Anticipating curriculum and course design for human–AI collaboration

Abstract

The increasing integration of artificial intelligence (AI) in workplace teams necessitates effective educational frameworks for human–AI collaboration. While technical aspects of AI development receive significant attention, there is limited research on incorporating diverse human perspectives in designing educational experiences for both human and AI agents. This study contributes to this gap by proposing and exploring a novel approach to anticipating educational frameworks for human–AI teaming, specifically examining the case of swarm shepherding teams in livestock farming. The research combined participatory curriculum design with futures studies methodology to engage both technical and non-technical stakeholders in shaping potential educational frameworks for human–AI collaboration. Through design-based research involving fieldwork with 15 human–AI swarm shepherding experts and 11 livestock farming practitioners, the study generated comprehensive data on anticipated knowledge requirements and skills development needs. Reflexive thematic analysis of interview transcripts and experiential vignettes informed the development of a set of curriculum design principles and educational materials, including course outlines, lesson plans, and assessment rubrics. Findings suggest that integrating participatory curriculum design with futures studies enables systematic engagement of diverse stakeholders in anticipating educational needs for human–AI teams. The study makes three key contributions: (1) establishing a methodology for anticipatory design of human-centred AI education, (2) developing prototype educational materials for human–AI swarm shepherding, and (3) advancing machine education research through participatory approaches to curriculum design. These findings support future work in implementing and validating educational frameworks while offering a replicable approach for curriculum design across other domains of human–AI teaming.

Date of Award	2025
Original language	English
Supervisor	Eleni PETRAKI (Supervisor) & Barney DALGARNO (Supervisor)