A Conceptual Framework for Designing Learning Environments for Human–Robot Collaboration in Construction

Advances in robotics are transforming the construction industry, creating a need for professionals skilled in human–robot collaboration (HRC). This paper presents a conceptual framework for designing a web-based learning environment integrated with multimodal large language models (MLLMs) to equip students with competencies for HRC in construction. Grounded in cognitive apprenticeship theory (CAT), the learning environment features four structured modules, a virtual tutor, and MLLMs to provide scaffolded, interactive, and personalized learning experiences. The modules align with CAT’s core principles, guiding learners from foundational knowledge of robotics to independent problem-solving in simulated construction scenarios. This research contributes to competency development in HRC by leveraging digital learning environments and artificial intelligence–driven tools, addressing critical gaps in traditional construction education, and advancing the application of CAT in the construction domain.