be to acknowledge that scientific knowledge as much as the knowledge of inhabitants, is generated within the practices of wayfaring. For scientists are people too and inhabit the same world as the rest of us. (Ingold, 2022, p.189

AI intelligent tutoring system tailored to the students’ personality and neurodiversity

Over the past few years, several Universities and Educational Institutes have introduced e-learning platforms to support robust alternatives to face-to-face teaching, where students can benefit from them by revisiting topics covered in class without the constraints of time and space. However, despite this considerable flexibility, the role of the instructor as a facilitator is crucial to support learners when they have doubts on their learning or get stuck, by encouraging them to consider suitable strategies to approach the problem, or by providing clarification on some organisational aspects of the module. Providing quality feedback that is tailored to the individual needs of each learner, including personality and neurodiversity, is a challenging task for educators. Developing different methods of learner-specific feedback increases the workload and often fails to fully address learning gaps. The lecturer's empathy, which consists of a deep understanding of students' personal and social situations, care and concern for students' emotions, and compassionate responses, also poses a critical role in student success. Several intelligent tutoring systems have been implemented in e-learning platforms to try to provide immediate feedback to support students, but they focus more on providing feedback on content and often don't tailor feedback with adaptive empathy based on different students' personalities or neurodiversity. In this paper, an AI intelligent tutoring system based on LLM has been implemented within an e-learning platform, fine-tuned to the content and organisational aspects of the final year project module in the IT programme, with the aim of providing immediate feedback based on students’ requests. The software can tailor comments to each student's personality and, where appropriate, neurodiversity, for example, showing genuine interest in responses from introverts or paraphrasing content to improve written comprehension for dyslexics. The neurodiversity information was taken from the user's profile, while personality was extracted using the MBTI (Myers-Briggs Type Indicator). Finally, the software was tested using a bespoke algorithm consisting in a matchmaking process able to detect the level of communication strategies (empathy, creativity, sensitivity) by cross matching the responses received with open online dictionaries to evaluate the effectiveness of the tailored responses

The deceleration paradox: the faster you run the slower you stop

This study examined the effect of approach momentum on horizontal deceleration (DEC) performance. Eighty team sports athletes performed three maximal horizontal DEC trials from a 15 m approach. Sprint performance was recorded using timing gates and instantaneous velocity was collected using a radar device. Correlation and multiple regression analysis were conducted to analyze the relationships between DEC-related variables. Between-subject (top 50% vs. bottom 50%) differences in DEC-related variables were also determined. Greater mean DEC was significantly correlated with lower approach momentum (r = -0.354, p = 0.001). Compared to lower DEC performers (in terms of mean and peak values), greater performers showed statistically significantly lower peak approach velocity (ES = 0.41-0.66, p < 0.05) and lower peak approach momentum (ES = 0.48-0.60, p < 0.05). Furthermore, the standardized Beta values of the multiple regression analysis demonstrated that body mass is a greater determinant of DEC performance compared to approach velocity. In conclusion, practitioners should be aware that approach momentum (body mass and approach velocity) is a factor influencing DEC performance, and an inverse relationship exists. Thus, to evaluate maximal DEC ability, approach velocity and body mass must be considered

Ensuring culturally competent nursing care for LGBT+ people

People who are lesbian, gay, bisexual, transgender and other sexual and gender minorities (LGBT+) can encounter various challenges when seeking healthcare. For example, many LGBT+ individuals experience discrimination and social stigma from healthcare professionals, leading to feelings of mistrust. This might manifest as explicit homophobia or transphobia, inappropriate questioning, or a lack of consideration for the sensitivities around LGBT+ identities. Similarly, healthcare organisations may have policies that lack inclusivity, with administrative forms and procedures that do not consider diverse sexual orientations and gender identities. Nurses are increasingly recognising the importance of providing inclusive care for individuals who identify as LGBT+, which involves being attentive to their specific needs. This article examines the barriers that may be encountered by LGBT+ individuals in healthcare services and offers recommendations for how nurses can deliver culturally sensitive healthcare to the LGBT+ community

Pre-service teachers and public speaking anxiety. Insights and possible interventions through AI and IoT

Public speaking is an essential skill for pre-service teachers as it plays a critical role in both professional success and the teaching-learning process. Despite its importance, many individuals, particularly students, experience public speaking anxiety, which can affect their performance. This paper explores the intersection of self-assessed public speaking anxiety levels and biometric data collected through stress tracker devices and AI-based emotion detection tools, aiming to investigate students’ awareness of their anxiety during public speaking. Data were collected from 257 students enrolled in a first-year course at the University of Macerata (2023/24). Students were asked to complete a survey and give an oral presentation in groups. A subset of 25 student responses were compared with biometric data, including heart rate measurements and data obtained by an AI emotion recognition system. Cross-referencing self-reported anxiety levels with heart rate data showed varying degrees of convergence, suggesting that students often misperceived their emotional state. In some cases, their self-assessments did not align with the biometric indicators of stress, suggesting a lack of self-awareness regarding their anxiety levels. These findings highlight the potential for AI and IoT technologies to provide useful data that can help teachers identify and support students who are not aware of their emotional state and who also have anxiety management issues. By incorporating these tools, university teachers can develop optimized and tailored interventions aimed at improving students’ public speaking skills and emotional regulation. Further research should explore the effectiveness of these tools across different courses and sample sizes