STIGMERGY AS A MICROMECHANISM OF COGNITIVE INTERFACE SHIFTS IN HIGHER EDUCATION: AN ECO-CENTERED PSYCHOLOGICAL FACILITATION APPROACH

Abstract

The growing discrepancy between linear models of instructional design and the actual dynamics of cognitive processes in learning groups calls for new theoretical tools capable of describing self-organization in the university classroom. This article explores stigmergy — a mechanism of indirect coordination through environmental traces — as a micromechanism of cognitive interface shifts in higher education. The aim is to conceptualize stigmergy as the mechanism underlying learning group transitions between interpretive frames and to reconceptualize the instructor-facilitator as a cartographer of desire paths within Eco-Centered Psychological Facilitation (ECPF). The methodology combines theoretical synthesis and conceptual analysis, integrating the biological theory of stigmergy (Grassé, 1959; Heylighen, 2016a), the theory of cognitive interfaces (Hoffman, 2019), distributed cognition frameworks (Hutchins, 1995), and ECPF (Lushyn & Sukhenko, 2025a, 2025c). Drawing on modified illustrative examples from practical sessions in psychology and philosophy of education courses, the article identifies five types of stigmergic traces — questions, emergent functional expertise, silence as a rhythmic marker, latent traces, and format contagion — and their corresponding cognitive interface shifts. The urbanistic phenomenon of desire paths is proposed as a unifying metaphor that structures a four-phase process model of stigmergic interface shift: rupture, search, formation, and integration. The facilitator's role is reconceptualized through four functions: detecting emerging trails, introducing calibrated dissonance, sustaining forks without premature closure, and protecting the ecosystem of trails. It is shown that core ECPF principles function not merely as ethical guidelines but as descriptions of how stigmergic coordination operates in educational environments. Further research may pursue empirical verification of the model and development of AI-supported tools for stigmergic facilitation.