Designing a human-AI collaborative model for precision teaching in undergraduate physiology laboratory education: a...

Area of Science:

• Physiology Education
• Artificial Intelligence in Education
• Educational Technology

Background:

• Artificial intelligence (AI) presents opportunities to enhance precision in undergraduate physiology laboratory education.
• Designing effective human-AI collaborative models faces ethical, pedagogical, and technical challenges.

Purpose of the Study:

• To develop and validate a precision teaching framework for human-AI collaboration in undergraduate physiology laboratories.
• To achieve expert consensus on the scientific validity and feasibility of the proposed model.

Main Methods:

• A modified Delphi method involving two rounds of consultation with 15 interdisciplinary experts.
• Expert consensus was sought on the scientific validity and practical feasibility of the framework's modules.

Main Results:

• The theoretical framework received high recognition from experts.
• Consensus was reached on practical implementation pathways: phased technology integration, teacher leadership, ethical safeguards, Knowledge Graph development, and teacher training.

Conclusions:

• A theoretically sound and ethically grounded human-AI collaborative model for physiology lab teaching was developed.
• The study provides a roadmap for integrating AI in education, preserving teacher agency and pedagogical integrity.