Abstract:

This paper presents the development of a systemic model, grounded in a critical realist framework, that reveals an interactive principle underpinning education, research, and innovation. It is our contention that if the deep-level structure of the mechanisms that govern social systems, such as education, can be identified, the systemic models thus formed can be used to gain insight into curriculum design and evaluation. The interactive principle underpinning our conceptual model is defined by five essential functions necessary for teaching and learning to occur: Contextual, Ideational, Interactive, Social, and Reflexive. This paper demonstrates how this principle has been applied in the development of two applications for use in higher education institutions. The first is an Online Course Design Evaluator, an AI agent produced by briefing agentic AI (Copilot) with the systemic model. This tool performs a verbal analysis of online course design texts, as demonstrated on public courses from MIT and GitHub, delivering a comprehensive evaluation with recommendations in under 45 seconds. The second application is a Course Feedback Survey, a simple Moodle tool , which is structured to elicit, collate, and analyse experiential feedback from course participants against the same five functions. The work suggests that AI should be envisaged as a mechanism to augment, rather than replace, human educator experience and judgement. By using a generalisable principle to inform AI tools, the abductive and creative work of designing a pedagogical framework remains a human endeavour, while the deductive and inductive processing required for mass evaluation can be delegated to AI. The projects described here provide exemplars of digital/human collaboration which form a basis for grounding the use of AI in established curriculum theory.

Keywords:

AI in education, systemic modelling, course evaluation, human-AI collaboration, critical realism.