Explaining is nothing but tracing out your own internal model's inferential relationships between the concepts.

I disagree. Your internal model cannot be copied into anyone else's head just by expounding it. To explain something successfully -- that is, to get someone else to understand something -- you have to take account of the state of the person you are explaining it to. An explanation that one person finds a model of clarity, another may find tedious and confusing. (I have seen both reactions to Eliezer's article on Bayes' theorem.)

When I am assisting students in a computer laboratory, and a student indicates they have a problem, the question I ask myself when I listen to them is "what information does this student need, and not have?" That is what I seek to provide, not a dump of my own thought processes around the subject.

I generally get favourable feedback, so I think I'm onto something here.

As a general rule, explanations share this property with software: until you have tried it and seen it work, you do not know that it works.