Allison Littlejohn

Strengthening health systems through workforce development is central to combating health crises and inequalities in some of the world's poorest countries and is a key objective for implementation research (IR). Workforce development programmes often include blended and online modalities, offering the means to reach relevant communities at scale, removing barriers in accessing lifelong learning opportunities. However, approaches that privilege issues of access, reach and scale are overlooking critical problems, such as the persistent gap between ‘what one knows’ and ‘what one practises’. In this paper, we describe the implementation of an EdTech innovation situated within a technology‐supported health workforce development programme in two distinct public health systems: Nepal and Ghana. This work focused on the challenge of antimicrobial resistance (AMR), a critical area of health practice related to the burden of bacterial infections. We report on an embedded multiple case study of a health workforce development programme across participating health facilities ( n = 12; 6 in each country). Taking a postdigital positionality and using critical analysis guided by Helfrich et al.'s (2007) adapted Framework for Complex Innovations, we examine contextual factors that facilitated or impeded implementation. We used an iterative process to collect and analyse qualitative data generated by healthcare workers (HCWs) leading implementation activities in their organisations. By bringing in the relevance of the health field perspectives on the EdTech, the analysis illustrates the impact on implementation climate and the fit between the innovation and the values of participants. It provides evidence of how the innovation supported HCWs in organising new spaces of action to negotiate wider work and learning arrangements and facilitate the move of knowledge into their practice, hence offering a potential pathway to address the ‘know‐do’ gap. The paper offers a significant contribution in understanding and conducting EdTech implementation research in professional settings in complex, resource‐constrained settings. Practitioner notes: What is already known about this topic Implementing professional learning interventions in the complex environments of LMICs presents significant challenges and the ‘know‐do’ gap in the provision of health services is pervasive and enduring. Implementation research (IR) focuses on understanding and addressing the barriers to effective implementation of policies, practices and interventions with an aim to generate transferrable and replicable insights that may lead to scalable interventions. IR is widely used in the health sector to bridge gaps between evidence and practice. However, it has not yet been systematically used to guide educational interventions in complex, resource‐constrained settings such as low‐ and middle‐income countries (LMICs). What this paper adds The study illustrates how IR can be applied effectively to address the determinants of complex innovations, enabling alignment between blended and online professional learning interventions and the needs and values of the participants. The paper emphasises ways of conducting EdTech IR that include commitments to epistemological diversity and plurality and treating workers as highly agentic and ‘resourceful practitioners’. Based on analysis guided by Helfrich et al.'s (2007) adapted Framework for Complex Innovations, a key contribution of this paper is evidence of the implementation climate and the need for leadership through local ‘Innovation Champions’ who can navigate power dynamics, promote team autonomy and adapt interventions to suit local contexts. The paper demonstrates that IR can be used to analyse EdTech interventions and shows that a greater emphasis is needed on how the ‘digital’ relates to and operates in response to pre‐existing practices, objects and activities and the broader organisational and social factors. Implications for practice and/or policy The paper provides evidence that IR, when applied in the context of professional learning supported by EdTech, can serve as a valuable tool to inform both policy and practice, ultimately contributing to improved health outcomes. IR can be used to support change in EdTech interventions, such as online professional learning—an essential element for effectively implementing health‐related interventions in LMICs. The Framework for Complex Innovations used in this study offers a practical approach for developing context‐sensitive practices and guiding policy in complex LMIC settings, including in non‐health settings.

This article explores the innovative use of chatbot technology to promote inclusive and equitable quality education, specifically focusing on teacher professional development ( tpd ) in challenging environments, where teachers are in short supply and/ or urgently need support on a large scale, such as contexts of mass displacement. It details the design and integration of the Reflect-And-Act Chatbot (Rebo) within Co-designed Massive Open Online Collaborations (CoMOOCs) as an innovative approach to bridge learning in online tpd and application to practice. The article discusses the design rationale of this innovation for supporting teachers in reflecting on their learning and planning for its application to practice, addressing the critical need for effective knowledge transfer in professional learning. Findings from 116 conversations demonstrate Rebo’s feasibility for stimulating meaningful reflection and initial insights into knowledge transfer were valuable. While Rebo effectively prompted planning, analysis using the smart goal framework revealed that plans often lacked specificity, measurability, and realism. This study affirms Rebo’s potential as a responsible ai innovation, paving the way for future llm integration to enhance goal structuring and responsiveness, ultimately improving equitable access to quality teacher professional development globally.

Artificial Intelligence (AI) is reshaping education, learning, and instruction, yet current research in this area is fragmented, often tool-specific, and dominated by short-term perspectives. This article develops a broader research agenda for AI and Education (AI&ED), bringing together Artificial Intelligence in Education (AIED) and AI literacy within an educational ecology framing. Using a collective writing methodology, an expert panel of eleven internationally recognised scholars from various disciplines within computer and learning sciences contributed ten standalone reflections on the challenges, opportunities, and transformations of AI&ED. Two additional leading scholars provided critical commentaries to strengthen the analysis. A thematic analysis of the contributions identifies five main challenges (learning and instructional practices and curricula, access and ethics, assessment and evaluation, research capacity, and stakeholder readiness), five areas of opportunity (enhanced pedagogies, innovation in design and research, support for learning processes, critical skills, and hybrid knowledge), and four transformational themes (AI technologies and the design of education, human-AI interplay, lifelong learning, and organisation of AI&ED research). The article proposes an educational ecology research agenda across macro (policy, research ecosystem, society), meso (curricula, institutions, leadership), and micro (instructors, learners, learning processes) levels. We argue for a future-oriented, critical, and inter- or multidisciplinary approach that recognises AI as a socio-technical assemblage and sustains educational values such as equity, democracy, and human dignity in postdigital societies.

The University College London’s Moving to Online Teaching and Homeworking (MOTH) project used this data to mobile and advocate for improved accessibility in remote meetings during the pandemic. We conducted a survey running from March to June 2020 with UCL’s staff. As part of the survey, staff who took part in teaching and research shared challenges and opportunities, as well as images that communicated their experience. The focus of our study was on how working from home impacted teaching and research, rather than asking staff members to report on their disability. Nonetheless, many staff members took the opportunity to write comments regarding disability implications in our open-ended qualitative questions. From the responses, it was clear that disabled people experience both challenges and opportunities from working at home. This paper reports that data and discusses the rapid responses to disseminate the data and make recommendations to ameliorate the situation. Rather than using a top-down approach led by literature, we worked with disabled activists as part of UCL’s Disability Equality Steering Group to act on the findings based on lived experience. We present our data and recommendations here modeling best practices for acting on research findings led by the disabled community in the spirit of “nothing about us without us”.

For decades, science communities have had digital technology embedded in their everyday work. However, new research infrastructures are amplifying the presence and use of digital technologies for scientists. In that respect, radio astronomy is undergoing a major transformation causing the community to enter a phase of postdigital work, due to the construction of the most sensitive telescope, the Square Kilometer Array Observatory (SKAO), which scales the presence of digital technology and the amount of data generated. As new digital research infrastructure is set up, sociotechnical imaginaries—symbols and visions of a shared future—emerge, while others become obsolete thus impacting structures and practices of meaning-making. In this paper, we explore the disruptive potential of sociotechnical imaginaries and how astronomers using SKA pathfinder and precursor telescope data respond to these imaginaries and incorporate them into their meaning-making. The analysis shows that postdigital imaginaries related to data circulation, storage, archiving, and reuse have been amplified as SKA facilities and services are set up. Two changes are highlighted regarding a new postdigital condition within the astronomy community. Firstly, as astronomers engage in new postdigital forms of collaboration, they need to reach a consensus on what types of analyses to use by agreeing which methods are appropriate. This affects how scientific questions and research proposals are negotiated collectively, impacting the agency of astronomers. Secondly, as digital tools are increasingly part of astronomers’ daily work, they have to rely on new data analysis methods, which determine what evidence is uninteresting. Overall, these changes pose new questions regarding how meaning-making processes are altered and the way science is undertaken because of these new entanglements of human and non-human actors.