Symposium: Reimagining Research Skills Development for UK Social Scientists: co-creating the Research Capability Hub
Bart Rienties, Duygu Bektik, Carina Bossu, Elizabeth Fitzgerald
Institute of Educational Technology (IET), The Open University, UK.
Abstract:
How should a national research training system be designed when existing provision is fragmented across institutions, sectors and career stages? The Research Capability Hub (RCH: rch.ac.uk) funded by The Economic and Social Research Council (ESRC) and led by The Open University, is building a federated infrastructure to address this question. Rather than creating courses in isolation, the RCH aggregates, quality-assures and connects training resources from universities, government and the third sector across all four UK nations, delivering them through a dual-platform architecture combining a discovery hub with OpenLearn Create for structured learning.
This symposium presents early insights from the Hub’s first operational year across five interconnected workstreams. The first presentation frames the RCH within ESRC strategy, positioning research capability as national infrastructure. The second reports on ecosystem curation: 934 resources catalogued across 15 sources and 12 thematic areas, revealing significant gaps in existing provision. The third examines co-creation, drawing on Q-methodology data, evidence cafes, and a set of ten co-creation principles developed to guide the Hub’s participatory design. The fourth presents nine learner personas spanning junior, mid-career and senior researchers, a bespoke metadata taxonomy, and AI-assisted tagging workflows that enable personalised learning pathways. The fifth outlines the RCH CPD2 (Context, Philosophy and Delivery) model, which informs the evaluation framework and the Flexible Fund mechanism for commissioning community-driven research and training. The symposium contributes to CALRG’s long-standing interest in technology-enhanced learning by examining what happens when educational technology infrastructure operates at national scale and across sectors.
This symposium presents early insights from the Hub’s first operational year across five interconnected workstreams. The first presentation frames the RCH within ESRC strategy, positioning research capability as national infrastructure. The second reports on ecosystem curation: 934 resources catalogued across 15 sources and 12 thematic areas, revealing significant gaps in existing provision. The third examines co-creation, drawing on Q-methodology data, evidence cafes, and a set of ten co-creation principles developed to guide the Hub’s participatory design. The fourth presents nine learner personas spanning junior, mid-career and senior researchers, a bespoke metadata taxonomy, and AI-assisted tagging workflows that enable personalised learning pathways. The fifth outlines a macro–meso–micro evaluation framework and the Flexible Fund mechanism for commissioning community-driven research and training. The symposium contributes to CALRG’s long-standing interest in technology-enhanced learning by examining what happens when educational technology infrastructure operates at national scale and across sectors.
Better Words for AI – a collaborative dynamic lexicon
Mirjam Hauck, Eleanor Moore, Olivia Kelly, Julia Molinari
The Open University, UK
Abstract:
Better Words for AI is a cross‑school research project funded by Praxis that aims to co‑create a dynamic, lexicon of Artificial Intelligence terminology collaboratively developed with students and staff from WELS. Motivated by the proliferation of ambiguous, anthropomorphic or hype‑driven language surrounding AI, the project addresses how unclear terminology can hinder understanding, exacerbate inequalities, and impede responsible use of AI in learning and teaching. Grounded in Critical AI Literacy (CAIL) and informed by a participatory approach, the project engages students and Associate Lecturers as co‑researchers throughout five phases, including focus groups, workshops, iterative peer review of lexicon entries and pilot deployment on OpenLearn Create. The resulting lexicon will offer ethically framed definitions, supporting clearer communication and enhancing pedagogical practice across disciplines. Beyond producing an open educational resource, the project aims to strengthen student voice, contribute to institutional EDIA priorities, and model a scalable approach to responsible AI communication at the OU and within the UK higher education sector.
Proposing Inclusive Ethical AI Policy Guidelines for Higher Education
Munir Moosa Sadruddin
World Institute on Disability
Abstract:
Persons with disabilities are particularly underrepresented in higher education, with only around 3% of adults accessing it (United Nations, 2020). Artificial Intelligence has emerged as a promising tool for making education more cost-effective, accessible, equitable, and engaging for learners with disabilities (OECD, 2024). The OHCHR (2021) report highlights the importance of technology for learners with disabilities in improving education, enhancing access to goods and services, and promoting inclusion and equality. Similarly, the UNESCO Recommendation on the Ethics of Artificial Intelligence emphasizes the need to promote inclusive AI (UNESCO, 2022).
This presentation proposes Inclusive Ethical AI Policy Guidelines for higher education institutions to ensure the visibility and representation of learners with disabilities in AI use. These guidelines create opportunities for collaboration, inclusion, and the development of innovative solutions for and by learners with disabilities, thereby supporting their educational experiences.
Re-visioning teaching practice and teacher professional development at scale through the lens of 360° video
Simon Cross
Institute of Educational Technology (IET), The Open University, UK
Abstract:
This summer, a project led by the OU will publish a paper setting out a vision for using 360° video at scale for teacher professional development (TPD) and training. In this presentation, I will describe the journey travelled over the last eighteen months to develop the vision, highlighting the teams’ original fieldwork into how teachers experimented with and used 360° video recordings and viewing to support their teaching practice and TPD and some new perspectives glimpsed by a reading 360° video from the perspective of spatial theory.
The focus of our fieldwork has been a joint project led by the OU and the National Institute of Applied Science in Bengaluru, India. In this, we have worked with over thirty-five teachers and teacher educators working in thirteen schools to co-create knowledge in authentic settings about how 360° video could be used support their teaching and professional development. We loaned each school an ‘equipment pack’ comprising a video camera, mobile device, VR headset, tripod and associated peripherals, and invited them to experiment and test uses for the technology however and wherever they wanted to. Training, on-site support and a community group were provided. Our loan cycles lasted weeks, giving teachers the opportunity to become familiar with and use the equipment without any preconditions.
Given that very little research has been conducted about the use of 360° video for in-service TPD, not only does this fieldwork offer new perspectives, it also underscores the need for further theorisation around the impact that 360° video technology has on how teachers envision their classroom. For this, our vision draws upon sociospatial theories of place, network and positionality. This adds some conceptual twists to a growing narrative that figures 360° video as a unique and valuable addition to teacher professional development programmes.
From Personalisation to Adaptation: Synthesising the Evidence and Extending the Framework
Maria Aristeidou, Felipe Tessarolo
The Open University, UK
Abstract:
Adaptive learning refers to the use of AI and data-driven technologies to dynamically adjust educational content, pacing, and feedback to individual learner needs. It has attracted growing institutional attention in higher education, yet significant conceptual confusion persists around what it is, what it does, and how it relates to personalised learning and differentiated instruction. In this presentation, we draw on a desk review carried out at the Institute of Educational Technology to clarify these distinctions and synthesise current evidence for institutional practice.
The first part of the presentation provides a conceptual overview of adaptive learning, distinguishing it from related approaches, tracing its development across three technological generations, and situating it within distance and asynchronous online education contexts.
The second part presents findings from an umbrella review of 13 rigorous systematic and scoping reviews published between 2015 and 2025, identified through a PRISMA-aligned search of Web of Science, Scopus, and ERIC. Using thematic meta-synthesis, we identified seven themes spanning: foundational concepts and architecture; technologies and digital infrastructure; the role of teachers and human agency; effectiveness and learning outcomes; ethical concerns and governance; student agency and learner autonomy; and learning pathways and curricular design. Academic performance improves in 59% of studies, with effect sizes ranging from small to large depending on context, discipline, and implementation quality. Larger effects are consistently found in informal learning and distance contexts, and learner-controlled progression outperforms purely system-controlled approaches for complex skill development. Insufficient teacher preparation and inadequate ethical governance emerge as the primary barriers to effective implementation.
The third part introduces an extended eight-dimensional framework for adaptive learning, building on FitzGerald et al.’s (2018) six-dimensional personalisation framework. The extension incorporates distance-learning contexts, dynamic learner modelling, a reconceptualised view of adaptive agency across technological, teacher, and learner dimensions, contemporary mechanisms, including generative AI, and two new dimensions addressing ethical governance and curricular design. The framework offers a practical analytical tool for institutions designing, evaluating, or scaling adaptive learning.
Teachers, Tools, and AI: Understanding the Role of Generative Systems in Curriculum Production
Thomas Ullmann, Duygu Bektik, Chris Edwards, Denise Whitelock, Christothea Herodotou
Institute of Educational Technology (IET), The Open University, UK
Abstract:
The rapid emergence and uptake of generative AI (genAI) is reshaping educational practice, with recent reports indicating that over half of teachers already use these systems for planning, assessment, communication, and other pedagogical tasks. Despite this widespread adoption, empirical research on how genAI can meaningfully support teaching remains limited. This presentation approaches genAI from an educational technology perspective and introduces findings from a multi phase investigation into how generative AI can aid curriculum production in higher education.
Our project examined the potential of genAI across a broad range of course writing activities, including developing learning outcomes, drafting outlines, designing activities and assessments, and reusing existing materials. To support this work, we developed Scribe, a collaborative AI enhanced workspace populated with customisable assistants such as quiz designers and activity sketchers. Scribe enables educators to inspect, adapt, and create their own AI assistants, upload materials for context-aware drafting, and collaborate within shared team spaces.
Our findings indicate that genAI can effectively support ideation, rapid drafting, and adherence to writing guidance, offering course teams a productive “third perspective” during early development stages. However, genAI remains an assistive rather than autonomous technology: outputs require expert evaluation for accuracy, bias, and pedagogical suitability. Key challenges include ensuring effective use of subject specific knowledge, avoiding teacher disempowerment by outsourcing creative tasks, and supporting educators in articulating tacit expertise through effective prompting.
Overall, our results suggest that genAI can enhance curriculum production when embedded within collaborative, reflective academic practice, with opportunities for increased productivity alongside important considerations for training, governance, and pedagogical quality.