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Video: AI Competencies for Students and Teachers

An overview of what competence with AI means in
education beyond operating a tool: mindset,

ethics, foundations, pedagogy, and design.
Duration: about 15 minutes | Level: Beginner
Learning objective: Recognize that AI competence
is a pedagogical capability, not a technical one.

Source: UNESCO Education Community [20].
https://youtu.be/O9jdwj5TDz8

Verified: June 6, 2026

6.2 Explaining Concepts at Different Levels Without Distorting Them
◆ Key idea: simplifying is not deleting the meaning.
A good explanation is not merely the replacement of hard words with easier ones. It is

the building of a bridge between what the learner already knows and what we want them
to understand, while surfacing misconceptions, highlighting the core relationships, and
then testing the ability to use the idea.

When someone asks AI to “explain the topic simply”, they may receive an easier text that is
not necessarily more educational. The explanation may drop an important condition, use an
attractive but misleading analogy, or offer a definition without connecting it to the learner’s
prior knowledge. Professional explanation therefore begins by establishing the starting level:

which concepts must already be present? Which words are familiar? And what is the most
likely error?

Explanation can be built in layers. The first layer begins with one central idea that answers:
what is the thing, and why does it matter? Then come the core relationships: what affects
what? After that, examples and non-examples are used; an example shows a case the rule

applies to, and a non-example shows a nearby case it does not apply to. This comparison
reveals the boundaries of a concept better than repeating its definition.

A graduated explanation does not mean that every learner must receive a completely
different version. A shared structure can be kept while the vocabulary, the amount of detail,

the type of example, and the degree of visual representation change. In a lesson on
probability, a beginner might start with a simple draw, while an advanced learner needs to
distinguish theoretical, empirical, and conditional probability. The idea is the same, but the

entry point and the depth of the relationships differ.

AI helps in generating analogies, but an analogy must be used with care. An analogy is not a
definition; it is a temporary device for carrying a relationship. We must always state where

it succeeds and where it fails. Comparing human memory to a file store may help in

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