12560 research outputs found
Sort by
Health psychology's role within the biopsychosocial sciences
Get PDFThis chapter focuses on understanding health psychology in the wider system. The main aim is to show the interdisciplinary reach of health psychology and to highlight the importance of interconnectivity and collaborative working. Initially, synergies and differences between health psychology and other practitioner psychology branches will be discussed. The chapter will then focus outwards on the connection of health psychology with the biopsychosocial sciences. A particular focus will be made on behavioural, social, and medical sciences. The chapter will conclude with a discussion on the role health psychology plays and could play in multi-, inter-, and transdisciplinary teams
Blessing or curse? A critical review of the paradoxical consequences of direct public funding for political parties
No full textDirect public funding (DPF) is a crucial resource for political parties in many of the world’s democracies. While research into the consequences of DPF has grown in prominence since the turn of the century, few efforts have been made to synthesize its findings. This article takes the first steps in doing so. Viewing DPF as an independent variable, we assess the impacts that party subsidization has on electoral competition, party organizations, party system development, and gender representation, before unpacking the intricacies of the DPF-corruption relationship. Given the inconclusive findings across these domains, the article discusses methodological challenges related to data availability and DPF operationalization, concluding with brief policy recommendations and several avenues for future research.</p
Better – problematically – together: the merits and challenges of inter-institutional evaluation collaborations
No full textBetter – problematically – together: the merits and challenges of inter-institutional evaluation collaborations
No full textCompact artificial neural network models for predicting protein residue - RNA base binding
No full textLarge Artificial Neural Network (ANN) models have demonstrated success in various domains, including general text and image generation, drug discovery, and protein-RNA (ribonucleic acid) binding tasks. However, these models typically demand substantial computational resources, time, and data for effective training. Given that such extensive resources are often inaccessible to many researchers and that life sciences data sets are frequently limited, we investigated whether small ANN models could achieve acceptable accuracy in protein-RNA prediction. We experimented with shallow feed-forward ANNs comprising two hidden layers and various non-linearities. These models did not utilize explicit structural information; instead, a sliding window approach was employed to implicitly consider the context of neighboring residues and bases. We explored different training techniques to address the issue of highly unbalanced data. Among the seven most popular non-linearities for feed-forward ANNs, only three—Rectified Linear Unit (ReLU), Gated Linear Unit (GLU), and Hyperbolic Tangent (Tanh)—yielded converging models. Common re-balancing techniques, such as under- and over-sampling of training sets, proved ineffective, whereas increasing the volume of training data and using model ensembles significantly improved performance. The optimal context window size, balancing both false negative and false positive errors, was found to be approximately 30 residues and bases. Our findings indicate that high-accuracy protein-RNA binding prediction is achievable using computing hardware accessible to most educational and research institutions.</p
Mapping writing revisions through keystroke logging:a methods-based approach
No full textThis book presents Keystroke Logging as a powerful methodological tool for investigating writers’ revision processes in writing. The volume demonstrates the ways in which Keystroke Logging can be used to observe, record, and analyse writing revisions in real time, especially useful given the growing use of computer-facilitated academic writing. Drawing on an integrated approach implementing both real-time observation and immediate stimulated recall, Anbreen seeks to bridge the gap between theory and practice by bringing together theoretical understandings of writing revisions with practical applications of Keystroke Logging. The work makes the case for the use of Keystroke Logging in computer-based writing research to better elucidate the cognitive processes L2 writers engage in during the revision process. This book will be of interest to students, scholars, and relevant stakeholders in applied linguistics, second language writing, academic writing, language learning and teaching, and educational technology.</p
Academic literacies: learning developers’ perspectives on informing the curriculum
Get PDFThis paper sets out the findings of a research project that explores how learning developers (LDers) translate academic literacies (AL) into practice for student learning (Lea and Street, 1998; Hilsdon, 2011; Hilsdon et al., 2019; Bassett and McNaught, 2024) through curriculum design and content creation. The findings reveal varied practice informed by each LDer’s theoretical foundations, wider debates within learning development, and local conditions within each participant’s university.A key emergent theme is that participants seek to influence the design of new and existing curriculum and resources by actively reaching out to colleagues, often from the ‘ground up’. Through interactions of sharing, persuasion, and collaboration, LDers are attempting to integrate multiple forms of academic knowledge and skills into wide-ranging courses so all students can fully participate and succeed in their disciplines. However, the participants’ reflections reveal structural and individual factors within higher education that manifest as challenges and affordances for informing curricula, content, and resources. The research reveals some unexpected results about how LDers engage with AL in their own practice and their relationships with discipline-based colleagues to promote and develop inclusive curricula (OfS, 2024).This paper uses the words of LDers across multiple disciplines and universities to share insights into how we seek to influence accessibility, equity, and inclusivity throughout students’ learning journeys. Participants will be invited to reflect on the findings and consider how they might inform their own strategies for their contexts
Advancing sustainable development in Jordan:a business and economic analysis of electric vehicle adoption in the transportation sector
Get PDFThis study explores electric vehicle (EV) adoption in Jordan, focusing on key transitional factors. It examines government policies, market dynamics, technological advancements, and infrastructure development through semi-structured interviews with key stakeholders, including government officials, industry experts, and consumers. The study provides insights into the economic prospects, infrastructure requirements, and regulatory measures necessary for widespread EV adoption. Government incentives, such as tax exemptions and reduced registration fees, are crucial, but challenges like insufficient charging infrastructure, high initial costs, and limited public awareness persist. Collaborative efforts between the public and private sectors are essential to develop resilient infrastructure, enhance consumer education, and foster technological innovation. The findings underscore the importance of government incentives and coordinated efforts to develop charging infrastructure and raise public awareness. Future research should focus on quantitative methods to validate these findings and explore additional strategies to overcome identified barriers.</p
Is AI-powered education sustainable and marketable in UK higher education? exploring opportunities and challenges in assessment through the lenses of staff and students
No full textPurpose: This study explored the sustainability of AI-powered education in UK higher education, with a focus on its implications for assessment practices. It aimed to identify the benefits and challenges associated with integrating AI technology. Methodology: A qualitative research approach was employed, utilizing eight focus group interviews conducted with academic staff and students from two UK universities and their overseas partner institutions. The study analyzed perspectives to assess the impact of AI on teaching and assessment. Findings: The research identified significant challenges, including concerns over academic integrity, biases in AI algorithms, and the need for staff and student upskilling. However, it also highlighted opportunities such as simplified assessment workflows, improved feedback quality, and increased inclusivity through adaptive technologies. Key themes included AI usage in assessments, authenticity of AI-driven assessments, and ethical considerations. Practical Implications: The findings suggested that while AI enhanced efficiency in educational practices, its integration required careful consideration of ethical and pedagogical standards. Recommendations included developing policies and training programs to support sustainable and inclusive AI practices in higher education. Originality: This study contributed to the discourse on the future of education in an AI-driven world, emphasizing the balance between leveraging technological advancements and maintaining ethical practices. It outlined specific challenges and advantages in the context of AI’s role in assessment and educational marketing.</p
An exploration of the relationship between ineffective modes of mentalization and difficulties related to borderline personality disorder: a network approach
Get PDFBackground: The mentalization-based perspective of Borderline Personality Disorder (BPD) underscores fluctuating interpersonal functionality, believed to arise from suboptimal mentalization modes, including hyper- and hypomentalizing. The connection between ineffective mentalizing and specific BPD challenges remains ambiguous. Network theory offers a unique means to investigate the hypothesis that distinct yet interconnected mental challenges (‘symptoms’) construct ‘disorders’ through their continuous mutual interactions. This study aimed to probe the pairwise interrelations between ineffective mentalizing and BPD challenges and to distinguish these relations between individuals with (clinical group) and without (community group) a BPD diagnosis using a network analysis approach. Methods: Through a cross-sectional secondary data analysis, a moderated Mixed Graphical Model was employed on data from 575 individuals (350 clinical, 225 community). The study evaluated associations between ineffective mentalization modes (hypermentalization, hypomentalization, and no mentalization) gauged by the MASC and self-reported BPD-associated challenges, using BPD diagnosis as the moderating variable. Results: The analysis confirmed the presence of significant links between ineffective mentalizing and specific interpersonal BPD challenges, which were moderated by BPD diagnosis. It implied that hypermentalization and hypomentalization might simultaneously shape BPD-associated challenges. Conclusions: The results offer fresh insights into the interplay between hypermentalization, hypomentalization, and BPD-related difficulties
Data sources:
Access Repository Dashboard
Do you manage University of Bedfordshire Repository? Access insider analytics, issue reports and manage access to outputs from your repository in the CORE Repository Dashboard!