Essays
A collection of essays exploring the implications of emergent scholarship across different education and practice contexts.
The learning alignment problem: AI and the loss of control in higher education
Higher education's focus on 'prompt engineering' misses the fundamental issue: prompts emerge from personal meaning-making frameworks, not technical skills. AI acts as a mirror, revealing that students were already optimising for grades over learning, long before AI exposed the problem in such clear terms. The learning alignment problem shows how education systems reward measurable proxies rather than authentic learning outcomes. Instead of controlling the mechanics of AI interaction, institutions should cultivate conditions where thoughtful AI partnership serves students' genuine learning purposes. Learning is inherently personal and contextual and cannot be engineered through technical specification or control.
Context sovereignty in AI-supported learning
Current AI education discourse focuses on prompting strategies, overlooking the dynamic and relational nature of context more broadly. Context sovereignty offers a framework based on three principles: persistent understanding, individual agency, and cognitive extension. This enables AI systems to adapt to human cognitive patterns rather than requiring human adaptation, creating genuine cognitive partnerships whilst preserving privacy and human agency. The framework transforms personalised learning from content delivery optimisation to collaborative intelligence, addresses concerns about echo chambers through sophisticated contextual challenge, and suggests assessment focusing on collaborative problem-solving rather than isolated performance.
Beyond text boxes: Exploring a network-based user interface for AI-supported learning
This essay critiques text-entry interfaces for AI-supported learning, arguing they perpetuate outdated container metaphors that do more to fragment and artificially separate knowledge structures than to connect them. Instead, network-based interfaces using interactive knowledge graphs better reflect how expertise actually develops. In this alternative user interface, AI serves as both conversational partner and network builder, with dialogue embedded within spatial knowledge landscapes rather than isolated chat histories. Features like multimodal nodes, multi-dimensional navigation, and progressive complexity management support integrative thinking. Though implementable with current technologies, the barriers are primarily conceptual—our attachment to container thinking. Network interfaces would better develop the connection-making capabilities that define professional expertise.
The ACADEMIC framework for integrating AI into health professions education
Health professions education faces the dual challenge of information overload and inadequate preparation for complex healthcare environments, while students rapidly adopt AI tools that highlight deficiencies in traditional education. The ACADEMIC framework proposes integrating AI into health professions education by focusing on learning processes rather than outputs, based on theoretical principles across six dimensions of learning interactions. Rather than seeing AI as merely a content delivery tool or threat to academic integrity, the framework positions it as a learning partner that can address persistent challenges and better prepare students for the complexity and collaborative nature of modern healthcare practice.
From teaching to learning: How emergent scholarship disrupts traditional education hierarchies
This essay argues that traditional higher education models built around teaching hierarchies are increasingly misaligned with how learning actually occurs in our information-rich, technology-enabled world. Emergent scholarship offers an alternative approach that reconceptualises learning as a networked process where knowledge emerges from connections between diverse participants rather than flowing 'downhill' from experts to novices. This transformation requires reimagining not just pedagogical approaches but institutions themselves, creating new kinds learning environments that better prepare graduates for complexity while fostering more meaningful experiences for all participants.
Publishing with purpose: Using AI to enhance scientific discourse
The use of generative AI in the scientific publishing system offers opportunities to enhance research processes, but risks reinforcing the problematic "research industrial complex" that represents the capture of academic scholarship. I argue that journals and editors must leverage AI to transform publishing into vibrant learning communities that facilitate discourse and collaborative engagement. This transformation requires coordinated action across stakeholders willing to prioritise the core purpose of advancing scientific knowledge, despite the entrenched incentives of the current academic publising ecosystem.
From journals to networks: How transparency transforms trust in scholarship
The essay critiques the academic system where trust is outsourced to publishers and journals, proposing instead a framework based on visible scholarly processes rather than institutional proxies. It advocates for a three-tier technical approach that maintains compatibility with traditional structures while creating new possibilities: a live working environment, preprints with DOIs, and journal publication. While offering benefits like greater autonomy and transparency, this approach also presents challenges including technical barriers, potential fragmentation, and resource demands.
Technological nature of language and the implications for health professions education
This essay examines language as a general purpose technology and presents large language models as a significant evolution in this continuum rather than merely new digital tools. It explores how LLMs extend language's core capabilities through scale, synthesis, adaptability, and multimodality, which is especially relevant to health professions education where students struggle with information overload and preparation for complex practice environments. By framing LLMs as an evolution of our fundamental technology, the essay suggests shifting educational focus to clinical reasoning and adaptive expertise, developing healthcare-specific AI literacy, and reimagining assessment approaches—offering a balanced perspective between uncritical enthusiasm and reflexive resistance.