Research Summary: Reconceptualizing outdoor geoscience learning for the generative AI era: a human-centered instructional model

The advent of Generative Artificial Intelligence (GenAI) presents a unique challenge and opportunity for outdoor geoscience learning. While GenAI can enhance inquiry and explanation, it also risks pre-structuring observation and displacing learners' direct interpretation of field evidence. This analysis posits GenAI as an epistemic reorganization of field inquiry, suggesting it will more likely augment, rather than entirely displace, human learning processes by redistributing epistemic work and authority.

Why it matters

The integration of Generative AI into educational and operational field settings redefines the nature of expertise and learning. Understanding how AI reallocates cognitive load and decision-making authority is critical for designing effective training programs and ensuring robust knowledge acquisition.

Key insights

• Generative AI introduces a dilemma in outdoor geoscience learning by simultaneously broadening questioning and potentially pre-structuring learner observations.
• GenAI may displace learners' independent interpretation of field evidence, shifting the traditional distribution of epistemic work.
• Existing field-learning frameworks do not fully account for the redistribution of epistemic work and authority caused by GenAI.
• The core hypothesis is that GenAI primarily reorganizes knowledge acquisition in field inquiry, rather than acting solely as a technical novelty.
• GenAI is anticipated to augment, rather than displace, learners' epistemic engagement in outdoor geoscience settings.

Source

Frontiers in Education — https://www.frontiersin.org/articles/10.3389/feduc.2026.1963429