Prior knowledge is the set of stable memories that you have already stored in your mind - it represents what you already know.
To be learned, new information must be relatable in some way to your prior knowledge.
If something is easily relatable to prior knowledge, it will "slot in" like a jigsaw puzzle piece into your prior knowledge.
Learning based on slotting new information into prior knowledge is
semantic learning, otherwise it is asemantic, or "rote" learning.
Semantic learning is easy and pleasurable while asemantic learning is difficult and displeasurable.
Assimilation Theory of cognitivist David Ausubel which emphasises prior knowledge as the most important determinant of future learning.
Semantic learning: learning based on slotting new information into stable networks of knowledge already stored in the mind.
A stream of information enters the brain. It undergoes neural processing, an unconscious comparison between the new information and prior knowledge.
Here's a simplified explanation of the "knowledge comparison" which takes place during neural processing that I gave in my summary of
Piotr Wozniak's Pleasure Of Learning article.
Information delivered to learners must account for their prior knowledge. This factor makes universal delivery, e.g. via lecturing, very difficult. -
The knowledge comparison between new and old knowledge is granular - it takes place at the level of individual memories.
A good example of asemantic learning can be seen in the 1885 memory experiments carried out by [Ebbinghaus]. In his experiments, Ebbinghaus chose to learn strings of nonsense syllables rather than poem stanzas to control for interference from his