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This paper aims to explore current inconsistencies within the theoretical framework of current posttraumatic growth (PTG) literature in support of the suggestion for an alternative novel phenomenon labelled “post-adversarial appreciation”.

This re-conceptualisation has developed from the findings of empirical research conducted by the authors and their understanding of PTG.

Significant inconsistencies persist across the PTG literature in relation to the parameters required for PTG to manifest. It appears that PTG or an alternative concept labelled adversarial growth does take place following adverse/traumatic events, but that a separate phenomenon may better explain positive improvements in perceived personal appreciation during such events. This phenomenon is theorised by the authors as “post-adversarial appreciation”.

This paper suggests the existence of a novel phenomenon that may address many of the inconsistencies and present within the current PTG literature. This highlights a significant need for further research within the field of trauma and adversity in relation to positive outcomes which may result from such negative experiences.

This paper aims to demonstrate how and why holistic thinking mitigates the negative impact of large assortments on satisfaction.

Five between-subject experiments demonstrate the mitigating role of holism on choice overload across a variety of contexts.

While large assortments create overload feeling, holistic thinking mitigates the negative impact of overload feeling on satisfaction for both chronic (Studies 1a and 1b) and decision-specific (Studies 1b and 1c) holistic thinkers, as well as those who adopt a more holistic thinking style because of the decision goal (Study 2) or incidental priming (Study 3).

This paper introduces a new moderator of choice overload effects – holistic thinking – and shows how it mitigates the negative indirect effect of assortment size on satisfaction. This paper contributes to the literature on assortment size effects and shows that even when assortment size increases overload feeling, this negative impact of assortment size can still be reduced.

Marketers with large assortments can reduce the negative impact of overload feeling and increase satisfaction by promoting the hedonic features of the products and encouraging holistic thinking. Similarly, consumers can reduce the negative impact of overload feeling by approaching their consumption more holistically either because of their individual traits or situational factors.

This research contributes a new moderator to the choice overload literature: holistic thinking. In doing so, it adopts a broader consideration of the decision-making process underlying overload effects and pinpoints how (i.e. by which path) holistic thinking mitigates the negative impact of large assortments.

The purpose of this paper is to investigate the effect of response bias and target gender on detecting deception.

Participants were randomly assigned to one of three experimental conditions: a stereotype condition (bogus training group), a tell-signs condition (empirically tested cues), and a control condition. Participants were required to decide whether eight targets were lying or telling the truth, based upon the information they had been given. Accuracy was measured via a correct or incorrect response to the stimuli. The data were then analyzed using a 2×2×3 mixed analysis of variance (ANOVA) to determine whether any main or interactional effects were present.

Results revealed training condition had no significant effect on accuracy, nor was there a within-subject effect of gender. However, there was a significant main effect of accuracy in detecting truth or lies, and a significant interaction between target gender and detecting truth or lies.

Future research should seek a larger sample of participants with a more extensive training aspect developed into the study, as the brief training offered here may not be fully reflective of the extent and intensity of training which could be offered to professionals.

Within the criminal justice system, the need for increased accuracy in detecting deception is of critical importance; not only to detect whether a guilty individual is being deceitful, but also whether someone is making a false confession, both to improve community safety by detaining the correct perpetrator for the crime but also to maintain public trust in the justice system. The present research provides a fresh insight into the importance of training effects in detecting deception.

This paper aims to compare the use of technology in language institutes before and amid the COVID-19 pandemic. Then, the authors illustrate the legacies of the COVID-19 pandemic for language institutes from the managers’ perspective.

In the current study, the authors went through a systematic process of collecting qualitative data, discovering sub-categories, forming categories out of them and explaining the topic under investigation using selected categories.

The findings showed that the use of technology has dramatically changed from limited usage for administrative purposes and computer-assisted language learning to building the future of an institute based on online education. Also, the health and education pandemics had positive legacies for language education in making a decision to move to fully online education for having a more sustainable organization, solving the potential problems of an organization with collaboration and cooperation between the managers and employees based on integrity, developing teachers’ knowledge, literacy and skills which lead to the best practices in online language teaching and shifting to flexible schedule based on the students’ needs and timetable which increases the accessibility of language education.

Based on the review, none of the previous research focused on the critical role of managers in language institutes facing the pandemic. Thus, the relationship between managerial decisions in technology integration, readiness for transformation and moving to online language education is still vague.

With the advent of AI-federated technologies, it is feasible to perform complex tasks in industrial Internet of Things (IIoT) environment by enhancing throughput of the network and by reducing the latency of transmitted data. The communications in IIoT and Industry 4.0 requires handshaking of multiple technologies for supporting heterogeneous networks and diverse protocols. IIoT applications may gather and analyse sensor data, allowing operators to monitor and manage production systems, resulting in considerable performance gains in automated processes. All IIoT applications are responsible for generating a vast set of data based on diverse characteristics. To obtain an optimum throughput in an IIoT environment requires efficiently processing of IIoT applications over communication channels. Because computing resources in the IIoT are limited, equitable resource allocation with the least amount of delay is the need of the IIoT applications. Although some existing scheduling strategies address delay concerns, faster transmission of data and optimal throughput should also be addressed along with the handling of transmission delay. Hence, this study aims to focus on a fair mechanism to handle throughput, transmission delay and faster transmission of data. The proposed work provides a link-scheduling algorithm termed as delay-aware resource allocation that allocates computing resources to computational-sensitive tasks by reducing overall latency and by increasing the overall throughput of the network. First of all, a multi-hop delay model is developed with multistep delay prediction using AI-federated neural network long–short-term memory (LSTM), which serves as a foundation for future design. Then, link-scheduling algorithm is designed for data routing in an efficient manner. The extensive experimental results reveal that the average end-to-end delay by considering processing, propagation, queueing and transmission delays is minimized with the proposed strategy. Experiments show that advances in machine learning have led to developing a smart, collaborative link scheduling algorithm for fairness-driven resource allocation with minimal delay and optimal throughput. The prediction performance of AI-federated LSTM is compared with the existing approaches and it outperforms over other techniques by achieving 98.2% accuracy.

With an increase of IoT devices, the demand for more IoT gateways has increased, which increases the cost of network infrastructure. As a result, the proposed system uses low-cost intermediate gateways in this study. Each gateway may use a different communication technology for data transmission within an IoT network. As a result, gateways are heterogeneous, with hardware support limited to the technologies associated with the wireless sensor networks. Data communication fairness at each gateway is achieved in an IoT network by considering dynamic IoT traffic and link-scheduling problems to achieve effective resource allocation in an IoT network. The two-phased solution is provided to solve these problems for improved data communication in heterogeneous networks achieving fairness. In the first phase, traffic is predicted using the LSTM network model to predict the dynamic traffic. In the second phase, efficient link selection per technology and link scheduling are achieved based on predicted load, the distance between gateways, link capacity and time required as per different technologies supported such as Bluetooth, Wi-Fi and Zigbee. It enhances data transmission fairness for all gateways, resulting in more data transmission achieving maximum throughput. Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation.

Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation. It also shows that AI- and IoT-federated devices can communicate seamlessly over IoT networks in Industry 4.0.

The concept is a part of the original research work and can be adopted by Industry 4.0 for easy and seamless connectivity of AI and IoT-federated devices.

The research questions probe into the heart of participatory learning’s scholarly landscape. They inquire about historical trends, shifts in research interest, and regional contributions, highlighting the global reach of participatory learning discourse. The study also reaches into the most cited papers, emphasizing their pivotal role in shaping the field’s trajectory.

The research design of our study involves a retrospective analysis focused on the topic of participatory learning in education. A retrospective analysis is a methodological approach that entails examining existing literature, data, and publications within a specific field to identify trends, patterns, and insights over a defined period. In the context of participatory learning in education, this research design allows us to gain a comprehensive understanding of the evolution, contributions, and emerging directions within this pedagogical approach.

The culmination of this study lies in formulating 75 thought-provoking future research questions. These questions are designed to guide the future trajectory of participatory learning research, addressing existing gaps and propelling the field toward new horizons. The findings of the study contribute to a panoramic view of participatory learning’s evolution, global impact, and potential for reshaping education. It is a compass for researchers, educators, and policymakers navigating the intricate landscape of participatory learning in education.

Themes and topics are thoroughly explored, unrevealed the multidimensional nature of participatory learning research. The investigation spans time, revealing enduring themes while unveiling emerging areas of inquiry that capture the attention of researchers and practitioners. Current trends and focus areas are scrutinized, offering insights into the ever-evolving scholarly pursuits within participatory learning.

This comprehensive study investigates the evolution and impact of research on participatory learning in education from 1995 to 2023. The research objectives encompass a broad spectrum, including trend analysis, geographical distribution assessment and identification of influential papers, thematic exploration, and the formulation of future research questions. Through a meticulous examination of published literature, this study aims to shed light on the development of participatory learning as a transformative educational approach.

This study’s originality lies in its comprehensive analysis of participatory learning in education from 1995 to 2023, revealing temporal trends, global contributions, influential papers, thematic nuances, and emerging trends. By amalgamating these dimensions, it offers a holistic view of participatory learning’s evolution, impact, and future directions, enriching the understanding of this transformative educational approach and guiding further research and practice.

The Triarchic Psychopathy Measure (Tri-PM) was developed in 2010 as an alternative approach to the assessment of psychopathy. The measure aims to capture psychopathic traits on a 3-factor model, which encompass the characteristics established in previous measures, as well as those evidenced within practise. Though support for the tool in academic research is growing, less is known about the scale’s utility within crime forensic settings. Thus, this study aims to explore the relationship between the Tri-PM psychopathy constructs and criminal cognition within a forensic sample.

Seventy-three adult male offenders, convicted for acquisitive or sexual crimes, from a Category B prison within the Northwest of England completed questionnaires measuring their criminal backgrounds, psychopathy traits (Tri-PM; Patrick, 2010) and criminal thinking styles (Psychology Inventory of Criminal Thinking Styles; Walters, 2001).

The Tri-PM measurement proved to be a successful predictor of most criminal thinking styles. Moreover, the meanness construct was the strongest predictor of proactive thinking styles, whereas the disinhibition construct was the strongest predictor of reactive thinking styles, and the boldness construct was negatively associated with reactive thinking. Comparisons among offender groups also indicated that acquisitive offenders reported higher scores of psychopathy and criminal thinking.

This study offers valuable insight into the proposed relationship between psychopathy and criminal thinking, using a recent addition to the repertoire of psychopathy measurements, the Tri-PM. This study also offers practical implications for those offering treatment within forensic settings, with significant relationships identified between the highly scoring psychopathy constructs and various criminal thinking styles.

The US fossil fuel industry is vulnerable to opposition from other sectors of the ruling class. Non-fossil fuel capitalists might conclude that climate breakdown jeopardizes their interests. State actors such as judges, regulators, and politicians may come to the same conclusion. However, these other elite actors are unlikely to take concerted collective action against fossil fuels in the absence of growing disruption by grassroots activists. Drawing from the history of the Obama, Trump, and Biden presidencies, I analyze the forces determining government climate policies and private-sector investments. I focus on how the climate and Indigenous movements have begun to force changes in the behavior of certain ruling-class interests. Of particular importance is these movements' progress in two areas: eroding the financial sector's willingness to fund and insure fossil fuels, and influencing judges and regulators to take actions that further undermine investors' confidence in fossil fuels. Our future hinges largely on whether the movements can build on these victories while expanding their base within labor unions and other strategically positioned sectors.

This research paper aimed to investigate the affordances of using virtual reality (VR) in teaching culture among in-service teachers of teaching Persian to speakers of other languages (TPSOL) in Iran.

This qualitative case study, conducted at two Iranian universities, used purposeful sampling to select 34 eligible in-service Persian teachers from a pool of 73. Data collection used an open-ended questionnaire and interviews.

Before the TPSOL in-service training workshop, teachers expressed their reservations regarding the use of VR to teach culture in TPSOL courses. The emerged themes were “skepticism toward effectiveness,” “practicality concerns,” “limited awareness of VR applications,” “technological apprehension” and “prevalence of traditional teaching paradigms.” During the post-workshop interview, it was discovered that the teachers’ perceptions of VR in teaching culture had undergone a positive shift. The workshop generated emergent themes that reflected positive perceptions and affordances for using VR to teach culture in TPSOL, including “enhanced cultural immersion,” “increased student engagement,” “simulation of authentic cultural experiences,” and “facilitation of interactive learning environments.”

One primary limitation is the lack of prior experience with VR for teaching practices in real-world classrooms among the participants. While the study aimed to explore the potential of VR in enhancing pedagogical approaches, the absence of participants with prior exposure to VR in educational contexts may impact the generalizability of the findings to a broader population. Additionally, the study faced practical constraints, such as the unavailability of sufficient facilities in the workshop. As a result, the instructor had to project the VR cont7ent on a monitor, potentially diverging from the immersive nature of true VR experiences. These limitations offer opportunities for future research to refine methodologies and gain a more comprehensive understanding of the implications of integrating VR into teaching practices.

Extensive research has been conducted on the effectiveness of VR in language education. However, there is a significant gap in research on TPSOL, which is considered a less commonly taught language. This study aims to address this gap by exploring the use of VR in the TPSOL through the lenses of in-service teachers. As part of a larger investigation, this qualitative inquiry focuses on the perceptions of in-service teachers about VR, with a particular emphasis on the cultural understanding of the Persian language.

This study aims to examine whether country of residence, sex trafficking attitudes, complainant gender, juror gender and right-wing authoritarianism (RWA) influenced juror decision-making within a sex trafficking case.

Jury-eligible participants from the USA and the UK participated in an online juror experiment in which an independent group design was used to manipulate the complainant’s gender. Participants completed the juror decision scale, the sex trafficking attitudes scale and the RWA scale.

Sex trafficking attitudes predicted the believability of both the defendant and complainant. Greater negative beliefs about victims predicted greater defendant believability and lower complainant believability. US jurors reported greater believability of both the complainant and defendant, and RWA was associated with greater defendant believability. However, none of the other factors, including complainant and juror gender, predicted participants’ verdicts. The findings suggest juror verdicts in sex trafficking cases may be less influenced by extra-legal factors, although further research is needed, especially with a more ambiguous case.

This is one of the few cross-cultural comparison studies in the area of jury decision-making, specifically regarding sex trafficking cases. The findings indicated that US participants held more problematic attitudes about sex trafficking than their UK counterparts, although all participants held problematic attitudes about sex trafficking. However, those attitudes did not affect verdict formation about either a male or female complainant. Participants who were more knowledgeable about sex trafficking reported greater complainant believability, suggesting that educational interventions may provide greater support for victims in court.