Artificial Intelligence as a “Knowledgeable Other” in Forest School Practice
DOI:
https://doi.org/10.55578/fepr.2603.005Keywords:
Forest School, More Knowledgeable Other (MKO), AI-assisted reflectionAbstract
Forest School, a learner-centred outdoor education approach rooted in constructivist pedagogy, emphasises child-initiated, autonomous play, environmental engagement, and facilitative adult roles to support holistic development. Despite its increasing adoption in the UK and internationally, Forest School practice often faces tension with mainstream educational pressures prioritising measurable outcomes, risking drift from its foundational principles. This paper explores a novel intersection of Forest School pedagogy and artificial intelligence (AI), investigating whether AI can function as a ‘more knowledgeable other’ or MKO (Vygotsky, 1934 in Luria et al., 1978) to support practitioner reflection in assessing how close their practice is aligned with Forest School Association principles.. Drawing on two empirically rich case studies, Mackinder (2024) and Mart & Waite (2023), selected through a systematic and purposive literature review, this paper employed thematic analysis to extract key patterns in child-led play, environmental affordances, adult facilitation, and social interaction. Cross-case comparison revealed strong conceptual and methodological alignment across datasets, highlighting consistent emphases on learner agency, adaptable spaces, scaffolding, narrative construction, and risk-mediated learning. AI-assisted analysis was then applied to evaluate these practices against Forest School Association (FSA) principles, conceptualising AI not as an assessor but as a reflective interlocutor capable of prompting insight, supporting interpretive dialogue, and extending professional reflexivity. Findings suggest that AI can act as a cognitive scaffold for practitioners, offering timely, theoretically informed feedback while preserving the facilitative, emergent, and learner-centred ethos of Forest School.
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