Contemporary architectural education requires students to apply technical knowledge from a wide variety of sub-disciplines, from drawing to the performative aspects of design, such as structures, acoustics, and thermal comfort. While certain technical aspects of architectural projects are readily incorporated into the design studio, other forms of specialised knowledge are often taught in seminar-based formats, and there is rarely a cohesive approach to current practice in architectural education, particularly across different technical disciplines. This inconsistency extends to how teaching activities are typically documented, making them difficult to replicate or compare, particularly when contextual constraints are not clearly articulated. Drawing on instructional design, cognitive load theory, and exemplar teaching activities, this paper develops a framework for mapping and analysing teaching activities that complements existing instructional design models and pedagogical strategies, while remaining adaptable across different topics, tools, techniques, delivery modes, and activity durations. We demonstrate the framework by applying it reflectively to our own teaching and to analyse selected examples from the literature. Its application revealed how different technical disciplines' structure and sequence knowledge, manage cognitive load, and integrate problem-solving activities, while also supporting reflective practice and comparative analysis across teaching contexts. The application of the framework illustrates how technical knowledge can be defined, sequenced, and integrated into problem-solving activities in architectural design in ways that support comparison, analysis, and replication in other contexts. In doing so, the framework provides a more systematic approach to mapping and analysing the structure of teaching activities, while also supporting the integration of technical knowledge into architectural design education.

Large old trees provide essential habitats for birds and many other species, yet they are rapidly disappearing from many landscapes. While artificial habitat structures have been trialled, their design rarely captures the morphological complexity of natural habitats. This limitation stems from both challenges in extracting relevant features from natural forms and the difficulty of developing cost-effective systems that can be reproduced at scale. This paper addresses this gap by presenting FloaTree, an experimental example of a human–machine design workflow to generate, optimise, and construct tensegrity structures derived from AI-generated visual abstractions of large trees. We developed a parametric workflow that translates such AI-generated polyline abstractions into X-module tensegrity configurations, refined through structural optimisation and represented via connectivity matrices. Iterative prototyping, from small-scale tests to an eight-module pavilion, validated the structural and constructability aspects of this workflow and culminated in the winning entry of the 2024 IASS “Design Competition and Exhibition of Innovative Lightweight Structures” in Zurich. The results demonstrate that tensegrity structures, typically confined to artistic installations or used with limitations as surrogates for other typologies, can be designed for packability, transport, and rapid low-tech assembly to enable their potential application in artificial habitat structures. The project also advances tensegrity design methods through a novel human-machine workflow and a visualisation technique based on connectivity matrices. It shows how the analogue and digital domains can co-exist in design workflows alongside emerging forms of human–AI collaboration. While ecological performance requires future field testing, the significance of this work lies in reframing tensegrity not only as an experimental artefact but as a transferable design framework integrating form abstraction, structural logic, and constructability, thereby suggesting broader applications for computationally optimised yet low-tech structures in disturbed landscapes.