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.     

Back to the Future – in support of a renewed emphasis on generic agility training within sports-specific developmental pathways

Perhaps as a consequence of increased specialism in training and support, the focus on engendering and maintaining agility as a generic quality has diminished within many contemporary sports performance programmes. Reflecting this, we outline a rationale suggesting that such a decreased focus represents an oversight which may be detrimental to maximising the potential of performers. We present an evidence-based argument that both generic and specific elements of agility performance should be consistently emphasised within long-term performance-training programmes. We contend that prematurely early specialisation in athlete development models can diminish focus on generic movement skill development with a subsequent detriment in adult performance. Especially when this is coupled with poor primary physical education and limited movement experiences. More speculatively, we propose that generic agility can play a role in operationalising movement development through facilitating skill transfer: thereby enabling the learning of new skills, reduce incidence of injury and facilitating re-learning of old skills during rehabilitation and Return-to-Play processes.     

Publisher–Society partnerships to further image accessibility and global inclusivity in the Humanities and Social Sciences: Comparing top-down and bottom-up approaches

• Collaboration between publishers and learned society partners can accelerate and amplify DEIA outcomes.
• 97 HSS titles have adopted alt-text publication workflows and this change has been welcomed by journal authors and editors.
• Efforts to promote global inclusivity do not always result in greater membership diversity, retention and growth.
• Top-down, publisher-led DEIA initiatives are effective when they are aligned strategically to pre-existing society initiatives.
• Bottom-up, member-led DEIA initiatives benefit from publisher support to mitigate financial and time-based barriers to active participation.
• To reliably track DEIA outcomes, publishers ought to adopt systematic data collection strategies through initiatives like C4 and the Joint Commitment.

     

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.