Learning as [processes of socialisation of challenges. A struggle for information and emotion] A network learning theory?

Questioning the ability to interact traces back to early physics lectures but is also the content of my profession as a special educator in a primary school.

This contribution proposes a relational reformulation of the concept of information by treating information as an operational topology of event spaces and their relations. Rather than beginning with messages, representations, knowledge, or semantic content, the approach starts from a more elementary question: under what conditions can something occur, be distinguished, transmitted, transformed, or identified as an event at all?

An event cannot be determined independently of the relational system within which it becomes possible. A pressure variation may constitute an acoustic event for a microphone, a temperature difference an event for a thermometer, and a change in behaviour a socially significant event within an interaction system. What these examples share is not a particular substance called information but an organized relation between possible events, sensory or responsive capacities, constraints, and processes of interaction. I therefore introduce the concepts of event space and sensor spaceto describe the structured domains within which events can become operationally accessible.

The analytical form of distinction I would like to discuss:

{[process | challenge] ~> sensor event)

On this account, information does not primarily designate an object that is transmitted from sender to receiver. It refers to transformations in the relational organization of possible events: differences in accessibility, reachability, admissibility, exclusion, adjacency, and consequence. “Topology” is used here initially in an operational rather than fully axiomatized mathematical sense. It describes how event spaces are related and how their structure is modified through interaction. Such a framework can subsequently be formalized using mathematical, computational, or network-theoretical methods.

The proposal connects Shannon’s analysis of communication under conditions of noise with broader questions concerning constraints, regulation, and interaction. Juarrero’s concept of constraints is particularly relevant because constraints do not merely restrict events; they shape landscapes of what can and cannot occur. Similarly, Conant and Ashby’s Good Regulator Theorem points toward the importance of adequate models of relational systems for regulation and identification.

The philosophical issue addressed is therefore one of epistemic integration. Technical, biological, neuronal, social, and pedagogical systems may differ radically in material realization while nevertheless confronting structurally comparable problems: how possible events become distinguishable, how interactions establish relations between event spaces, and how systems remain capable of responding to transformations within them. Information, understood as an operational topology of such relations, may provide a common conceptual framework without presupposing ontological identity between these domains.

This shifts the question from What is information? to a more operational one: What relational organization must exist for something to become informative for a system? In this sense, information becomes less a thing than a property of structured possibilities of interaction.