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Refinement is a learning process that involves modifications to knowledge components, particularly to the conditions or features under which the knowledge is retrieved and should be applied. The refinement process may add a missing relevant feature to a knowledge component or remove an irrelevant feature. For instance, consider a typical novice knowledge component in geometry: "If angles look equal, then they are equal". While this knowledge component can yield correct answers, it is incorrect in general. Through learning a student may refine it, by removing the irrelevant feature "angles look equal" and adding a relevant feature, like "angles opposite each other in crossing lines" or "angles that are base angles of an isosceles triangle". Such refinement leads a new knowledge component with higher feature validity. Of course, during learning sometimes students may add an irrelevant feature (e.g., because in an example the angles that are concluded to be equal, do look equal, a student may incorrectly induce that looking equal is a relevant feature) and perhaps remove a relevant feature (seems more rare).

At present we use refinement to refer to such feature changes whether they are more explicit, involving declarative or verbal knowledge components, or more implicit, involving procedural, non-verbal knowledge components like skills. Implicit instruction, like the use of examples, may lead the learner to feature refinements that they cannot verbalize. For instance, first language learners acquire the features for correct choice of articles, like "a" and "the", without being able to articulate the explicit rules for article choice. Even second language learners, as well as math and science learners, engage in such implicit feature refinement. Some instructional methods, like feature focusing, co-training, or tutoring feedback, may accelerate such implicit feature refinement. Other instructional methods, like prompted self-explanation, peer tutoring, or collaborative observing , engage students in verbalizing and reasoning about features and their relevance. Such sense making may lead students to better acquire explicit, declarative or verbal knowledge components with higher feature validity.