Managing expert learning systems

As an avid learner, looking to pick up new tricks, here is a list of tools and techniques I have used and experimented for knowledge management and specifically for expertise management over the years.

The whole process of learning starts with discovery and exploration through questioning, then making links between ideas and thoughts. Finding a way to record this information through an e-learning or a chat bot, a wiki and the diffusing this information in a community of practice that can improve upon the shared knowledge.

Mapping knowledge

An ontology — Helps to map out concepts and categories in a subject area or domain that shows their properties and the relations between them to understand a domain of knowledge.

A flowchart — a diagram capturing a process, flow or causal decision tree

Mental models:

First principle thinking — helps to break down a domain of knowledge to its first principles and make an ontology of a domain

Metaphorical thinking — the ability to abstract and transpose a concept from one domain to a more familiar one to explain a lesser known phenomenon using knowledge of a more familiar system.

Linking your thinking — Organizing, curating and sharing expert notes and resources by linking them on note taking tools (Obsidian, Notion, scrintal…)

Methods:

ACTA model- Applied Cognitive Task Analysis method to extract Tacit knowledge through an interview process (CommonCog)

Modeling excellence — Through a combination of interview techniques by comparing and contrasting experiences, the ability to recognise smart patterns and shortcuts used by the expert to get a job done.

Reverse engineering — process to make sense of expertise by analyzing the medium or through an interview process

Theory of change — Framework to capture the DNA of a process, activity or organization through a meticulous process of questioning the whole value chain and identifying the causal chain to explain the change.

Medium:

Expert systems — help in decision making using expert knowledge using a causal tree, can be developed with nocode chatbot tools today.

E-learning — helps to diffuse training and expertise.

Learning communities — social networks and platforms to discover, learn, capitalize, and share best practices and feedback around a certain topic like Mightynetwork !

Machine learning —computer systems that are able to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyse and draw inferences from patterns in data and code an expertise.