Psycho-Education with Asylum Seekers and Survivors of Torture

This article examines psycho-educational programmes for asylum-seekers and tortured refugees at the Danish Red Cross Asylum Department and Rehabilitation and Research Centre for Torture victims respectively. The psycho-education programme is based on a cognitive theoretical framework. However, it is argued that the processes observed during the programmes and the changes in the participants’ lives may be conjointly understood within theoretical frameworks of narrative therapy, social constructionism, and community psychology, emphasizing professionals’ and participants’ co-construction of alternative stories and action possibilities, and the importance of the context and social network outside the intervention context.

Racial and Ethnic Heterogeneity in the Effect of MESA on AP STEM Coursework and College STEM Major Aspirations

Previous research suggests that racial and ethnic disparities in postsecondary STEM outcomes are rooted much earlier in the educational pipeline. One possible remedy to these disparities is participation in early STEM enrichment programs. We examine the impact of MESA, which is an early program that targets socioeconomically disadvantaged students, on outcomes that may lead students down the path to STEM. We analyze three waves of restricted nationally-representative data from the High School Longitudinal Study that trace the STEM progress of more than 25,000 students throughout high school and into their postsecondary careers. Propensity score matching models reveal that MESA participation increases students’ odds of taking AP STEM courses in high school and their aspirations for declaring a STEM major in college. However, these effects are driven primarily by black and white students, respectively. Latino and Asian students remain largely unaffected. A formal sensitivity analysis concludes that these findings are moderately robust to unobserved confounding. The results are also robust to alternative matching schemes. Collectively, the findings suggest that MESA may improve black students’ high school STEM engagement but may have little impact on black and Latino students’ STEM outcomes in college.     

Urinary Urea,Uric Acid and Hippuric Acid as Potential Biomarkers in Multiple Sclerosis Patients

Urine is a proven source of metabolite biomarkers and has the potential to be a rapid, noninvasive, inexpensive, and efficient diagnostic tool for various human diseases. Despite these advantages, urine is an under-investigated source of biomarkers for multiple sclerosis (MS). The objective was to investigate the level of some urinary metabolites (urea, uric acid and hippuric acid) in patients with MS and correlate their levels to the severity of the disease, MS subtypes and MS treatment. The urine samples were collected from 73 MS patients-48 with RRMS and 25 with SPMS- and age matched 75 healthy controls. The values of urinary urea, uric acid and hippuric acid in MS patients were significantly decreased, and these metabolites in SPMS pattern showed significantly decrease than RRMS pattern. Also showed significant inverse correlation with expanded disability status scale and number of relapses. Accordingly, they may act as a potential urinary biomarkers for MS, and correlate to disease progression.     

Pedagogical possibilities for unruly bodies

Project Re?Vision uses disability arts to disrupt stereotypical understandings of disability and difference that create barriers to healthcare. In this paper, we examine how digital stories produced through Re?Vision disrupt biopedagogies by working as body-becoming pedagogies to create non-didactic possibilities for living in/with difference. We engage in meaning making about eight stories made by women and trans people living with disabilities and differences, with our interpretations guided by the following considerations: what these stories ‘teach’ about new ways of living with disability; how these stories resist neoliberalism through their production of new possibilities for living; how digital stories wrestle with representing disability in a culture in which disabled bodies are on display or hidden away; how vulnerability and receptivity become ‘conditions of possibility’ for the embodiments represented in digital stories; and how curatorial practice allows disability-identified artists to explore possibilities of ‘looking back’ at ableist gazes.     

Institutional attention to European policy agendas: exploring the relevance of instrumental and neo-institutional explanations

This article addresses how European policy initiatives in higher education, research and innovation are diffused in the European higher education research and education area. Based on an instrumental and an institutional perspective, specific expectations are developed as to how policy diffusion might unfold, and, through an in-depth analysis of the strategic plans of 19 higher education institutions in Latvia and Norway, the article identifies factors that potentially mediate European policies into the strategic agenda of universities and colleges. The findings show that European Union membership and policy area seems to matter for the attention given to European policy initiatives, while administrative capacity at institutional level have less or quite mixed effects. The article concludes that both instrumental and institutional perspectives are of value in explaining how European policy diffusion takes place.

     

Using natural language processing to support peer-feedback in the age of artificial intelligence: A cross-disciplinary framework and a research agenda

Advancements in artificial intelligence are rapidly increasing. The new-generation large language models, such as ChatGPT and GPT-4, bear the potential to transform educational approaches, such as peer-feedback. To investigate peer-feedback at the intersection of natural language processing (NLP) and educational research, this paper suggests a cross-disciplinary framework that aims to facilitate the development of NLP-based adaptive measures for supporting peer-feedback processes in digital learning environments. To conceptualize this process, we introduce a peer-feedback process model, which describes learners' activities and textual products. Further, we introduce a terminological and procedural scheme that facilitates systematically deriving measures to foster the peer-feedback process and how NLP may enhance the adaptivity of such learning support. Building on prior research on education and NLP, we apply this scheme to all learner activities of the peer-feedback process model to exemplify a range of NLP-based adaptive support measures. We also discuss the current challenges and suggest directions for future cross-disciplinary research on the effectiveness and other dimensions of NLP-based adaptive support for peer-feedback. Building on our suggested framework, future research and collaborations at the intersection of education and NLP can innovate peer-feedback in digital learning environments.

Practitioner notes

What is already known about this topic

• There is considerable research in educational science on peer-feedback processes.
• Natural language processing facilitates the analysis of students' textual data.
• There is a lack of systematic orientation regarding which NLP techniques can be applied to which data to effectively support the peer-feedback process.

What this paper adds

• A comprehensive overview model that describes the relevant activities and products in the peer-feedback process.
• A terminological and procedural scheme for designing NLP-based adaptive support measures.
• An application of this scheme to the peer-feedback process results in exemplifying the use cases of how NLP may be employed to support each learner activity during peer-feedback.

Implications for practice and/or policy

• To boost the effectiveness of their peer-feedback scenarios, instructors and instructional designers should identify relevant leverage points, corresponding support measures, adaptation targets and automation goals based on theory and empirical findings.
• Management and IT departments of higher education institutions should strive to provide digital tools based on modern NLP models and integrate them into the respective learning management systems; those tools should help in translating the automation goals requested by their instructors into prediction targets, take relevant data as input and allow for evaluating the predictions.