CoExplorer isn't built on AI hype. It implements thirty years of peer-reviewed research into how people actually construct understanding through dialogue. Here's the full picture.
Most AI learning tools are built on an assumption so widespread it's invisible: that learning means delivering content and testing whether people can recall it. Slide decks, video modules, multiple-choice quizzes — the entire architecture assumes that if you expose someone to information and they can recognise it on a test, learning has occurred.
It hasn't. Recognising the right answer is not the same as understanding. Understanding means being able to derive the knowledge from principles, explain it in your own words, apply it in new contexts, and teach it to someone else. That requires a fundamentally different process — and a fundamentally different theory of what learning actually is.
CoExplorer is built on three interlocking frameworks, each addressing a different dimension of the problem. Together, they form a complete system for capturing expert knowledge, detecting where a learner stands, and supporting them in constructing genuine understanding.
A note on credibility, not ideology: We present this methodology because it explains why CoExplorer works differently from other AI learning tools — not because we expect our clients to become learning theorists. The science is rigorous. The implementation is practical. You don't need to understand the theory to benefit from it, any more than you need to understand pharmacology to benefit from effective medicine.
The Three Frameworks
Gordon Pask's Conversation Theory, developed over thirty years of research and experimentation, provides the core mechanism. The central insight: genuine understanding is not transmitted from teacher to learner. It is constructed through conversation — a specific kind of structured dialogue in which the learner must explain, derive, and demonstrate knowledge, not merely receive and repeat it.
Pask demonstrated experimentally that when learners are required to "teach back" — to explain what they've learned in their own terms, derive it from first principles, and demonstrate it in application — the resulting understanding is deeper, more durable, and more transferable than any form of content delivery achieves.
This is why CoExplorer uses voice-first dialogue, not reading materials. This is why our assessment asks learners to explain and teach, not to select answers from a list. The conversation is the learning mechanism.
Elliott Jaques's research, spanning decades of work with organisations worldwide, provides a framework for understanding how a person's capacity to handle complexity develops. People at different stages of development can process information at different levels of abstraction, time-horizon, and systemic scope.
This matters for knowledge transfer because expert knowledge is often complex, multi-layered, and systemic. If the learning system doesn't account for where the learner currently stands in their capacity to handle complexity, it either overwhelms them or bores them. Jaques's framework allows CoExplorer to calibrate what is presented and how, matching the complexity of the material to the learner's current capacity.
Gillian Stamp developed a methodology for detecting where a person currently operates in terms of their capacity for complexity — without reducing them to a test score or a ranking. Her approach is "appreciative" in the precise sense: it seeks to understand and value what a person brings, not merely to measure them against a benchmark.
In CoExplorer, this translates to the system's ability to detect — through conversational interaction — how each learner processes information, where they are in their development, and how to support their growth without either overwhelming or condescending to them. It's the difference between a system that sorts people into categories and one that genuinely sees them.
Integration
The conversation mechanism: how knowledge is extracted from experts and constructed in learners through dialogue, derivation, and teachback.
The structural framework: what level of complexity the learner is ready for, and how to present material that stretches without overwhelming.
The appreciative method: how the system sees each individual learner as they are and meets them where they actually stand.
In practice, the three frameworks operate simultaneously. When a subject matter expert sits with CoExplorer's AI-assisted system, Pask's conversational methodology structures the dialogue — insisting on explanation, derivation, and connection. The result is not a transcript but a navigable knowledge architecture.
When a learner enters that knowledge architecture, Jaques's complexity framework ensures the material is presented at the right level — neither dumbed down nor pitched over their head. And Stamp's appreciative methodology allows the system to detect how the learner thinks, where they currently stand, and how to support their development — all through the natural flow of conversation.
The technology to implement this integration — voice-based conversational AI, graph databases for knowledge structures, adaptive interfaces — has only recently become possible. The theory has been ready for decades. Now the implementation can match it.
What This Means
When your most experienced people retire or move on, their knowledge doesn't disappear. It's captured in structured, navigable form that future employees can learn from directly.
Learners can explain, derive, and apply what they've learned — not just recognise it on a test. You get genuine capability, not checkbox completion.
The system adapts to how each individual thinks and processes information. No two learners take the same path. Everyone arrives at genuine understanding.
Conversation-based assessment produces more reliable evidence of genuine understanding than any multiple-choice test. You know what your people actually know.
Further Reading
The foundational work. Pask's account of how understanding emerges through structured dialogue, with experimental evidence and formal models.
The educational applications of Conversation Theory, including the teachback methodology and learning strategy detection.
Jaques's framework for understanding how organisational structure should align with the complexity of the work and the capability of the people.
The developmental framework for cognitive complexity — how people's capacity to process information grows through identifiable stages.
Stamp's framework for assessing how people process complexity in organisational contexts, using appreciative rather than reductive methods.
Our ongoing research in cybernetics, systems thinking, and their application to knowledge architecture and adaptive learning.
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